The International Journal of Advanced Manufacturing Technology
Smart industries use modern technologies such as machine learning and big data to maintain supply... more Smart industries use modern technologies such as machine learning and big data to maintain supply chain management and increase productivity but still the main challenge faced during quality control as this might affect the production rate. Smart industries are completely based on supervised learning that enables better inspection and effectively controls the parameter involved in the production process. Smart industries choose the mechanism that improves production and assures maximum quality. The various kernel function is initially used to select and extract a parameter. Support vector machine (SVM) is a supervised learning approach used in manufacturing industries to evaluate quality control. The SVM model uses the kernel function, namely RBF, along with Neural Networks, in identifying the parameter involved in quality management and undergoes the classification process. SVM consists of C-SVM and V-SVM classifier models involved in the classification process and undergoes training to handle the multiple numbers of consequence aroused during manufacturing. The performance of SVM classifiers and RBF NNs is evaluated. Different kernel functions, such as polynomial, linear, sigmoid, RBF, and over-varying gamma coefficient values, are tested in the experimental evaluation concerned with the comparative analysis of the continuous quality control function of the SVM classifier. Experimental results demonstrate the superiority of the SVM classifier in terms of the estimated computational time (88.1%), F1-measure (89.4%), ROC (65%), and accuracy (94.6%). The goal of the proposed model is to monitor the manufacturing process and control fault occurrence.
The internet, like automated tools, has grown to better our daily lives. Interacting IoT products... more The internet, like automated tools, has grown to better our daily lives. Interacting IoT products and cyber-physical systems. Generative Adversarial Network's (GANs') generator and discriminator may have different inputs, allowing feedback in supervised models. AI systems use neural networks, and adversarial networks analyse neural network feedback. Cyber-physical production systems (CPPS) herald intelligent manufacturing. CPPS may launch cross-domain attacks since the virtual and real worlds are interwoven. This project addresses enhanced Cyber-Physical System(CPS) feedback structure for Denial-of-Service (DoS) defence. Comparing sensor-controller and controller-to-actuator DoS attack channels shows a swapping system modelling solution for the CPS's complex response feedback. Because of the differential in bandwidth between the two channels and the suspects' limited energy, one person can only launch so many DoS assaults. DoS attacks are old and widespread. Create a layered switching paradigm that employs packet-based transfer techniques to prevent assaults. The discriminator's probability may be used to assess whether feedback samples came from real or fictional data. Cognitive feedback can assess GA feedback data.
The International Journal of Advanced Manufacturing Technology, 2023
Smart industries use modern technologies such as machine learning and big data to maintain supply... more Smart industries use modern technologies such as machine learning and big data to maintain supply chain management and increase productivity but still the main challenge faced during quality control as this might affect the production rate. Smart industries are completely based on supervised learning that enables better inspection and effectively controls the parameter involved in the production process. Smart industries choose the mechanism that improves production and assures maximum quality. The various kernel function is initially used to select and extract a parameter. Support vector machine (SVM) is a supervised learning approach used in manufacturing industries to evaluate quality control. The SVM model uses the kernel function, namely RBF, along with Neural Networks, in identifying the parameter involved in quality management and undergoes the classification process. SVM consists of C-SVM and V-SVM classifier models involved in the classification process and undergoes training to handle the multiple numbers of consequence aroused during manufacturing. The performance of SVM classifiers and RBF NNs is evaluated. Different kernel functions, such as polynomial, linear, sigmoid, RBF, and over-varying gamma coefficient values, are tested in the experimental evaluation concerned with the comparative analysis of the continuous quality control function of the SVM classifier. Experimental results demonstrate the superiority of the SVM classifier in terms of the estimated computational time (88.1%), F1-measure (89.4%), ROC (65%), and accuracy (94.6%). The goal of the proposed model is to monitor the manufacturing process and control fault occurrence.
The internet, like automated tools, has grown to better our daily lives. Interacting IoT products... more The internet, like automated tools, has grown to better our daily lives. Interacting IoT products and cyber-physical systems. Generative Adversarial Network's (GANs') generator and discriminator may have different inputs, allowing feedback in supervised models. AI systems use neural networks, and adversarial networks analyse neural network feedback. Cyber-physical production systems (CPPS) herald intelligent manufacturing. CPPS may launch cross-domain attacks since the virtual and real worlds are interwoven. This project addresses enhanced Cyber-Physical System(CPS) feedback structure for Denial-of-Service (DoS) defence. Comparing sensor-controller and controller-to-actuator DoS attack channels shows a swapping system modelling solution for the CPS's complex response feedback. Because of the differential in bandwidth between the two channels and the suspects' limited energy, one person can only launch so many DoS assaults. DoS attacks are old and widespread. Create a layered switching paradigm that employs packet-based transfer techniques to prevent assaults. The discriminator's probability may be used to assess whether feedback samples came from real or fictional data. Cognitive feedback can assess GA feedback data.
International Journal of System Assurance Engineering and Management
We reside in an environment wherein robotics is used in a variety of circumstances daily. In the ... more We reside in an environment wherein robotics is used in a variety of circumstances daily. In the best-case scenario, this contact seems as natural and comfortable as human-to-human conversation. Audiovisual speech synthesis is an appropriate way of communication between a human and a robot in this case. The robot is able to communicate to its users due to audiovisual text-to-speech synthesis technology. A diverse range of approaches are conducted to synthesis audiovisual speech has been established during the previous few years. The proposed Robot Operating System (ROS) performs the collaborative analysis of audio-visual speech synthesis using sensors measurement to enable the interaction between humans and robots. Skeletal tracking, gesture identification are performed by utilizing a depth camera, as well as facial recognition utilizing an RGB camera are aspects of visual-based entities. Auditory perception is dependent on the use of a microphone array to locate sound sources. We offer a top-down hierarchy communication protocol-based integration architecture for these entities. The top layer of integration contains the message about the number of people and associated states that are changed from a number of the lower-level perceptive entity.
Waste Electric and Electronic Component (WEEE) is becoming a major issue for the environment and ... more Waste Electric and Electronic Component (WEEE) is becoming a major issue for the environment and the society. The hazardous metal contents available in WEEE can leave harmful impact on the well-being of humans and animals. The existing methods of Electronic Waste (E-waste) treatment are reuse, recycle and remanufacture. Along with these methods incineration and landfilling are also considered as options for Ewaste treatment. The recycling of E-waste helps in waste treatment and in the recovery of valuable metals. This paper gives a systematic review of existing recycling techniques for Ewaste management, their advantages and limitations and valuable metals recovery from E-waste. This article may help in waste utilization and metal recovery from E-waste. This article also reviews the opportunities and challenges faced in the process of metal recovery from E-waste.
In the Modern World, women are no longer considered as the minor group. They share the same power... more In the Modern World, women are no longer considered as the minor group. They share the same power, privileges, rights, and opportunities as men. They have been excelled in many fields and contributing to the development of the entire globe. But, in many developing and under developed countries, still women community has not raised up, specifically due to the challenges they face in terms of unethical physical harassment from the society. This paper presents a comprehensive survey on design and application approaches in women safety systems. There are many promising technologies relied on women security systems using IoT, Embedded, Artificial Intelligence, Machine Learning, Augmented Reality, android Mobile apps etc. We have undergone with a comparative analysis of such techniques and open research issues that would enable the researchers to design a complete women security system for the beneficial of the entire women community in global level.
International Journal of Systems Assurance Engineering & Management , 2022
We reside in an environment wherein robotics is
used in a variety of circumstances daily. In the ... more We reside in an environment wherein robotics is used in a variety of circumstances daily. In the best-case scenario, this contact seems as natural and comfortable as human-to-human conversation. Audiovisual speech synthesis is an appropriate way of communication between a human and a robot in this case. The robot is able to communicate to its users due to audiovisual text-to-speech synthesis technology. A diverse range of approaches are conducted to synthesis audiovisual speech has been established during the previous few years. The proposed Robot Operating System (ROS) performs the collaborative analysis of audio-visual speech synthesis using sensors measurement to enable the interaction between humans and robots. Skeletal tracking, gesture identification are performed by utilizing a depth camera, as well as facial recognition utilizing an RGB camera are aspects of visual-based entities. Auditory perception is dependent on the use of a microphone array to locate sound sources. We offer a top-down hierarchy communication protocol-based integration architecture for these entities. The top layer of integration contains the message about the number of people and associated states that are changed from a number of the lower-level perceptive entity.
The use of MIMO networks in wireless communication results in increased data rate but leads to se... more The use of MIMO networks in wireless communication results in increased data rate but leads to severe interference issues and power losses. Promising beamforming (BF) architecture with Conditional Time split-Energy Extraction (CT-EE) is proposed to maximize the Energy Efficiency while optimizing the Mean Square Error (MSE) and Achievable Sum Rate (ASR). A distributed BF system using Minimum Mean Square Error algorithm is jointly implemented at all cooperating nodes. Energy Extraction (EE) from RF signal at the relay nodes facilitates full connectivity among the users. The signal transmission and EE phases are jointly implemented using time-split architecture, without using fixed pre-assigned time slots. Time split from information decoding to EE phase is done only if the battery life is found to be critical. The paper investigates the scope of bypassing the EE phase after ensuring the required power level. The performance of the proposed architecture is compared with the conventional BF and existing EE methods in terms of MSE, ASR and energy efficiency. The proposed architecture is well suitable to establish uninterrupted connectivity between user nodes which are frequently used and have severe power drain-off issues as they can be a part of natural disaster like flood affected wireless networks. INDEX TERMS Achievable sum rate, beamforming, conditional time split, energy efficiency, energy extraction, MIMO networks, minimum mean square error.
Multiple Input Multiple Output (MIMO) networks operating in millimeter wave frequency band bring ... more Multiple Input Multiple Output (MIMO) networks operating in millimeter wave frequency band bring promising solutions for the increased demand of future generation networks in terms of data rate, signal quality, power optimization and computational complexity. A joint beam-forming (JBF) system working concurrently on source-relay-destination nodes leads to faithful delivery of signals by mitigating the effect of interferences. The traditional JBF designs in MIMO networks yield power wastage due to undesirable participation of intermediate relay nodes for message forwarding. The computational delay in beam-forming (BF) matrix update is tedious in traditional systems. This paper proposes a novel design of power-optimized JBF that facilitates optimum relay selection for solving power wastage issues. The selected relays cooperate in BF with the power constraint, and all other relays are powered down and enter into sleeping mode. Modified Cuckoo-Search Optimization (MCSO) algorithm is used for relay selection and minimum mean square error algorithm is used for BF matrix calculation. The proposed JBF is able to maximize Achievable Sum Rate (ASR) for optimum value of transmission power. The maximum power efficiency is achieved for distant communication with the aid of selected relays contributing to maximizing the ASR value. The proposed work minimizes the sum of mean square error and concurrently computes optimum time slot for BF matrix update, and hence computational delay is reduced. Thus a hybrid optimization for power and time in JBF design is achieved with relay selection and it can be widely used in future generation networks for high-quality and interference-free communication.
International journal of Advanced Engineering Research & Technology, 2016
Image decomposition is an ill-posed problem usually
addressed in various applications of image p... more Image decomposition is an ill-posed problem usually
addressed in various applications of image processing such as
image denoising, enhancement etc.. In normal image
denoising processes, it is not clear how to decompose the
image into multiple semantic components and thereby
removing those components which correspond to undesirable
noise patterns. Here in this paper, we introduces an image
decomposition framework using Discrete Wavelet
Transform(DWT) filters. The system first identifies and
learns an over-complete dictionary from the high spatial
frequency parts of the input image for reconstruction
purposes. Then performs unsupervised clustering on the
observed dictionary atoms via method of affinity
propagation. Once the proposed system identifies the image
components which are similar, then the proposed framework
automatically removes the noise contaminated image
components directly from the input image. The performance
of this approach depends on the relative denoising techniques
used and on the number of iterations of the algorithm and in
most of the cases we require more than hundred iterations
which increase the efficiency of the system. In this paper, we
propose a new and improved method for increasing the
overall efficiency of the system. Introduction of DWT filter
into the existing system for images corrupted by Gaussian
noise or rain noise are very useful because of its ability to
capture the signal energy in few energy transformation
values. Our experiments show that the proposed system
yields improvements in PSNR and thereby increases the
sharpness of images mainly at the edges.
International Journal of Scientific Engineering and Technology Research, 2017
This letter shows a back slide predicated verbalization enhancement framework using significant n... more This letter shows a back slide predicated verbalization enhancement framework using significant neural frameworks (DNNs) with a various layer significant designing. In the DNN discernment process, a sizably voluminous get ready set finds a horrifying showing personnel to assess the perplexed nonlinear mapping from optically solicited strepitous verbalization to needed clean banners. Acoustic setting was found to enhance the movement of verbalization to be dissevered from the substructure disturbances prosperously without the annoying melodic relic for the most part outwardly saw in customary verbalization overhaul figurings. A movement of pilot tests was coordinated under multi-condition planning with more than 100 hours of replicated verbalization data, setting up a good notional hypothesis limit even in scrambled testing conditions. Right when differentiated and the logarithmic minimum mean square mix-up approach, the proposed DNN-predicated computation inclines to fulfill significant improvements to the extent sundry target quality measures. In addition, in a subjective slant evaluation with 10 group of onlookers individuals, 76.35% of the subjects were found to lean toward DNN-predicated improved verbalization to that got with other standard strategy.
The rapid growth of wide band wireless services
has led to the need of improvement in capacity an... more The rapid growth of wide band wireless services has led to the need of improvement in capacity and data-rate transmission of wireless communications systems. Hence, in a multi-tier network, the requirement for signal quality and interference-free transmission and reception is necessary. Beamforming plays a vital role in placing an antenna towards the signal source so as to suppress the interferences and enhance desired signal quality. Many fundamental problems in multi user communication through relay nodes can be mitigated by using proper beamforming algorithms. This paper deals with a review focused on the performance of various beamforming techniques and algorithms on Multiple Input Multiple Output (MIMO) relay networks. Furthermore, the paper provides a comparative analysis of recent beamforming techniques used in MIMO relay networks and their respective benefits and drawbacks. Finally, some future directions to improve the signal quality and mitigate the interferences are also discussed.
Speech is the best way to communicate between two
people.Since this is the most common method of ... more Speech is the best way to communicate between two people.Since this is the most common method of communication, people also need to interface with machines utilizing speech. Based on this, automatic speech recognition has gained up a big momentum in recent years. In this paper, an efficient Speech Emotion Recognition (SER) system using Modified Cuckoo Search Optimization (MCS) based optimization technique for Actor Critic Neural Network (ACNN) is presented. Nowadays lot of researches has been done in the emotion recognition and the speech enhancement.The other difficult task behind this emotion recognition is none other than choosing the emotion recognition corpora(speech database), identification of different features related to speech and an appropriate choice of a classification model.The various types of classifiers are used to differentiate emotions. Preprocessing,feature extraction and classification are the important stages in this signal model.Local invariant features and salient discriminating features are extracted in the feature extraction.These features are given to the neural network for training and based on that the text correspond to the speech signal is recognized.This system will be a speaker independent,since it use recorded standard database of speech samples which have different speech emotions.
Abstract—World is experiencing an explosive growth in
wireless communication and wireless network... more Abstract—World is experiencing an explosive growth in wireless communication and wireless networks which has led to a huge increase in the energy consumption. In low-power scenarios like wireless sensors and networks, it is highly impractical or expensive to replace batteries of low-cost devices. To overcome these problems, relying on energy harvesting has proved to be the best solution and this is due to the potential for mobile devices to scan power from their surrounding that is solar, wind, vibration, thermo-electric effects, ambient radio power and so on. The use of Energy harvesting nodes in wireless communication is a promising approach for maximizing the energy efficiency. However, it requires signal processing algorithms and allied architectures to harvest the energy along with the information transfer. This paper deals with a comprehensive presentation of new research contributions on Wireless Energy Harvesting techniques, algorithms, architectures, performance metrics, and applications which are suitable for future wireless networks. Different architectures are examined in this paper that imposes optimization targets on various parameters that are very much essential to design energy efficient high speed wireless systems.
High Speed Electric vehicles are very significant in urban environment to accomplish the informat... more High Speed Electric vehicles are very significant in urban environment to accomplish the information exchange wirelessly. Meanwhile, energy crisis that the present generation is facing is contributed in major by wireless communication, specifically in (V2V) domain. As the traffic grows and the information content is quite bulky, V2V faces many challenges in terms of energy utilization and power wastage. Modern wireless architectures and allied researches need to be intact on V2V communication to minimize the power loss issues and maximizes the energy efficiency. This paper is focused on recent advance technologies in the field of V2V communication that aims in uninterrupted connectivity in a very dynamic and congested environment. A comparative study of different architectures and algorithms are provided in this paper, to enable the readers to select appropriate techniques based on the real-time traffic conditions. In addition, energy efficient beamforming algorithms and related optimization techniques are briefly described that contributes to a faithful information exchange between the highspeed vehicles.
Waste Electric and Electronic Component (WEEE) is becoming a major issue for the environment and ... more Waste Electric and Electronic Component (WEEE) is becoming a major issue for the environment and the society. The hazardous metal contents available in WEEE can leave harmful impact on the well-being of humans and animals. The existing methods of Electronic Waste (E-waste) treatment are reuse, recycle and remanufacture. Along with these methods incineration and landfilling are also considered as options for Ewaste treatment. The recycling of E-waste helps in waste treatment and in the recovery of valuable metals. This paper gives a systematic review of existing recycling techniques for Ewaste management, their advantages and limitations and valuable metals recovery from E-waste. This article may help in waste utilization and metal recovery from E-waste. This article also reviews the opportunities and challenges faced in the process of metal recovery from E-waste.
Future wireless generation networks using MIMO systems have wide demand on transmission speed, co... more Future wireless generation networks using MIMO systems have wide demand on transmission speed, coverage range and signal quality. The traditional joint beamforming (JBF) approaches are carried out concurrently at relay and receiver nodes. The existing beamforming (BF) architectures are computationally complex and the communication system lacks an efficient relay selection scheme. The problem becomes severe for dynamic and fast moving communication nodes. This paper proposes a novel JBF architecture with relay selection to mitigate the effects of time delay in BF matrix update in a dynamic mobile environment. Relay switching is carried out based on sensing the speed of mobile nodes. Switching phase is bypassed and BF continues with the selected relay if the mobile nodes are static or mobility is negligible. For dynamic environment, it is necessary to update BF matrix after each time when new set of relays are selected. Minimum Mean Square Error algorithm is used for BF vector calculation and Hybrid Cuckoo Search Optimization algorithm is used for speed sensitive relay selection. The proposed JBF algorithm outperforms well in terms of weighted sum rate and Sum of Mean Square Error along with guaranteed time delay for beam steering. The proposed hybrid optimized solution for speed sensitive relay selection with JBF is best suitable for next generation wireless networks.
The International Journal of Advanced Manufacturing Technology
Smart industries use modern technologies such as machine learning and big data to maintain supply... more Smart industries use modern technologies such as machine learning and big data to maintain supply chain management and increase productivity but still the main challenge faced during quality control as this might affect the production rate. Smart industries are completely based on supervised learning that enables better inspection and effectively controls the parameter involved in the production process. Smart industries choose the mechanism that improves production and assures maximum quality. The various kernel function is initially used to select and extract a parameter. Support vector machine (SVM) is a supervised learning approach used in manufacturing industries to evaluate quality control. The SVM model uses the kernel function, namely RBF, along with Neural Networks, in identifying the parameter involved in quality management and undergoes the classification process. SVM consists of C-SVM and V-SVM classifier models involved in the classification process and undergoes training to handle the multiple numbers of consequence aroused during manufacturing. The performance of SVM classifiers and RBF NNs is evaluated. Different kernel functions, such as polynomial, linear, sigmoid, RBF, and over-varying gamma coefficient values, are tested in the experimental evaluation concerned with the comparative analysis of the continuous quality control function of the SVM classifier. Experimental results demonstrate the superiority of the SVM classifier in terms of the estimated computational time (88.1%), F1-measure (89.4%), ROC (65%), and accuracy (94.6%). The goal of the proposed model is to monitor the manufacturing process and control fault occurrence.
The internet, like automated tools, has grown to better our daily lives. Interacting IoT products... more The internet, like automated tools, has grown to better our daily lives. Interacting IoT products and cyber-physical systems. Generative Adversarial Network's (GANs') generator and discriminator may have different inputs, allowing feedback in supervised models. AI systems use neural networks, and adversarial networks analyse neural network feedback. Cyber-physical production systems (CPPS) herald intelligent manufacturing. CPPS may launch cross-domain attacks since the virtual and real worlds are interwoven. This project addresses enhanced Cyber-Physical System(CPS) feedback structure for Denial-of-Service (DoS) defence. Comparing sensor-controller and controller-to-actuator DoS attack channels shows a swapping system modelling solution for the CPS's complex response feedback. Because of the differential in bandwidth between the two channels and the suspects' limited energy, one person can only launch so many DoS assaults. DoS attacks are old and widespread. Create a layered switching paradigm that employs packet-based transfer techniques to prevent assaults. The discriminator's probability may be used to assess whether feedback samples came from real or fictional data. Cognitive feedback can assess GA feedback data.
The International Journal of Advanced Manufacturing Technology, 2023
Smart industries use modern technologies such as machine learning and big data to maintain supply... more Smart industries use modern technologies such as machine learning and big data to maintain supply chain management and increase productivity but still the main challenge faced during quality control as this might affect the production rate. Smart industries are completely based on supervised learning that enables better inspection and effectively controls the parameter involved in the production process. Smart industries choose the mechanism that improves production and assures maximum quality. The various kernel function is initially used to select and extract a parameter. Support vector machine (SVM) is a supervised learning approach used in manufacturing industries to evaluate quality control. The SVM model uses the kernel function, namely RBF, along with Neural Networks, in identifying the parameter involved in quality management and undergoes the classification process. SVM consists of C-SVM and V-SVM classifier models involved in the classification process and undergoes training to handle the multiple numbers of consequence aroused during manufacturing. The performance of SVM classifiers and RBF NNs is evaluated. Different kernel functions, such as polynomial, linear, sigmoid, RBF, and over-varying gamma coefficient values, are tested in the experimental evaluation concerned with the comparative analysis of the continuous quality control function of the SVM classifier. Experimental results demonstrate the superiority of the SVM classifier in terms of the estimated computational time (88.1%), F1-measure (89.4%), ROC (65%), and accuracy (94.6%). The goal of the proposed model is to monitor the manufacturing process and control fault occurrence.
The internet, like automated tools, has grown to better our daily lives. Interacting IoT products... more The internet, like automated tools, has grown to better our daily lives. Interacting IoT products and cyber-physical systems. Generative Adversarial Network's (GANs') generator and discriminator may have different inputs, allowing feedback in supervised models. AI systems use neural networks, and adversarial networks analyse neural network feedback. Cyber-physical production systems (CPPS) herald intelligent manufacturing. CPPS may launch cross-domain attacks since the virtual and real worlds are interwoven. This project addresses enhanced Cyber-Physical System(CPS) feedback structure for Denial-of-Service (DoS) defence. Comparing sensor-controller and controller-to-actuator DoS attack channels shows a swapping system modelling solution for the CPS's complex response feedback. Because of the differential in bandwidth between the two channels and the suspects' limited energy, one person can only launch so many DoS assaults. DoS attacks are old and widespread. Create a layered switching paradigm that employs packet-based transfer techniques to prevent assaults. The discriminator's probability may be used to assess whether feedback samples came from real or fictional data. Cognitive feedback can assess GA feedback data.
International Journal of System Assurance Engineering and Management
We reside in an environment wherein robotics is used in a variety of circumstances daily. In the ... more We reside in an environment wherein robotics is used in a variety of circumstances daily. In the best-case scenario, this contact seems as natural and comfortable as human-to-human conversation. Audiovisual speech synthesis is an appropriate way of communication between a human and a robot in this case. The robot is able to communicate to its users due to audiovisual text-to-speech synthesis technology. A diverse range of approaches are conducted to synthesis audiovisual speech has been established during the previous few years. The proposed Robot Operating System (ROS) performs the collaborative analysis of audio-visual speech synthesis using sensors measurement to enable the interaction between humans and robots. Skeletal tracking, gesture identification are performed by utilizing a depth camera, as well as facial recognition utilizing an RGB camera are aspects of visual-based entities. Auditory perception is dependent on the use of a microphone array to locate sound sources. We offer a top-down hierarchy communication protocol-based integration architecture for these entities. The top layer of integration contains the message about the number of people and associated states that are changed from a number of the lower-level perceptive entity.
Waste Electric and Electronic Component (WEEE) is becoming a major issue for the environment and ... more Waste Electric and Electronic Component (WEEE) is becoming a major issue for the environment and the society. The hazardous metal contents available in WEEE can leave harmful impact on the well-being of humans and animals. The existing methods of Electronic Waste (E-waste) treatment are reuse, recycle and remanufacture. Along with these methods incineration and landfilling are also considered as options for Ewaste treatment. The recycling of E-waste helps in waste treatment and in the recovery of valuable metals. This paper gives a systematic review of existing recycling techniques for Ewaste management, their advantages and limitations and valuable metals recovery from E-waste. This article may help in waste utilization and metal recovery from E-waste. This article also reviews the opportunities and challenges faced in the process of metal recovery from E-waste.
In the Modern World, women are no longer considered as the minor group. They share the same power... more In the Modern World, women are no longer considered as the minor group. They share the same power, privileges, rights, and opportunities as men. They have been excelled in many fields and contributing to the development of the entire globe. But, in many developing and under developed countries, still women community has not raised up, specifically due to the challenges they face in terms of unethical physical harassment from the society. This paper presents a comprehensive survey on design and application approaches in women safety systems. There are many promising technologies relied on women security systems using IoT, Embedded, Artificial Intelligence, Machine Learning, Augmented Reality, android Mobile apps etc. We have undergone with a comparative analysis of such techniques and open research issues that would enable the researchers to design a complete women security system for the beneficial of the entire women community in global level.
International Journal of Systems Assurance Engineering & Management , 2022
We reside in an environment wherein robotics is
used in a variety of circumstances daily. In the ... more We reside in an environment wherein robotics is used in a variety of circumstances daily. In the best-case scenario, this contact seems as natural and comfortable as human-to-human conversation. Audiovisual speech synthesis is an appropriate way of communication between a human and a robot in this case. The robot is able to communicate to its users due to audiovisual text-to-speech synthesis technology. A diverse range of approaches are conducted to synthesis audiovisual speech has been established during the previous few years. The proposed Robot Operating System (ROS) performs the collaborative analysis of audio-visual speech synthesis using sensors measurement to enable the interaction between humans and robots. Skeletal tracking, gesture identification are performed by utilizing a depth camera, as well as facial recognition utilizing an RGB camera are aspects of visual-based entities. Auditory perception is dependent on the use of a microphone array to locate sound sources. We offer a top-down hierarchy communication protocol-based integration architecture for these entities. The top layer of integration contains the message about the number of people and associated states that are changed from a number of the lower-level perceptive entity.
The use of MIMO networks in wireless communication results in increased data rate but leads to se... more The use of MIMO networks in wireless communication results in increased data rate but leads to severe interference issues and power losses. Promising beamforming (BF) architecture with Conditional Time split-Energy Extraction (CT-EE) is proposed to maximize the Energy Efficiency while optimizing the Mean Square Error (MSE) and Achievable Sum Rate (ASR). A distributed BF system using Minimum Mean Square Error algorithm is jointly implemented at all cooperating nodes. Energy Extraction (EE) from RF signal at the relay nodes facilitates full connectivity among the users. The signal transmission and EE phases are jointly implemented using time-split architecture, without using fixed pre-assigned time slots. Time split from information decoding to EE phase is done only if the battery life is found to be critical. The paper investigates the scope of bypassing the EE phase after ensuring the required power level. The performance of the proposed architecture is compared with the conventional BF and existing EE methods in terms of MSE, ASR and energy efficiency. The proposed architecture is well suitable to establish uninterrupted connectivity between user nodes which are frequently used and have severe power drain-off issues as they can be a part of natural disaster like flood affected wireless networks. INDEX TERMS Achievable sum rate, beamforming, conditional time split, energy efficiency, energy extraction, MIMO networks, minimum mean square error.
Multiple Input Multiple Output (MIMO) networks operating in millimeter wave frequency band bring ... more Multiple Input Multiple Output (MIMO) networks operating in millimeter wave frequency band bring promising solutions for the increased demand of future generation networks in terms of data rate, signal quality, power optimization and computational complexity. A joint beam-forming (JBF) system working concurrently on source-relay-destination nodes leads to faithful delivery of signals by mitigating the effect of interferences. The traditional JBF designs in MIMO networks yield power wastage due to undesirable participation of intermediate relay nodes for message forwarding. The computational delay in beam-forming (BF) matrix update is tedious in traditional systems. This paper proposes a novel design of power-optimized JBF that facilitates optimum relay selection for solving power wastage issues. The selected relays cooperate in BF with the power constraint, and all other relays are powered down and enter into sleeping mode. Modified Cuckoo-Search Optimization (MCSO) algorithm is used for relay selection and minimum mean square error algorithm is used for BF matrix calculation. The proposed JBF is able to maximize Achievable Sum Rate (ASR) for optimum value of transmission power. The maximum power efficiency is achieved for distant communication with the aid of selected relays contributing to maximizing the ASR value. The proposed work minimizes the sum of mean square error and concurrently computes optimum time slot for BF matrix update, and hence computational delay is reduced. Thus a hybrid optimization for power and time in JBF design is achieved with relay selection and it can be widely used in future generation networks for high-quality and interference-free communication.
International journal of Advanced Engineering Research & Technology, 2016
Image decomposition is an ill-posed problem usually
addressed in various applications of image p... more Image decomposition is an ill-posed problem usually
addressed in various applications of image processing such as
image denoising, enhancement etc.. In normal image
denoising processes, it is not clear how to decompose the
image into multiple semantic components and thereby
removing those components which correspond to undesirable
noise patterns. Here in this paper, we introduces an image
decomposition framework using Discrete Wavelet
Transform(DWT) filters. The system first identifies and
learns an over-complete dictionary from the high spatial
frequency parts of the input image for reconstruction
purposes. Then performs unsupervised clustering on the
observed dictionary atoms via method of affinity
propagation. Once the proposed system identifies the image
components which are similar, then the proposed framework
automatically removes the noise contaminated image
components directly from the input image. The performance
of this approach depends on the relative denoising techniques
used and on the number of iterations of the algorithm and in
most of the cases we require more than hundred iterations
which increase the efficiency of the system. In this paper, we
propose a new and improved method for increasing the
overall efficiency of the system. Introduction of DWT filter
into the existing system for images corrupted by Gaussian
noise or rain noise are very useful because of its ability to
capture the signal energy in few energy transformation
values. Our experiments show that the proposed system
yields improvements in PSNR and thereby increases the
sharpness of images mainly at the edges.
International Journal of Scientific Engineering and Technology Research, 2017
This letter shows a back slide predicated verbalization enhancement framework using significant n... more This letter shows a back slide predicated verbalization enhancement framework using significant neural frameworks (DNNs) with a various layer significant designing. In the DNN discernment process, a sizably voluminous get ready set finds a horrifying showing personnel to assess the perplexed nonlinear mapping from optically solicited strepitous verbalization to needed clean banners. Acoustic setting was found to enhance the movement of verbalization to be dissevered from the substructure disturbances prosperously without the annoying melodic relic for the most part outwardly saw in customary verbalization overhaul figurings. A movement of pilot tests was coordinated under multi-condition planning with more than 100 hours of replicated verbalization data, setting up a good notional hypothesis limit even in scrambled testing conditions. Right when differentiated and the logarithmic minimum mean square mix-up approach, the proposed DNN-predicated computation inclines to fulfill significant improvements to the extent sundry target quality measures. In addition, in a subjective slant evaluation with 10 group of onlookers individuals, 76.35% of the subjects were found to lean toward DNN-predicated improved verbalization to that got with other standard strategy.
The rapid growth of wide band wireless services
has led to the need of improvement in capacity an... more The rapid growth of wide band wireless services has led to the need of improvement in capacity and data-rate transmission of wireless communications systems. Hence, in a multi-tier network, the requirement for signal quality and interference-free transmission and reception is necessary. Beamforming plays a vital role in placing an antenna towards the signal source so as to suppress the interferences and enhance desired signal quality. Many fundamental problems in multi user communication through relay nodes can be mitigated by using proper beamforming algorithms. This paper deals with a review focused on the performance of various beamforming techniques and algorithms on Multiple Input Multiple Output (MIMO) relay networks. Furthermore, the paper provides a comparative analysis of recent beamforming techniques used in MIMO relay networks and their respective benefits and drawbacks. Finally, some future directions to improve the signal quality and mitigate the interferences are also discussed.
Speech is the best way to communicate between two
people.Since this is the most common method of ... more Speech is the best way to communicate between two people.Since this is the most common method of communication, people also need to interface with machines utilizing speech. Based on this, automatic speech recognition has gained up a big momentum in recent years. In this paper, an efficient Speech Emotion Recognition (SER) system using Modified Cuckoo Search Optimization (MCS) based optimization technique for Actor Critic Neural Network (ACNN) is presented. Nowadays lot of researches has been done in the emotion recognition and the speech enhancement.The other difficult task behind this emotion recognition is none other than choosing the emotion recognition corpora(speech database), identification of different features related to speech and an appropriate choice of a classification model.The various types of classifiers are used to differentiate emotions. Preprocessing,feature extraction and classification are the important stages in this signal model.Local invariant features and salient discriminating features are extracted in the feature extraction.These features are given to the neural network for training and based on that the text correspond to the speech signal is recognized.This system will be a speaker independent,since it use recorded standard database of speech samples which have different speech emotions.
Abstract—World is experiencing an explosive growth in
wireless communication and wireless network... more Abstract—World is experiencing an explosive growth in wireless communication and wireless networks which has led to a huge increase in the energy consumption. In low-power scenarios like wireless sensors and networks, it is highly impractical or expensive to replace batteries of low-cost devices. To overcome these problems, relying on energy harvesting has proved to be the best solution and this is due to the potential for mobile devices to scan power from their surrounding that is solar, wind, vibration, thermo-electric effects, ambient radio power and so on. The use of Energy harvesting nodes in wireless communication is a promising approach for maximizing the energy efficiency. However, it requires signal processing algorithms and allied architectures to harvest the energy along with the information transfer. This paper deals with a comprehensive presentation of new research contributions on Wireless Energy Harvesting techniques, algorithms, architectures, performance metrics, and applications which are suitable for future wireless networks. Different architectures are examined in this paper that imposes optimization targets on various parameters that are very much essential to design energy efficient high speed wireless systems.
High Speed Electric vehicles are very significant in urban environment to accomplish the informat... more High Speed Electric vehicles are very significant in urban environment to accomplish the information exchange wirelessly. Meanwhile, energy crisis that the present generation is facing is contributed in major by wireless communication, specifically in (V2V) domain. As the traffic grows and the information content is quite bulky, V2V faces many challenges in terms of energy utilization and power wastage. Modern wireless architectures and allied researches need to be intact on V2V communication to minimize the power loss issues and maximizes the energy efficiency. This paper is focused on recent advance technologies in the field of V2V communication that aims in uninterrupted connectivity in a very dynamic and congested environment. A comparative study of different architectures and algorithms are provided in this paper, to enable the readers to select appropriate techniques based on the real-time traffic conditions. In addition, energy efficient beamforming algorithms and related optimization techniques are briefly described that contributes to a faithful information exchange between the highspeed vehicles.
Waste Electric and Electronic Component (WEEE) is becoming a major issue for the environment and ... more Waste Electric and Electronic Component (WEEE) is becoming a major issue for the environment and the society. The hazardous metal contents available in WEEE can leave harmful impact on the well-being of humans and animals. The existing methods of Electronic Waste (E-waste) treatment are reuse, recycle and remanufacture. Along with these methods incineration and landfilling are also considered as options for Ewaste treatment. The recycling of E-waste helps in waste treatment and in the recovery of valuable metals. This paper gives a systematic review of existing recycling techniques for Ewaste management, their advantages and limitations and valuable metals recovery from E-waste. This article may help in waste utilization and metal recovery from E-waste. This article also reviews the opportunities and challenges faced in the process of metal recovery from E-waste.
Future wireless generation networks using MIMO systems have wide demand on transmission speed, co... more Future wireless generation networks using MIMO systems have wide demand on transmission speed, coverage range and signal quality. The traditional joint beamforming (JBF) approaches are carried out concurrently at relay and receiver nodes. The existing beamforming (BF) architectures are computationally complex and the communication system lacks an efficient relay selection scheme. The problem becomes severe for dynamic and fast moving communication nodes. This paper proposes a novel JBF architecture with relay selection to mitigate the effects of time delay in BF matrix update in a dynamic mobile environment. Relay switching is carried out based on sensing the speed of mobile nodes. Switching phase is bypassed and BF continues with the selected relay if the mobile nodes are static or mobility is negligible. For dynamic environment, it is necessary to update BF matrix after each time when new set of relays are selected. Minimum Mean Square Error algorithm is used for BF vector calculation and Hybrid Cuckoo Search Optimization algorithm is used for speed sensitive relay selection. The proposed JBF algorithm outperforms well in terms of weighted sum rate and Sum of Mean Square Error along with guaranteed time delay for beam steering. The proposed hybrid optimized solution for speed sensitive relay selection with JBF is best suitable for next generation wireless networks.
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Papers by Dr. Ashok K
used in a variety of circumstances daily. In the best-case
scenario, this contact seems as natural and comfortable as
human-to-human conversation. Audiovisual speech synthesis
is an appropriate way of communication between a
human and a robot in this case. The robot is able to communicate
to its users due to audiovisual text-to-speech synthesis
technology. A diverse range of approaches are conducted
to synthesis audiovisual speech has been established
during the previous few years. The proposed Robot Operating
System (ROS) performs the collaborative analysis of
audio-visual speech synthesis using sensors measurement to
enable the interaction between humans and robots. Skeletal
tracking, gesture identification are performed by utilizing
a depth camera, as well as facial recognition utilizing an
RGB camera are aspects of visual-based entities. Auditory
perception is dependent on the use of a microphone array to
locate sound sources. We offer a top-down hierarchy communication
protocol-based integration architecture for these entities. The top layer of integration contains the message about the number of people and associated states that are changed from a number of the lower-level perceptive entity.
addressed in various applications of image processing such as
image denoising, enhancement etc.. In normal image
denoising processes, it is not clear how to decompose the
image into multiple semantic components and thereby
removing those components which correspond to undesirable
noise patterns. Here in this paper, we introduces an image
decomposition framework using Discrete Wavelet
Transform(DWT) filters. The system first identifies and
learns an over-complete dictionary from the high spatial
frequency parts of the input image for reconstruction
purposes. Then performs unsupervised clustering on the
observed dictionary atoms via method of affinity
propagation. Once the proposed system identifies the image
components which are similar, then the proposed framework
automatically removes the noise contaminated image
components directly from the input image. The performance
of this approach depends on the relative denoising techniques
used and on the number of iterations of the algorithm and in
most of the cases we require more than hundred iterations
which increase the efficiency of the system. In this paper, we
propose a new and improved method for increasing the
overall efficiency of the system. Introduction of DWT filter
into the existing system for images corrupted by Gaussian
noise or rain noise are very useful because of its ability to
capture the signal energy in few energy transformation
values. Our experiments show that the proposed system
yields improvements in PSNR and thereby increases the
sharpness of images mainly at the edges.
has led to the need of improvement in capacity and data-rate
transmission of wireless communications systems. Hence, in a
multi-tier network, the requirement for signal quality and
interference-free transmission and reception is necessary.
Beamforming plays a vital role in placing an antenna towards the
signal source so as to suppress the interferences and enhance
desired signal quality. Many fundamental problems in multi user
communication through relay nodes can be mitigated by using
proper beamforming algorithms. This paper deals with a review
focused on the performance of various beamforming techniques
and algorithms on Multiple Input Multiple Output (MIMO)
relay networks. Furthermore, the paper provides a comparative
analysis of recent beamforming techniques used in MIMO relay
networks and their respective benefits and drawbacks. Finally,
some future directions to improve the signal quality and mitigate
the interferences are also discussed.
people.Since this is the most common method of communication,
people also need to interface with machines utilizing speech.
Based on this, automatic speech recognition has gained up a big
momentum in recent years. In this paper, an efficient Speech
Emotion Recognition (SER) system using Modified Cuckoo
Search Optimization (MCS) based optimization technique for
Actor Critic Neural Network (ACNN) is presented. Nowadays lot
of researches has been done in the emotion recognition and the
speech enhancement.The other difficult task behind this emotion
recognition is none other than choosing the emotion recognition
corpora(speech database), identification of different features
related to speech and an appropriate choice of a classification
model.The various types of classifiers are used to differentiate
emotions. Preprocessing,feature extraction and classification are
the important stages in this signal model.Local invariant features
and salient discriminating features are extracted in the feature
extraction.These features are given to the neural network for
training and based on that the text correspond to the speech signal
is recognized.This system will be a speaker independent,since
it use recorded standard database of speech samples which have
different speech emotions.
Conference Presentations by Dr. Ashok K
wireless communication and wireless networks which has led to a
huge increase in the energy consumption. In low-power scenarios
like wireless sensors and networks, it is highly impractical or
expensive to replace batteries of low-cost devices. To overcome
these problems, relying on energy harvesting has proved to be the
best solution and this is due to the potential for mobile devices to
scan power from their surrounding that is solar, wind, vibration,
thermo-electric effects, ambient radio power and so on. The use of
Energy harvesting nodes in wireless communication is a promising
approach for maximizing the energy efficiency. However, it
requires signal processing algorithms and allied architectures to
harvest the energy along with the information transfer. This paper
deals with a comprehensive presentation of new research
contributions on Wireless Energy Harvesting techniques,
algorithms, architectures, performance metrics, and applications
which are suitable for future wireless networks. Different
architectures are examined in this paper that imposes optimization
targets on various parameters that are very much essential to
design energy efficient high speed wireless systems.
used in a variety of circumstances daily. In the best-case
scenario, this contact seems as natural and comfortable as
human-to-human conversation. Audiovisual speech synthesis
is an appropriate way of communication between a
human and a robot in this case. The robot is able to communicate
to its users due to audiovisual text-to-speech synthesis
technology. A diverse range of approaches are conducted
to synthesis audiovisual speech has been established
during the previous few years. The proposed Robot Operating
System (ROS) performs the collaborative analysis of
audio-visual speech synthesis using sensors measurement to
enable the interaction between humans and robots. Skeletal
tracking, gesture identification are performed by utilizing
a depth camera, as well as facial recognition utilizing an
RGB camera are aspects of visual-based entities. Auditory
perception is dependent on the use of a microphone array to
locate sound sources. We offer a top-down hierarchy communication
protocol-based integration architecture for these entities. The top layer of integration contains the message about the number of people and associated states that are changed from a number of the lower-level perceptive entity.
addressed in various applications of image processing such as
image denoising, enhancement etc.. In normal image
denoising processes, it is not clear how to decompose the
image into multiple semantic components and thereby
removing those components which correspond to undesirable
noise patterns. Here in this paper, we introduces an image
decomposition framework using Discrete Wavelet
Transform(DWT) filters. The system first identifies and
learns an over-complete dictionary from the high spatial
frequency parts of the input image for reconstruction
purposes. Then performs unsupervised clustering on the
observed dictionary atoms via method of affinity
propagation. Once the proposed system identifies the image
components which are similar, then the proposed framework
automatically removes the noise contaminated image
components directly from the input image. The performance
of this approach depends on the relative denoising techniques
used and on the number of iterations of the algorithm and in
most of the cases we require more than hundred iterations
which increase the efficiency of the system. In this paper, we
propose a new and improved method for increasing the
overall efficiency of the system. Introduction of DWT filter
into the existing system for images corrupted by Gaussian
noise or rain noise are very useful because of its ability to
capture the signal energy in few energy transformation
values. Our experiments show that the proposed system
yields improvements in PSNR and thereby increases the
sharpness of images mainly at the edges.
has led to the need of improvement in capacity and data-rate
transmission of wireless communications systems. Hence, in a
multi-tier network, the requirement for signal quality and
interference-free transmission and reception is necessary.
Beamforming plays a vital role in placing an antenna towards the
signal source so as to suppress the interferences and enhance
desired signal quality. Many fundamental problems in multi user
communication through relay nodes can be mitigated by using
proper beamforming algorithms. This paper deals with a review
focused on the performance of various beamforming techniques
and algorithms on Multiple Input Multiple Output (MIMO)
relay networks. Furthermore, the paper provides a comparative
analysis of recent beamforming techniques used in MIMO relay
networks and their respective benefits and drawbacks. Finally,
some future directions to improve the signal quality and mitigate
the interferences are also discussed.
people.Since this is the most common method of communication,
people also need to interface with machines utilizing speech.
Based on this, automatic speech recognition has gained up a big
momentum in recent years. In this paper, an efficient Speech
Emotion Recognition (SER) system using Modified Cuckoo
Search Optimization (MCS) based optimization technique for
Actor Critic Neural Network (ACNN) is presented. Nowadays lot
of researches has been done in the emotion recognition and the
speech enhancement.The other difficult task behind this emotion
recognition is none other than choosing the emotion recognition
corpora(speech database), identification of different features
related to speech and an appropriate choice of a classification
model.The various types of classifiers are used to differentiate
emotions. Preprocessing,feature extraction and classification are
the important stages in this signal model.Local invariant features
and salient discriminating features are extracted in the feature
extraction.These features are given to the neural network for
training and based on that the text correspond to the speech signal
is recognized.This system will be a speaker independent,since
it use recorded standard database of speech samples which have
different speech emotions.
wireless communication and wireless networks which has led to a
huge increase in the energy consumption. In low-power scenarios
like wireless sensors and networks, it is highly impractical or
expensive to replace batteries of low-cost devices. To overcome
these problems, relying on energy harvesting has proved to be the
best solution and this is due to the potential for mobile devices to
scan power from their surrounding that is solar, wind, vibration,
thermo-electric effects, ambient radio power and so on. The use of
Energy harvesting nodes in wireless communication is a promising
approach for maximizing the energy efficiency. However, it
requires signal processing algorithms and allied architectures to
harvest the energy along with the information transfer. This paper
deals with a comprehensive presentation of new research
contributions on Wireless Energy Harvesting techniques,
algorithms, architectures, performance metrics, and applications
which are suitable for future wireless networks. Different
architectures are examined in this paper that imposes optimization
targets on various parameters that are very much essential to
design energy efficient high speed wireless systems.