In general, modern operating systems can be divided into two essential parts, real-time operating systems (RTOS) and general-purpose operating systems (GPOS). The main difference between GPOS and RTOS is the system is time-critical or not. It means that; in GPOS, a high-priority thread cannot preempt a kernel call. But, in RTOS, a low-priority task is preempted by a high-priority task if necessary, even if it’s executing a kernel call. Most Linux distributions can be used as both GPOS and RTOS with kernel modifications. In this study, two Linux distributions, Ubuntu and Pardus, were analyzed and their performances were compared both as GPOS and RTOS for path planning of the multi-robot systems. Robot groups with different numbers of members were used to perform the path tracking tasks using both Ubuntu and Pardus as GPOS and RTOS. In this way, both the performance of two different Linux distributions in robotic applications were observed and compared in two forms, GPOS, and RTOS.
Real-time traffic sign detection and recognition using Raspberry Pi IJECEIAES
Nowadays, the number of road accident in Malaysia is increasing expeditiously. One of the ways to reduce the number of road accident is through the development of the advanced driving assistance system (ADAS) by professional engineers. Several ADAS system has been proposed by taking into consideration the delay tolerance and the accuracy of the system itself. In this work, a traffic sign recognition system has been developed to increase the safety of the road users by installing the system inside the car for driver’s awareness. TensorFlow algorithm has been considered in this work for object recognition through machine learning due to its high accuracy. The algorithm is embedded in the Raspberry Pi 3 for processing and analysis to detect the traffic sign from the real-time video recording from Raspberry Pi camera NoIR. This work aims to study the accuracy, delay and reliability of the developed system using a Raspberry Pi 3 processor considering several scenarios related to the state of the environment and the condition of the traffic signs. A real-time testbed implementation has been conducted considering twenty different traffic signs and the results show that the system has more than 90% accuracy and is reliable with an acceptable delay.
Comparative study to realize an automatic speaker recognition system IJECEIAES
In this research, we present an automatic speaker recognition system based on adaptive orthogonal transformations. To obtain the informative features with a minimum dimension from the input signals, we created an adaptive operator, which helped to identify the speaker’s voice in a fast and efficient manner. We test the efficiency and the performance of our method by comparing it with another approach, mel-frequency cepstral coefficients (MFCCs), which is widely used by researchers as their feature extraction method. The experimental results show the importance of creating the adaptive operator, which gives added value to the proposed approach. The performance of the system achieved 96.8% accuracy using Fourier transform as a compression method and 98.1% using Correlation as a compression method.
Design and development of DrawBot using image processing IJECEIAES
Extracting text from an image and reproducing them can often be a laborious task. We took it upon ourselves to solve the problem. Our work is aimed at designing a robot which can perceive an image shown to it and reproduce it on any given area as directed. It does so by first taking an input image and performing image processing operations on the image to improve its readability. Then the text in the image is recognized by the program. Points for each letter are taken, then inverse kinematics is done for each point with MATLAB/Simulink and the angles in which the servo motors should be moved are found out and stored in the Arduino. Using these angles, the control algorithm is generated in the Arduino and the letters are drawn.
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.
Neural network based image compression with lifting scheme and rlceSAT Publishing House
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.
Real-time traffic sign detection and recognition using Raspberry Pi IJECEIAES
Nowadays, the number of road accident in Malaysia is increasing expeditiously. One of the ways to reduce the number of road accident is through the development of the advanced driving assistance system (ADAS) by professional engineers. Several ADAS system has been proposed by taking into consideration the delay tolerance and the accuracy of the system itself. In this work, a traffic sign recognition system has been developed to increase the safety of the road users by installing the system inside the car for driver’s awareness. TensorFlow algorithm has been considered in this work for object recognition through machine learning due to its high accuracy. The algorithm is embedded in the Raspberry Pi 3 for processing and analysis to detect the traffic sign from the real-time video recording from Raspberry Pi camera NoIR. This work aims to study the accuracy, delay and reliability of the developed system using a Raspberry Pi 3 processor considering several scenarios related to the state of the environment and the condition of the traffic signs. A real-time testbed implementation has been conducted considering twenty different traffic signs and the results show that the system has more than 90% accuracy and is reliable with an acceptable delay.
Comparative study to realize an automatic speaker recognition system IJECEIAES
In this research, we present an automatic speaker recognition system based on adaptive orthogonal transformations. To obtain the informative features with a minimum dimension from the input signals, we created an adaptive operator, which helped to identify the speaker’s voice in a fast and efficient manner. We test the efficiency and the performance of our method by comparing it with another approach, mel-frequency cepstral coefficients (MFCCs), which is widely used by researchers as their feature extraction method. The experimental results show the importance of creating the adaptive operator, which gives added value to the proposed approach. The performance of the system achieved 96.8% accuracy using Fourier transform as a compression method and 98.1% using Correlation as a compression method.
Design and development of DrawBot using image processing IJECEIAES
Extracting text from an image and reproducing them can often be a laborious task. We took it upon ourselves to solve the problem. Our work is aimed at designing a robot which can perceive an image shown to it and reproduce it on any given area as directed. It does so by first taking an input image and performing image processing operations on the image to improve its readability. Then the text in the image is recognized by the program. Points for each letter are taken, then inverse kinematics is done for each point with MATLAB/Simulink and the angles in which the servo motors should be moved are found out and stored in the Arduino. Using these angles, the control algorithm is generated in the Arduino and the letters are drawn.
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.
Neural network based image compression with lifting scheme and rlceSAT Publishing House
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.
Genetic Algorithm Processor for Image Noise Filtering Using Evolvable HardwareCSCJournals
General-purpose image filters lack the flexibility and adaptability of un-modeled noise types. On the contrary, evolutionary algorithm based filter architectures seem to be very promising due to their capability of providing solutions to hard design problems. Through this novel approach, it is made possible to have an image filter that can employ a completely different design style that is performed by an evolutionary algorithm. In this context, an evolutionary algorithm based filter is designed in this paper with the kernel or the whole circuit for automatically evolved. The Evolvable Hard Ware architecture proposed in this paper can evolve filters without a priori information. The proposed filter architecture considers spatial domain approach and uses the overlapping window to filter the signal. The approach that is chosen in this work is based on functional level evolution whose architecture includes nonlinear functions and uses genetic algorithm for finding the best filter configuration.
STUDY OF TASK SCHEDULING STRATEGY BASED ON TRUSTWORTHINESS ijdpsjournal
MapReduce is a distributed computing model for cloud computing to process massive data. It simplifies the
writing of distributed parallel programs. For the fault-tolerant technology in the MapReduce programming
model, tasks may be allocated to nodes with low reliability. It causes the task to be reexecuted, wasting time
and resources. This paper proposes a reliability task scheduling strategy with a failure recovery mechanism,
evaluates the trustworthiness of resource nodes in the cloud environment and builds a trustworthiness model.
By using the simulation platform CloudSim, the stability of the task scheduling algorithm and scheduling
model are verified in this paper.
CONFIGURABLE TASK MAPPING FOR MULTIPLE OBJECTIVES IN MACRO-PROGRAMMING OF WIR...ijassn
Macro-programming is the new generation advanced method of using Wireless Sensor Network (WSNs), where application developers can extract data from sensor nodes through a high level abstraction of the system. Instead of developing the entire application, task graph representation of the WSN model presents simplified approach of data collection. However, mapping of tasks onto sensor nodes highlights several problems in energy consumption and routing delay. In this paper, we present an efficient hybrid approach of task mapping for WSN – Hybrid Genetic Algorithm, considering multiple objectives of optimization – energy consumption, routing delay and soft real time requirement. We also present a method to configure the algorithm as per user's need by changing the heuristics used for optimization. The trade-off analysis between energy consumption and delivery delay was performed and simulation results are presented. The algorithm is applicable during macro-programming enabling developers to choose a better mapping according to their application requirements.
Implementation of an arithmetic logic using area efficient carry lookahead adderVLSICS Design
An arithmetic logic unit acts as the basic building blocks or cell of a central processing unit of a computer.
And it is a digital circuit comprised of the basic electronics components, which is used to perform various
function of arithmetic and logic and integral operations further the purpose of this work is to propose the
design of an 8-bit ALU which supports 4-bit multiplication. Thus, the functionalities of the ALU in this
study consist of following main functions like addition also subtraction, increment, decrement, AND, OR,
NOT, XOR, NOR also two complement generation Multiplication. And the functions with the adder in the
airthemetic logic unit are implemented using a Carry Look Ahead adder joined by a ripple carry approach.
The design of the following multiplier is achieved using the Booths Algorithm therefore the proposed ALU
can be designed by using verilog or VHDL and can also be designed on Cadence Virtuoso platform.
n recent years, with the development of graphics p
rocessors, graphics cards have been widely
used to perform general-purpose calculations. Espec
ially with release of CUDA C
programming languages in 2007, most of the research
ers have been used CUDA C
programming language for the processes which needs
high performance computing.
In this paper, a scaling approach for image segment
ation using level sets is carried out by the
GPU programming techniques. Approach to level sets
is mainly based on the solution of partial
differential equations. The proposed method does no
t require the solution of partial differential
equation. Scaling approach, which uses basic geomet
ric transformations, is used. Thus, the
required computational cost reduces. The use of the
CUDA programming on the GPU has taken
advantage of classic programming as spending time a
nd performance. Thereby results are
obtained faster. The use of the GPU has provided to
enable real-time processing. The developed
application in this study is used to find tumor on
MRI brain images.
Face recognition using assemble of low frequency of DCT featuresjournalBEEI
Face recognition is a challenge due to facial expression, direction, light, and scale variations. The system requires a suitable algorithm to perform recognition task in order to reduce the system complexity. This paper focuses on a development of a new local feature extraction in frequency domain to reduce dimension of feature space. In the propose method, assemble of DCT coefficients are used to extract important features and reduces the features vector. PCA is performed to further reduce feature dimension by using linear projection of original image. The proposed of assemble low frequency coefficients and features reduction method is able to increase discriminant power in low dimensional feature space. The classification is performed by using the Euclidean distance score between the projection of test and train images. The algorithm is implemented on DSP processor which has the same performance as PC based. The experiment is conducted using ORL standard face databases the best performance achieved by this method is 100%. The execution time to recognize 40 peoples is 0.3313 second when tested using DSP processor. The proposed method has a high degree of recognition accuracy and fast computational time when implemented in embedded platform such as DSP processor.
Application and evaluation of the neural network in gearboxTELKOMNIKA JOURNAL
We developed old designed of a Back-Propagation neural network (BPNN), which it was designed by other researchers, and we made modification in their structure. The 1st velocity ratio was discriminated by lowest speed, and highest twist. The 6th velocity ratio was discriminated by highest speed, and lowest twist. The aim of this paper is to design neural structure get best performance to control an electrical automotive transportation six-speed gearbox of the vehicle. We focus on the evaluation of the BPNN to select the suitable number of layers and neurons. Experimentally, the structure of the proposed BPNN are constructed from four layers: eight input nodes in the first layer that received data in binary number, 45 neurons in 1st hidden-layer, 25 neurons in 2nd hidden-layer, and 6 neurons in the fourth layer. The MSE and number of Epochs are the main factors used for the evaluation of the proposed structure, and compared with the other structures which was designed by other researchers. Experimentally, we discovered that the best value of Epoch and MSE was chosen when the BPNN consisted of two hidden-layers, 45, and 25 neurons in the 1st and 2nd hidden-layer respectively. The implementation was applied using MATLAB software.
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology
DYNAMIC HW PRIORITY QUEUE BASED SCHEDULERS FOR EMBEDDED SYSTEMijesajournal
A real-time operating system (RTOs) is often used in embedded system, to structure the application code
and to ensure that the deadlines are met by reacting on events by executing the functions within precise
time. Most embedded systems are bound to real-time constraints with determinism and latency as a critical
metrics. RTOs are generally implemented in software, increases computational overheads, jitter and
memory footprint. Modern FPGA technology, enables the implementation of a full featured and flexible
hardware based RTOs, which helps in reducing to greater extent these overheads even if not remove
completely. Scheduling algorithms play an important role in the design of real-time systems. An Adaptive
Fuzzy Inference System (FIS) based scheduler framework proposed in this article is based on the study and
conclusion drawn from the research over the years in HW SW co-design domain. The proposed novel two
phase FIS based adaptive hardware task scheduler minimizes the processor time for scheduling activity
which uses fuzzy logic to model the uncertainty at first stage along with adaptive framework that uses
feedback which allows processors share of task running on multiprocessor to be controlled dynamically at
runtime. This Fuzzy logic based adaptive hardware scheduler breakthroughs the limit of the number of
total task and thus improves efficiency of the entire real-time system. The increased computation overheads
resulted from proposed two phase FIS scheduler can be compensated by utilising the basic characteristics
of parallelism of the hardware as scheduler being migrated to FPGA.
Dynamic HW Priority Queue Based Schedulers for Embedded System[ijesajournal
A real-time operating system (RTOs) is often used in embedded system, to structure the application code
and to ensure that the deadlines are met by reacting on events by executing the functions within precise
time. Most embedded systems are bound to real-time constraints with determinism and latency as a critical
metrics. RTOs are generally implemented in software, increases computational overheads, jitter and
memory footprint. Modern FPGA technology, enables the implementation of a full featured and flexible
hardware based RTOs, which helps in reducing to greater extent these overheads even if not remove
completely. Scheduling algorithms play an important role in the design of real-time systems. An Adaptive
Fuzzy Inference System (FIS) based scheduler framework proposed in this article is based on the study and
conclusion drawn from the research over the years in HW SW co-design domain. The proposed novel two
phase FIS based adaptive hardware task scheduler minimizes the processor time for scheduling activity
which uses fuzzy logic to model the uncertainty at first stage along with adaptive framework that uses
feedback which allows processors share of task running on multiprocessor to be controlled dynamically at
runtime. This Fuzzy logic based adaptive hardware scheduler breakthroughs the limit of the number of
total task and thus improves efficiency of the entire real-time system. The increased computation overheads
resulted from proposed two phase FIS scheduler can be compensated by utilising the basic characteristics
of parallelism of the hardware as scheduler being migrated to FPGA.
REAL-TIME SCHEDULING ALGORITHMS FOR WIRELESS SENSOR NETWORKcsijjournal
In Recent era, researchers attention is get magnetize towards a widely used technology known as a wireless sensor networks (WSNs) used in the many of applications related to variety of fields including military, healthcare
monitoring, biological, home, vehicular monitoring, infrastructure monitoring, building energy monitoring and industrial sensing. Many of applications in WSNs are real time applications that are requested to run in real time
way. To support such real time applications we need Real Time Operating System (RTOS) which provides logically correct results and also deadline has to be met. This paper presents an overview of existing scheduling
algorithms which helps to schedule tasks in real time systems. Next, we discuss work in sensornet operating system (OS) design. Then, the specialties what sensornet OS should posses are discussed in detail. At last, we
proposed Micro Controller OS-II (µC/OS-II) with Earliest Deadline First (EDF) algorithm.
A low cost, real-time algorithm for embedded devices based on freertos kerneleSAT Journals
Abstract A low-cost, real-time methodology for embedded devices based on well-known open source kernel - freeRTOS is presented in this study. The real-time algorithm designed consists of three main steps. Firstly, the algorithm is designed and evaluated by utilizing Matlab/Simulink toolboxes. Secondly, the generic embedded C code is generated by Matlab program. Finally, freeRTOS Tasks code is utilized based on C code generated to build and run on embedded targets. This real-time algorithm is demonstrated on a two-wheeled self-balancing robot which is employed a fuzzy PID self-tuning controller. The designed controller is executed on a famous ARM Cortex M4 core microcontroller STM32F407VTG. The experimental results show that algorithm designed operated well on embedded systems. The tracking position and rotation angle response are so good with low steady error (i.e. 0.01 [m] and less than 1.15 degrees, respectively) while stabilizing the two-wheeled at the upright. The real-time system designed is a low cost methodology and suitable for embedded system designers. Key Words: Open source, RTOS, embedded system, ARM Cortex and fuzzy PID controller
Genetic Algorithm Processor for Image Noise Filtering Using Evolvable HardwareCSCJournals
General-purpose image filters lack the flexibility and adaptability of un-modeled noise types. On the contrary, evolutionary algorithm based filter architectures seem to be very promising due to their capability of providing solutions to hard design problems. Through this novel approach, it is made possible to have an image filter that can employ a completely different design style that is performed by an evolutionary algorithm. In this context, an evolutionary algorithm based filter is designed in this paper with the kernel or the whole circuit for automatically evolved. The Evolvable Hard Ware architecture proposed in this paper can evolve filters without a priori information. The proposed filter architecture considers spatial domain approach and uses the overlapping window to filter the signal. The approach that is chosen in this work is based on functional level evolution whose architecture includes nonlinear functions and uses genetic algorithm for finding the best filter configuration.
STUDY OF TASK SCHEDULING STRATEGY BASED ON TRUSTWORTHINESS ijdpsjournal
MapReduce is a distributed computing model for cloud computing to process massive data. It simplifies the
writing of distributed parallel programs. For the fault-tolerant technology in the MapReduce programming
model, tasks may be allocated to nodes with low reliability. It causes the task to be reexecuted, wasting time
and resources. This paper proposes a reliability task scheduling strategy with a failure recovery mechanism,
evaluates the trustworthiness of resource nodes in the cloud environment and builds a trustworthiness model.
By using the simulation platform CloudSim, the stability of the task scheduling algorithm and scheduling
model are verified in this paper.
CONFIGURABLE TASK MAPPING FOR MULTIPLE OBJECTIVES IN MACRO-PROGRAMMING OF WIR...ijassn
Macro-programming is the new generation advanced method of using Wireless Sensor Network (WSNs), where application developers can extract data from sensor nodes through a high level abstraction of the system. Instead of developing the entire application, task graph representation of the WSN model presents simplified approach of data collection. However, mapping of tasks onto sensor nodes highlights several problems in energy consumption and routing delay. In this paper, we present an efficient hybrid approach of task mapping for WSN – Hybrid Genetic Algorithm, considering multiple objectives of optimization – energy consumption, routing delay and soft real time requirement. We also present a method to configure the algorithm as per user's need by changing the heuristics used for optimization. The trade-off analysis between energy consumption and delivery delay was performed and simulation results are presented. The algorithm is applicable during macro-programming enabling developers to choose a better mapping according to their application requirements.
Implementation of an arithmetic logic using area efficient carry lookahead adderVLSICS Design
An arithmetic logic unit acts as the basic building blocks or cell of a central processing unit of a computer.
And it is a digital circuit comprised of the basic electronics components, which is used to perform various
function of arithmetic and logic and integral operations further the purpose of this work is to propose the
design of an 8-bit ALU which supports 4-bit multiplication. Thus, the functionalities of the ALU in this
study consist of following main functions like addition also subtraction, increment, decrement, AND, OR,
NOT, XOR, NOR also two complement generation Multiplication. And the functions with the adder in the
airthemetic logic unit are implemented using a Carry Look Ahead adder joined by a ripple carry approach.
The design of the following multiplier is achieved using the Booths Algorithm therefore the proposed ALU
can be designed by using verilog or VHDL and can also be designed on Cadence Virtuoso platform.
n recent years, with the development of graphics p
rocessors, graphics cards have been widely
used to perform general-purpose calculations. Espec
ially with release of CUDA C
programming languages in 2007, most of the research
ers have been used CUDA C
programming language for the processes which needs
high performance computing.
In this paper, a scaling approach for image segment
ation using level sets is carried out by the
GPU programming techniques. Approach to level sets
is mainly based on the solution of partial
differential equations. The proposed method does no
t require the solution of partial differential
equation. Scaling approach, which uses basic geomet
ric transformations, is used. Thus, the
required computational cost reduces. The use of the
CUDA programming on the GPU has taken
advantage of classic programming as spending time a
nd performance. Thereby results are
obtained faster. The use of the GPU has provided to
enable real-time processing. The developed
application in this study is used to find tumor on
MRI brain images.
Face recognition using assemble of low frequency of DCT featuresjournalBEEI
Face recognition is a challenge due to facial expression, direction, light, and scale variations. The system requires a suitable algorithm to perform recognition task in order to reduce the system complexity. This paper focuses on a development of a new local feature extraction in frequency domain to reduce dimension of feature space. In the propose method, assemble of DCT coefficients are used to extract important features and reduces the features vector. PCA is performed to further reduce feature dimension by using linear projection of original image. The proposed of assemble low frequency coefficients and features reduction method is able to increase discriminant power in low dimensional feature space. The classification is performed by using the Euclidean distance score between the projection of test and train images. The algorithm is implemented on DSP processor which has the same performance as PC based. The experiment is conducted using ORL standard face databases the best performance achieved by this method is 100%. The execution time to recognize 40 peoples is 0.3313 second when tested using DSP processor. The proposed method has a high degree of recognition accuracy and fast computational time when implemented in embedded platform such as DSP processor.
Application and evaluation of the neural network in gearboxTELKOMNIKA JOURNAL
We developed old designed of a Back-Propagation neural network (BPNN), which it was designed by other researchers, and we made modification in their structure. The 1st velocity ratio was discriminated by lowest speed, and highest twist. The 6th velocity ratio was discriminated by highest speed, and lowest twist. The aim of this paper is to design neural structure get best performance to control an electrical automotive transportation six-speed gearbox of the vehicle. We focus on the evaluation of the BPNN to select the suitable number of layers and neurons. Experimentally, the structure of the proposed BPNN are constructed from four layers: eight input nodes in the first layer that received data in binary number, 45 neurons in 1st hidden-layer, 25 neurons in 2nd hidden-layer, and 6 neurons in the fourth layer. The MSE and number of Epochs are the main factors used for the evaluation of the proposed structure, and compared with the other structures which was designed by other researchers. Experimentally, we discovered that the best value of Epoch and MSE was chosen when the BPNN consisted of two hidden-layers, 45, and 25 neurons in the 1st and 2nd hidden-layer respectively. The implementation was applied using MATLAB software.
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology
DYNAMIC HW PRIORITY QUEUE BASED SCHEDULERS FOR EMBEDDED SYSTEMijesajournal
A real-time operating system (RTOs) is often used in embedded system, to structure the application code
and to ensure that the deadlines are met by reacting on events by executing the functions within precise
time. Most embedded systems are bound to real-time constraints with determinism and latency as a critical
metrics. RTOs are generally implemented in software, increases computational overheads, jitter and
memory footprint. Modern FPGA technology, enables the implementation of a full featured and flexible
hardware based RTOs, which helps in reducing to greater extent these overheads even if not remove
completely. Scheduling algorithms play an important role in the design of real-time systems. An Adaptive
Fuzzy Inference System (FIS) based scheduler framework proposed in this article is based on the study and
conclusion drawn from the research over the years in HW SW co-design domain. The proposed novel two
phase FIS based adaptive hardware task scheduler minimizes the processor time for scheduling activity
which uses fuzzy logic to model the uncertainty at first stage along with adaptive framework that uses
feedback which allows processors share of task running on multiprocessor to be controlled dynamically at
runtime. This Fuzzy logic based adaptive hardware scheduler breakthroughs the limit of the number of
total task and thus improves efficiency of the entire real-time system. The increased computation overheads
resulted from proposed two phase FIS scheduler can be compensated by utilising the basic characteristics
of parallelism of the hardware as scheduler being migrated to FPGA.
Dynamic HW Priority Queue Based Schedulers for Embedded System[ijesajournal
A real-time operating system (RTOs) is often used in embedded system, to structure the application code
and to ensure that the deadlines are met by reacting on events by executing the functions within precise
time. Most embedded systems are bound to real-time constraints with determinism and latency as a critical
metrics. RTOs are generally implemented in software, increases computational overheads, jitter and
memory footprint. Modern FPGA technology, enables the implementation of a full featured and flexible
hardware based RTOs, which helps in reducing to greater extent these overheads even if not remove
completely. Scheduling algorithms play an important role in the design of real-time systems. An Adaptive
Fuzzy Inference System (FIS) based scheduler framework proposed in this article is based on the study and
conclusion drawn from the research over the years in HW SW co-design domain. The proposed novel two
phase FIS based adaptive hardware task scheduler minimizes the processor time for scheduling activity
which uses fuzzy logic to model the uncertainty at first stage along with adaptive framework that uses
feedback which allows processors share of task running on multiprocessor to be controlled dynamically at
runtime. This Fuzzy logic based adaptive hardware scheduler breakthroughs the limit of the number of
total task and thus improves efficiency of the entire real-time system. The increased computation overheads
resulted from proposed two phase FIS scheduler can be compensated by utilising the basic characteristics
of parallelism of the hardware as scheduler being migrated to FPGA.
REAL-TIME SCHEDULING ALGORITHMS FOR WIRELESS SENSOR NETWORKcsijjournal
In Recent era, researchers attention is get magnetize towards a widely used technology known as a wireless sensor networks (WSNs) used in the many of applications related to variety of fields including military, healthcare
monitoring, biological, home, vehicular monitoring, infrastructure monitoring, building energy monitoring and industrial sensing. Many of applications in WSNs are real time applications that are requested to run in real time
way. To support such real time applications we need Real Time Operating System (RTOS) which provides logically correct results and also deadline has to be met. This paper presents an overview of existing scheduling
algorithms which helps to schedule tasks in real time systems. Next, we discuss work in sensornet operating system (OS) design. Then, the specialties what sensornet OS should posses are discussed in detail. At last, we
proposed Micro Controller OS-II (µC/OS-II) with Earliest Deadline First (EDF) algorithm.
A low cost, real-time algorithm for embedded devices based on freertos kerneleSAT Journals
Abstract A low-cost, real-time methodology for embedded devices based on well-known open source kernel - freeRTOS is presented in this study. The real-time algorithm designed consists of three main steps. Firstly, the algorithm is designed and evaluated by utilizing Matlab/Simulink toolboxes. Secondly, the generic embedded C code is generated by Matlab program. Finally, freeRTOS Tasks code is utilized based on C code generated to build and run on embedded targets. This real-time algorithm is demonstrated on a two-wheeled self-balancing robot which is employed a fuzzy PID self-tuning controller. The designed controller is executed on a famous ARM Cortex M4 core microcontroller STM32F407VTG. The experimental results show that algorithm designed operated well on embedded systems. The tracking position and rotation angle response are so good with low steady error (i.e. 0.01 [m] and less than 1.15 degrees, respectively) while stabilizing the two-wheeled at the upright. The real-time system designed is a low cost methodology and suitable for embedded system designers. Key Words: Open source, RTOS, embedded system, ARM Cortex and fuzzy PID controller
AN EFFICIENT HYBRID SCHEDULER USING DYNAMIC SLACK FOR REAL-TIME CRITICAL TASK...ijesajournal
Task intensive electronic control units (ECUs) in automotive domain, equipped with multicore processors ,
real time operating systems (RTOSs) and various application software, should perform efficiently and time
deterministically. The parallel computational capability offered by this multicore hardware can only be
exploited and utilized if the ECU application software is parallelized. Having provided with such
parallelized software, the real time operating system scheduler component should schedule the time critical
tasks so that, all the computational cores are utilized to a greater extent and the safety critical deadlines
are met. As original equipment manufacturers (OEMs) are always motivated towards adding more
sophisticated features to the existing ECUs, a large number of task sets can be effectively scheduled for
execution within the bounded time limits. In this paper, a hybrid scheduling algorithm has been proposed,
that meticulously calculates the running slack of every task and estimates the probability of meeting
deadline either being in the same partitioned queue or by migrating to another. This algorithm was run and
tested using a scheduling simulator with different real time task models of periodic tasks . This algorithm
was also compared with the existing static priority scheduler, which is suggested by Automotive Open
Systems Architecture (AUTOSAR). The performance parameters considered here are, the % of core
utilization, average response time and task deadline missing rate. It has been verified that, this proposed
algorithm has considerable improvements over the existing partitioned static priority scheduler based on
each performance parameter mentioned above.
Embedded operating system and industrial applications: a reviewjournalBEEI
The complexity of an embedded system is directly proportional to the requirements of industrial applications. Various embedded operating system (OS) approaches had been built to fulfil the requirements. This review aims to systematically address the similarities and differences of the embedded OS solutions and analyse the factors that will influence decision-making when choosing what solution to use in the applications. This paper reviews three standard solutions; super loop, cooperative, and real-time operating system (RTOS). These are commonly used in industrial applications. By grouping the tasks in the foreground and background execution region, the concept and working principle of each of them are reviewed. The unique feature of RTOS in the context of task switching was used to define the deterministic characteristic of meeting the deadlines. The importance and performance of this characteristic is addressed and compared among various solutions in this paper. Subsequently, this paper reviewed the internet of things (IoT) requirements, automotive, medical and consumer electronics industry. The influential factors on choosing the right embedded OS to be used are extracted based on the requirements. They are reviewed in the perspective of memory footprint, regulated standards, cost-effectiveness, time effectiveness, and scalability.
A CLOUD BASED ARCHITECTURE FOR WORKING ON BIG DATA WITH WORKFLOW MANAGEMENTIJwest
In real environment there is a collection of many noisy and vague data, called Big Data. On the other hand,
to work on the data middleware have been developed and is now very widely used. The challenge of
working on Big Data is its processing and management. Here, integrated management system is required
to provide a solution for integrating data from multiple sensors and maximize the target success. This is in
situation that the system has constant time constrains for processing, and real-time decision-making
processes. A reliable data fusion model must meet this requirement and steadily let the user monitor data
stream. With widespread using of workflow interfaces, this requirement can be addressed. But, the work
with Big Data is also challenging. We provide a multi-agent cloud-based architecture for a higher vision to
solve this problem. This architecture provides the ability to Big Data Fusion using a workflow management
interface. The proposed system is capable of self-repair in the presence of risks and its risk is low.
Driving cycle tracking device big data storing and managementIJECEIAES
Driving cycle is commonly known as a series of speed-time profile. Research on this discipline aids vehicle manufacturing industries in vehicle manufacturing, environmentalists to study on environment quality and profile in accordance to vehicle emissions besides traffic engineers to further investigate the behavior of drivers and the conditions of roads in a certain area or cluster. This also assists automotive industries to innovate energy efficient vehicles which reduce vehicle emissions and energy wastages which lead to air pollution in which a major threat for human health according to Goal 3 of united nations (UN) sustainable development goals (SDG). To construct an accurate driving cycle, data based on real-world driving behavior is crucial and as the world is advancing in technology, the usage of internet of things (IoT) plays an important role in innovatietcons. IoT is an idea of computing every day physical object and information into computers, devices and software. These devices work by using sensors that transmit data to a computer or software allowing them to perform important tasks as needed. In this research, an idea of data collecting device, driving cycle tracking device (DC-TRAD) is constructed with implementation of IoT in which the collected data will be saved into my structured query language (MySQL) database instantly for data storing.
HW/SW Partitioning Approach on Reconfigurable Multimedia System on ChipCSCJournals
Due to the complexity and the high performance requirement of multimedia applications, the design of embedded systems is the subject of different types of design constraints such as execution time, time to market, energy consumption, etc. Some approaches of joint software/hardware design (Co-design) were proposed in order to help the designer to seek an adequacy between applications and architecture that satisfies the different design constraints. This paper presents a new methodology for hardware/software partitioning on reconfigurable multimedia system on chip, based on dynamic and static steps. The first one uses the dynamic profiling and the second one uses the design trotter tools. The validation of our approach is made through 3D image synthesis.
An Efficient and Optimal Systems For Medical & Industries With Concept of IOTIJERA Editor
Its quit interesting to starts with some philosophical manner rather than the aim of paper, that is, human kind
likes more and more simplified life in their daily activities. The people like, simplification in cooking, travel,
education, fashion design, dressing, information availability about certain things, communication from one place
to another and so on. That means, the people like intelligent automated life. In contrast artificial things can
interact with the human kind and solves their desires. For example, someone may have lost something,
somewhere, but they forget where they lost. The difficulty here is, how find the thing, someone may give the
solutions RFID technology but it works in certain range. So from the discussions, we need, the autonomous
mechanism, that can trace out the locality or information regarding to what we lost? In simple manner, we need
a common platform to integrate entire world of thing. For a little while, the common platform is internet and
hence we labeled Internet of Things(IoT). That’s what, the paper is going to deal. So the principal objective is to
monitoring the thing of parameters from anywhere in the world. The paper is not aimed to integrate entire world
of things right now but dedicated to two fields, medical & small, medium enterprises. In medical field, monitor
the patient through camera interface and patient’s moments using WSN interface. And in case of SM Enterprises
monitors, temperature, water level, machine motion detection using WSN and visual through Camera Interface.
The paper is built with high speed and low cost Raspberry-Pi Controller
System on Chip Based RTC in Power ElectronicsjournalBEEI
Current control systems and emulation systems (Hardware-in-the-Loop, HIL or Processor-in-the-Loop, PIL) for high-end power-electronic applications often consist of numerous components and interlinking busses: a micro controller for communication and high level control, a DSP for real-time control, an FPGA section for fast parallel actions and data acquisition, multiport RAM structures or bus systems as interconnecting structure. System-on-Chip (SoC) combines many of these functions on a single die. This gives the advantage of space reduction combined with cost reduction and very fast internal communication. Such systems become very relevant for research and also for industrial applications. The SoC used here as an example combines a Dual-Core ARM 9 hard processor system (HPS) and an FPGA, including fast interlinks between these components. SoC systems require careful software and firmware concepts to provide real-time control and emulation capability. This paper demonstrates an optimal way to use the resources of the SoC and discusses challenges caused by the internal structure of SoC. The key idea is to use asymmetric multiprocessing: One core uses a bare-metal operating system for hard real time. The other core runs a “real-time” Linux for service functions and communication. The FPGA is used for flexible process-oriented interfaces (A/D, D/A, switching signals), quasi-hard-wired protection and the precise timing of the real-time control cycle. This way of implementation is generally known and sometimes even suggested–but to the knowledge of the author’s seldomly implemented and documented in the context of demanding real-time control or emulation. The paper details the way of implementation, including process interfaces, and discusses the advantages and disadvantages of the chosen concept. Measurement results demonstrate the properties of the solution.
Similar to Performance analysis of real-time and general-purpose operating systems for path planning of the multi-robot systems (20)
Bibliometric analysis highlighting the role of women in addressing climate ch...IJECEIAES
Fossil fuel consumption increased quickly, contributing to climate change
that is evident in unusual flooding and draughts, and global warming. Over
the past ten years, women's involvement in society has grown dramatically,
and they succeeded in playing a noticeable role in reducing climate change.
A bibliometric analysis of data from the last ten years has been carried out to
examine the role of women in addressing the climate change. The analysis's
findings discussed the relevant to the sustainable development goals (SDGs),
particularly SDG 7 and SDG 13. The results considered contributions made
by women in the various sectors while taking geographic dispersion into
account. The bibliometric analysis delves into topics including women's
leadership in environmental groups, their involvement in policymaking, their
contributions to sustainable development projects, and the influence of
gender diversity on attempts to mitigate climate change. This study's results
highlight how women have influenced policies and actions related to climate
change, point out areas of research deficiency and recommendations on how
to increase role of the women in addressing the climate change and
achieving sustainability. To achieve more successful results, this initiative
aims to highlight the significance of gender equality and encourage
inclusivity in climate change decision-making processes.
Voltage and frequency control of microgrid in presence of micro-turbine inter...IJECEIAES
The active and reactive load changes have a significant impact on voltage
and frequency. In this paper, in order to stabilize the microgrid (MG) against
load variations in islanding mode, the active and reactive power of all
distributed generators (DGs), including energy storage (battery), diesel
generator, and micro-turbine, are controlled. The micro-turbine generator is
connected to MG through a three-phase to three-phase matrix converter, and
the droop control method is applied for controlling the voltage and
frequency of MG. In addition, a method is introduced for voltage and
frequency control of micro-turbines in the transition state from gridconnected mode to islanding mode. A novel switching strategy of the matrix
converter is used for converting the high-frequency output voltage of the
micro-turbine to the grid-side frequency of the utility system. Moreover,
using the switching strategy, the low-order harmonics in the output current
and voltage are not produced, and consequently, the size of the output filter
would be reduced. In fact, the suggested control strategy is load-independent
and has no frequency conversion restrictions. The proposed approach for
voltage and frequency regulation demonstrates exceptional performance and
favorable response across various load alteration scenarios. The suggested
strategy is examined in several scenarios in the MG test systems, and the
simulation results are addressed.
Enhancing battery system identification: nonlinear autoregressive modeling fo...IJECEIAES
Precisely characterizing Li-ion batteries is essential for optimizing their
performance, enhancing safety, and prolonging their lifespan across various
applications, such as electric vehicles and renewable energy systems. This
article introduces an innovative nonlinear methodology for system
identification of a Li-ion battery, employing a nonlinear autoregressive with
exogenous inputs (NARX) model. The proposed approach integrates the
benefits of nonlinear modeling with the adaptability of the NARX structure,
facilitating a more comprehensive representation of the intricate
electrochemical processes within the battery. Experimental data collected
from a Li-ion battery operating under diverse scenarios are employed to
validate the effectiveness of the proposed methodology. The identified
NARX model exhibits superior accuracy in predicting the battery's behavior
compared to traditional linear models. This study underscores the
importance of accounting for nonlinearities in battery modeling, providing
insights into the intricate relationships between state-of-charge, voltage, and
current under dynamic conditions.
Smart grid deployment: from a bibliometric analysis to a surveyIJECEIAES
Smart grids are one of the last decades' innovations in electrical energy.
They bring relevant advantages compared to the traditional grid and
significant interest from the research community. Assessing the field's
evolution is essential to propose guidelines for facing new and future smart
grid challenges. In addition, knowing the main technologies involved in the
deployment of smart grids (SGs) is important to highlight possible
shortcomings that can be mitigated by developing new tools. This paper
contributes to the research trends mentioned above by focusing on two
objectives. First, a bibliometric analysis is presented to give an overview of
the current research level about smart grid deployment. Second, a survey of
the main technological approaches used for smart grid implementation and
their contributions are highlighted. To that effect, we searched the Web of
Science (WoS), and the Scopus databases. We obtained 5,663 documents
from WoS and 7,215 from Scopus on smart grid implementation or
deployment. With the extraction limitation in the Scopus database, 5,872 of
the 7,215 documents were extracted using a multi-step process. These two
datasets have been analyzed using a bibliometric tool called bibliometrix.
The main outputs are presented with some recommendations for future
research.
Use of analytical hierarchy process for selecting and prioritizing islanding ...IJECEIAES
One of the problems that are associated to power systems is islanding
condition, which must be rapidly and properly detected to prevent any
negative consequences on the system's protection, stability, and security.
This paper offers a thorough overview of several islanding detection
strategies, which are divided into two categories: classic approaches,
including local and remote approaches, and modern techniques, including
techniques based on signal processing and computational intelligence.
Additionally, each approach is compared and assessed based on several
factors, including implementation costs, non-detected zones, declining
power quality, and response times using the analytical hierarchy process
(AHP). The multi-criteria decision-making analysis shows that the overall
weight of passive methods (24.7%), active methods (7.8%), hybrid methods
(5.6%), remote methods (14.5%), signal processing-based methods (26.6%),
and computational intelligent-based methods (20.8%) based on the
comparison of all criteria together. Thus, it can be seen from the total weight
that hybrid approaches are the least suitable to be chosen, while signal
processing-based methods are the most appropriate islanding detection
method to be selected and implemented in power system with respect to the
aforementioned factors. Using Expert Choice software, the proposed
hierarchy model is studied and examined.
Enhancing of single-stage grid-connected photovoltaic system using fuzzy logi...IJECEIAES
The power generated by photovoltaic (PV) systems is influenced by
environmental factors. This variability hampers the control and utilization of
solar cells' peak output. In this study, a single-stage grid-connected PV
system is designed to enhance power quality. Our approach employs fuzzy
logic in the direct power control (DPC) of a three-phase voltage source
inverter (VSI), enabling seamless integration of the PV connected to the
grid. Additionally, a fuzzy logic-based maximum power point tracking
(MPPT) controller is adopted, which outperforms traditional methods like
incremental conductance (INC) in enhancing solar cell efficiency and
minimizing the response time. Moreover, the inverter's real-time active and
reactive power is directly managed to achieve a unity power factor (UPF).
The system's performance is assessed through MATLAB/Simulink
implementation, showing marked improvement over conventional methods,
particularly in steady-state and varying weather conditions. For solar
irradiances of 500 and 1,000 W/m2
, the results show that the proposed
method reduces the total harmonic distortion (THD) of the injected current
to the grid by approximately 46% and 38% compared to conventional
methods, respectively. Furthermore, we compare the simulation results with
IEEE standards to evaluate the system's grid compatibility.
Enhancing photovoltaic system maximum power point tracking with fuzzy logic-b...IJECEIAES
Photovoltaic systems have emerged as a promising energy resource that
caters to the future needs of society, owing to their renewable, inexhaustible,
and cost-free nature. The power output of these systems relies on solar cell
radiation and temperature. In order to mitigate the dependence on
atmospheric conditions and enhance power tracking, a conventional
approach has been improved by integrating various methods. To optimize
the generation of electricity from solar systems, the maximum power point
tracking (MPPT) technique is employed. To overcome limitations such as
steady-state voltage oscillations and improve transient response, two
traditional MPPT methods, namely fuzzy logic controller (FLC) and perturb
and observe (P&O), have been modified. This research paper aims to
simulate and validate the step size of the proposed modified P&O and FLC
techniques within the MPPT algorithm using MATLAB/Simulink for
efficient power tracking in photovoltaic systems.
Adaptive synchronous sliding control for a robot manipulator based on neural ...IJECEIAES
Robot manipulators have become important equipment in production lines, medical fields, and transportation. Improving the quality of trajectory tracking for
robot hands is always an attractive topic in the research community. This is a
challenging problem because robot manipulators are complex nonlinear systems
and are often subject to fluctuations in loads and external disturbances. This
article proposes an adaptive synchronous sliding control scheme to improve trajectory tracking performance for a robot manipulator. The proposed controller
ensures that the positions of the joints track the desired trajectory, synchronize
the errors, and significantly reduces chattering. First, the synchronous tracking
errors and synchronous sliding surfaces are presented. Second, the synchronous
tracking error dynamics are determined. Third, a robust adaptive control law is
designed,the unknown components of the model are estimated online by the neural network, and the parameters of the switching elements are selected by fuzzy
logic. The built algorithm ensures that the tracking and approximation errors
are ultimately uniformly bounded (UUB). Finally, the effectiveness of the constructed algorithm is demonstrated through simulation and experimental results.
Simulation and experimental results show that the proposed controller is effective with small synchronous tracking errors, and the chattering phenomenon is
significantly reduced.
Remote field-programmable gate array laboratory for signal acquisition and de...IJECEIAES
A remote laboratory utilizing field-programmable gate array (FPGA) technologies enhances students’ learning experience anywhere and anytime in embedded system design. Existing remote laboratories prioritize hardware access and visual feedback for observing board behavior after programming, neglecting comprehensive debugging tools to resolve errors that require internal signal acquisition. This paper proposes a novel remote embeddedsystem design approach targeting FPGA technologies that are fully interactive via a web-based platform. Our solution provides FPGA board access and debugging capabilities beyond the visual feedback provided by existing remote laboratories. We implemented a lab module that allows users to seamlessly incorporate into their FPGA design. The module minimizes hardware resource utilization while enabling the acquisition of a large number of data samples from the signal during the experiments by adaptively compressing the signal prior to data transmission. The results demonstrate an average compression ratio of 2.90 across three benchmark signals, indicating efficient signal acquisition and effective debugging and analysis. This method allows users to acquire more data samples than conventional methods. The proposed lab allows students to remotely test and debug their designs, bridging the gap between theory and practice in embedded system design.
Detecting and resolving feature envy through automated machine learning and m...IJECEIAES
Efficiently identifying and resolving code smells enhances software project quality. This paper presents a novel solution, utilizing automated machine learning (AutoML) techniques, to detect code smells and apply move method refactoring. By evaluating code metrics before and after refactoring, we assessed its impact on coupling, complexity, and cohesion. Key contributions of this research include a unique dataset for code smell classification and the development of models using AutoGluon for optimal performance. Furthermore, the study identifies the top 20 influential features in classifying feature envy, a well-known code smell, stemming from excessive reliance on external classes. We also explored how move method refactoring addresses feature envy, revealing reduced coupling and complexity, and improved cohesion, ultimately enhancing code quality. In summary, this research offers an empirical, data-driven approach, integrating AutoML and move method refactoring to optimize software project quality. Insights gained shed light on the benefits of refactoring on code quality and the significance of specific features in detecting feature envy. Future research can expand to explore additional refactoring techniques and a broader range of code metrics, advancing software engineering practices and standards.
Smart monitoring technique for solar cell systems using internet of things ba...IJECEIAES
Rapidly and remotely monitoring and receiving the solar cell systems status parameters, solar irradiance, temperature, and humidity, are critical issues in enhancement their efficiency. Hence, in the present article an improved smart prototype of internet of things (IoT) technique based on embedded system through NodeMCU ESP8266 (ESP-12E) was carried out experimentally. Three different regions at Egypt; Luxor, Cairo, and El-Beheira cities were chosen to study their solar irradiance profile, temperature, and humidity by the proposed IoT system. The monitoring data of solar irradiance, temperature, and humidity were live visualized directly by Ubidots through hypertext transfer protocol (HTTP) protocol. The measured solar power radiation in Luxor, Cairo, and El-Beheira ranged between 216-1000, 245-958, and 187-692 W/m 2 respectively during the solar day. The accuracy and rapidity of obtaining monitoring results using the proposed IoT system made it a strong candidate for application in monitoring solar cell systems. On the other hand, the obtained solar power radiation results of the three considered regions strongly candidate Luxor and Cairo as suitable places to build up a solar cells system station rather than El-Beheira.
An efficient security framework for intrusion detection and prevention in int...IJECEIAES
Over the past few years, the internet of things (IoT) has advanced to connect billions of smart devices to improve quality of life. However, anomalies or malicious intrusions pose several security loopholes, leading to performance degradation and threat to data security in IoT operations. Thereby, IoT security systems must keep an eye on and restrict unwanted events from occurring in the IoT network. Recently, various technical solutions based on machine learning (ML) models have been derived towards identifying and restricting unwanted events in IoT. However, most ML-based approaches are prone to miss-classification due to inappropriate feature selection. Additionally, most ML approaches applied to intrusion detection and prevention consider supervised learning, which requires a large amount of labeled data to be trained. Consequently, such complex datasets are impossible to source in a large network like IoT. To address this problem, this proposed study introduces an efficient learning mechanism to strengthen the IoT security aspects. The proposed algorithm incorporates supervised and unsupervised approaches to improve the learning models for intrusion detection and mitigation. Compared with the related works, the experimental outcome shows that the model performs well in a benchmark dataset. It accomplishes an improved detection accuracy of approximately 99.21%.
Developing a smart system for infant incubators using the internet of things ...IJECEIAES
This research is developing an incubator system that integrates the internet of things and artificial intelligence to improve care for premature babies. The system workflow starts with sensors that collect data from the incubator. Then, the data is sent in real-time to the internet of things (IoT) broker eclipse mosquito using the message queue telemetry transport (MQTT) protocol version 5.0. After that, the data is stored in a database for analysis using the long short-term memory network (LSTM) method and displayed in a web application using an application programming interface (API) service. Furthermore, the experimental results produce as many as 2,880 rows of data stored in the database. The correlation coefficient between the target attribute and other attributes ranges from 0.23 to 0.48. Next, several experiments were conducted to evaluate the model-predicted value on the test data. The best results are obtained using a two-layer LSTM configuration model, each with 60 neurons and a lookback setting 6. This model produces an R 2 value of 0.934, with a root mean square error (RMSE) value of 0.015 and a mean absolute error (MAE) of 0.008. In addition, the R 2 value was also evaluated for each attribute used as input, with a result of values between 0.590 and 0.845.
A review on internet of things-based stingless bee's honey production with im...IJECEIAES
Honey is produced exclusively by honeybees and stingless bees which both are well adapted to tropical and subtropical regions such as Malaysia. Stingless bees are known for producing small amounts of honey and are known for having a unique flavor profile. Problem identified that many stingless bees collapsed due to weather, temperature and environment. It is critical to understand the relationship between the production of stingless bee honey and environmental conditions to improve honey production. Thus, this paper presents a review on stingless bee's honey production and prediction modeling. About 54 previous research has been analyzed and compared in identifying the research gaps. A framework on modeling the prediction of stingless bee honey is derived. The result presents the comparison and analysis on the internet of things (IoT) monitoring systems, honey production estimation, convolution neural networks (CNNs), and automatic identification methods on bee species. It is identified based on image detection method the top best three efficiency presents CNN is at 98.67%, densely connected convolutional networks with YOLO v3 is 97.7%, and DenseNet201 convolutional networks 99.81%. This study is significant to assist the researcher in developing a model for predicting stingless honey produced by bee's output, which is important for a stable economy and food security.
A trust based secure access control using authentication mechanism for intero...IJECEIAES
The internet of things (IoT) is a revolutionary innovation in many aspects of our society including interactions, financial activity, and global security such as the military and battlefield internet. Due to the limited energy and processing capacity of network devices, security, energy consumption, compatibility, and device heterogeneity are the long-term IoT problems. As a result, energy and security are critical for data transmission across edge and IoT networks. Existing IoT interoperability techniques need more computation time, have unreliable authentication mechanisms that break easily, lose data easily, and have low confidentiality. In this paper, a key agreement protocol-based authentication mechanism for IoT devices is offered as a solution to this issue. This system makes use of information exchange, which must be secured to prevent access by unauthorized users. Using a compact contiki/cooja simulator, the performance and design of the suggested framework are validated. The simulation findings are evaluated based on detection of malicious nodes after 60 minutes of simulation. The suggested trust method, which is based on privacy access control, reduced packet loss ratio to 0.32%, consumed 0.39% power, and had the greatest average residual energy of 0.99 mJoules at 10 nodes.
Fuzzy linear programming with the intuitionistic polygonal fuzzy numbersIJECEIAES
In real world applications, data are subject to ambiguity due to several factors; fuzzy sets and fuzzy numbers propose a great tool to model such ambiguity. In case of hesitation, the complement of a membership value in fuzzy numbers can be different from the non-membership value, in which case we can model using intuitionistic fuzzy numbers as they provide flexibility by defining both a membership and a non-membership functions. In this article, we consider the intuitionistic fuzzy linear programming problem with intuitionistic polygonal fuzzy numbers, which is a generalization of the previous polygonal fuzzy numbers found in the literature. We present a modification of the simplex method that can be used to solve any general intuitionistic fuzzy linear programming problem after approximating the problem by an intuitionistic polygonal fuzzy number with n edges. This method is given in a simple tableau formulation, and then applied on numerical examples for clarity.
The performance of artificial intelligence in prostate magnetic resonance im...IJECEIAES
Prostate cancer is the predominant form of cancer observed in men worldwide. The application of magnetic resonance imaging (MRI) as a guidance tool for conducting biopsies has been established as a reliable and well-established approach in the diagnosis of prostate cancer. The diagnostic performance of MRI-guided prostate cancer diagnosis exhibits significant heterogeneity due to the intricate and multi-step nature of the diagnostic pathway. The development of artificial intelligence (AI) models, specifically through the utilization of machine learning techniques such as deep learning, is assuming an increasingly significant role in the field of radiology. In the realm of prostate MRI, a considerable body of literature has been dedicated to the development of various AI algorithms. These algorithms have been specifically designed for tasks such as prostate segmentation, lesion identification, and classification. The overarching objective of these endeavors is to enhance diagnostic performance and foster greater agreement among different observers within MRI scans for the prostate. This review article aims to provide a concise overview of the application of AI in the field of radiology, with a specific focus on its utilization in prostate MRI.
Seizure stage detection of epileptic seizure using convolutional neural networksIJECEIAES
According to the World Health Organization (WHO), seventy million individuals worldwide suffer from epilepsy, a neurological disorder. While electroencephalography (EEG) is crucial for diagnosing epilepsy and monitoring the brain activity of epilepsy patients, it requires a specialist to examine all EEG recordings to find epileptic behavior. This procedure needs an experienced doctor, and a precise epilepsy diagnosis is crucial for appropriate treatment. To identify epileptic seizures, this study employed a convolutional neural network (CNN) based on raw scalp EEG signals to discriminate between preictal, ictal, postictal, and interictal segments. The possibility of these characteristics is explored by examining how well timedomain signals work in the detection of epileptic signals using intracranial Freiburg Hospital (FH), scalp Children's Hospital Boston-Massachusetts Institute of Technology (CHB-MIT) databases, and Temple University Hospital (TUH) EEG. To test the viability of this approach, two types of experiments were carried out. Firstly, binary class classification (preictal, ictal, postictal each versus interictal) and four-class classification (interictal versus preictal versus ictal versus postictal). The average accuracy for stage detection using CHB-MIT database was 84.4%, while the Freiburg database's time-domain signals had an accuracy of 79.7% and the highest accuracy of 94.02% for classification in the TUH EEG database when comparing interictal stage to preictal stage.
Analysis of driving style using self-organizing maps to analyze driver behaviorIJECEIAES
Modern life is strongly associated with the use of cars, but the increase in acceleration speeds and their maneuverability leads to a dangerous driving style for some drivers. In these conditions, the development of a method that allows you to track the behavior of the driver is relevant. The article provides an overview of existing methods and models for assessing the functioning of motor vehicles and driver behavior. Based on this, a combined algorithm for recognizing driving style is proposed. To do this, a set of input data was formed, including 20 descriptive features: About the environment, the driver's behavior and the characteristics of the functioning of the car, collected using OBD II. The generated data set is sent to the Kohonen network, where clustering is performed according to driving style and degree of danger. Getting the driving characteristics into a particular cluster allows you to switch to the private indicators of an individual driver and considering individual driving characteristics. The application of the method allows you to identify potentially dangerous driving styles that can prevent accidents.
Hyperspectral object classification using hybrid spectral-spatial fusion and ...IJECEIAES
Because of its spectral-spatial and temporal resolution of greater areas, hyperspectral imaging (HSI) has found widespread application in the field of object classification. The HSI is typically used to accurately determine an object's physical characteristics as well as to locate related objects with appropriate spectral fingerprints. As a result, the HSI has been extensively applied to object identification in several fields, including surveillance, agricultural monitoring, environmental research, and precision agriculture. However, because of their enormous size, objects require a lot of time to classify; for this reason, both spectral and spatial feature fusion have been completed. The existing classification strategy leads to increased misclassification, and the feature fusion method is unable to preserve semantic object inherent features; This study addresses the research difficulties by introducing a hybrid spectral-spatial fusion (HSSF) technique to minimize feature size while maintaining object intrinsic qualities; Lastly, a soft-margins kernel is proposed for multi-layer deep support vector machine (MLDSVM) to reduce misclassification. The standard Indian pines dataset is used for the experiment, and the outcome demonstrates that the HSSF-MLDSVM model performs substantially better in terms of accuracy and Kappa coefficient.
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
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.
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/
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• Indigenized local Support/presence in India.
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Performance analysis of real-time and general-purpose operating systems for path planning of the multi-robot systems
1. International Journal of Electrical and Computer Engineering (IJECE)
Vol. 12, No. 1, February 2022, pp. 285~292
ISSN: 2088-8708, DOI: 10.11591/ijece.v12i1.pp285-292 285
Journal homepage: http://ijece.iaescore.com
Performance analysis of real-time and general-purpose
operating systems for path planning of the multi-robot systems
Seçkin Canbaz1
, Gökhan Erdemir2
1
Department of Information Technologies, İstanbul Sabahattin Zaim University, Instanbul, Turkey
2
Department of Electrical and Electronics Engineering, İstanbul Sabahattin Zaim University, Instanbul, Turkey
Article Info ABSTRACT
Article history:
Received Mar 31, 2020
Revised Jun 17, 2021
Accepted Jun 30, 2021
In general, modern operating systems can be divided into two essential parts,
real-time operating systems (RTOS) and general-purpose operating systems
(GPOS). The main difference between GPOS and RTOS is the system is
time-critical or not. It means that; in GPOS, a high-priority thread cannot
preempt a kernel call. But, in RTOS, a low-priority task is preempted by a
high-priority task if necessary, even if it’s executing a kernel call. Most
Linux distributions can be used as both GPOS and RTOS with kernel
modifications. In this study, two Linux distributions, Ubuntu and Pardus,
were analyzed and their performances were compared both as GPOS and
RTOS for path planning of the multi-robot systems. Robot groups with
different numbers of members were used to perform the path tracking tasks
using both Ubuntu and Pardus as GPOS and RTOS. In this way, both the
performance of two different Linux distributions in robotic applications were
observed and compared in two forms, GPOS, and RTOS.
Keywords:
GPOS
Mobile robotics
Multi-robot systems
Path planning
RTOS
This is an open access article under the CC BY-SA license.
Corresponding Author:
Gökhan Erdemir
Department of Electrical and Electronics Engineering, Istanbul Sabahattin Zaim University
Halkali, Kucukcekmece, Istanbul 34303, Turkey
Email: gokhan.erdemir@izu.edu.tr
1. INTRODUCTION
In recent, almost all of electronic devices are designed for the devices to operate independently from
human beings and autonomously have operating systems to perform a specific task [1]-[5]. Commonly used
operating systems can be listed as android for mobile devices, windows for PCs, Linux and iOS for both
platforms. The main purpose of operating systems is to use the hardware most effectively and also to fulfill
the tasks in the fastest way [6]. On the other hand, operating systems have some dependencies while
performing described tasks. The time is one of the important dependencies for operating systems. The
calculation of the processing time is crucial parameter in especially time depended on operations and tasks. It
is an important parameter that determines the performance of an operating system and minimizes the
possibility of error [6]. Therefore, all operating systems have time dependencies. Two different time
calculation methods have been used which were named based on their kernel structures which depend on
operating systems type [4], [7]-[13]. These are general purpose operating system (GPOS) and real-time
operating system (RTOS).
GPOS is a common operating system type such as windows, Linux, android. that is designed to
fulfill personal use. The main purpose of GPOS, which is an operating system design that can be used by
everybody, is high efficiency. Efficiency is directly related to the number of tasks completed per unit cycle. It
means that GPOSs must support multi-tasking [8], [14]. On the other hand, task scheduling and allocation are
performed without priority levels of the tasks in GPOSs [15]. It is possible to execute lower priority tasks
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instead of higher priority tasks, primarily. In this way, system performance can be increased which depends
on the task-scheduling algorithms. It means that system efficiency can increase at the same time. However, it
is possible to occur delays in processing time in GPOS. This is a tolerable error, and it can be solved by using
effective task-scheduling and allocation algorithms. But, this situation can cause crucial errors if the task has
time dependency [4], [16]-[19]. For example, in the obstacle avoidance for mobile robots, when an obstacle
is detected, an obstacle avoidance task must be performed simultaneously. It means that the task must have
higher priority. Otherwise, the robot may hit the obstacle and an accident occurs. This is an undesirable and
unexpected situation. In order to avoid such an error, the task with high priority should be executed quickly.
RTOSs have been designed to solve high-time dependency tasks [9], [16], [17], [20]. RTOSs are
divided into three subcategories according to their time dependency. These are soft real-time, hard real-time,
and firm real-time, respectively [3], [9], [21]. The task processing and completion times are absolutely
certain in RTOS [22]. Since the task that is processed will finish at the end of a predetermined maximum
scheduling time, it is terminated or completed in a certain time [11], [23]. However, in some possible delays,
the responses of the system are various which depends on the type of RTOS. Delays are tolerable in soft real-
time systems, poorly tolerable in hard real-time systems, and no tolerance in firm real-time systems [12],
[24]-[26]. If the task is not completed on time, it is terminated or canceled in firm real-time systems [12],
[24]-[26]. It is crucially important to have highly precise decision ability for autonomous robot applications
in a dynamic and unknown environment [27]-[29]. The decision process is one of the high-time dependency
tasks, especially, detection and identification of obstacles [28], [30], [31].
RTOSs are divided into two types according to their core architectures which are monolithic kernel
and microkernel [32]-[35], as well. In a monolithic kernel, all processes in the operating system are defined
in the kernel. All processes such as file management and networking. run in the kernel. On the other hand,
applications work on the user side. The disadvantage of this design is the entire system can be affected by
any negativity in the kernel [32], [33]. In this structure, the whole kernel must be recompiled for a change
that can be performed [32], [33]. And, this process is a cause of the time loss [32], [33]. The whole operating
system processes work on the user side in microkernel systems [32]-[34]. All processes communicate with
each other. This approach increases the message traffic and decreases performance. But, the microkernel
architecture is more secure than the monolithic kernel architecture. An occurred error during task-processing
does not affect the whole system. It is not more complex because it contains less code [32]-[34].
In this study, GPOS and RTOS versions of Ubuntu and Pardus which are two Linux distributions
were analyzed to compare their performances on path planning of the multi-robot systems. Moreover, it is
possible to compare the performance of robot operating system (ROS) on these two distributions, in this
study. Robot groups with different numbers of members were used to perform the path tracking tasks using
both Ubuntu and Pardus as GPOS and RTOS to analyze their performance in the turtlesim simulation
environment. In this way, both the performance of two different Linux distributions in multi-robotic
applications were observed and compared. Two different path planning cases were performed, and results
were discussed.
2. RESEARCH METHOD
In this study, GPOS and RTOS were installed on two different Linux distributions which are Ubuntu
and Pardus, and system performances were analyzed. Ubuntu is one of the most popular Linux distribution
with a Linux kernel, using the Debian infrastructure and architecture [36]. This operating system, distributed
as open-source, has been developed since October 2004 and is currently the most popular Linux-based
system [36]. Pardus is an open-source operating system developed by Ulakbim and Tübitak using the Debian
infrastructure. Its distributions have been on the market since 2005 [37]. Experimental studies on the
simulation have been performed on ROS. Although ROS is perceived as a real operating system, it is actually
software based on an operating system and used for robot control [38]-[43]. It is possible to test mobile
robots in a virtual environment with the turtlesim package installed in the ROS noetic version. The turtlesim
package is a visualization tool that allows us to observe the movements of a virtual robot by working on ROS
via user codes [38]-[40]. ROS rqt plugin for turtlesim was used as a trajectory planning application of multi-
robot systems [44]. Free distribution and usage permissions are given in the license file in the application
[45]. The turtlesim plug-in in the rqt of [44], a selected picture as a planned path is drawn with the help of
swarm robots. In drawing the picture, the number of robots is various according to the size and complexity of
the picture [44]. In case studies, the computer which has an Intel Atom® N2600 1.6 Ghz processor, 2 GB
DDR3 RAM, 500 GB hard disk was used.
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3. EXPERIMENTAL STUDIES
All experimental studies were designed for path planning and formation control of multi-robot
system. Official logos of operating systems were used. In all case studies, [44] were used to draw robots's
paths.
3.1. Experiment 1 draw a path using Pardus logo
In this experiment, Pardus logo was drawn as simple path planning using [44]. Pardus GPOS-RTOS
and Ubuntu GPOS-RTOS operating systems were used with the same parameters. The results were recorded,
and performance comparison was performed. In Figure 1, Pardus official logo and selected paths were
shown, separately. The code was run with its default settings without changing and the same shape was
drawn in 4 different operating systems. In Figure 2, drawing paths by robots are shown by using turtlesim.
Thus, processor usage and processing time on the turtlesim were measured and recorded in the data table.
Results were presented in Figure 3, separately. According to results which were shown in Figure 3, central
processing unit (CPU) usage is lower and processing time is shorter than other operating systems when
Ubuntu GPOS was used. On the other hand, low CPU usage of RTOSs were observed than GPOS versions,
in Figure 3, as well.
Figure 1. Pardus logo and rqt turtlesim view
Figure 2. Drawing Padus logo path result drawn using turtlesim
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Figure 3. Processor usage graphs for experiment 1
3.2. Experiment 2 draw a path using Ubuntu-Linux logo
In this experiment, Ubuntu-Linux logo was drawn as simple path planning using [44]. Pardus
GPOS-RTOS and Ubuntu GPOS-RTOS operating systems were used with the same parameters. The results
were recorded, and performance comparison was performed. In Figure 4, Ubuntu-Linux official logo and
selected paths were shown, separately. The code was run with its default settings without changing and the
same shape was drawn in 4 different operating systems. In Figure 5, drawing paths by robots are shown by
using turtlesim. Thus, processor usage and processing time on the turtlesim were measured and recorded in
the data table. Results were presented in Figure 6, separately. According to results which were shown in
Figure 6, CPU usage is lower and processing time is shorter than other operating systems when Ubuntu
GPOS was used. On the other hand, low CPU usage of RTOSs were observed than GPOS versions, in Figure
6. Low CPU usage of RTOS was observed in both experiments. We can say that the main reason for this is
that the long processes are terminated and the other process is executed, in RTOS.
Figure 4. Ubuntu-Linux logo and rqt turtlesim view
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Figure 5. Drawing Ubuntu-Linux logo path result drawn using turtlesim
Figure 6. Processor usage graphs for experiment 2
4. RESULTS AND DISCUSSION
In experiment 1 and 2, complex trajectory tracking and formation control for multi-robot systems
were performed by using [44] on all operating systems. The processing times for each operating system are
presented in Table 1. As can be seen from the results in Table 1, in the comparison of RTOS and GPOS,
GPOSs give better results than RTOS in processing time. The main reason for this is while drawing a picture
in GPOS, when each robot's task is finished during drawing, the operating system reads the value and the
process of the next robot begins. But before beginning of the process in RTOS, the beginning and ending
times of the process is determined. If the processing time is set as 100 milliseconds for each process, even if
robot completes its task before 100 milliseconds, the resources will be available for the other robot at the end
of the 100 milliseconds. Although, this situation increases system security and reduces the margin of error, it
causes delays in processing times as it extends the processing time.
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Table 1. The processing times for each operating system (milliseconds)
Experiment
Ubuntu Pardus
GPOS RTOS GPOS RTOS
1 61.890 68.940 76.700 78000
2 48.130 49.960 57.160 58.210
As a result of this application, there are two results that can be observed clearly in the performance
evaluation of multi-robots in path planning and formation control. The first one is, GPOSs completed their
task earlier than RTOSs in two different operating systems. The second one is, Ubuntu GPOS and RTOS
completed processes faster than Pardus with limited resources. At the same time, it has been observed that all
operating systems completed their tasks without any problems.
5. CONCLUSION
In this study, open-source operating systems, Ubuntu and Pardus, were used as operating systems in
order to freely modify in the core codes and structure. The main aim of this study is to observe and to
compare usability of RTOS and GPOS in multi-robot systems. RTOSs were completed tasks later than the
GPOSs as expected. Because, even if the processes were completed, the operating system read the value at
the end of the exact processing time determined for the processes. The results vary due to the structural
features of the operating systems. When choosing an operating system for the multi-robot applications,
features such as possible failure conditions, process security, processing time speeds should be taken into
consideration. A defined process is terminated or completed at certain time when a process run on RTOS.
This is very important feature, if robot is used in time dependency applications. Since the processing times
are clearly defined, that task is canceled in the delay that occurs in a task and the whole system is not affected
by an error that occurs and the system remains alive. GPOS and RTOS were compared for path planning and
formation control of multi-robot systems using two different Linux distributions. According to the
experimental results, it was seen that GPOS concluded all defined task faster than RTOS. GPOS can be
preferred in a way that performance is in the foreground in studies to be carried out in the field of multi-
robotic systems. If the task has time dependency or the task requires certain processing time, RTOSs must be
used, absolutely.
ACKNOWLEDGEMENTS
This study was supported by the Istanbul Sabahattin Zaim University Scientific Research Program
[grant number: BAP-1000-62, 2021].
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BIOGRAPHIES OF AUTHORS
Seçkin Canbaz received his B.Sc. degree form Istanbul University, Faculty of
Science, Department of Physics in 2015. He started to work at Istanbul Sabahattin Zaim
University in the Department of Information Technologies in 2016. He is currently master
student at Istanbul Sabahattin Zaim University, Department of Computer Science and
Engineering. His research interests are open-source operating systems, real-time operating
systems and ROS. He can be contacted at email: seckin.canbaz@izu.edu.tr.
Gökhan Erdemir received his B.Sc., M.Sc. and Ph.D. degrees from Marmara
University, Turkey, respectively. During his Ph.D., we worked as a research scholar at
Michigan State University, Department of Electrical and Computer in East Lansing MI,
USA. Now, he is an assistant professor at Istanbul Sabahattin Zaim University, Department
of Electrical and Electronics Engineering. His research topics include robotics, control
systems, and intelligent algorithms. He can be contacted at email: gokhan.erdemir@izu.edu.tr.