This document discusses key technologies for smart grid knowledge visualization. It proposes a three-dimensional smart grid knowledge visualization model that addresses issues with single manifestations, low efficient use, and low model reuse rates. The model constructs grid device models based on knowledge-based reasoning and builds visual scenes using a rapid organization strategy while exploring storage and reuse mechanisms. It also proposes using swarm intelligence and bionic computing to solve existing problems with collision detection. The feasibility of the approach is verified through an intelligent power virtual drill platform.
PREDICTIVE MAINTENANCE AND ENGINEERED PROCESSES IN MECHATRONIC INDUSTRY: AN I...ijaia
The paper proposes the results of a research industry project concerning predictive maintenance process
optimization, applied to a machine cutting polyurethane. A company producing cutting machines, has been
provided with an online control system able to detect blade status of a machine supplied to a customer
producing polyurethane components. A software platform has been developed for the real time monitoring
of the blade status and for the prediction of the break up conditions adopting a multi-parametric data
analysis approach, based on the simultaneous use of unsupervised and supervised machine learning
algorithms. Specifically, the proposed method adopts a k-Means algorithm to classify bidimensional risk
maps, and a Long Short Term Memory (LSTM) one to predict the alerting levels based on the analysis of
the last values for some process variables. The analysed algorithms are applied to an experimental dataset.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
In recent times, the definition of internet of things has evolved to great extent and it means different things
to different people. However the basic idea of Internet of Things remains the same which is use of information and
communication Technologies(ICT’s) as well as Internet to provide efficient services to the mankind for their
optimum benefits. While implementing the Internet of Things itself is complex due to large of devices various link
layer technologies and services that are involved in such systems. In this paper, we specifically implement an urban
Internet of Things system which primarily gives an emphasis on smart educational institute which aims at
exploiting advanced communication technologies to support for administration of the institute and for the new
visitor who find it difficult to find their way around the institute. This paper thereby provides a comprehensive
survey of various technologies such as Android , Java, protocols and architecture for using Internet of Things in
Smart Institute. Furthermore ,this system will provide an overlook of the institute via the administration office
,playground and canteens. The user of the system will also get an static image map to roam around the institute.
Lastly the system will provide technical solutions and best practice guidelines for finding the way around the
institute and also help a new visitor in reaching his desired location.
Real Time Object Identification for Intelligent Video Surveillance ApplicationsEditor IJCATR
Intelligent video surveillance system has emerged as a very important research topic in the computer vision field in the
recent years. It is well suited for a broad range of applications such as to monitor activities at traffic intersections for detecting
congestions and predict the traffic flow. Object classification in the field of video surveillance is a key component of smart
surveillance software. Two robust methodology and algorithms adopted for people and object classification for automated surveillance
systems is proposed in this paper. First method uses background subtraction model for detecting the object motion. The background
subtraction and image segmentation based on morphological transformation for tracking and object classification on highways is
proposed. This algorithm uses erosion followed by dilation on various frames. Proposed algorithm in first method, segments the image
by preserving important edges which improves the adaptive background mixture model and makes the system learn faster and more
accurately. The system used in second method adopts the object detection method without background subtraction because of the static
object detection. Segmentation is done by the bounding box registration technique. Then the classification is done with the multiclass
SVM using the edge histogram as features. The edge histograms are calculated for various bin values in different environment. The
result obtained demonstrates the effectiveness of the proposed approach.
PREDICTIVE MAINTENANCE AND ENGINEERED PROCESSES IN MECHATRONIC INDUSTRY: AN I...ijaia
The paper proposes the results of a research industry project concerning predictive maintenance process
optimization, applied to a machine cutting polyurethane. A company producing cutting machines, has been
provided with an online control system able to detect blade status of a machine supplied to a customer
producing polyurethane components. A software platform has been developed for the real time monitoring
of the blade status and for the prediction of the break up conditions adopting a multi-parametric data
analysis approach, based on the simultaneous use of unsupervised and supervised machine learning
algorithms. Specifically, the proposed method adopts a k-Means algorithm to classify bidimensional risk
maps, and a Long Short Term Memory (LSTM) one to predict the alerting levels based on the analysis of
the last values for some process variables. The analysed algorithms are applied to an experimental dataset.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
In recent times, the definition of internet of things has evolved to great extent and it means different things
to different people. However the basic idea of Internet of Things remains the same which is use of information and
communication Technologies(ICT’s) as well as Internet to provide efficient services to the mankind for their
optimum benefits. While implementing the Internet of Things itself is complex due to large of devices various link
layer technologies and services that are involved in such systems. In this paper, we specifically implement an urban
Internet of Things system which primarily gives an emphasis on smart educational institute which aims at
exploiting advanced communication technologies to support for administration of the institute and for the new
visitor who find it difficult to find their way around the institute. This paper thereby provides a comprehensive
survey of various technologies such as Android , Java, protocols and architecture for using Internet of Things in
Smart Institute. Furthermore ,this system will provide an overlook of the institute via the administration office
,playground and canteens. The user of the system will also get an static image map to roam around the institute.
Lastly the system will provide technical solutions and best practice guidelines for finding the way around the
institute and also help a new visitor in reaching his desired location.
Real Time Object Identification for Intelligent Video Surveillance ApplicationsEditor IJCATR
Intelligent video surveillance system has emerged as a very important research topic in the computer vision field in the
recent years. It is well suited for a broad range of applications such as to monitor activities at traffic intersections for detecting
congestions and predict the traffic flow. Object classification in the field of video surveillance is a key component of smart
surveillance software. Two robust methodology and algorithms adopted for people and object classification for automated surveillance
systems is proposed in this paper. First method uses background subtraction model for detecting the object motion. The background
subtraction and image segmentation based on morphological transformation for tracking and object classification on highways is
proposed. This algorithm uses erosion followed by dilation on various frames. Proposed algorithm in first method, segments the image
by preserving important edges which improves the adaptive background mixture model and makes the system learn faster and more
accurately. The system used in second method adopts the object detection method without background subtraction because of the static
object detection. Segmentation is done by the bounding box registration technique. Then the classification is done with the multiclass
SVM using the edge histogram as features. The edge histograms are calculated for various bin values in different environment. The
result obtained demonstrates the effectiveness of the proposed approach.
An Improved Tracking Using IMU and Vision Fusion for Mobile Augmented Reality...ijma
Mobile Augmented Reality (MAR) is becoming an important cyber-physical system application given the
ubiquitous availability of mobile phones. With the need to operate in unprepared environments, accurate
and robust registration and tracking has become an important research problem to solve. In fact, when
MAR is used for tele-interactive applications involving large distances, say from an accident site to
insurance office, tracking at both the ends is desirable and further it is essential to appropriately fuse
inertial and vision sensors’ data. In this paper, we present results and discuss some insights gained in
marker-less tracking during the development of a prototype pertaining to an example use case related to
breakdown/damage assessment of a vehicle. The novelty of this paper is in bringing together different
components and modules with appropriate enhancements towards a complete working system.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Secure and reliable wireless advertising system using intellectual characteri...TELKOMNIKA JOURNAL
Smart cities wireless advertising (smart mobile-AD) filed is one of the well-known area of research where smart devices using mobile ad hoc networks (MANET) platform for advertisement and marketing purposes. Wireless advertising through multiple fusion internet of things (IoT) sensors is one of the important field where the sensors combines multiple sensors information and accomplish the control of self-governing intelligent machines for smart cities advertising framework. With many advantages, this field has suffered with data security. In order to tackle security threats, intrusion detection system (IDS) is adopted. However, the existing IDS system are not able to fulfill the security requirements. This paper proposes an intellectual characteristic selection algorithm (ICSA) integrated with normalized intelligent genetic algorithm-based min-max feature selection (NIGA-MFS). The proposed solution designs for wireless advertising system for business/advertising data security and other transactions using independent reconfigurable architecture. This approach supports the wireless advertising portals to manage the data delivery by using 4G standard. The proposed reconfigurable architecture is validated by using applications specific to microcontrollers with multiple fusion IoT sensors.
Face Recognition Based Intelligent Door Control Systemijtsrd
This paper presents the intelligent door control system based on face detection and recognition. This system can avoid the need to control by persons with the use of keys, security cards, password or pattern to open the door. The main objective is to develop a simple and fast recognition system for personal identification and face recognition to provide the security system. Face is a complex multidimensional structure and needs good computing techniques for recognition. The system is composed of two main parts face recognition and automatic door access control. It needs to detect the face before recognizing the face of the person. In face detection step, Viola Jones face detection algorithm is applied to detect the human face. Face recognition is implemented by using the Principal Component Analysis PCA and Neural Network. Image processing toolbox which is in MATLAB 2013a is used for the recognition process in this research. The PIC microcontroller is used to automatic door access control system by programming MikroC language. The door is opened automatically for the known person according to the result of verification in the MATLAB. On the other hand, the door remains closed for the unknown person. San San Naing | Thiri Oo Kywe | Ni Ni San Hlaing ""Face Recognition Based Intelligent Door Control System"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23893.pdf
Paper URL: https://www.ijtsrd.com/engineering/electrical-engineering/23893/face-recognition-based-intelligent-door-control-system/san-san-naing
Intelligent GIS-Based Road Accident Analysis and Real-Time Monitoring Automat...CSCJournals
It has been a big concern for many people and government to reduce the amount of road accident specially in Malaysia since it could be a big threat to this country. Malaysian government has spent millions of money in order to reduce the number of accident occurrence through several modes of campaign. Unfortunately, from years to years the number keeps increasing. The lack of a comprehensive accident recording and analysis system in Malaysia can be effective in these kinds of problems. By making use of IRAS (Intelligent Road Accident System), the police would be control and manage whole accident events as a real-time monitoring system. This system exploits WiMAX and GPRS communications to connect to the server for transfer the specific data to the data center. This system can be used for a comprehensive intelligent GIS-based solution for accident analysis and management. The system is developed based on object and aspect oriented software design such as .NET technology.
Improving face recognition by artificial neural network using principal compo...TELKOMNIKA JOURNAL
The face-recognition system is among the most effective pattern recognition and image analysis techniques. This technique has met great attention from academic and industrial fields because of its extensive use in detecting the identity of individuals for monitoring systems, security and many other practical fields. In this paper, an effective method of face recognition was proposed. Ten person's faces images were selected from ORL dataset, for each person (42) image with total of (420) images as dataset. Features are extracted using principle component analysis PCA to reduce the dimensionality of the face images. Four models where created, the first one was trained using feed forward back propagation learning (FFBBL) with 40 features, the second was trained using 50 features with FFBBL, the third was trained using the same features but using Elman Neural Network. For each person (24) image used as training set for the neural networks, while the remaining images used as testing set. The results showed that the proposed method was effective and highly accurate. FFBBL give accuracy of (98.33,97.14) with (40, 50) features respectively, while Elman gives (98.33, 98.80) for with (40, 50) features respectively.
IEEE EED2021 AI use cases in Computer VisionSAMeh Zaghloul
AI Use Cases in Computer Vision
Introduction and Overview about AI Use Cases in Computer Vision, to answer a basic question: “How Machines See?”, covering Neural Networks, Object detection and recognition, Content-based image retrieval, Object tracking, Image restoration, Scene reconstruction, Computer Vision Tools, Frameworks, Pretrained Models, and Public Train/Test Datasets.
With real-project examples on using Computer Vision in Egyptian Hieroglyph Alphabet recognition, Face Recognition/Matching, in addition to hands-on interactive session on Object/Image Tagging/Annotation on Videos/Images to prepare model training dataset.
Emergence of Industry 4.0 in current economic trend promotes the usage of Internet of Things (IoT) in product development. Counting people on streets or at entrances of places is indeed beneficial for security, tracking and marketing purposes. The usage of cameras or closed-circuit television (CCTV) for surveillance purposes has emerged the need of tools for the digital imagery content analysis to improve the system. The purpose of this project is to design a cloud-based people counter using Raspberry Pi embedded system and send the received data to ThingSpeak, IoT platform. The initial stage of the project is simulation and coding development using OpenCV and Python. For the hardware development, a Pi camera is used to capture the video footage and monitor the people movement. Raspberry Pi acts as the microcontroller for the system and process the video to perform people counting. Experiment have been conducted to measure the performance of the system in the actual environment, people counting on saved video footage and visualized the data on ThingSpeak platform.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Image steganography is the art of hiding a message, image, or file within another message, image, or file. Likely, an old term in Ancient Greek, Steganography is derived from steganos meaning ―”concealed” and graphein meaning ―”writing”, in other word we can say it refers to the science of “invisible” communication. Unlike cryptography, where the goal is to secure communications from an eavesdropper, steganography techniques strive to hide the very presence of the message itself froman observer. In this research paper we deal with hiding a digital message image inside a digital cover image leading us to the stego image. With the combination of Message Preparation using Spatial Domain image modification technique, discrete cosine transforms (DCT) and image scrambled using modified Arnold Transform, an algorithm based on the three technologies is proposed. The effectiveness of the proposed methods has been estimated by computing Mean square error (MSE) and Peak Signal to Noise Ratio (PSNR) and experimental result shows that the proposed algorithm is highly secured with good perceptual invisibility
A Survey on Mobile Sensing Technology and its PlatformEswar Publications
Now a days, mobile networks is increasingly becoming important part of everyday life due which there is a rapid evolution mobile phone. Mobile phone comes into a powerful sensing platform. There are many scientists which are engaged in the emerging field of mobile sensing from a variety of existing communities, such as, mobile systems, machine learning and human computer interaction. The research and development in this field is rapid resulting in indispensable carry-on of daily life. But with the increase in development, data integrity and security has also become an important factor to take into consideration. Importantly, today’s smart phones are programmable and come with a growing set of cheap powerful embedded sensors, which are enabling the emergence of personal, group, and community scale sensing applications. The mobile sensing platform provides many facilities like, it helps to communicate to Wireless sensor networks through a mobile sensor router Which attached to a users mobile phone. It helps in analysis of the sensed data which is derived from networks by cooperating with sensor middle- ware on a remote server to capture ones contexts. It also helps in providing context aware services for mobile users of cellular telephones. In this paper, we will discuss about
different mobile sensing platforms that provides context-aware services for mobile users by accessing the surrounding wireless sensor networks. Along with this, we will briefly discuss some of the emerging sensing paradigms.
The detection of moving object is an important in many applications such as a vehicle identification in a traffic monitoring system,human detection in a crime branch.In this paper we identify a vehicle in a video sequence.This paper briefly explain the detection of moving vehicle in a video.We introduce a new algorithm BGS for idntifying vehicle in a video sequence. First, we differentiate the foreground from background in frames by learning the background. Then, the image is divided into many small nonoverlapped frames. The candidates of the vehicle part can be found from the frames if there is some change in gray level between the current image and the background. The extracted background subtraction method is used in subsequent analysis to detect a vehicle and classify moving vehicle.
Software engineering model based smart indoor localization system using deep-...TELKOMNIKA JOURNAL
During the last few years, the allocation of objects or persons inside a specific
building is highly required. It is well known that the global positioning system
(GPS) cannot be adopted in indoor environment due to the lack of signals.
Therefore, it is important to discover a new way that works inside.
The proposed system uses the deep learning techniques to classify places based
on capturing images. The proposed system contains two parts: software part
and hardware part. The software part is built based on software engineering
model to increase the reliability, flexibility, and scalability. In addition,
this part, the dataset is collected using the Raspberry Pi III camera as training
and validating data set. This dataset is used as an input to the proposed deep
learning model. In the hardware part, Raspberry Pi III is used for loading
the proposed model and producing prediction results and a camera that is used
to collect the images dataset. Two wheels’ car is adopted as an object
for introducing indoor localization project. The obtained training accuracy
is 99.6% for training dataset and 100% for validating dataset.
An Improved Tracking Using IMU and Vision Fusion for Mobile Augmented Reality...ijma
Mobile Augmented Reality (MAR) is becoming an important cyber-physical system application given the
ubiquitous availability of mobile phones. With the need to operate in unprepared environments, accurate
and robust registration and tracking has become an important research problem to solve. In fact, when
MAR is used for tele-interactive applications involving large distances, say from an accident site to
insurance office, tracking at both the ends is desirable and further it is essential to appropriately fuse
inertial and vision sensors’ data. In this paper, we present results and discuss some insights gained in
marker-less tracking during the development of a prototype pertaining to an example use case related to
breakdown/damage assessment of a vehicle. The novelty of this paper is in bringing together different
components and modules with appropriate enhancements towards a complete working system.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Secure and reliable wireless advertising system using intellectual characteri...TELKOMNIKA JOURNAL
Smart cities wireless advertising (smart mobile-AD) filed is one of the well-known area of research where smart devices using mobile ad hoc networks (MANET) platform for advertisement and marketing purposes. Wireless advertising through multiple fusion internet of things (IoT) sensors is one of the important field where the sensors combines multiple sensors information and accomplish the control of self-governing intelligent machines for smart cities advertising framework. With many advantages, this field has suffered with data security. In order to tackle security threats, intrusion detection system (IDS) is adopted. However, the existing IDS system are not able to fulfill the security requirements. This paper proposes an intellectual characteristic selection algorithm (ICSA) integrated with normalized intelligent genetic algorithm-based min-max feature selection (NIGA-MFS). The proposed solution designs for wireless advertising system for business/advertising data security and other transactions using independent reconfigurable architecture. This approach supports the wireless advertising portals to manage the data delivery by using 4G standard. The proposed reconfigurable architecture is validated by using applications specific to microcontrollers with multiple fusion IoT sensors.
Face Recognition Based Intelligent Door Control Systemijtsrd
This paper presents the intelligent door control system based on face detection and recognition. This system can avoid the need to control by persons with the use of keys, security cards, password or pattern to open the door. The main objective is to develop a simple and fast recognition system for personal identification and face recognition to provide the security system. Face is a complex multidimensional structure and needs good computing techniques for recognition. The system is composed of two main parts face recognition and automatic door access control. It needs to detect the face before recognizing the face of the person. In face detection step, Viola Jones face detection algorithm is applied to detect the human face. Face recognition is implemented by using the Principal Component Analysis PCA and Neural Network. Image processing toolbox which is in MATLAB 2013a is used for the recognition process in this research. The PIC microcontroller is used to automatic door access control system by programming MikroC language. The door is opened automatically for the known person according to the result of verification in the MATLAB. On the other hand, the door remains closed for the unknown person. San San Naing | Thiri Oo Kywe | Ni Ni San Hlaing ""Face Recognition Based Intelligent Door Control System"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23893.pdf
Paper URL: https://www.ijtsrd.com/engineering/electrical-engineering/23893/face-recognition-based-intelligent-door-control-system/san-san-naing
Intelligent GIS-Based Road Accident Analysis and Real-Time Monitoring Automat...CSCJournals
It has been a big concern for many people and government to reduce the amount of road accident specially in Malaysia since it could be a big threat to this country. Malaysian government has spent millions of money in order to reduce the number of accident occurrence through several modes of campaign. Unfortunately, from years to years the number keeps increasing. The lack of a comprehensive accident recording and analysis system in Malaysia can be effective in these kinds of problems. By making use of IRAS (Intelligent Road Accident System), the police would be control and manage whole accident events as a real-time monitoring system. This system exploits WiMAX and GPRS communications to connect to the server for transfer the specific data to the data center. This system can be used for a comprehensive intelligent GIS-based solution for accident analysis and management. The system is developed based on object and aspect oriented software design such as .NET technology.
Improving face recognition by artificial neural network using principal compo...TELKOMNIKA JOURNAL
The face-recognition system is among the most effective pattern recognition and image analysis techniques. This technique has met great attention from academic and industrial fields because of its extensive use in detecting the identity of individuals for monitoring systems, security and many other practical fields. In this paper, an effective method of face recognition was proposed. Ten person's faces images were selected from ORL dataset, for each person (42) image with total of (420) images as dataset. Features are extracted using principle component analysis PCA to reduce the dimensionality of the face images. Four models where created, the first one was trained using feed forward back propagation learning (FFBBL) with 40 features, the second was trained using 50 features with FFBBL, the third was trained using the same features but using Elman Neural Network. For each person (24) image used as training set for the neural networks, while the remaining images used as testing set. The results showed that the proposed method was effective and highly accurate. FFBBL give accuracy of (98.33,97.14) with (40, 50) features respectively, while Elman gives (98.33, 98.80) for with (40, 50) features respectively.
IEEE EED2021 AI use cases in Computer VisionSAMeh Zaghloul
AI Use Cases in Computer Vision
Introduction and Overview about AI Use Cases in Computer Vision, to answer a basic question: “How Machines See?”, covering Neural Networks, Object detection and recognition, Content-based image retrieval, Object tracking, Image restoration, Scene reconstruction, Computer Vision Tools, Frameworks, Pretrained Models, and Public Train/Test Datasets.
With real-project examples on using Computer Vision in Egyptian Hieroglyph Alphabet recognition, Face Recognition/Matching, in addition to hands-on interactive session on Object/Image Tagging/Annotation on Videos/Images to prepare model training dataset.
Emergence of Industry 4.0 in current economic trend promotes the usage of Internet of Things (IoT) in product development. Counting people on streets or at entrances of places is indeed beneficial for security, tracking and marketing purposes. The usage of cameras or closed-circuit television (CCTV) for surveillance purposes has emerged the need of tools for the digital imagery content analysis to improve the system. The purpose of this project is to design a cloud-based people counter using Raspberry Pi embedded system and send the received data to ThingSpeak, IoT platform. The initial stage of the project is simulation and coding development using OpenCV and Python. For the hardware development, a Pi camera is used to capture the video footage and monitor the people movement. Raspberry Pi acts as the microcontroller for the system and process the video to perform people counting. Experiment have been conducted to measure the performance of the system in the actual environment, people counting on saved video footage and visualized the data on ThingSpeak platform.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Image steganography is the art of hiding a message, image, or file within another message, image, or file. Likely, an old term in Ancient Greek, Steganography is derived from steganos meaning ―”concealed” and graphein meaning ―”writing”, in other word we can say it refers to the science of “invisible” communication. Unlike cryptography, where the goal is to secure communications from an eavesdropper, steganography techniques strive to hide the very presence of the message itself froman observer. In this research paper we deal with hiding a digital message image inside a digital cover image leading us to the stego image. With the combination of Message Preparation using Spatial Domain image modification technique, discrete cosine transforms (DCT) and image scrambled using modified Arnold Transform, an algorithm based on the three technologies is proposed. The effectiveness of the proposed methods has been estimated by computing Mean square error (MSE) and Peak Signal to Noise Ratio (PSNR) and experimental result shows that the proposed algorithm is highly secured with good perceptual invisibility
A Survey on Mobile Sensing Technology and its PlatformEswar Publications
Now a days, mobile networks is increasingly becoming important part of everyday life due which there is a rapid evolution mobile phone. Mobile phone comes into a powerful sensing platform. There are many scientists which are engaged in the emerging field of mobile sensing from a variety of existing communities, such as, mobile systems, machine learning and human computer interaction. The research and development in this field is rapid resulting in indispensable carry-on of daily life. But with the increase in development, data integrity and security has also become an important factor to take into consideration. Importantly, today’s smart phones are programmable and come with a growing set of cheap powerful embedded sensors, which are enabling the emergence of personal, group, and community scale sensing applications. The mobile sensing platform provides many facilities like, it helps to communicate to Wireless sensor networks through a mobile sensor router Which attached to a users mobile phone. It helps in analysis of the sensed data which is derived from networks by cooperating with sensor middle- ware on a remote server to capture ones contexts. It also helps in providing context aware services for mobile users of cellular telephones. In this paper, we will discuss about
different mobile sensing platforms that provides context-aware services for mobile users by accessing the surrounding wireless sensor networks. Along with this, we will briefly discuss some of the emerging sensing paradigms.
The detection of moving object is an important in many applications such as a vehicle identification in a traffic monitoring system,human detection in a crime branch.In this paper we identify a vehicle in a video sequence.This paper briefly explain the detection of moving vehicle in a video.We introduce a new algorithm BGS for idntifying vehicle in a video sequence. First, we differentiate the foreground from background in frames by learning the background. Then, the image is divided into many small nonoverlapped frames. The candidates of the vehicle part can be found from the frames if there is some change in gray level between the current image and the background. The extracted background subtraction method is used in subsequent analysis to detect a vehicle and classify moving vehicle.
Software engineering model based smart indoor localization system using deep-...TELKOMNIKA JOURNAL
During the last few years, the allocation of objects or persons inside a specific
building is highly required. It is well known that the global positioning system
(GPS) cannot be adopted in indoor environment due to the lack of signals.
Therefore, it is important to discover a new way that works inside.
The proposed system uses the deep learning techniques to classify places based
on capturing images. The proposed system contains two parts: software part
and hardware part. The software part is built based on software engineering
model to increase the reliability, flexibility, and scalability. In addition,
this part, the dataset is collected using the Raspberry Pi III camera as training
and validating data set. This dataset is used as an input to the proposed deep
learning model. In the hardware part, Raspberry Pi III is used for loading
the proposed model and producing prediction results and a camera that is used
to collect the images dataset. Two wheels’ car is adopted as an object
for introducing indoor localization project. The obtained training accuracy
is 99.6% for training dataset and 100% for validating dataset.
Cooperative hierarchical based edge-computing approach for resources allocati...IJECEIAES
Using mobile and Internet of Things (IoT) applications is becoming very popular and obtained researchers’ interest and commercial investment, in order to fulfill future vision and the requirements for smart cities. These applications have common demands such as fast response, distributed nature, and awareness of service location. However, these requirements’ nature cannot be satisfied by central systems services that reside in the clouds. Therefore, edge computing paradigm has emerged to satisfy such demands, by providing an extension for cloud resources at the network edge, and consequently, they become closer to end-user devices. In this paper, exploiting edge resources is studied; therefore, a cooperative-hierarchical approach for executing the pre-partitioned applications’ modules between edges resources is proposed, in order to reduce traffic between the network core and the cloud, where this proposed approach has a polynomial-time complexity. Furthermore, edge computing increases the efficiency of providing services, and improves end-user experience. To validate our proposed cooperative-hierarchical approach for modules placement between edge nodes’ resources, iFogSim toolkit is used. The obtained simulation results show that the proposed approach reduces network’s load and the total delay compared to a baseline approach for modules’ placement, moreover, it increases the network’s overall throughput.
Compact optimized deep learning model for edge: a reviewIJECEIAES
Most real-time computer vision applications, such as pedestrian detection, augmented reality, and virtual reality, heavily rely on convolutional neural networks (CNN) for real-time decision support. In addition, edge intelligence is becoming necessary for low-latency real-time applications to process the data at the source device. Therefore, processing massive amounts of data impact memory footprint, prediction time, and energy consumption, essential performance metrics in machine learning based internet of things (IoT) edge clusters. However, deploying deeper, dense, and hefty weighted CNN models on resource-constraint embedded systems and limited edge computing resources, such as memory, and battery constraints, poses significant challenges in developing the compact optimized model. Reducing the energy consumption in edge IoT networks is possible by reducing the computation and data transmission between IoT devices and gateway devices. Hence there is a high demand for making energy-efficient deep learning models for deploying on edge devices. Furthermore, recent studies show that smaller compressed models achieve significant performance compared to larger deep-learning models. This review article focuses on state-of-the-art techniques of edge intelligence, and we propose a new research framework for designing a compact optimized deep learning (DL) model deployment on edge devices.
Satellite image processing is an intricate task that requires vast computation and data processing, which cannot
be handled by a single computer. Furthermore, the processing of the massive amount of data accumulated by
the satellite is a huge challenge for the end user. Hence, grid computing is the essential platform to provide high
computing performance at the user end. This article reviews the grid services used for satellite image processing
and significant data processing.
Efficient and secure real-time mobile robots cooperation using visual servoing IJECEIAES
This paper deals with the challenging problem of navigation in formation of mobiles robots fleet. For that purpose, a secure approach is used based on visual servoing to control velocities (linear and angular) of the multiple robots. To construct our system, we develop the interaction matrix which combines the moments in the image with robots velocities and we estimate the depth between each robot and the targeted object. This is done without any communication between the robots which eliminate the problem of the influence of each robot errors on the whole. For a successful visual servoing, we propose a powerful mechanism to execute safely the robots navigation, exploiting a robot accident reporting system using raspberry Pi3. This reporting system testbed is used to send an accident notification, in the form of a specifical message. Experimental results are presented using nonholonomic mobiles robots with on-board real time cameras, to show the effectiveness of the proposed method.
Residual balanced attention network for real-time traffic scene semantic segm...IJECEIAES
Intelligent transportation systems (ITS) are among the most focused research in this century. Actually, autonomous driving provides very advanced tasks in terms of road safety monitoring which include identifying dangers on the road and protecting pedestrians. In the last few years, deep learning (DL) approaches and especially convolutional neural networks (CNNs) have been extensively used to solve ITS problems such as traffic scene semantic segmentation and traffic signs classification. Semantic segmentation is an important task that has been addressed in computer vision (CV). Indeed, traffic scene semantic segmentation using CNNs requires high precision with few computational resources to perceive and segment the scene in real-time. However, we often find related work focusing only on one aspect, the precision, or the number of computational parameters. In this regard, we propose RBANet, a robust and lightweight CNN which uses a new proposed balanced attention module, and a new proposed residual module. Afterward, we have simulated our proposed RBANet using three loss functions to get the best combination using only 0.74M parameters. The RBANet has been evaluated on CamVid, the most used dataset in semantic segmentation, and it has performed well in terms of parameters’ requirements and precision compared to related work.
Analysis and assessment software for multi-user collaborative cognitive radi...IJECEIAES
Computer simulations are without a doubt a useful methodology that allows to explore research queries and develop prototypes at lower costs and timeframes than those required in hardware processes. The simulation tools used in cognitive radio networks (CRN) are undergoing an active process. Currently, there is no stable simulator that enables to characterize every element of the cognitive cycle and the available tools are a framework for discrete-event software. This work presents the spectral mobility simulator in CRN called “App MultiColl-DCRN”, developed with MATLAB’s app designer. In contrast with other frameworks, the simulator uses real spectral occupancy data and simultaneously analyzes features regarding spectral mobility, decision-making, multi-user access, collaborative scenarios and decentralized architectures. Performance metrics include bandwidth, throughput level, number of failed handoffs, number of total handoffs, number of handoffs with interference, number of anticipated handoffs and number of perfect handoffs. The assessment of the simulator involves three scenarios: the first and second scenarios present a collaborative structure using the multi-criteria optimization and compromise solution (VIKOR) decision-making model and the naïve Bayes prediction technique respectively. The third scenario presents a multi-user structure and uses simple additive weighting (SAW) as a decision-making technique. The present development represents a contribution in the cognitive radio network field since there is currently no software with the same features.
Adaptive photovoltaic solar module based on internet of things and web-based ...IJECEIAES
This paper presents an intelligent of single axis automatic adaptive photovoltaic solar module. A static solar panel has an issue of efficiency on shading effects, irradiance of sunlight absorbed, and less power generates. This aims to design an effective algorithm tracking system and a prototype automatic adaptive solar photovoltaic (PV) module connected through internet of things (IoT). The system has successfully designated on solving efficiency optimization. A tracking system by using active method orientation and allows more power and energy are captured. The solar rotation angle facing aligned to the light-dependent resistor (LDR) voltage captured and high solar panel voltage measured by using Arduino microcontroller. Real-time data is collected from the dynamic solar panel, published on Node-Red webpage, and running interactive via android device. The system has significantly reduced time. Data captured by the solar panel then analyzed based on irradiance, voltage, current, power generated and efficiency. Successful results present a live data analytic platform with active tracking system that achieved larger power generated and efficiency of solar panel compared to a fixed mounted array. This research is significant that can help the user to monitor parameters collected by the solar panel thus able to increase 51.82% efficiency of the PV module.
DESIGN PATTERNS IN THE WORKFLOW IMPLEMENTATION OF MARINE RESEARCH GENERAL INF...AM Publications
This paper proposes the use of design patterns in a marine research general information platform. The development of the platform refers to a design of complicated system architecture. Creation and execution of the research workflow nodes and designing of visualization library suited for marine users play an important role in the whole software architecture. This paper studies the requirements characteristic in marine research fields and has implemented a series of framework to solve these problems based on object-oriented and design patterns techniques. These frameworks make clear the relationship in all directions between modules and layers of software, which communicate through unified abstract interface and reduce the coupling between modules and layers. The building of these frameworks is importantly significant in advancing the reusability of software and strengthening extensibility and maintainability of the system.
Homogenous and interoperable signaling computer interlocking through IEC 6149...IJECEIAES
The technological evolution of signaling systems has created a dependency from infrastructure managers to suppliers and industrials dominating the market. Indeed, for each deployed computer interlocking, the modification of field equipment is required to allow an adaptation with the new interlocking in terms of communication protocols and logical interface. In addition, to ensure safe traffic of trains, the communication of railway signaling data is necessary between interlockings. However, delayed deployments from one station to another make the establishment of communication channels costly and difficult, or even impossible, since each supplier keeps confidential its communication protocols and usually opts for interfacing based on wired logic. This paper presents our approach to a homogeneous architecture of interlocking meeting modularity requirements, interoperability, and logical interfacing between interlockings. This approach relies on a classification of internal functions of the computer interlocking, a distribution of the execution of those functions and making useful information available for interfaces between adjacent interlockings through the IEC 61499 standard coupled with service-oriented architecture (SOA).
Smart surveillance systems play an important role in security today. The goal of security systems is to protect users against fires, car accidents, and
other forms of violence. The primary function of these systems is to offer security in residential areas. In today’s culture, protecting our homes is
critical. Surveillance, which ranges from private houses to large corporations, is critical in making us feel safe. There are numerous machine learning algorithms for home security systems; however, the deep learning convolutional neural network (CNN) technique outperforms the others. The
Keras, Tensorflow, Cv2, Glob, Imutils, and PIL libraries are used to train and assess the detection method. A web application is used to provide a
user-friendly environment. The flask web framework is used to construct it. The flash-mail, requests, and telegram application programming interface (API) apps are used in the alerting approach. The surveillance system tracks
abnormal activities and uses machine learning to determine if the scenario is normal or not based on the acquired image. After capturing the image, it is
compared with the existing dataset, and the model is trained using normal events. When there is an anomalous event, the model produces an output from which the mean distance for each frame is calculated.
In recent years, the number of end users connected to the internet of things (IoT) has increased, and we have witnessed the emergence of the cloud computing paradigm. These users utilize network resources to meet their quality of service (QoS) requirements, but traditional networks are not configured to backing maximum of scalability, real-time data transfer, and dynamism, resulting in numerous challenges. This research presents a new platform of IoT architecture that adds the benefits of two new technologies: software-defined networking and fog paradigm. Software-defined networking (SDN) refers to a centralized control layer of the network that enables sophisticated methods for traffic control and resource allocation. So, fog paradigm allows for data to be analyzed and managed at the edge of the network, making it suitable for tasks that require low and predictable delay. Thus, this research provides an in-depth view of the platform organize and performance of its base ingredients, as well as the potential uses of the suggested platform in various applications.
Technology Content Analysis with Technometric Theory Approach to Improve Perf...Nooria Sukmaningtyas
Radiologic installation be facilitated with medical equipment for supporting of health services in
investigation of disease. There are 3 (three) criteria technology of equipment: investigation with
sophisticated equipment (CT scans single slice), investigation with a medium-sized enterprises equipment
(general x-ray 300 mA / 125 KV) and simple equipment (Portable Dental x-ray 8mA /70 KV). In view of
contribution to the Hospital, Radiologic installation from 2008 until 2012 has decreased, the data as
follows: The year 2008 was 6.8 percent; in 2009 was 4.3 percent; in 2010 was 2.5 percent; in 2011 was
2.3 percent; and in 2012 was 2.6 percent.By using approach of technometric theory, the study measures
the significant contribution of each component of technology that consists of aspects: Technoware,
Humanware, Inforware, Orgaware in Radiologic Installation, and also want to know about the
sophistication of the technology which is used in indicators Technology contribution coefficien (TCC), so
factors that affect experienced performance result can be known, where TCC are: TCC High Technology
TCC_tt =0,490 if T_tt= 0,387 H= 0,519 I= 0,538 O=0,534 TCC Middle technology TCC_tm=0,443 if
T_tm=0,258 H=0,519 I=0,538 O=0,534TCC Simple technology TCC_ts =0,398 if T_ts=0,168 H=0,519
I=0,538 O=0,534If the value of component technology (T,H,I,O) is less than TCC, its means that
Radiologic Installation Unit is in decreasing phase, a condition that cannot be left, need the directors’s
action immediately to formulate the right and fast policies to protect it from lost. The final result of study is a
gap almost everywhere from the three technology component Humanware = 0,519, Inforware = 0,538,
Orgaware = 0,534, but the gap between most components in technology aspects Technoware (0,387,
0,258, 0,168), that means that development strategy of Radiologic Installation unit be prioritized on
increasing aspects Technoware (rejuvenation medical equipment).
Data Exchange Design with SDMX Format for Interoperability Statistical DataNooria Sukmaningtyas
Today’s concept of Open Government Data (OGD) for openness, transparency and ease of
access of data owned by government agencies becomes increasingly important. This initiative emerges
from the demand of data usersforthe data belongs to the government agencies. The data services
providing an easy access, cheap, fast, and interoperability are needed by the users and becomes
important indicator performance for respective government agencies. Statistical Data and Metadata
Exchange (SDMX) is a new standard format in the data dissemination activities particularly in the
exchange of statistical data and metadata via Internet. In this respect SDMX support the implementation of
OGD project. This paper is on the technical design, development and implementation of data and
metadata exchange service of statistical data using SDMX format to support interoperability data through
web services. Three results are proposed: (i) framework for standardization of structure of statistical
publications data model with SDMX; (ii) design architecture of data sharing model; and (iii) web service
implementation of data and metadata exchange service using Service Oriented Analysis and Design
(SOAD) method. Implementation at Statistics Indonesia (BPS) is chosen as a case study to prove the
design concept. It is shown through quantitative assessment and black box testing that the design
achieves its objective.
The knowledge management is a model involving the information system in the knowledge
processing. “Tim Penyelesaian Kerugian Negara” (TPKN) is one of sources of information related to the
state loss settlement, so it needs the development of knowledge management system on the state loss
settlement to ease the users when looking for the references of knowledge as completely as possible,
accurately, and quickly. This research aims to develop the system of knowledge management on the state
loss in LAPAN (SIMAPKLA). The used research methodology is Knowledge Management System Life
Cycle (KMSLC). The tacit, explicit knowledge is taken from the experts and it is stored in the Knowledge
Base (KB). The design model uses the approach with the orientation of object and implementation with Yii
Framework and blackbox testing. The menu on this system includes home, about us, dictionary, news,
meeting schedulles, knowledge about state loss, e-document, progress, forum, and contact us. Based on a
series of tests, in the aspect of functionality, this system is suitable and useful to share knowledge and
know the development of state loss settlement.
Automatic Extraction of Diaphragm Motion and Respiratory Pattern from Time-se...Nooria Sukmaningtyas
Thoracic time-sequential MRI can be used to assess diaphragm motion pattern without exposing
radiation to subject. Clinicians may employ the motion to evaluate the severeness of chronic obstructive
pulmonary disease (COPD). This study proposed a novel method of diaphragm motion extraction method
on time-sequential thoracic MRI in sagittal plane. Otsu’s threshold and active contour algorithm are used to
obtain diaphragm boundary. An automatic diaphragm motion tracking and extraction of respiratory pattern
are also performed based on the diaphragm boundary. A total of 1200 frames time-sequential MRI in
sagittal plane was obtained for total of 15 subjects (8 healthy volunteers and 7 COPD patients). The
proposed method successfully extracts diaphragm motion and respiratory patterns for both healthy
volunteers and COPD patients.
A dual-frequency microstrip patch antennas has been presented and used for 802.11WLAN
applications. The antennas had been designed, simulated and parametrically studied in CST Microwave
studio. By introducing u-slot, dual-band operation with its operating mode centered at frequency 2.4GHz,
3.65GHz and 5.2GHz had been obtained. The gain and directivity had been improved by adjusting the
parameters of the antennas. The gain of the proposed designs was 6.019dBi, 4.04dBi and 6.22dBi and
directivity was 6.02dBi, 4.05dBi and 6.22dBi at resonant frequencies 2.4GHz, 3.6GHz and 5.2GHz
respectively. The patch antennas had been proposed to be used in portable devices that require
miniaturized constituent parts.
The Detection of Straight and Slant Wood Fiber through Slop Angle Fiber FeatureNooria Sukmaningtyas
Quality control is one of important process that can not be avoided in industry. Image processing
technique is required to distinguish the quality of wood. If it can be done automatically by the computer, it
will be very helpful. This paper discusses the detection of straight and slant wood fiber to distinguish its
quality. This paper proposes an algorithm by using only two features i.e. mean (average value of slop
angle fiber) and maximumangle (the maximum value of slop angle fiber). Then the classification method is
used by tresholding. The result shows the performance is achieved on accuracy 79.2%
Active Infrared Night Vision System of Agricultural VehiclesNooria Sukmaningtyas
Active infrared night vision system was significant for night driving and it has been greatly used on
limousine car. Design active infrared night vision system for agricultural vehicles greatly improved the night
vision of them and it was an inevitable trend. Comparing parameters of various night vision systems and
designing active infrared night vision system of agricultural vehicles was significant for improving active
security of agricultural vehicles working at nighttime. By analyzing the infrared night vision system basic
parameters determined the structure form and basic parameters, calculated the infrared light wave width
and emission power to choose each components, designed active infrared night vision system’s structure
and determined parameters of agricultural vehicles.
Robot Three Dimensional Space Path-planning Applying the Improved Ant Colony ...Nooria Sukmaningtyas
To make robot avoid obstacles in 3D space, the Pheromone of Ant Colony Optimization (ACO) in
Fuzzy Control Updating is put forward, the Pheromone Updating value varies with The number of iterations
and the path-planning length by each ant . the improved Transition Probability Function is also proposed,
which makes more sense for each ant choosing next feasible point .This paper firstly, describes the Robot
Workspace Modeling and its path-planning basic method, which is followed by introducing the improved
designing of the Transition Probability Function and the method of Pheromone Fuzzy Control Updating of
ACO in detail. At the same time, the comparison of optimization between the pre-improved ACO and the
improved ACO is made. The simulation result verifies that the improved ACO is feasible and available.
Research on a Kind of PLC Based Fuzzy-PID Controller with Adjustable FactorNooria Sukmaningtyas
A kind of fuzzy-PID controller with adjustable factor is designed in this paper. Scale factor’s selfadjust
will come true. Fuzzy control algorithm is finished in STEP7 software, and then downloaded in S7-
300 PLC. WinCC software will be used to control the change-trend in real time. Data communication
between S7-300 PLC and WinCC is achieved by MPI. The research shows that this fuzzy-PID controller
has better robust capability and stability. It’s an effective method in controlling complex long time-varying
delay systems.
This paper proposed a nonlinear robust control for spacecraft attitude based on passivity and
disturbance suppression vector. The spacecraft model was described using quaternion. The control law
introduced the suppression vector of external disturbances and had no information related to the system
parameters. The desired performance of spacecraft attitude control could be achieved using the designed
control law. And stability conditions of the nonlinear robust control for spacecraft attitude were given. The
stability could be proved by applying Lyapunov approach. The verification of the proposed attitude control
method was performed through a series of simulations. The numerical results showed the effectiveness of
the proposed control method in controlling the spacecraft attitude in the presence of external disturbances.
The main benefit of the proposed attitude control method does not need angular velocity measurement
and has its robustness against model uncertainties and external disturbances.
Remote Monitoring System for Communication Base Based on Short MessageNooria Sukmaningtyas
The automatic monitoring system of communication base which is an important means to realize
modernization of mobile communication base station management. In this paper, we implement a
monitoring system for communication base with three essential functions which are telemetry, remote
control and communication. In this system, data acquisition unit, data transmit unit and monitoring centre
unit are combined to form this monitoring system. The system can check the communication base status
anytime through GSM SMS (short message service), and can send predefined command to perform
remote data collection and monitoring in the special conditions. It is suitable especially for the alarm of
unusual situation, the monitoring of environmental information and entrance guard information. The paper,
firstly, proposes the architecture of the monitoring system; secondly, proposes the terminal of monitoring
system. The data collection terminal is studied and designed, including hardware design based on
embedded system and software design. Finally, presents implmentation and results. The monitoring
system can improve the integrity, reliability, flexibility and intellectuality of monitoring system. The system
with modular structure, which is low-cost, fitter and easier to move and operate, can be expanded
according to practical need and is reliable and effective through field test.
Tele-Robotic Assisted Dental Implant Surgery with Virtual Force FeedbackNooria Sukmaningtyas
The dental implant surgical applications full of risk because of the complex anatomical
architecture of craio-maxillofacial area. Therefore, the surgeons move towards computer-aided planning
for surgeries and then implementation using robotic assisted tele-operated techniques. This study divided
into four main parts. The first part is developed by computer-aided surgical planning by image modalities.
The second part is based on Virtual Surgical Environment through virtual force feedback haptic device.
The third part is implemented the experimental surgery by integrating the prototype surgical manipulator
with the haptic device poses using inverse kinematics method. The fourth part based on monitoring the
robotic manipulator pose by using image guided navigation system to calculate the position error of the
surgical manipulator. Thus, this tele-robotic system is able to comprehend the sense of complete practice,
improve skills and gain experience of the surgeon during the surgery. Finally, the experimental outcomes
show in satisfactory boundaries.
This paper proposes an adaptation mechanism based on adaptation planning graph for servicebased
business processes. First, a three-layer representation model of service-based business process is
introduced. Second, control-flow patterns of tasks, goal, logic model of service-based business process
and adaptation planning graph are introduced to enforce reliability of composite web services at run-time.
Finally, a simulation example of adaptation in service-based business processes is given. Simulations
prove that this approach can efficiently guarantee the reliability of composite services at run-time.
Review on Islanding Detection Methods for Photovoltaic InverterNooria Sukmaningtyas
Solar power generation, which is regarded as an ideal environment-friendly manner for power
generation, is getting more and more attention. When photovoltaic inverter is connected to the grid, the
island effect is a special problem to confront. This paper briefly analyzes the island effects and makes a
summary of both domestic and external research progress concerning islanding detection methods; the
islanding detection methods can be divided into two classes: one is grid-side detection; the other is local
detection. The local detection is generally divided into passive methods and active methods. The theory of
advantages and disadvantages of those methods are briefly introduced in this paper. At the end of the
paper, to deal with the disadvantages of those methods that are mentioned, it proposes the research
direction for deeper study of islanding detection methods.
Stabilizing Planar Inverted Pendulum System Based on Fuzzy Nine-point ControllerNooria Sukmaningtyas
In order to stabilize planar inverted pendulum, after analyzing the physical characteristics of the
planar inverted pendulum system, a pendulum nine-point controller and a car nine-point controller for Xaxis
and Y-axis were designed respectively. Then a fuzzy coordinator was designed using the fuzzy
control theory based on the priority of those two controllers, and the priority level of the pendulum is higher
than the car. Thus, the control tasks of each controller in each axis were harmonized successfully. The
designed control strategy did not depend on mathematical model of the system; it depended on the control
experience of people or the control experts. The compared experiments showed that the control strategy
was easy and effective, what was’s more; it had a very good robust feature.
Gross Error Elimination Based on the Polynomial Least Square Method in Integr...Nooria Sukmaningtyas
The measurement data of parameter in the electrical equipment contains many noises in subway
integrated monitoring system. To eliminate the impact of gross error in the measurement data, a
polynomial least square curve fitting algorithm is used in this paper. Based on the Rajda criterion, the
algorithm gives the variance estimation of the noises, and then uses dynamic threshold to detect and
replace the measurement data with gross error by statistical estimation. Finally, a data processing
procedure has been presented to deal with the gross error. The practical application indicates that the
proposed algorithm can effectively eliminate the gross error in many types of measurement signals so as
to ensure the reliability of the monitoring system.
Design on the Time-domain Airborne Electromagnetic Weak Signal Data Acquisiti...Nooria Sukmaningtyas
According to principle of transient electromagnetic method as well as its signal characteristics,
this paper designed and implemented a time-domain airborne electromagnetic weak signal data
acquisition system. With the use of the floating-point amplification technology, the system amplifies the
weak transient electromagnetic signal dynamically. CPLD and DSP were used as the decoding control
circuit and the main controller for processing the sampled data, respectively. The transient electromagnetic
signal acquisition system, which was designed with a dynamic range up to 144dB and a sampling rate up
to 100 kHz, meets the requirements of the high sampling rate with high precision and it has been applied in
the time-domain fixed-wing airborne electromagnetic mineral exploration.
INS/GPS integrated navigation system is studied in this paper for the hypersonic UAV in order to
satisfy the precise guidance requirements of hypersonic UAV and in response to the defects while the
inertial navigation system (INS) and the global positioning system (GPS) are being applied separately. The
information of UAV including position, velocity and attitude can be obtained by using INS and GPS
respectively after generating a reference trajectory. The corresponding errors of two navigation systems
can be obtained through comparing the navigation information of the above two guidance systems.
Kalman filter is designed to estimate the navigation errors and then the navigation information of INS are
corrected. The non-equivalence relationship between the platform misalignment angle and attitude error
angle are considered so that the navigation accuracy is further improved. The Simulink simulation results
show that INS/GPS integrated navigation system can help to achieve higher accuracy and better antiinterference
ability than INS navigation system and this system can also satisfy the navigation accuracy
requirements of hypersonic UAV.
Research on Space Target Recognition Algorithm Based on Empirical Mode Decomp...Nooria Sukmaningtyas
The space target recognition algorithm, which is based on the time series of radar cross section
(RCS), is proposed in this paper to solve the problems of space target recognition in the active radar
system. In the algorithm, EMD method is applied for the first time to extract the eigen of RCS time series.
The normalized instantaneous frequencies of high-frequency intrinsic mode functions obtained by EMD are
used as the eigen values for the recognition, and an effective target recognition criterion is established.
The effectiveness and the stability of the algorithm are verified by both simulation data and real data. In
addition, the algorithm could reduce the estimation bias of RCS caused by inaccurate evaluation, and it is
of great significance in promoting the target recognition ability of narrow-band radar in practice.
With the expanding of database of the watch list of anti-money laundering, improving the speed in
matching between the watch list and the database of account holders and clients’ transaction is especially
important. This paper proposes an improved AC-BM Algorithm, a matching algorithm of subsection, to
improve the speed of matching. Experiment results show the time performance of the improved algorithm
is better than traditional BM algorithm, AC algorithm and the AC-BM algorithm. It can improve the
efficiency of on-line monitoring of anti-money laundering.
Quality defects in TMT Bars, Possible causes and Potential Solutions.PrashantGoswami42
Maintaining high-quality standards in the production of TMT bars is crucial for ensuring structural integrity in construction. Addressing common defects through careful monitoring, standardized processes, and advanced technology can significantly improve the quality of TMT bars. Continuous training and adherence to quality control measures will also play a pivotal role in minimizing these defects.
NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...Amil Baba Dawood bangali
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Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
Vaccine management system project report documentation..pdfKamal Acharya
The Division of Vaccine and Immunization is facing increasing difficulty monitoring vaccines and other commodities distribution once they have been distributed from the national stores. With the introduction of new vaccines, more challenges have been anticipated with this additions posing serious threat to the already over strained vaccine supply chain system in Kenya.
Event Management System Vb Net Project Report.pdfKamal Acharya
In present era, the scopes of information technology growing with a very fast .We do not see any are untouched from this industry. The scope of information technology has become wider includes: Business and industry. Household Business, Communication, Education, Entertainment, Science, Medicine, Engineering, Distance Learning, Weather Forecasting. Carrier Searching and so on.
My project named “Event Management System” is software that store and maintained all events coordinated in college. It also helpful to print related reports. My project will help to record the events coordinated by faculties with their Name, Event subject, date & details in an efficient & effective ways.
In my system we have to make a system by which a user can record all events coordinated by a particular faculty. In our proposed system some more featured are added which differs it from the existing system such as security.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Automobile Management System Project Report.pdfKamal Acharya
The proposed project is developed to manage the automobile in the automobile dealer company. The main module in this project is login, automobile management, customer management, sales, complaints and reports. The first module is the login. The automobile showroom owner should login to the project for usage. The username and password are verified and if it is correct, next form opens. If the username and password are not correct, it shows the error message.
When a customer search for a automobile, if the automobile is available, they will be taken to a page that shows the details of the automobile including automobile name, automobile ID, quantity, price etc. “Automobile Management System” is useful for maintaining automobiles, customers effectively and hence helps for establishing good relation between customer and automobile organization. It contains various customized modules for effectively maintaining automobiles and stock information accurately and safely.
When the automobile is sold to the customer, stock will be reduced automatically. When a new purchase is made, stock will be increased automatically. While selecting automobiles for sale, the proposed software will automatically check for total number of available stock of that particular item, if the total stock of that particular item is less than 5, software will notify the user to purchase the particular item.
Also when the user tries to sale items which are not in stock, the system will prompt the user that the stock is not enough. Customers of this system can search for a automobile; can purchase a automobile easily by selecting fast. On the other hand the stock of automobiles can be maintained perfectly by the automobile shop manager overcoming the drawbacks of existing system.
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needs high requirement for real-time and stability. So a universal smart grid knowledge
visualization engine is designed based on open source game engine JME in this paper.
This paper mainly studies the implementation method of smart grid knowledge
visualization using VR technology. Create a attribute integration between different virtual
electrical facilities based on knowledge-base reasoning. Build the grid knowledge display scene
through the rational organization strategy, and then design its rapid generation algorithm.
Achieve collision detection based on a combination intelligent optimization algorithm of genetic
and non-linear programming. Propose scene rendering method based on interactive
coordination mechanism. Study on scene storage mechanism for the re-use preparation of
models and scene. Finally, verify feasibility and practicability of the method by the application
platform development of power operation virtual drill.
2.The Model of Smart Grid Knowledge Visualization Method
2.1. Related Work
Grid knowledge-base involves grid operation, management control, production and
sales as well as some other aspects of knowledge. Specifically, it includes: grid topology
knowledge base, electrical atomic devices knowledge base, grid operation control rules base,
grid stability analysis knowledge, grid fault diagnosis knowledge, power grid outliers monitoring
knowledge, the forecasting class knowledge base of power consumption, power generation and
load forecasting etc.
Figure 1. Grid knowledge visualization method processing model
In this paper, the grid knowledge is divided into reasoning, physics and events
knowledge. Reasoning type is the knowledge of decision support, and they are primarily used
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for knowledge property integration. Physics knowledge is defined as the nature properties
(manufacturer, model, etc.) of electrical equipment, which is used for static properties
integration. Event knowledge refers to the available equipment operating rules, and it is used for
action integration.
2.2. The Knowledge Visualization Model for Smart Grid
The process of the method (show as Figure 1) is: In VR technology, the smart grid
knowledge 3-D visualization model is implemented through establishing the mapping rules
between grid knowledge and virtual power device models. And Based on the rational
organization strategy of knowledge, the large-scale grid display scene is built, and then their
storage mechanism is studied for re-use preparation. This can achieve real-time and a full range
of virtual reality display for grid operation status, thereby increasing the hierarchy level of grid
visualization. Users can not only enjoy the visual feast but also improve understanding on use
grid knowledge more intuitively and quickly.
3. Virtual Electrical Equipment Model Construction
3.1. Model Base Construction
In order to solve slow loading because of the large size, quantity of models and the
opacity problem for animation model parameter-call[8], the format conversion concept of original
models is proposed.
Its implementation is: import original models into format converter using modeling
software (MAYA, etc.) to isolate the geometric model and physical parameters. The physical
parameters files will be called only when the corresponding event is triggered in the scene. The
experiment shows that this mechanism can improve the model loading speed significantly, and
is very convenient for developers to call the model parameters, improving the working efficiency.
The specific implementation process is shown in Figure 2.
Figure 2. Model format conversion
3.2. Property Integration Method Based on Knowledge-base Reasoning Technology
Property integration mainly includes knowledge integration, action integration, and static
properties integration. In property integration process, Use knowledge reasoning technique to
give the corresponding definition for them, and make preparation for their three-dimensional,
dynamic display. Specific description is as follows:
Knowledge integration, associate the electrical equipment with knowledge in knowledge
base by device number. When a user interacts with the device, you can view the knowledge of
device in particular time and specific circumstances. Action integration, on the one hand, the
device can respond to appropriate action in accordance with operating rules, such as circuit
breakers actions including opening and closing, etc, on the other hand, it includes voice
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tracking, visual tracking and viewpoint induction.An equipment property integration display chart
is showed in Figure 3
Figure 3. An equipment property integration display chart
4. Building of Electricity Virtual Scene
The virtual scene of smart grid knowledge visualization restored the actual electrical
work environment. It covers interior scene of cockpit and outside scene which used to perform
field operation. Construction of the virtual scene including organizational strategy, scene
rendering and scene store three parts, its construction process can be described as repeated
execution of these three stages.
The traditional platform used for scene building has many limitations [9]. Firstly, most of
them are focus on same fixed fields, just like many of them focused on the substation simulation
at present, this will result in that their versatility is reduced. Secondly, their scalability and
reusability are mostly confined to models and external programs, there are still large room for
improvement. Finally, there is no detailed design for the reusability of the whole scene and the
operational tasks.
4.1. Organizational Strategy of Electricity Virtual Scene
To maximize improve the efficiency of system development, this paper from the reality
proposed a scene dynamic building mechanism used for specific factors. The models (such as:
topography, light, etc.) that have lower factors and more general were extracted then packaged
in this mechanism which used a tree organization. Fixed node that created for each type of
generic model were bound to the scene tree root node. Thereby an original scene XML file was
created. Every time when you need to create a new scene, you must import the original scene
XML file first. Then you just need to edit the part that must be changed in the actual of the work
tasks.
Meanwhile, in order to improve the realism and immersion experience of the scene, you
can select corresponding knowledge or event from the knowledge-base then add them to the
relevant geometry model when you use modular construction technique to dynamically
construct geometric scene. The input and output interfaces that provided by the scene can
easily realize the use of data glove, virtual helmet and other three-dimensional interactive
devices. Details shown in Figure 4.
This mechanism can be applied to every areas of the smart grid. You only need to
improve the database of model and knowledge according to the requirement.
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4.2. Interactive Collaborative Rendering
A large number of structurally complex device model were contained in the electricity
virtual scene. For example, there will be millions of faces to be rendered in a single substation
virtual scene [10], it will seriously affect the overall visual effect if the rendering speed is to slow.
Therefore, in this paper, in order to improve the scene rendering speed and allow users to feel
more smoothly, the interactive collaborative rendering algorithms were used to render the scene
and the huge number of equipments.
Figure 4. Organizational strategy of electricity virtual scene
In order to achieve some kind of overall goal or function, the process that establishing
interconnected relationships between individuals to coordinate their interactions and regulate
their activities is named collaboration. Interactive collaborative rendering is based on distributed
rendering technology. Firstly, a number of scene rendering tasks on the screen were divided,
then the assigned rendering information node, which were corresponded to a data node, was
rendered separately and their rendering result was showed independently. Meanwhile, there
exist coordinate relationships between the tasks of rendering information node. These
coordination relationships which needed to be coordinated with each other include information
synchronization, edge stitching, the consistency of the scene content, etc. Finally, all the display
nodes were combined to display the final rendering results.
4.3. Scene Store and Reuse
In order to improve the reusability and promotional of the scene [11], this paper
introduced a file information storing method which is based on XML. Firstly, The no operating
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factors (such as: topography, illumination , etc.) were extracted and added to the original three-
dimensional scene in a generic model style. Meanwhile, the scene description file will
automatically record these information about the generic models, ultimately generate the
original scene description file. Every time when you create a new scene, you need call for the
original scene description file first, the existing generic model will be loaded according to the file,
then an original scene will be created. Details shown as Figure 5.
In this method, the models and their description information files that loaded in the
scene are separated. When building a new scene, the original scene will be generated
according to the original scene description file. Your job is to select the models form the model
database and add them to the scene according to the system wiring diagram, then select
knowledge from the knowledge-base and add them to the relevant model according to the
specific task.A new scene description information file will be reproduced after you finish
construction job. The new XML file directory information will be stored in the database. When
you need to re-operate the same scene, you can easily make calls from the database .
Figure 5. Scene store and reuse
5. Collision Detection Based on Swarm Intelligence and Bionic Computing
Corresponding to the real power scene, operators’ manipulate objects are electrical
equipment in virtual environment. Essentially, this is overall performance of the changing
relationship between the 3-D models shape and position. In order to manipulate virtual objects,
operators and other objects will appear “collision”. The two purposes of collision detection are
respectively the orientation of virtual objects detection and increasing realism [12, 13]. Solving
the shortest distance among different objects is one of the key technologies in collision
detection algorithm. The distance between two polyhedral is calculated by seeking and tracking
their nearest point in this class algorithm and if its value less than or equal to zero, the collision
will occur. In addition, to solve the existing problems of collision detection, low speed and
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precision, the distance in it is reduced to the calculation of a constrained nonlinear programming
problem in this paper. Moreover, traditional optimization algorithms, such as linear programming
and integer programming, is applied to solve the small scale problems due to their complexity,
while they are not suitable for practical engineering applications. So the swarm intelligence and
bionic computing technologies are introduced to solve the collision detection problems.
Specifically, combined tabu search with genetic algorithm is proposed in this paper.
Tabu search algorithm local search ability is strong while the global search capability is weak.
On the contrary, the global search ability is strong and the local search capability is weak of
genetic algorithm, so generally, it only gets suboptimal solution, rather than the optimal one. The
genetic algorithm adopts selection, cross and mutation operators to search. Thus, this method
combines the advantages of two algorithms, one for global search using genetic algorithm, one
using tabu search algorithm for local search in order to get the optimal solution.
5.1. Related Theoretical Foundation
Definition 1: given m number points 1 2, , ..., n
mx x x R ( n
R is the n-dimensional space)
real number 1 2, ,..., n ,and 1 1 ... n mx x is linear combination of 1 2, , ..., mx x x . Specially,
when 1 ... 1n and 1 2, ,..., 0n , then 1 1 ... n mx x is known as the convex
combination of 1 2, ,..., mx x x .
Definition 2: Suppose n
s R , then all of convex combinations of any finite points in s
is called the convex hull of it, and it can be described as ( )H s .
1
1
| , 0, 1,...,
( )
1,
m
i i i
i
m
i
i
x x s i m
H s
m N
(1)
Here: N is represented as the set of all positive numbers.
Definition 3: the definition of convex polyhedron distance model: ,A BMind x y is
represented as the shortest distance between convex bodies A and B, x represents a point on
the object A, and y represents a point on the object B. Combined with the above definitions, the
shortest distance between objects can be defined as below:
,
1 1
m n
A B i i j j
i j
M ind x y
(2)
Here:
1
m
i i
i
x
is represented as a point x on A,
1
n
j j
j
y
is represented as a point y on B,
and i with j should meet the requirements respectively as below:
1
1
1, 0, 1, 2, ..., ;
1; 0, 1, 2, ..., .
n
i i
i
n
j j
j
st i n
st j n
(3)
So by using a convex hull of vertices to represent convex polyhedron, the shortest
distance between objects can be converted into a nonlinear programming problem with
constraints. Suppose i and j are the points at ,A BMind getting the minimum value under
satisfying the equations and inequalities constraints. For example, if , 0A BMind then, A and B
will occur collision. Else , 0A BMind then, A and B are separated from each other. Since A and
B vertex information is known, it is mainly solving the time complexity of optimization, and
combined nonlinear programming with genetic algorithm is proposed to solve it in this paper.
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5.2. The Implementation of Tasu Search-Genetic Algorithm
5.2.1. The Algorithm Flowchart
Figure 6. The algorithm flowchart
5.2.2. Dealing with Constraints
The key step that applied the algorithm to solving the optimal problem is constraints
processing. Therefore, the mathematical model makes processing on equality constraints and
constraints contained only upper and lower limits. Conditions for equality constraints, assuming
that there are m independent equations, then the m variables can be linearly expressed by
remaining n-m variables. Taking the converted equations into constraints contained lower and
upper limits or inequality ones, thus equality constraints will be eliminated. Conditions for
constrains processing only contained the upper and lower limits, based on the solutions
accuracy requirements, use the binary code variables, connect n binary bit strings together
sequentially to form each individual code.
5.2.3. Genetic Operation
(1) The fitness function determination
Fitness function is used to distinguish individuals’ quality in a group, is the sole basis for
natural selection, and generally is transformed by the objective function. since the algorithm is
used to solve the minimum value of function, fitness assignment function using sequential
method: [ ( )] ( )F f x ranking obj (here, obj represents the output of object function) is taken as
the fitness function. The smaller function value is, the greater fitness value is, and the better
individual is.
(2) Selection operation
Ergodic random sampling (sus) is taken as the selection operator in this algorithm.
Cross strategy
Cross strategy is based on the cross probability of two individuals exchanging bit value
one-by-bit. First select two individuals randomly to form a pair, and select the cross bit from
them randomly. And then generate a random number in range [0,1], and if it is greater than the
cross bit then the exchange occurs otherwise keep intact.
(3) Mutation operation
Mutation operation select an individual from the population randomly, and then select a
point of the individual mutation to produce better individuals. ija is represented as the j gene of
the i individual, and its mutation operation method is:
m ax
m in
( ) ( ), 0.5
( ) ( ), 0.5
ij ij
ij
ij ij
a a a f g r
a
a a a f g r
(4)
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Here, maxa is the upper limit of gene ija while mina is the lower limit of gene ija .In
addition,
2
2 max( ) (1 / )f g r g G , 2r is a random number, g is the current iteration number, maxG
is the maximum number of evolution, r is a random number in range [0,1].
(4) Tasu search local optimization
Use the tasu search algorithm to search for local optimization, and select the local
optimum value as a new individual chromosome to evolve, taking the results after some algebra
as the initial value.
5.2.4. Algorithm Description
5.2.5. Algorithm Simulation
From the above chart we can see that under the same conditions, the SA-genetic
algorithm is better than traditional genetic algorithm in the convergence speed and solution
results. So the new algorithm improves search performance of the genetic algorithm.
(a) Convergence speed of SA algorithm (b) Convergence speed of genetic
algorithm
(c) Convergence speed of nonlinear
programming-genetic algorithm
Figure 7. Algorithm simulation comparison
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6. Instance of the Virtual Electrically Operation Drill Platform
Based on the above theoretical results, combined with JME engine, this paper
developed a common intelligent power operation virtual drill platform which is used for
substation employees' safety training. After the field research in multiple substation, we through
the use of knowledge engineering technology constructed the appropriate knowledge base,
which includes electrical safety knowledge, equipment operating procedures, handling
precautions. Based on the extraction of device model, system wiring diagrams and equipment
operation information from the collection of live photos and videos we completed the
construction of equipment model and the expansion of the model events knowledge base.
Practice has proved that the platform can quickly achieve the construction of the target
scene and the setting of operational tasks. With high practicality and promotional value, the
platform can not only meet the requirements of operation drill but also greatly improve the reuse
rate of the model and knowledge, reduce the costs of system maintenance.
7. Conclusion
This paper focused on the research of the key technology of smart grid domain
knowledge three-dimensional visualization. Firstly, through the use of knowledge reasoning
technology build the smart grid knowledge base and model library; Secondly, the organizational
strategy of scene construction and interactive collaborative rendering mechanism of three-
dimensional scene were studied, improved algorithms for collision detection based on nonlinear
genetic algorithm; Again, explored the storage and reuse mechanisms of the virtual three-
dimensional scene; Finally, developed a common platform for intelligent power operation virtual
drill based on the above findings, through the practical application verified the practicality and
efficiency of these findings. However, for the issues of complex scene generation and rendering
speed, there is further room for improvement, which will also be the direction of future research
work.
Acknowledgment
This work is supported by National Natural Science Foundation of China (NO.
51277023 and 51077010), Natural Science Foundation of Jilin Province (NO. 20130206085SF
and 20120338).
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