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5th IEEE International Conference on Recent Trends in Computer Science and technology, ICRTCST 2024

作者： Anitha Kumari, D. Shaikh, Irfan Abdul Karim Gangadharan, S. Narendra Kiran, P.B. Ramya, S.R. Nargunde, Amarja Satish Vels Institute of Science Technology and Advanced Studies Pallavaram TamilNadu Chennai India Bahrain Polytechnic Faculty of Business Bahrain St. Joseph's College of Engineering Department of Management Studies Chennai India Lovely Professional University Jalandhar-Delhi Mittal School of Business Punjab Phagwara India Karpagam College of Engineering School of Management Studies Tamilnadu Coimbatore India Bharati Vidyapeeth Institute of Management and Rural Development Administration Sangli Bharati Vidyapeeth Bhavan Rajwada Chowk Maharashtra Sangli India

ISBN: (纸本)9798350351378

As organizations strive to foster diverse and inclusive workplaces, the role of technology, particularly machine learning, becomes crucial in addressing biases inherent in Human Resources (HR) practices. This research explores the application of machine learning algorithms to mitigate biases in recruitment, performance evaluation, and talent management processes, ultimately promoting diversity and inclusion. Biases, whether conscious or unconscious, can affect decision-making at various stages, leading to underrepresentation and disparities within the workforce. Recognizing the need for innovative solutions, this paper advocates for the integration of machine learning techniques to augment HR processes. By leveraging advanced algorithms, organizations can develop unbiased job descriptions, eliminate resume screening biases, and create diverse candidate shortlists. Machine learning models can provide objective insights by analyzing performance metrics, removing subjective biases, and fostering a more equitable assessment of employees. Talent management, the focus of the fourth section, is critical for the retention and development of a diverse workforce. Machine learning algorithms can assist in identifying high-potential employees based on merit, skills, and contributions, thus promoting a fair and inclusive talent pipeline. Addressing concerns related to algorithmic biases, the research suggests guidelines for responsible ML implementation to ensure that technology aligns with organizational values and legal requirements. In conclusion, this research underscores the transformative potential of machine learning in creating more equitable and inclusive workplaces. By addressing biases in HR practices, organizations can harness the power of technology to build diverse teams, foster innovation, and promote a culture of inclusion. However, it also emphasizes the need for ongoing research, collaboration, and ethical considerations to maximize the positive impact of machi

关键词： Decision making

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Smart Electronic Arm Module using Arduino Applications

Smart Electronic Arm Module using Arduino Applications

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2022 IEEE International Conference on Current Development in engineering and technology, CCET 2022

作者： Kanna, R. Kishore Hema, L.K. Ramya, V. Subha Kripa, N. Gomalavalli, R. Ambikapathy, A. Vels Institute of Science Technology Advanced Studies Department of Biomedical Engineering Chennai India Department of Biomedical Engineering Chennai India Bharath Institute of Higher Education and Research Department of Biomedical Engineering Chennai India Siddharth Institute of Engineering and Technology Department of Electronics and Communication Engineering Andhra Pradesh India Department of Electrical and Electronics Engineering Chennai India

ISBN: (纸本)9781665454155

Automation is often employed in today's society to assist people in doing their jobs and improve work efficiency. One kind of automation device that is often employed to assist humans in doing their jobs is the robot. Robots play a variety of functions in human life and are used to make a variety of human tasks easier. Robots are often used because they can make tasks simpler and more productively do them. Robots are used in many different ways to assist people in their work, including drones, welding robots, and agricultural robots. One sort of robot that we come across often is a robot arm, which performs duties comparable to those of a human arm. The robot may be controlled in its application utilizing a variety of techniques, some of which directly use a cable connection and others which utilize a wireless technique. Additionally, a controller-the robot's brain-is required to operate a robot. In order to operate the robot arm via Bluetooth, this research will create a controller based on Arduino, one of the most popular microcontroller boards for use in education, hobbies, and the workplace. The identification of the programme and data collection from various sources, such as a journal or discussion forum, are the first steps in the methodology used in this study. Next, the systems schematic design of the hardware used in this research is done, and then the Arduino programme and smartphone app are added. The select and place activity may be carried out wirelessly utilizing a Bluetooth connection by the Arduino software and the simple Android applications created using App Inventor. © 2022 IEEE.

关键词： Agricultural robots

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Systematic Stress Detection in CNN Application 10

Systematic Stress Detection in CNN Application

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10th International Conference on Reliability, Infocom Technologies and Optimization ,Trends and Future Directions, ICRITO 2022

作者： Mohapatra, Srikanta Kumar Kishore Kanna, R. Arora, Ginni Sarangi, Prakash Kumar Mohanty, Jayashree Sahu, Premananda Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Vels Institute of Science Technology & Advanced Studies Department of Biomedical Engineering Amity University Department of Computer Science and Engineering New Delhi Noida India Hyderabad India Odisha Bhubaneswar India Srm Institute of Science and Technology Srmist UP Ghaziabad India

ISBN: (数字)9781665474337

ISBN: (纸本)9781665474337

Emotional strain is referred to as stress. Both our mental health and the mental health of others around us may be affected. While anxiety is a normal response to stress that may be frightening, it can also cause panic attacks. Everyone needs to address these mental health problems. The method we use to identify stress and anxiety in a person using vocal/audio information is described in this study. We have created a deep neural network model for stress and anxiety detection. Here, Kaggle audio datasets with 7 different emotions―joy, fear, disgust, neutral, sorrow, surprise, and anger―are taken into consideration. To train and evaluate classification algorithms like CNN, these audio datasets are employed. The audio is then pre-processed using acoustic feature extraction, and CNN is used to classify it, providing accuracy based on those seven emotions. This allows us to foretell if the individual is stressed out or anxious. © 2022 IEEE.

关键词： Deep neural networks

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Optimal Voltage Regulation and Energy Efficiency in Photovoltaic Grid system

Optimal Voltage Regulation and Energy Efficiency in Photovol...

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Advances in Signal Processing, Power, Communication, and Computing (ASPCC), IEEE International Conference on

作者： Debarchita Mishra D. Karan C Sanjay Rahul j Benito Micheal Abhsha Arok Biror Abuoi Sharmistha Mandal Department of Electrical and Electronics Engineering Vels Institute of Science Technology and Advanced Studies Chennai India Electrical Engineering Department Aliah University Kolkata India

ISBN: (数字)9798350355093

ISBN: (纸本)9798350355109

Photovoltaic (PV) energy is the most vital renewable energy sources, and it has appeared as a feasible solution to the world’s energy issue. This paper proposes a sophisticated PV integrated architecture including a coupled inductor based second order buck-boost converter, synergized with a particle swarm optimized proportional integral (PSO-PI) controller. With its ability to handle a broad range of input voltages, the converter’s topology is designed to reduce energy losses and improve overall system efficiency. The objective is to guarantee excellent power quality and improve system reliability. To further improve performance, the system also includes a PI controller that is supported by PSO. The output is delivered to the grid via a single-phase voltage source inverter and grid synchronization is attained by the PI controller. The developed research is validated in MATLAB/Simulink and comparison with traditional approaches is conducted. The observed results show better converter efficiency of 92% with higher performance in terms of power quality enhancement.

关键词： Photovoltaic systems Renewable energy sources PI control Voltage source inverters Power quality Signal processing Topology Synchronization Particle swarm optimization Voltage control

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Mitochondrial flashes are interlinked with adaptive thermogenesis in brown adipocytes

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hLife 2024年第4期2卷 179-188页

作者： Xinyu Chen Huwatibieke Bahetiyaer Xuejiao Song Zuzhi Jiang Wenfeng Qi Weizheng Gao Lin Zhang Jue Zhang Heping Cheng Xianhua Wang State Key Laboratory of Membrane Biology Institute of Molecular MedicineCollege of Future TechnologyPeking UniversityBeijingChina Academy for Advanced Interdisciplinary Studies Peking UniversityBeijingChina College of Engineering Peking UniversityBeijingChina Research Unit of Mitochondria in Brain Diseases Chinese Academy of Medical SciencesPKU-Nanjing Institute of Translational MedicineJiangsuChina

Mitochondrial flash(mitoflash)is the electrochemical excitation of a single mitochondrion and plays diverse signaling roles in a variety of *** the viewpoint of bioenergetics,it represents the transient uncoupling of mitochondrial respiration from ATP *** adipose tissue(BAT)produces heat,primarily via mitochondrial uncoupled ***,we aim to illustrate the mitoflash activity in BAT *** show that BAT mitochondria undergo stochastic and intermittent mitoflashes at the levels of isolated mitochondria,cultured brown adipocytes,and even intact BAT.A BAT mitoflash contains multiple signals,including transient depolarization of mitochondrial membrane potential,transient matrix alkalization,and bursting production of reactive oxygen ***,thermogenic activation by b3-adrenergic stimulation dramatically augments mitoflash incidence,with mild effects on its unitary *** of the thermogenic uncoupling protein 1(UCP1)showed little effect on mitoflash biogenesis during heat ***,our results suggest that mitoflash might constitute an elemental signaling activity of mitochondria to regulate BAT thermogenesis.

关键词： mitochondrial flash(mitoflash) mitochondria thermogenesis brown adipocyte

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Comparative study on electroless composite coatings of textured and untextured Al-substrates

Comparative study on electroless composite coatings of textu...

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作者： Singh, Garima Mohanty, Shalini Kumar Singh, Rabesh Rai Dixit, Amit Kumar Sharma, Anuj Centre for Advanced Studies Uttar Pradesh Lucknow226031 India Department of Mechanical and Industrial Engineering Tallinn University of Technology Tallinn12616 Estonia Dhanbad826004 India Department of Mechanical Engineering S R institute of management and technology Bakshi Ka Talab U.P. Lucknow226201 India

In the present work, electroless composite coating of Ni-P-MoS2 is deposited on EDM textured Al-alloy substrate. A comparative study is carried out to analyse the effect of textures (prepared through electrical discharge machining) on the coated surface properties. The coatings were analysed on account of their surface morphology through Field Emission Scanning Electron Microscopy (FESEM), composition using Electron Dispersion Spectroscopy (EDS), surface roughness and topography by means of optical profilometer. Results indicate that the composite coatings produced on the textured surfaces have better deposition as compared to non-textured surfaces. The transfer of different elements i.e., Ni, P, Mo, and S on both the coated surfaces was confirmed from the EDS plots while the profilometer images showed the areal surface roughness parameters. © 2022

关键词： Scanning electron microscopy

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High Speed Neural Network MPPT Algorithm for DFIG Based Wind Energy Conversion System 7

High Speed Neural Network MPPT Algorithm for DFIG Based Wind...

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7th International Conference on Circuit Power and Computing Technologies, ICCPCT 2024

作者： Tharwin Kumar, R. Balaji, V. Sakthidhasan, K. Gomathi, S. Sreedhar, R. Janaki, N. Puducherry Technological University Department of Electrical and Electronics Engineering Puducherry India MAI-NEFHI College of Engineering and Technology Faculty of Electrical and Electronics Engineering Asmara Eritrea Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College Department of Electrical and Electronics Engineering Chennai India St. Joseph's College of Engineering Department of Electrical and Electronics Engineering Chennai India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Electrical and Electronics Engineering Chennai India Vels Institute of Science Technology and Advanced Studies Department of Electrical and Electronics Engineering Chennai India

ISBN: (纸本)9798350372816

For the generation of electrical energy, breeze energy is a trustworthy and talented renewable vitality basis. An innovative proposal with many scientific and economic benefits is using wind source technology to charge electric vehicles. Worldwide, the market for Wind Energy Conversion System (WECS) has been expanding significantly. High-quality output power is commonly produced when wind energy demand grows. WECS has significant modelling, control, and grid integration issues as a result of the intermittent nature of wind energy. A proper controller mechanism has to be created in order to significantly improve WECS. An innovative method for maximizing the power of wind energy founded on Radial Basis Function Neural Networks (RBFNN) is proposed in this study to increase the power of Double Fed Induction Generators (DFIG). DFIG based wind turbine, and to provide outstanding dynamic performance in response to breeze rapidity fluctuations. MPPT is a strong algorithm that operates around an ideal rotating speed by utilizing RBFNN for mechanical speed control. We evaluated the performance of DFIG founded WECS with MATLAB/Simulink. The RBFNN efficiency is 91% when comparing MPPT controllers. © 2024 IEEE.

关键词： Radial basis function networks

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Applications of advanced Optimized Neuro Fuzzy Models for Enhancing Daily Suspended Sediment Load Prediction

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Computer Modeling in engineering & Sciences 2025年第4期143卷 1249-1272页

作者： Rana Muhammad Adnan Mo Wang Adil Masood Ozgur Kisi Shamsuddin Shahid Mohammad Zounemat-Kermani College of Architecture and Urban Planning Guangzhou UniversityGuangzhou510006China Center for Global Health Research Saveetha Institute of Medical and Technical SciencesChennai600001India Department of Natural and Applied Sciences TERI School of Advanced StudiesNew Delhi110070India Department of Civil Engineering Lübeck University of Applied ScienceLübeck23562Germany Department of Civil Engineering School of TechnologyIlia State UniversityTbilisi0162Georgia School of Civil Environmental and Architectural EngineeringKorea UniversitySeoul02841Republic of Korea School of Civil Engineering Faculty of EngineeringUniversiti Teknologi Malaysia(UTM)Johor Bahru81310Malaysia Department of Civil Engineering Shahid Bahonar University of KermanKerman***Iran

Accurate daily suspended sediment load(SSL)prediction is essential for sustainable water resource management,sediment control,and environmental ***,SSL prediction is highly complex due to its nonlinear and dynamic nature,making traditional empirical models *** study proposes a novel hybrid approach,integrating the Adaptive Neuro-Fuzzy Inference System(ANFIS)with the Gradient-Based Optimizer(GBO),to enhance SSL forecasting *** research compares the performance of ANFIS-GBO with three alternative models:standard ANFIS,ANFIS with Particle Swarm Optimization(ANFIS-PSO),and ANFIS with Grey Wolf Optimization(ANFIS-GWO).Historical SSL and streamflow data from the Bailong River Basin,China,are used to train and validate the *** input selection process is optimized using the Multivariate Adaptive Regression Splines(MARS)*** performance is evaluated using statistical metrics such as Root Mean Square Error(RMSE),Mean Absolute Error(MAE),Mean Absolute Percentage Error(MAPE),Nash Sutcliffe Efficiency(NSE),and Determination Coefficient(R^(2)).Additionally,visual assessments,including scatter plots,Taylor diagrams,and violin plots,provide further insights into model *** results indicate that including historical SSL data improves predictive accuracy,with ANFIS-GBO outperforming the other ***-GBO achieves the lowest RMSE and MAE and the highest NSE and R^(2),demonstrating its superior learning ability and *** findings highlight the effectiveness of nature-inspired optimization algorithms in enhancing sediment load forecasting and contribute to the advancement of AI-based hydrological *** research should explore the integration of additional environmental and climatic variables to enhance predictive capabilities further.

关键词： Suspended sediment load prediction neuro-fuzzy gradient-based optimizer ANFIS

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Performance analysis of Micro-blowers for the design of Micro Automatic Positive Airway Pressure System for Obstructive Sleep Apnea Treatment 16

Performance analysis of Micro-blowers for the design of Micr...

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16th International Conference on Sensing technology, ICST 2023

作者： Priya, L. Vidhyapriya, R. Mathu Mitha, V. Venkataraman, K.K. Nandagopal, V. Muthupavithran, M. Sri Ramakrishna Engineering College Department of Biomedical Engineering Tamil Nadu Coimbatore India Psg College of Technology Department of Biomedical Engineering Tamil Nadu India Nanotech Research Innovation and Incubation Centre Psg Institute of Advanced Studies Department of Electronics and Communication Engineering Tamil Nadu India Institute of Lung Care & Research Hindusthan Hospital Tamil Nadu India

ISBN: (纸本)9798350395341

Obstructive Sleep Apnea (OSA) is a condition, in which during the sleep the upper airway is obstructed due to the throat muscles relaxation. The conventional systems used for treatment of OSA are Continuous positive airway pressure (CPAP) and Automatic positive airway pressure (APAP) devices which deliver required air pressure to open the airway obstruction. The major drawback of these systems is the presence of tubing that tangles around the patient's neck causing discomfort and curbs the freedom of sleep position during sleep. This research work aims at analysing and selecting Micro-Electro-Mechanical System (MEMS) based micro-blowers for the design of an APAP system. It is planned to design a hoseless APAP system which embeds the APAP system within a face mask. Five different micro blowers such as Murata MZB1001T02, Delta BSB01703HA300CAJ, TF029B-1000F, TF037F-2000F, Sunon UB5U3-700 have been identified based on weight, flow rate, pressure and operating voltage. The performance metrics such as air pressure, flow specifications, current and power consumption of these 5 different micro-blowers are analysed for the effective use in the hoseless APAP system. Two micro-blowers namely, TF029B-1000F and UB5U3-700 were found to deliver the required pressure and air flow as per the conventional APAP systems. TF029B micro-blowers were used for the design of hoseless APAP device as it weighs less compared to TF037F micro-blower. This hoseless APAP device does not disturb the patients when changing their sleep position. It is acting as a user comfortable sleep aiding device compared to existing CPAP/APAP devices available in the market. © 2023 IEEE.

关键词： MEMS

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Fostering environmental sustainability of leather industry: environmental impact assessment and improvement prospects for leather-tanning technologies

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Environmental Science and Pollution Research 2024年 1-18页

作者： Daddi, Tiberio Ahmad, Shamraiz Albano, Francesca Sant’Anna School of Advanced Studies Institute of Management Piazza Martiri Della Libertà 33 Pisa56127 Italy Ergo S.R.L. Via Oberdan 11 PI Pisa56127 Italy School of Mechanical and Manufacturing Engineering National University of Sciences and Technology Islamabad44000 Pakistan Interdepartmental Research Center for Environmental Sciences University of Bologna Ravenna48123 Italy

Because of various negative impacts of chromium intensive manufacturing, the leather-based fashion industry is under pressure to use environmentally friendly tanning technologies. However, there is a lack of scientific research that evaluates the environmental impacts of novel tanning processes. Thus, this study is aimed to quantify and compare the environmental impacts of traditional chromium-based process and a novel metal-free tanning technology. The novel metal-free technology is based on synthetic tannins, instead of metal or vegetable-based tannins. To achieve the objectives, a detailed life cycle assessment was done for 1 m2 of finished leather. The primary data were gathered from two different leather manufacturing plants located in the same Italian municipality and the background data were extracted from the Ecoinvent database. SimaPro 9.4 was used as the modeling software tool, and the impacts were evaluated for midpoint impact categories. For the novel metal-free tanning technology, the results revealed a significant reduction in various impact categories, such as particulate matter impacts were reduced by 25%, human toxicity (non-carcinogenic) by 31%, human toxicity (carcinogenic) by 56%, and acidification by 29%. Overall, based on single point performance score, the novel metal-free tanning system showed 18.4% less environmental impacts than the chrome-based tanning. For the most relevant impact categories, the novel metal-free tanning system again showed significantly less impact. The cattle breeding phase contributed most to various relevant impact categories, including acidification, particulate matter, and terrestrial eutrophication. Two alternative scenarios were also developed and evaluated to show how the solar energy may help further reduce the environmental impacts. A sensitivity analysis was also carried out to see the influence of uncertainty linked with the choice of thermal energy source. Overall, the study highlighted how the green tanning

关键词： Eutrophication

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