This document provides an overview of various neural network architectures and their applications. It discusses deep neural networks, graph neural networks, fully convolutional neural networks, and recurrent neural networks. Applications mentioned include signal processing, pattern recognition, medical diagnosis, speech recognition, fault detection, and more. The document reviews several recent research papers on neural networks and their use in domains like gravitational wave detection, rolling bearing fault detection, neutrino detection, control systems, and speech segmentation.
A survey of models for computer networks managementIJCNCJournal
The virtualization concept along with its underlyin
g technologies has been warmly adopted in many fiel
ds
of computer science. In this direction, network vir
tualization research has presented considerable res
ults.
In a parallel development, the convergence of two d
istinct worlds, communications and computing, has
increased the use of computing server resources (vi
rtual machines and hypervisors acting as active
network elements) in network implementations. As a
result, the level of detail and complexity in such
architectures has increased and new challenges need
to be taken into account for effective network
management. Information and data models facilitate
infrastructure representation and management and
have been used extensively in that direction. In th
is paper we survey available modelling approaches a
nd
discuss how these can be used in the virtual machin
e (host) based computer network landscape; we prese
nt
a qualitative analysis of the current state-of-the-
art and offer a set of recommendations on adopting
any
particular method.
Analysis and assessment software for multi-user collaborative cognitive radi...IJECEIAES
Computer simulations are without a doubt a useful methodology that allows to explore research queries and develop prototypes at lower costs and timeframes than those required in hardware processes. The simulation tools used in cognitive radio networks (CRN) are undergoing an active process. Currently, there is no stable simulator that enables to characterize every element of the cognitive cycle and the available tools are a framework for discrete-event software. This work presents the spectral mobility simulator in CRN called “App MultiColl-DCRN”, developed with MATLAB’s app designer. In contrast with other frameworks, the simulator uses real spectral occupancy data and simultaneously analyzes features regarding spectral mobility, decision-making, multi-user access, collaborative scenarios and decentralized architectures. Performance metrics include bandwidth, throughput level, number of failed handoffs, number of total handoffs, number of handoffs with interference, number of anticipated handoffs and number of perfect handoffs. The assessment of the simulator involves three scenarios: the first and second scenarios present a collaborative structure using the multi-criteria optimization and compromise solution (VIKOR) decision-making model and the naïve Bayes prediction technique respectively. The third scenario presents a multi-user structure and uses simple additive weighting (SAW) as a decision-making technique. The present development represents a contribution in the cognitive radio network field since there is currently no software with the same features.
Wideband Sensing for Cognitive Radio Systems in Heterogeneous Next Generation...CSCJournals
Mobile Next Generation Network (MNGN) is characterized as heterogeneous network where variety of access technologies are meant to coexist. Decisions on choosing an air interface that meets a particular need at a particular time will be shifted from the network’s side to (a more intelligent) user’s side. On top of that network operators and regularities have come to the realization that assigned spectrum bands are not utilized as they should be. Cognitive radio stands out as a candidate technology to address many emerging issues in MNGN such as capacity, quality of service and spectral efficiency. As a transmission strategy, cognitive radio systems depend greatly on sensing the radio environment. In this paper, we present a novel approach for interference characterization in cognitive radio networks based on wideband chirp signal. The results presented show that improved sensing accuracy is maintained at tolerable system complexity.
DESIGN ISSUES ON SOFTWARE ASPECTS AND SIMULATION TOOLS FOR WIRELESS SENSOR NE...IJNSA Journal
In this paper, various existing simulation environments for general purpose and specific purpose WSNs are discussed. The features of number of different sensor network simulators and operating systems are compared. We have presented an overview of the most commonly used operating systems that can be used in different approaches to address the common problems of WSNs. For different simulation environments there are different layer, components and protocols implemented so that it is difficult to compare them. When same protocol is simulated using two different simulators still each protocol implementation differs, since their functionality is exactly not the same. Selection of simulator is purely based on the application, since each simulator has a varied range of performance depending on application.
Controller selection in software defined networks using best-worst multi-crit...journalBEEI
Controllers are the key component of Software-defined Network (SDN) architecture. Given the diversity of open SDN controllers, the following question arises for the network administrators: How can we choose the appropriate SDN controller? Different characteristics of the controllers have greatly increased the complexity of the right decision. Multi-Criteria Decision-making Methods (MCDMs) is a family of robust mathematical tools to address complex problems regarding multiple objectives. In this paper, we study the most important features of SDN controllers. To this end, we compare the well-known SDN controllers including NOX, POX, Beacon, Floodlight, Ryu, ODL, and ONOS. Leveraging a novel MCDM technique called the Best–Worst Multi-criteria (BWM), we find the most appropriate SDN controller. We solve an optimization problem and evaluate its performance in terms of significant criteria such as throughput and latency. Initial evaluation revealed that the ONOS and ODL have the highest throughput, while the lowest throughputs belong to the NOX, POX, and Ryu. However, final evaluation concerning all criteria confirmed the robustness of the ONOS and the ODL compared to other controllers.
A survey of models for computer networks managementIJCNCJournal
The virtualization concept along with its underlyin
g technologies has been warmly adopted in many fiel
ds
of computer science. In this direction, network vir
tualization research has presented considerable res
ults.
In a parallel development, the convergence of two d
istinct worlds, communications and computing, has
increased the use of computing server resources (vi
rtual machines and hypervisors acting as active
network elements) in network implementations. As a
result, the level of detail and complexity in such
architectures has increased and new challenges need
to be taken into account for effective network
management. Information and data models facilitate
infrastructure representation and management and
have been used extensively in that direction. In th
is paper we survey available modelling approaches a
nd
discuss how these can be used in the virtual machin
e (host) based computer network landscape; we prese
nt
a qualitative analysis of the current state-of-the-
art and offer a set of recommendations on adopting
any
particular method.
Analysis and assessment software for multi-user collaborative cognitive radi...IJECEIAES
Computer simulations are without a doubt a useful methodology that allows to explore research queries and develop prototypes at lower costs and timeframes than those required in hardware processes. The simulation tools used in cognitive radio networks (CRN) are undergoing an active process. Currently, there is no stable simulator that enables to characterize every element of the cognitive cycle and the available tools are a framework for discrete-event software. This work presents the spectral mobility simulator in CRN called “App MultiColl-DCRN”, developed with MATLAB’s app designer. In contrast with other frameworks, the simulator uses real spectral occupancy data and simultaneously analyzes features regarding spectral mobility, decision-making, multi-user access, collaborative scenarios and decentralized architectures. Performance metrics include bandwidth, throughput level, number of failed handoffs, number of total handoffs, number of handoffs with interference, number of anticipated handoffs and number of perfect handoffs. The assessment of the simulator involves three scenarios: the first and second scenarios present a collaborative structure using the multi-criteria optimization and compromise solution (VIKOR) decision-making model and the naïve Bayes prediction technique respectively. The third scenario presents a multi-user structure and uses simple additive weighting (SAW) as a decision-making technique. The present development represents a contribution in the cognitive radio network field since there is currently no software with the same features.
Wideband Sensing for Cognitive Radio Systems in Heterogeneous Next Generation...CSCJournals
Mobile Next Generation Network (MNGN) is characterized as heterogeneous network where variety of access technologies are meant to coexist. Decisions on choosing an air interface that meets a particular need at a particular time will be shifted from the network’s side to (a more intelligent) user’s side. On top of that network operators and regularities have come to the realization that assigned spectrum bands are not utilized as they should be. Cognitive radio stands out as a candidate technology to address many emerging issues in MNGN such as capacity, quality of service and spectral efficiency. As a transmission strategy, cognitive radio systems depend greatly on sensing the radio environment. In this paper, we present a novel approach for interference characterization in cognitive radio networks based on wideband chirp signal. The results presented show that improved sensing accuracy is maintained at tolerable system complexity.
DESIGN ISSUES ON SOFTWARE ASPECTS AND SIMULATION TOOLS FOR WIRELESS SENSOR NE...IJNSA Journal
In this paper, various existing simulation environments for general purpose and specific purpose WSNs are discussed. The features of number of different sensor network simulators and operating systems are compared. We have presented an overview of the most commonly used operating systems that can be used in different approaches to address the common problems of WSNs. For different simulation environments there are different layer, components and protocols implemented so that it is difficult to compare them. When same protocol is simulated using two different simulators still each protocol implementation differs, since their functionality is exactly not the same. Selection of simulator is purely based on the application, since each simulator has a varied range of performance depending on application.
Controller selection in software defined networks using best-worst multi-crit...journalBEEI
Controllers are the key component of Software-defined Network (SDN) architecture. Given the diversity of open SDN controllers, the following question arises for the network administrators: How can we choose the appropriate SDN controller? Different characteristics of the controllers have greatly increased the complexity of the right decision. Multi-Criteria Decision-making Methods (MCDMs) is a family of robust mathematical tools to address complex problems regarding multiple objectives. In this paper, we study the most important features of SDN controllers. To this end, we compare the well-known SDN controllers including NOX, POX, Beacon, Floodlight, Ryu, ODL, and ONOS. Leveraging a novel MCDM technique called the Best–Worst Multi-criteria (BWM), we find the most appropriate SDN controller. We solve an optimization problem and evaluate its performance in terms of significant criteria such as throughput and latency. Initial evaluation revealed that the ONOS and ODL have the highest throughput, while the lowest throughputs belong to the NOX, POX, and Ryu. However, final evaluation concerning all criteria confirmed the robustness of the ONOS and the ODL compared to other controllers.
An IOT Based Low Power Health Monitoring with Active Personal Assistanceijtsrd
Among sensible goals of active and assisted living paradigm is the unobtrusive monitoring of daily living activities. A lot of research has been going on continuous home and personal monitoring applications. There are many solutions were adapted by these technologies to make better remote monitoring applications. The traditional continuous home and personal monitoring systems which are implemented with traditional client server architecture which may fail in factors like low power consumption, un deterministic data delivery time, More sensitive to external connectivity issues temporary failures of servers , adhoc networks using ZigBee and Z wave etc. and also increase the cost of implementation. However, when dealing with the home environment, and especially with older adults, obtrusiveness, usability, and cost concerns are of the utmost relevance for active and assisted Living AAL joint program. With advent of cloud services, the continuous remote monitoring based applications became truly plug and play' approach implementation and also reduce the problems of temporary failures. One of the biggest challenges in this area is to make such application devices work with low power battery based applications . The main drawback comes from the higher power consumption, inherently needed to sustain much higher data rates. In this project, a solution is proposed to improve the low power consumption in Wi Fi sensors by making use of advanced RF based Microprocessor from Texas instruments CC3200 . Bed Occupancy sensor automation has been designed and implemented to test the feasibility of the approach. The TI CC3200 comes with ARM Cortex M4 as a core and inbuilt Wi Fi subsystem. The CC3200 provides different power modes to make the device enter into sleep or hibernate mode. This device will only enter only in work phase when the sensor is active state. During this phase, the processor sample and processes the sensor data and uploads to the cloud using REST API. Thing speak is an IoT cloud service used to present the sensory data as graphs, bar charts, and dashboards on the cloud remaining time it will enter into sleep phase to save the power of the device, so that it will extend the battery life time of the device. B. N. Meenakshi | Mrs. N. V. Durga "An IOT Based Low Power Health Monitoring with Active Personal Assistance" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-1 , December 2019, URL: https://www.ijtsrd.com/papers/ijtsrd29603.pdfPaper URL: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/29603/an-iot-based-low-power-health-monitoring-with-active-personal-assistance/b-n-meenakshi
SELF-ORGANIZATION AND AUTONOMOUS NETWORK SURVEYIJNSA Journal
The autonomic network gathers several aspects of Self-organization, which is depicted, into different
autonomous function such as the Self- configuration, the Self-optimization, the Self-repair, the Selfprotection, and the Self-cure. The latter is considered as one of the autonomous functions wished of a system network, which could be described by autonomous behavior is realized by structures of the control
loops and loop of control.
AN EFFICIENT SECURE CRYPTOGRAPHY SCHEME FOR NEW ML-BASED RPL ROUTING PROTOCOL...IJNSA Journal
Internet of Things (IoT) offers reliable and seamless communication for the heterogeneous dynamic lowpower and lossy network (LLNs). To perform effective routing in IoT communication, LLN Routing Protocol (RPL) is developed for the tiny nodes to establish connection by using deflaut objective functions: OF0, MRHOF, for which resources are constraints like battery power, computation capacity, memory communication link impacts on varying traffic scenarios in terms of QoS metrics like packet delivery ratio, delay, secure communication channel. At present, conventional Internet of Things (IoT) are having secure communication channels issue for transmission of data between nodes. To withstand those issues, it is necessary to balance resource constraints of nodes in the network. In this paper, we developed a security algorithm for IoT networks with RPL routing. Initially, the constructed network in corporates optimizationbased deep learning (reinforcement learning) for route establishment in IoT. Upon the establishment of the route, the ClonQlearn based security algorithm is implemented for improving security which is based onaECC scheme for encryption and decryption of data. The proposed security technique incorporates reinforcement learning-based ClonQlearnintegrated with ECC (ClonQlearn+ECC) for random key generation. The proposed ClonQlearn+ECCexhibits secure data transmission with improved network performance when compared with the earlier works in simulation. The performance of network expressed that the proposed ClonQlearn+ECC increased the PDR of approximately 8% - 10%, throughput of 7% - 13%, end-to-end delay of 5% - 10% and power consumption variation of 3% - 7%.
Minimum Process Coordinated Checkpointing Scheme For Ad Hoc Networks pijans
The wireless mobile ad hoc network (MANET) architecture is one consisting of a set of mobile hosts
capable of communicating with each other without the assistance of base stations. This has made possible
creating a mobile distributed computing environment and has also brought several new challenges in
distributed protocol design. In this paper, we study a very fundamental problem, the fault tolerance
problem, in a MANET environment and propose a minimum process coordinated checkpointing scheme.
Since potential problems of this new environment are insufficient power and limited storage capacity, the
proposed scheme tries to reduce the amount of information saved for recovery. The MANET structure used
in our algorithm is hierarchical based. The scheme is based for Cluster Based Routing Protocol (CBRP)
which belongs to a class of Hierarchical Reactive routing protocols. The protocol proposed by us is nonblocking coordinated checkpointing algorithm suitable for ad hoc environments. It produces a consistent
set of checkpoints; the algorithm makes sure that only minimum number of nodes in the cluster are
required to take checkpoints; it uses very few control messages. Performance analysis shows that our
algorithm outperforms the existing related works and is a novel idea in the field. Firstly, we describe an
organization of the cluster. Then we propose a minimum process coordinated checkpointing scheme for
cluster based ad hoc routing protocols.
Remote temperature and humidity monitoring system using wireless sensor networkseSAT Journals
Abstract Today’s world has become very advanced with smart appliances and devices like laptops, tablets, televisions. smart phones with different features and their usage has been enormously increasing in our day-to-day life. The technology advancement in Digital Electronics and Micro Electro Mechanical Systems. In this scenario the most important role is played by Wireless Sensor Networks and its development and usage in heterogeneous fields and several contexts. the home automation field and process control systems and health control systems widely uses wireless sensor networks. Moreover with WSN we can monitor environments and its conditions also. We are designing a protocol to monitor the environmental temperature and humidity at different conditions. The architecture is simple to construct and ease to implement and also has an advantage of low power consumption. The aim of our paper to describe and show how to create a simple protocol for environment monitoring using a wireless development kit. we are using advanced technology of crossbow motes and NESC Language Programming. Keywords: Motes, WSN, sensor, TinyOS, Nesc.
Compact optimized deep learning model for edge: a reviewIJECEIAES
Most real-time computer vision applications, such as pedestrian detection, augmented reality, and virtual reality, heavily rely on convolutional neural networks (CNN) for real-time decision support. In addition, edge intelligence is becoming necessary for low-latency real-time applications to process the data at the source device. Therefore, processing massive amounts of data impact memory footprint, prediction time, and energy consumption, essential performance metrics in machine learning based internet of things (IoT) edge clusters. However, deploying deeper, dense, and hefty weighted CNN models on resource-constraint embedded systems and limited edge computing resources, such as memory, and battery constraints, poses significant challenges in developing the compact optimized model. Reducing the energy consumption in edge IoT networks is possible by reducing the computation and data transmission between IoT devices and gateway devices. Hence there is a high demand for making energy-efficient deep learning models for deploying on edge devices. Furthermore, recent studies show that smaller compressed models achieve significant performance compared to larger deep-learning models. This review article focuses on state-of-the-art techniques of edge intelligence, and we propose a new research framework for designing a compact optimized deep learning (DL) model deployment on edge devices.
Wireless Sensor Network Based Clustering Architecture for Cooperative Communi...ijtsrd
We propose clusters based cooperatives based verbal architecture coop on the cellular ad hoc wireless sensor network Mawsn with the environment fading Rayleigh. The main ability and contributions of this paper are as follows. First, the proposed cage uses a cluster as a underlying system to help stable transmission services. 2D, the proposed enclosure uses a cluster based verbal cooperative exchange to effectively guide the package delivery ratio with multi hop power saving transmission. 0.33, we do not forget reasonable methods mainly based on cellular ad hoc nodes with sensing features and constant sensor nodes in the sensor field along with conventional research for the introduction of constant network sensors. Fourth, we have theoretical analysis with blackouts opportunities for proposed cooperative transmissions. Overall performance evaluation is run through simulation and evaluation. Sweeti Kumari | Dr. Ranjan Kumar Singh "Wireless Sensor Network Based Clustering Architecture for Cooperative Communication" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd43670.pdf Paper URL: https://www.ijtsrd.comengineering/electronics-and-communication-engineering/43670/wireless-sensor-network-based-clustering-architecture-for-cooperative-communication/sweeti-kumari
Feasibility of Artificial Neural Network in Civil Engineeringijtsrd
An Artificial neural network ANN is an information processing hypothesis that is stimulated by the way natural nervous system, such as brain, process information. The using of artificial neural network in civil engineering is getting more and more credit all over the world in last decades. This soft computing method has been shown to be very effective in the analysis and solution of civil engineering problems. It is defined as a body which works out the more and more complex problem through sequential algorithms. It is designed on the basis of artificial intelligence which is proficient of storing more and more information's. In this work, we have investigated the various architectures of ANN and their learning process. The artificial neural network based method was widely applied to the civil engineering because of the strong non linear relationship between known and un known of the problems. They come with good modelling in areas where conventional approaches finite elements, finite differences etc. require large computing resources or time to solve problems. These includes to study the behaviour of building materials, structural identification and control problems, in geo technical engineering like earthquake induced liquefaction potential, in heat transfer problems in civil engineering to improve air quality, in transportation engineering like identification of traffic problems to improve its flexibility , in construction technology and management to estimate the cost of buildings and in building services issues like analyzing the water distribution network etc. Researches reveals that the method is realistic and it will be fascinated for more civil engineering applications. Vikash Singh | Samreen Bano | Anand Kumar Yadav | Dr. Sabih Ahmad ""Feasibility of Artificial Neural Network in Civil Engineering"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019, URL: https://www.ijtsrd.com/papers/ijtsrd22985.pdf
Paper URL: https://www.ijtsrd.com/engineering/civil-engineering/22985/feasibility-of-artificial-neural-network-in-civil-engineering/vikash-singh
A Network Intrusion Detection System (NIDS) monitors a network for malicious activities or policy violations [1]. The Kernel-based Virtual Machine (KVM) is a full virtualization solution for Linux on x86 hardware virtualization extensions [2]. We design and implement a back-propagation network intrusion detection system in KVM. Compared to traditional Back Propagation (BP) NIDS, the Particle Swarm Optimization (PSO) algorithm is applied to improve efficiency. The results show an improved system in terms of recall and precision along with missing detection rates.
An IOT Based Low Power Health Monitoring with Active Personal Assistanceijtsrd
Among sensible goals of active and assisted living paradigm is the unobtrusive monitoring of daily living activities. A lot of research has been going on continuous home and personal monitoring applications. There are many solutions were adapted by these technologies to make better remote monitoring applications. The traditional continuous home and personal monitoring systems which are implemented with traditional client server architecture which may fail in factors like low power consumption, un deterministic data delivery time, More sensitive to external connectivity issues temporary failures of servers , adhoc networks using ZigBee and Z wave etc. and also increase the cost of implementation. However, when dealing with the home environment, and especially with older adults, obtrusiveness, usability, and cost concerns are of the utmost relevance for active and assisted Living AAL joint program. With advent of cloud services, the continuous remote monitoring based applications became truly plug and play' approach implementation and also reduce the problems of temporary failures. One of the biggest challenges in this area is to make such application devices work with low power battery based applications . The main drawback comes from the higher power consumption, inherently needed to sustain much higher data rates. In this project, a solution is proposed to improve the low power consumption in Wi Fi sensors by making use of advanced RF based Microprocessor from Texas instruments CC3200 . Bed Occupancy sensor automation has been designed and implemented to test the feasibility of the approach. The TI CC3200 comes with ARM Cortex M4 as a core and inbuilt Wi Fi subsystem. The CC3200 provides different power modes to make the device enter into sleep or hibernate mode. This device will only enter only in work phase when the sensor is active state. During this phase, the processor sample and processes the sensor data and uploads to the cloud using REST API. Thing speak is an IoT cloud service used to present the sensory data as graphs, bar charts, and dashboards on the cloud remaining time it will enter into sleep phase to save the power of the device, so that it will extend the battery life time of the device. B. N. Meenakshi | Mrs. N. V. Durga "An IOT Based Low Power Health Monitoring with Active Personal Assistance" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-1 , December 2019, URL: https://www.ijtsrd.com/papers/ijtsrd29603.pdfPaper URL: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/29603/an-iot-based-low-power-health-monitoring-with-active-personal-assistance/b-n-meenakshi
SELF-ORGANIZATION AND AUTONOMOUS NETWORK SURVEYIJNSA Journal
The autonomic network gathers several aspects of Self-organization, which is depicted, into different
autonomous function such as the Self- configuration, the Self-optimization, the Self-repair, the Selfprotection, and the Self-cure. The latter is considered as one of the autonomous functions wished of a system network, which could be described by autonomous behavior is realized by structures of the control
loops and loop of control.
AN EFFICIENT SECURE CRYPTOGRAPHY SCHEME FOR NEW ML-BASED RPL ROUTING PROTOCOL...IJNSA Journal
Internet of Things (IoT) offers reliable and seamless communication for the heterogeneous dynamic lowpower and lossy network (LLNs). To perform effective routing in IoT communication, LLN Routing Protocol (RPL) is developed for the tiny nodes to establish connection by using deflaut objective functions: OF0, MRHOF, for which resources are constraints like battery power, computation capacity, memory communication link impacts on varying traffic scenarios in terms of QoS metrics like packet delivery ratio, delay, secure communication channel. At present, conventional Internet of Things (IoT) are having secure communication channels issue for transmission of data between nodes. To withstand those issues, it is necessary to balance resource constraints of nodes in the network. In this paper, we developed a security algorithm for IoT networks with RPL routing. Initially, the constructed network in corporates optimizationbased deep learning (reinforcement learning) for route establishment in IoT. Upon the establishment of the route, the ClonQlearn based security algorithm is implemented for improving security which is based onaECC scheme for encryption and decryption of data. The proposed security technique incorporates reinforcement learning-based ClonQlearnintegrated with ECC (ClonQlearn+ECC) for random key generation. The proposed ClonQlearn+ECCexhibits secure data transmission with improved network performance when compared with the earlier works in simulation. The performance of network expressed that the proposed ClonQlearn+ECC increased the PDR of approximately 8% - 10%, throughput of 7% - 13%, end-to-end delay of 5% - 10% and power consumption variation of 3% - 7%.
Minimum Process Coordinated Checkpointing Scheme For Ad Hoc Networks pijans
The wireless mobile ad hoc network (MANET) architecture is one consisting of a set of mobile hosts
capable of communicating with each other without the assistance of base stations. This has made possible
creating a mobile distributed computing environment and has also brought several new challenges in
distributed protocol design. In this paper, we study a very fundamental problem, the fault tolerance
problem, in a MANET environment and propose a minimum process coordinated checkpointing scheme.
Since potential problems of this new environment are insufficient power and limited storage capacity, the
proposed scheme tries to reduce the amount of information saved for recovery. The MANET structure used
in our algorithm is hierarchical based. The scheme is based for Cluster Based Routing Protocol (CBRP)
which belongs to a class of Hierarchical Reactive routing protocols. The protocol proposed by us is nonblocking coordinated checkpointing algorithm suitable for ad hoc environments. It produces a consistent
set of checkpoints; the algorithm makes sure that only minimum number of nodes in the cluster are
required to take checkpoints; it uses very few control messages. Performance analysis shows that our
algorithm outperforms the existing related works and is a novel idea in the field. Firstly, we describe an
organization of the cluster. Then we propose a minimum process coordinated checkpointing scheme for
cluster based ad hoc routing protocols.
Remote temperature and humidity monitoring system using wireless sensor networkseSAT Journals
Abstract Today’s world has become very advanced with smart appliances and devices like laptops, tablets, televisions. smart phones with different features and their usage has been enormously increasing in our day-to-day life. The technology advancement in Digital Electronics and Micro Electro Mechanical Systems. In this scenario the most important role is played by Wireless Sensor Networks and its development and usage in heterogeneous fields and several contexts. the home automation field and process control systems and health control systems widely uses wireless sensor networks. Moreover with WSN we can monitor environments and its conditions also. We are designing a protocol to monitor the environmental temperature and humidity at different conditions. The architecture is simple to construct and ease to implement and also has an advantage of low power consumption. The aim of our paper to describe and show how to create a simple protocol for environment monitoring using a wireless development kit. we are using advanced technology of crossbow motes and NESC Language Programming. Keywords: Motes, WSN, sensor, TinyOS, Nesc.
Compact optimized deep learning model for edge: a reviewIJECEIAES
Most real-time computer vision applications, such as pedestrian detection, augmented reality, and virtual reality, heavily rely on convolutional neural networks (CNN) for real-time decision support. In addition, edge intelligence is becoming necessary for low-latency real-time applications to process the data at the source device. Therefore, processing massive amounts of data impact memory footprint, prediction time, and energy consumption, essential performance metrics in machine learning based internet of things (IoT) edge clusters. However, deploying deeper, dense, and hefty weighted CNN models on resource-constraint embedded systems and limited edge computing resources, such as memory, and battery constraints, poses significant challenges in developing the compact optimized model. Reducing the energy consumption in edge IoT networks is possible by reducing the computation and data transmission between IoT devices and gateway devices. Hence there is a high demand for making energy-efficient deep learning models for deploying on edge devices. Furthermore, recent studies show that smaller compressed models achieve significant performance compared to larger deep-learning models. This review article focuses on state-of-the-art techniques of edge intelligence, and we propose a new research framework for designing a compact optimized deep learning (DL) model deployment on edge devices.
Wireless Sensor Network Based Clustering Architecture for Cooperative Communi...ijtsrd
We propose clusters based cooperatives based verbal architecture coop on the cellular ad hoc wireless sensor network Mawsn with the environment fading Rayleigh. The main ability and contributions of this paper are as follows. First, the proposed cage uses a cluster as a underlying system to help stable transmission services. 2D, the proposed enclosure uses a cluster based verbal cooperative exchange to effectively guide the package delivery ratio with multi hop power saving transmission. 0.33, we do not forget reasonable methods mainly based on cellular ad hoc nodes with sensing features and constant sensor nodes in the sensor field along with conventional research for the introduction of constant network sensors. Fourth, we have theoretical analysis with blackouts opportunities for proposed cooperative transmissions. Overall performance evaluation is run through simulation and evaluation. Sweeti Kumari | Dr. Ranjan Kumar Singh "Wireless Sensor Network Based Clustering Architecture for Cooperative Communication" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd43670.pdf Paper URL: https://www.ijtsrd.comengineering/electronics-and-communication-engineering/43670/wireless-sensor-network-based-clustering-architecture-for-cooperative-communication/sweeti-kumari
Feasibility of Artificial Neural Network in Civil Engineeringijtsrd
An Artificial neural network ANN is an information processing hypothesis that is stimulated by the way natural nervous system, such as brain, process information. The using of artificial neural network in civil engineering is getting more and more credit all over the world in last decades. This soft computing method has been shown to be very effective in the analysis and solution of civil engineering problems. It is defined as a body which works out the more and more complex problem through sequential algorithms. It is designed on the basis of artificial intelligence which is proficient of storing more and more information's. In this work, we have investigated the various architectures of ANN and their learning process. The artificial neural network based method was widely applied to the civil engineering because of the strong non linear relationship between known and un known of the problems. They come with good modelling in areas where conventional approaches finite elements, finite differences etc. require large computing resources or time to solve problems. These includes to study the behaviour of building materials, structural identification and control problems, in geo technical engineering like earthquake induced liquefaction potential, in heat transfer problems in civil engineering to improve air quality, in transportation engineering like identification of traffic problems to improve its flexibility , in construction technology and management to estimate the cost of buildings and in building services issues like analyzing the water distribution network etc. Researches reveals that the method is realistic and it will be fascinated for more civil engineering applications. Vikash Singh | Samreen Bano | Anand Kumar Yadav | Dr. Sabih Ahmad ""Feasibility of Artificial Neural Network in Civil Engineering"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019, URL: https://www.ijtsrd.com/papers/ijtsrd22985.pdf
Paper URL: https://www.ijtsrd.com/engineering/civil-engineering/22985/feasibility-of-artificial-neural-network-in-civil-engineering/vikash-singh
A Network Intrusion Detection System (NIDS) monitors a network for malicious activities or policy violations [1]. The Kernel-based Virtual Machine (KVM) is a full virtualization solution for Linux on x86 hardware virtualization extensions [2]. We design and implement a back-propagation network intrusion detection system in KVM. Compared to traditional Back Propagation (BP) NIDS, the Particle Swarm Optimization (PSO) algorithm is applied to improve efficiency. The results show an improved system in terms of recall and precision along with missing detection rates.
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6th International Conference on Machine Learning & Applications (CMLA 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of on Machine Learning & Applications.
Online aptitude test management system project report.pdfKamal Acharya
The purpose of on-line aptitude test system is to take online test in an efficient manner and no time wasting for checking the paper. The main objective of on-line aptitude test system is to efficiently evaluate the candidate thoroughly through a fully automated system that not only saves lot of time but also gives fast results. For students they give papers according to their convenience and time and there is no need of using extra thing like paper, pen etc. This can be used in educational institutions as well as in corporate world. Can be used anywhere any time as it is a web based application (user Location doesn’t matter). No restriction that examiner has to be present when the candidate takes the test.
Every time when lecturers/professors need to conduct examinations they have to sit down think about the questions and then create a whole new set of questions for each and every exam. In some cases the professor may want to give an open book online exam that is the student can take the exam any time anywhere, but the student might have to answer the questions in a limited time period. The professor may want to change the sequence of questions for every student. The problem that a student has is whenever a date for the exam is declared the student has to take it and there is no way he can take it at some other time. This project will create an interface for the examiner to create and store questions in a repository. It will also create an interface for the student to take examinations at his convenience and the questions and/or exams may be timed. Thereby creating an application which can be used by examiners and examinee’s simultaneously.
Examination System is very useful for Teachers/Professors. As in the teaching profession, you are responsible for writing question papers. In the conventional method, you write the question paper on paper, keep question papers separate from answers and all this information you have to keep in a locker to avoid unauthorized access. Using the Examination System you can create a question paper and everything will be written to a single exam file in encrypted format. You can set the General and Administrator password to avoid unauthorized access to your question paper. Every time you start the examination, the program shuffles all the questions and selects them randomly from the database, which reduces the chances of memorizing the questions.
NUMERICAL SIMULATIONS OF HEAT AND MASS TRANSFER IN CONDENSING HEAT EXCHANGERS...ssuser7dcef0
Power plants release a large amount of water vapor into the
atmosphere through the stack. The flue gas can be a potential
source for obtaining much needed cooling water for a power
plant. If a power plant could recover and reuse a portion of this
moisture, it could reduce its total cooling water intake
requirement. One of the most practical way to recover water
from flue gas is to use a condensing heat exchanger. The power
plant could also recover latent heat due to condensation as well
as sensible heat due to lowering the flue gas exit temperature.
Additionally, harmful acids released from the stack can be
reduced in a condensing heat exchanger by acid condensation. reduced in a condensing heat exchanger by acid condensation.
Condensation of vapors in flue gas is a complicated
phenomenon since heat and mass transfer of water vapor and
various acids simultaneously occur in the presence of noncondensable
gases such as nitrogen and oxygen. Design of a
condenser depends on the knowledge and understanding of the
heat and mass transfer processes. A computer program for
numerical simulations of water (H2O) and sulfuric acid (H2SO4)
condensation in a flue gas condensing heat exchanger was
developed using MATLAB. Governing equations based on
mass and energy balances for the system were derived to
predict variables such as flue gas exit temperature, cooling
water outlet temperature, mole fraction and condensation rates
of water and sulfuric acid vapors. The equations were solved
using an iterative solution technique with calculations of heat
and mass transfer coefficients and physical properties.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.