Pub Date : 2023-12-31DOI: 10.52228/jrub.2023-36-2-10
Neha Dewangan, K. Thakur, S. Mandal, BikeshKumar Singh
Automatic Speech Emotion Recognition (ASER) is a state-of-the-art application in artificial intelligence. Speech recognition intelligence is employed in various applications such as digital assistance, security, and other human-machine interactive products. In the present work, three open-source acoustic datasets, namely SAVEE, RAVDESS, and EmoDB, have been utilized (Haq et al., 2008, Livingstone et al., 2005, Burkhardt et al., 2005). From these datasets, six emotions namely anger, disgust, fear, happy, neutral, and sad, are selected for automatic speech emotion recognition. Various types of algorithms are already reported for extracting emotional content from acoustic signals. This work proposes a time-frequency (t-f) image-based multiclass speech emotion classification model for the six emotions mentioned above. The proposed model extracts 472 grayscale image features from the t-f images of speech signals. The t-f image is a visual representation of the time component and frequency component at that time in the two-dimensional space, and differing colors show its amplitude. An artificial neural network-based multiclass machine learning approach is used to classify selected emotions. The experimental results show that the above-mentioned emotions' average classification accuracy (CA) of 88.6%, 85.5%, and 93.56% is achieved using SAVEE, RAVDESS, and EmoDB datasets, respectively. Also, an average CA of 83.44% has been achieved for the combination of all three datasets. The maximum reported average classification accuracy (CA) using spectrogram for SAVEE, RAVDESS, and EmoDB dataset is 87.8%, 79.5 %, and 83.4%, respectively (Wani et al., 2020, Mustaqeem and Kwon, 2019, Badshah et al., 2017). The proposed t-f image-based classification model shows improvement in average CA by 0.91%, 7.54%, and 12.18 % for SAVEE, RAVDESS, and EmoDB datasets, respectively. This study can be helpful in human-computer interface applications to detect emotions precisely from acoustic signals.
{"title":"Time-Frequency Image-based Speech Emotion Recognition using Artificial Neural Network","authors":"Neha Dewangan, K. Thakur, S. Mandal, BikeshKumar Singh","doi":"10.52228/jrub.2023-36-2-10","DOIUrl":"https://doi.org/10.52228/jrub.2023-36-2-10","url":null,"abstract":"Automatic Speech Emotion Recognition (ASER) is a state-of-the-art application in artificial intelligence. Speech recognition intelligence is employed in various applications such as digital assistance, security, and other human-machine interactive products. In the present work, three open-source acoustic datasets, namely SAVEE, RAVDESS, and EmoDB, have been utilized (Haq et al., 2008, Livingstone et al., 2005, Burkhardt et al., 2005). From these datasets, six emotions namely anger, disgust, fear, happy, neutral, and sad, are selected for automatic speech emotion recognition. Various types of algorithms are already reported for extracting emotional content from acoustic signals. This work proposes a time-frequency (t-f) image-based multiclass speech emotion classification model for the six emotions mentioned above. The proposed model extracts 472 grayscale image features from the t-f images of speech signals. The t-f image is a visual representation of the time component and frequency component at that time in the two-dimensional space, and differing colors show its amplitude. An artificial neural network-based multiclass machine learning approach is used to classify selected emotions. The experimental results show that the above-mentioned emotions' average classification accuracy (CA) of 88.6%, 85.5%, and 93.56% is achieved using SAVEE, RAVDESS, and EmoDB datasets, respectively. Also, an average CA of 83.44% has been achieved for the combination of all three datasets. The maximum reported average classification accuracy (CA) using spectrogram for SAVEE, RAVDESS, and EmoDB dataset is 87.8%, 79.5 %, and 83.4%, respectively (Wani et al., 2020, Mustaqeem and Kwon, 2019, Badshah et al., 2017). The proposed t-f image-based classification model shows improvement in average CA by 0.91%, 7.54%, and 12.18 % for SAVEE, RAVDESS, and EmoDB datasets, respectively. This study can be helpful in human-computer interface applications to detect emotions precisely from acoustic signals.","PeriodicalId":17214,"journal":{"name":"Journal of Ravishankar University (PART-B)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139136298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-31DOI: 10.52228/jrub.2023-36-2-7
H. Bhardwaj, Sulekha Khute, R. Jangde
The compromised wound healing observed in diabetic patients poses significant hurdles, escalating the risk of infections. The growing interest in natural polymeric materials is fueled by their abundant availability, cost-effectiveness, and eco-friendly attributes. Advances in polymer science have expanded the applications, especially in tissue engineering and regenerative medicine. These interdisciplinary fields integrate knowledge and technology from diverse domains to restore damaged tissues and organs in medical interventions. Polymers function as versatile tools, serving as carriers for drugs and cells and facilitating host-cell integration to meet the requisites of regeneration and repair. This intricate process involves multiple stages, necessitating the development of various components to construct the desired neo-tissue or organ. Diverse biopolymers, encompassing biological, synthetic, and hybrid varieties, find extensive utility across various medical applications. Their tunable physical, chemical, and biological properties render them ideal for tailoring to specific application requirements. This review provides a comprehensive overview of the wound-healing process, with a specific focus on the challenges presented by diabetic wounds. Additionally, it explores various biopolymers, including alginate, gelatin, cellulose, silk sericin, chondroitin sulfate, chitosan, xanthan gum, cyclodextrin, and hyaluronic acid, elucidating their roles in the management of diabetic wounds.
{"title":"Biopolymeric Materials in the Management of Diabetic Wound Healing: A Comprehensive Review","authors":"H. Bhardwaj, Sulekha Khute, R. Jangde","doi":"10.52228/jrub.2023-36-2-7","DOIUrl":"https://doi.org/10.52228/jrub.2023-36-2-7","url":null,"abstract":"The compromised wound healing observed in diabetic patients poses significant hurdles, escalating the risk of infections. The growing interest in natural polymeric materials is fueled by their abundant availability, cost-effectiveness, and eco-friendly attributes. Advances in polymer science have expanded the applications, especially in tissue engineering and regenerative medicine. These interdisciplinary fields integrate knowledge and technology from diverse domains to restore damaged tissues and organs in medical interventions. Polymers function as versatile tools, serving as carriers for drugs and cells and facilitating host-cell integration to meet the requisites of regeneration and repair. This intricate process involves multiple stages, necessitating the development of various components to construct the desired neo-tissue or organ. Diverse biopolymers, encompassing biological, synthetic, and hybrid varieties, find extensive utility across various medical applications. Their tunable physical, chemical, and biological properties render them ideal for tailoring to specific application requirements. This review provides a comprehensive overview of the wound-healing process, with a specific focus on the challenges presented by diabetic wounds. Additionally, it explores various biopolymers, including alginate, gelatin, cellulose, silk sericin, chondroitin sulfate, chitosan, xanthan gum, cyclodextrin, and hyaluronic acid, elucidating their roles in the management of diabetic wounds.","PeriodicalId":17214,"journal":{"name":"Journal of Ravishankar University (PART-B)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139133691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-31DOI: 10.52228/jrub.2023-36-2-4
S. Shukla, Syed Shamroz Arshad, Kavita Thakur, G. Srivastava
Two circuit models of Small Signal amplifier, constituted with BJT-MOSFET hybrid unit under Sziklai pair topology are designed and analyzed using ‘PSpice’ and ‘Cadence Virtuoso and Spectre simulation tool (at GPDK 180nm technology)’ respectively. First amplifier (Circuit-1) uses PSpice user-defined model of BJT and MOSFET whereas the second amplifier (Circuit-2) consists of transistors available at GPDK 180nm technology. Circuit-1 can amplify the AC signals of 1mV-1nV range with optimum voltage gain 389.532, 137.570 current gain, 14.464MHz bandwidth and 2.43% THD. However, Circuit-2 can amplify AC signals of 0.1mV-10nV range with 164.018 voltage gain, 32.775 current gain, 11.906 MHz bandwidth, and 13.608E-6% THD. Both the proposed amplifier circuits remove narrow band problem and generate better results than earlier announced small signal Sziklai pair amplifier with BJT-MOSFET hybrid unit in respect of voltage and current gains, bandwidth, THD, and power consumption. Proposed amplifiers successfully address the problem of poor frequency response of small signal Darlington pair amplifier in higher frequency range and narrow bandwidth limitations of small-signal PNP Sziklai pair amplifier. Dependency of the proposed amplifiers at various biasing resistances and performance with temperature variation, noise variation, DC supply variation, and phase variation are also discussed herein. Proposed Circuits display strong dependency over ideal maximum forward beta ‘β’ of NPN transistor, Transconductance ‘VTO’ of P-MOS transistor and additional biasing resistances ‘RA’. Layout of Circuit-2 is found to cover 96.3898µm2 area with 11.32µm length and 8.515µm breadth. Minor percentage variation between pre-layout and post-layout simulation results of Circuit-2 validates the proposed design at GPDK 180nm technology. Monte Carlo and Process Corner analysis are also performed to test the robustness and insensitivity of Circuit-2 against mean value of the parameters and process and mismatch respectively. Performance summary of the proposed circuits and comparison with the recently reported designs shows effectiveness of the proposed circuits in terms of power gain, THD, voltage gain, current gain, input referred noise and power gain. Qualitative analysis of the proposed Circuits recommends its usability as Low Noise Amplifier in the portable RF noise measurement system.
{"title":"Sziklai Pair based Small signal Amplifier with bjt-mosfet Hybrid Unit at 180nm Technology","authors":"S. Shukla, Syed Shamroz Arshad, Kavita Thakur, G. Srivastava","doi":"10.52228/jrub.2023-36-2-4","DOIUrl":"https://doi.org/10.52228/jrub.2023-36-2-4","url":null,"abstract":"Two circuit models of Small Signal amplifier, constituted with BJT-MOSFET hybrid unit under Sziklai pair topology are designed and analyzed using ‘PSpice’ and ‘Cadence Virtuoso and Spectre simulation tool (at GPDK 180nm technology)’ respectively. First amplifier (Circuit-1) uses PSpice user-defined model of BJT and MOSFET whereas the second amplifier (Circuit-2) consists of transistors available at GPDK 180nm technology. Circuit-1 can amplify the AC signals of 1mV-1nV range with optimum voltage gain 389.532, 137.570 current gain, 14.464MHz bandwidth and 2.43% THD. However, Circuit-2 can amplify AC signals of 0.1mV-10nV range with 164.018 voltage gain, 32.775 current gain, 11.906 MHz bandwidth, and 13.608E-6% THD. Both the proposed amplifier circuits remove narrow band problem and generate better results than earlier announced small signal Sziklai pair amplifier with BJT-MOSFET hybrid unit in respect of voltage and current gains, bandwidth, THD, and power consumption. Proposed amplifiers successfully address the problem of poor frequency response of small signal Darlington pair amplifier in higher frequency range and narrow bandwidth limitations of small-signal PNP Sziklai pair amplifier. Dependency of the proposed amplifiers at various biasing resistances and performance with temperature variation, noise variation, DC supply variation, and phase variation are also discussed herein. Proposed Circuits display strong dependency over ideal maximum forward beta ‘β’ of NPN transistor, Transconductance ‘VTO’ of P-MOS transistor and additional biasing resistances ‘RA’. Layout of Circuit-2 is found to cover 96.3898µm2 area with 11.32µm length and 8.515µm breadth. Minor percentage variation between pre-layout and post-layout simulation results of Circuit-2 validates the proposed design at GPDK 180nm technology. Monte Carlo and Process Corner analysis are also performed to test the robustness and insensitivity of Circuit-2 against mean value of the parameters and process and mismatch respectively. Performance summary of the proposed circuits and comparison with the recently reported designs shows effectiveness of the proposed circuits in terms of power gain, THD, voltage gain, current gain, input referred noise and power gain. Qualitative analysis of the proposed Circuits recommends its usability as Low Noise Amplifier in the portable RF noise measurement system.","PeriodicalId":17214,"journal":{"name":"Journal of Ravishankar University (PART-B)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139135898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-31DOI: 10.52228/jrub.2023-36-2-3
Vyas Dubey, Yeesha Verma
In this paper, a modified regression type estimator has been proposed for estimating population mean using two auxiliary variables under simple random sampling. The optimum properties of proposed estimator is determined and we find that the proposed estimator is more efficient than the Desraj (1965) and Srivastva (1967). Empirical studies have also done to demonstrate the efficiency of the proposed estimator.
{"title":"A Modified Regression Type Estimator Using Two Auxiliary Variables","authors":"Vyas Dubey, Yeesha Verma","doi":"10.52228/jrub.2023-36-2-3","DOIUrl":"https://doi.org/10.52228/jrub.2023-36-2-3","url":null,"abstract":"In this paper, a modified regression type estimator has been proposed for estimating population mean using two auxiliary variables under simple random sampling. The optimum properties of proposed estimator is determined and we find that the proposed estimator is more efficient than the Desraj (1965) and Srivastva (1967). Empirical studies have also done to demonstrate the efficiency of the proposed estimator.","PeriodicalId":17214,"journal":{"name":"Journal of Ravishankar University (PART-B)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139130829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-31DOI: 10.52228/jrub.2023-36-2-8
Tarun Kumar Patel
Insect pests pose significant challenges to agricultural productivity and crop yield worldwide. Conventional pest control methods, such as chemical pesticides, have limitations and adverse environmental effects. Therefore, there is a growing need for sustainable and eco-friendly alternatives in pest management. This review explores the potential of entomopathogenic fungi as a promising biological control agent for insect pests in agriculture. The review begins by providing an overview of entomopathogenic fungi and their significancce. These fungi possess unique mechanisms to infect and kill insect pests. The mode of action involves attachment of fungal spores to the insect's cuticle, followed by penetration, colonization, and release of toxic metabolites within the host. Various factors influence the efficacy of entomopathogenic fungi, including environmental conditions, insect host susceptibility, and formulation/application methods. The benefits of entomopathogenic fungi as biological control agents are discussed, including their compatibility with integrated pest management (IPM) strategies and minimal impact on non-target organisms. However, challenges exist in scaling up their commercial application. The review presents case studies showcasing successful field applications of entomopathogenic fungi in pest management. Future prospects and research directions are identified, emphasizing the importance of continued advancements in understanding the interactions between entomopathogenic fungi and insect pests. Regulatory frameworks and public acceptance are crucial for the widespread adoption of these fungi in agriculture. In conclusion, entomopathogenic fungi offer immense potential as sustainable and effective tools for biological control of insect pests in agriculture. Their ability to target specific pests, compatibility with IPM, and minimal environmental impact make them a viable alternative to chemical pesticides. Further research, collaboration, and implementation are necessary to fully harness the potential of entomopathogenic fungi in integrated pest management strategies.
{"title":"Entomopathogenic Fungi: Nature's Secret Weapon Against Agricultural Pests","authors":"Tarun Kumar Patel","doi":"10.52228/jrub.2023-36-2-8","DOIUrl":"https://doi.org/10.52228/jrub.2023-36-2-8","url":null,"abstract":"Insect pests pose significant challenges to agricultural productivity and crop yield worldwide. Conventional pest control methods, such as chemical pesticides, have limitations and adverse environmental effects. Therefore, there is a growing need for sustainable and eco-friendly alternatives in pest management. This review explores the potential of entomopathogenic fungi as a promising biological control agent for insect pests in agriculture. The review begins by providing an overview of entomopathogenic fungi and their significancce. These fungi possess unique mechanisms to infect and kill insect pests. The mode of action involves attachment of fungal spores to the insect's cuticle, followed by penetration, colonization, and release of toxic metabolites within the host. Various factors influence the efficacy of entomopathogenic fungi, including environmental conditions, insect host susceptibility, and formulation/application methods. The benefits of entomopathogenic fungi as biological control agents are discussed, including their compatibility with integrated pest management (IPM) strategies and minimal impact on non-target organisms. However, challenges exist in scaling up their commercial application. The review presents case studies showcasing successful field applications of entomopathogenic fungi in pest management. Future prospects and research directions are identified, emphasizing the importance of continued advancements in understanding the interactions between entomopathogenic fungi and insect pests. Regulatory frameworks and public acceptance are crucial for the widespread adoption of these fungi in agriculture. In conclusion, entomopathogenic fungi offer immense potential as sustainable and effective tools for biological control of insect pests in agriculture. Their ability to target specific pests, compatibility with IPM, and minimal environmental impact make them a viable alternative to chemical pesticides. Further research, collaboration, and implementation are necessary to fully harness the potential of entomopathogenic fungi in integrated pest management strategies.","PeriodicalId":17214,"journal":{"name":"Journal of Ravishankar University (PART-B)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139135601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-31DOI: 10.52228/jrub.2023-36-2-6
Nikita Raghuvanshi, Bhanushree Gupta
In recent decades, essential oils have emerged as natural supplements to synthetic substances in medicine, agriculture, food industries etc. The modern techniques for extraction of essential oils have significantly reduced the time consumption and increased the yield in comparison to the conventional techniques that have been in use for so long. Advancedcharacterisation techniques like Gas chromatography (GC), Liquid Chromatography (LC), Mass Spectrometry (MS) etc., provide high accuracy incharacterisation depending upon the nature of essential oils or other major phytoconstituents. Studies have shown essential oils to possess biologically significant activities like antibacterial, antifungal, anti-inflammatory, antioxidant, antihistamine, anticholinesterase, anti-cancer, antiaging etc. These activities of essential oils have made them eligible for their application in food preservation, medicines, industries, agriculture etc. Thus, the traditional knowledge of plants and extraction of essential oils from their different parts of significance can contribute to a healthy society if efforts are made towards enhancing their natural properties for maximum utilisation. The present review discusses different sources and compositions of essential oils, common extraction and characterisation techniques, some biological properties of essential oils and their applications in various industries.
{"title":"Extraction, Characterisation, Biological Properties and Applications of Essential Oils: A Review","authors":"Nikita Raghuvanshi, Bhanushree Gupta","doi":"10.52228/jrub.2023-36-2-6","DOIUrl":"https://doi.org/10.52228/jrub.2023-36-2-6","url":null,"abstract":"In recent decades, essential oils have emerged as natural supplements to synthetic substances in medicine, agriculture, food industries etc. The modern techniques for extraction of essential oils have significantly reduced the time consumption and increased the yield in comparison to the conventional techniques that have been in use for so long. Advancedcharacterisation techniques like Gas chromatography (GC), Liquid Chromatography (LC), Mass Spectrometry (MS) etc., provide high accuracy incharacterisation depending upon the nature of essential oils or other major phytoconstituents. Studies have shown essential oils to possess biologically significant activities like antibacterial, antifungal, anti-inflammatory, antioxidant, antihistamine, anticholinesterase, anti-cancer, antiaging etc. These activities of essential oils have made them eligible for their application in food preservation, medicines, industries, agriculture etc. Thus, the traditional knowledge of plants and extraction of essential oils from their different parts of significance can contribute to a healthy society if efforts are made towards enhancing their natural properties for maximum utilisation. The present review discusses different sources and compositions of essential oils, common extraction and characterisation techniques, some biological properties of essential oils and their applications in various industries.","PeriodicalId":17214,"journal":{"name":"Journal of Ravishankar University (PART-B)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139132702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-31DOI: 10.52228/jrub.2023-36-2-5
Vaibhav Dixit, Rajiv Nayan, Shubhra Sinha, Suryakant Manikpuri, M. L. Satnami, Kallol K. Ghosh, M. Deb, S. Pervez, Indrapal Karbhal
A novel composite electrode material has been synthesized using in-situ chemical polymerization of aniline over the surface of rice straw-derived carbon (RSC). The detailed structural characterization validates the effective incorporation of granular polyaniline (PANI) over the RSC surface. The supercapacitor performance of the RSC@PANI electrode was systematically investigated and achieved as high as specific capacitance of 408 Fg-1 at a current density of 1 Ag-1. Moreover, RSC@PANI shows 93% capacitance retention after 1000 cycles at a current density 10 Ag-1. Apart from its outstanding electrochemical performance, the resulting RSC@PANI electrode exhibits exceptional characteristics such as scalability and lightweight properties. This study contributes valuable insights into the synthesis and characterization of RSC@PANI as a promising electrode material for supercapacitors.
{"title":"Rice Straw-Derived Carbon Integrated with PANI as an Electrode Material for High-performance Supercapacitor","authors":"Vaibhav Dixit, Rajiv Nayan, Shubhra Sinha, Suryakant Manikpuri, M. L. Satnami, Kallol K. Ghosh, M. Deb, S. Pervez, Indrapal Karbhal","doi":"10.52228/jrub.2023-36-2-5","DOIUrl":"https://doi.org/10.52228/jrub.2023-36-2-5","url":null,"abstract":"A novel composite electrode material has been synthesized using in-situ chemical polymerization of aniline over the surface of rice straw-derived carbon (RSC). The detailed structural characterization validates the effective incorporation of granular polyaniline (PANI) over the RSC surface. The supercapacitor performance of the RSC@PANI electrode was systematically investigated and achieved as high as specific capacitance of 408 Fg-1 at a current density of 1 Ag-1. Moreover, RSC@PANI shows 93% capacitance retention after 1000 cycles at a current density 10 Ag-1. Apart from its outstanding electrochemical performance, the resulting RSC@PANI electrode exhibits exceptional characteristics such as scalability and lightweight properties. This study contributes valuable insights into the synthesis and characterization of RSC@PANI as a promising electrode material for supercapacitors.","PeriodicalId":17214,"journal":{"name":"Journal of Ravishankar University (PART-B)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139136162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-31DOI: 10.52228/jrub.2023-36-2-2
Manisha Chandrakar, V. K. Patle
Various sensor nodes whose deployment is done in a random way are included in Wireless sensor networks (WSN) within a region for gathering the information out of the respective atmospheres as well as forwards it towards the Base Station (BS). Constrained sources of energy are allotted to the WSN nodes. The consumption of energy of nodes must be reduced for obtaining the enhanced lifetime of the network. Clustering is referred as a technique that reduced the consumption of energy in WSNs. By transmitting the gathered data to the sink through the Cluster Head (CH) nodes located within the clustered networks, the energy of the node can be saved. In WSNs, fault tolerance is a significant issue to consider. The entire data communication system can be rendered inoperable by the failure of just one cluster head. Within the scope of this research, a cluster-based routing method with fault tolerance is provided. The purpose of this study is to present an innovative technique for increasing tolerance of failure and data accumulation in clustered WSN by making use of backup CHs and improving the relay node selection mechanism by modifying ACO. The selection of the backup cluster head is what allows for fault tolerance in this case (BKCH). The method can be broken down into two distinct stages. In the first step, the network is categorized into clusters; in the second step, CHs and BCHs are chosen from the pool of candidates. Communication within the cluster takes place between the member nodes and the CH nodes. Aggregator nodes (AG) are utilised for the purpose of inter-cluster communication, and the modified ACO is utilised to determine which node serves as the most effective relay between CH and AG. When compared with other energy-conserving protocols, this technique uses less energy while increasing fault resilience and PDR.
{"title":"Enhanced ACO in clustering algorithm for QoS in WSN enabled IoT","authors":"Manisha Chandrakar, V. K. Patle","doi":"10.52228/jrub.2023-36-2-2","DOIUrl":"https://doi.org/10.52228/jrub.2023-36-2-2","url":null,"abstract":"Various sensor nodes whose deployment is done in a random way are included in Wireless sensor networks (WSN) within a region for gathering the information out of the respective atmospheres as well as forwards it towards the Base Station (BS). Constrained sources of energy are allotted to the WSN nodes. The consumption of energy of nodes must be reduced for obtaining the enhanced lifetime of the network. Clustering is referred as a technique that reduced the consumption of energy in WSNs. By transmitting the gathered data to the sink through the Cluster Head (CH) nodes located within the clustered networks, the energy of the node can be saved. In WSNs, fault tolerance is a significant issue to consider. The entire data communication system can be rendered inoperable by the failure of just one cluster head. Within the scope of this research, a cluster-based routing method with fault tolerance is provided. The purpose of this study is to present an innovative technique for increasing tolerance of failure and data accumulation in clustered WSN by making use of backup CHs and improving the relay node selection mechanism by modifying ACO. The selection of the backup cluster head is what allows for fault tolerance in this case (BKCH). The method can be broken down into two distinct stages. In the first step, the network is categorized into clusters; in the second step, CHs and BCHs are chosen from the pool of candidates. Communication within the cluster takes place between the member nodes and the CH nodes. Aggregator nodes (AG) are utilised for the purpose of inter-cluster communication, and the modified ACO is utilised to determine which node serves as the most effective relay between CH and AG. When compared with other energy-conserving protocols, this technique uses less energy while increasing fault resilience and PDR.","PeriodicalId":17214,"journal":{"name":"Journal of Ravishankar University (PART-B)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139131250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-13DOI: 10.52228/jrub.2023-36-1-8
T. Kukreja, Sanjana Yadav, Arushi Saloki, S. Saraf
Chemical contamination could lead to one of the worst environmental risks to humanity, but knowledge of the problem is still unevenly distributed worldwide. This review consists of risks associated with human exposure to a chemical pollutant depend on the degree of exposure and the chemical nature of the pollutant. Our knowledge of the scope of pollutants on human health and their hazards. Although some pollution control measures are in place, they are frequently not implemented at the rate required to prevent both acute and chronic consequences on human health today and in the decades to come. Increased global awareness and scientific examination of the whole scope of chemical risk are urgently needed. This review covers numerous aspects that may have negative impacts on human health in polluted places, with a focus on variables influencing the behaviour of pollutants.
{"title":"Chemical Pollutants: A Concern to The Environment","authors":"T. Kukreja, Sanjana Yadav, Arushi Saloki, S. Saraf","doi":"10.52228/jrub.2023-36-1-8","DOIUrl":"https://doi.org/10.52228/jrub.2023-36-1-8","url":null,"abstract":"\u0000 Chemical contamination could lead to one of the worst environmental risks to humanity, but knowledge of the problem is still unevenly distributed worldwide. This review consists of risks associated with human exposure to a chemical pollutant depend on the degree of exposure and the chemical nature of the pollutant. Our knowledge of the scope of pollutants on human health and their hazards. Although some pollution control measures are in place, they are frequently not implemented at the rate required to prevent both acute and chronic consequences on human health today and in the decades to come. Increased global awareness and scientific examination of the whole scope of chemical risk are urgently needed. This review covers numerous aspects that may have negative impacts on human health in polluted places, with a focus on variables influencing the behaviour of pollutants. \u0000","PeriodicalId":17214,"journal":{"name":"Journal of Ravishankar University (PART-B)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85887632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-13DOI: 10.52228/jrub.2023-36-1-3
Mayank Lovanshi, Vivek Tiwari
The segmentation of human body parts is a task that entails assigning labels to pixels in an image to identify the corresponding body part classes. To enhance accuracy, a technique known as sample class distribution was developed, considering the hierarchical structure of the human body and the unique positioning of each part. This technique involves gathering and applying primary human parsing labels in both vertical and horizontal dimensions to exploit the distribution of classes. By combining these guided features, a spatial guidance map is generated and incorporated into the backbone network. These semantic-guided features contribute to the effective recognition of human activity through semantic segmentation-enabled human pose. To assess the effectiveness of this approach, extensive experiments were performed on a large dataset called CIHP, using metrics such as mean IOU, pixel accuracy, and mean accuracy.
{"title":"Human Part Semantic Segmentation Using CDGNET Architecture for Human Activity Recognition","authors":"Mayank Lovanshi, Vivek Tiwari","doi":"10.52228/jrub.2023-36-1-3","DOIUrl":"https://doi.org/10.52228/jrub.2023-36-1-3","url":null,"abstract":"\u0000 The segmentation of human body parts is a task that entails assigning labels to pixels in an image to identify the corresponding body part classes. To enhance accuracy, a technique known as sample class distribution was developed, considering the hierarchical structure of the human body and the unique positioning of each part. This technique involves gathering and applying primary human parsing labels in both vertical and horizontal dimensions to exploit the distribution of classes. By combining these guided features, a spatial guidance map is generated and incorporated into the backbone network. These semantic-guided features contribute to the effective recognition of human activity through semantic segmentation-enabled human pose. To assess the effectiveness of this approach, extensive experiments were performed on a large dataset called CIHP, using metrics such as mean IOU, pixel accuracy, and mean accuracy. \u0000","PeriodicalId":17214,"journal":{"name":"Journal of Ravishankar University (PART-B)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79565134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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