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Sustainable Thermoelectric Air-Cooling Systems: A Review 2nd

Sustainable Thermoelectric Air-Cooling Systems: A Review

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2nd Biennial International Symposium on Fluids and Thermal engineering, FLUTE 2023

作者： Giri, Jitendra Mohan Nain, Pawan Kumar Singh Dubey, Kaushalendra Kumar Lloyd Institute of Engineering and Technology Greater Noida201310 India Galgotias University Greater Noida201312 India

ISBN: (纸本)9789819724802

Numerous recent reports indicate that buildings account for more than forty percent of total energy consumption. A major cause of the current energy crisis is the proliferation of HVAC systems that consume a disproportionate amount of power. In this paper, a review of the thermoelectric cooling systems fitted in the building to reduce its thermal load is presented. This begins by discussing the fundamentals of thermoelectric module (TEM). The factors that improve the system's performance are discussed. Then, the incorporation of thermoelectric cooling systems into the structure and its benefits in terms of energy consumption are discussed. Thermoelectric technology applications are expected to become increasingly more prevalent as new materials emerge on the market with improved levels of efficiency. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Thermoelectric refrigeration

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Strategic Framework for Implementing Artificial Intelligence in Organizations from Conceptualization to Practical Execution and Performance Evaluation

Strategic Framework for Implementing Artificial Intelligence...

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2024 International Conference on Sustainable Computing and Integrated Communication in Changing Landscape of AI, ICSCAI 2024

作者： Gupta, Anish Tyagi, Lalit Sisodia, Vibhash Singh AmanVerma CEC Chandigarh Engineering college Jhanjeri Mohali India Shri Bhawani Niketan Institute of Technology and Management Jaipur India Lloyd Institute of Engineering & Technology Gr. Noida India

ISBN: (纸本)9798350355338

This paper provides a conceptual model of the strategic AI integration process in organizations that outlines the steps for conceptualization, implementation, and assessment. Key principles of the framework include the focus on strategy and goals by choosing AI projects that support strategic goals, objectives, and priorities of an organization. It also underscores the need to put in place proper structures of governance of the utilization of artificial intelligence in ways that will not be misleading and unethical. Starting from the conceptual levels, the framework states the need for the existence of AI vision and purpose or specific goals to achieve in AI integration. It contains useful tips or guidelines for choosing right AI technologies based on Organization readiness, existing infrastructure & scenarios of its implementation. The necessity of creating cross-functional teams is described, focusing on cooperation between specialists in the field of AI and domain experts, which is crucial to achieve the desired outcomes. This paper covers significant aspects like data issues where they explored the problem of acquiring quality data for training the AI models. Stakeholder management, infrastructure necessities for AI deployment, and integration of AI into existing business models and processes are also outlined here, for continuity and effectiveness of operations. In addition, the framework contains insights on how to assess AI outcomes and enforce best practices with regards to performance and reusability. Finally, to enumerate the success stories from different industries and learn from them, samples of AI plans are included. As noted the following is the strategic framework that, when applied by business leaders and technologists will allow AI to be used as a force multiplier to permanently alter organizations and provide sustainable success in a hostile world economy. The holistic approach promotes AI projects that are both technically and organizationally re

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Skin Cancer Detection Using Deep Block Convolutional Neural Networks 10

Skin Cancer Detection Using Deep Block Convolutional Neural ...

引用

10th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer engineering, UPCON 2023

作者： Mittal, Ruchi Malik, Varun Singh, Jaiteg Gupta, Shubhi Srivastava, Arun Pratap Sankhyan, Akhil Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Amity School of Engineering and Technology Amity University Greater Noida India Lloyd Institute of Engineering & Technology Greater Noida India Lloyd Law College Greater Noida India

ISBN: (纸本)9798350382471

One of the most common and potentially fatal forms of cancer, skin cancer is on the increase across the world. The likelihood of a positive outcome from therapy increases dramatically with early and precise diagnosis. This is especially true with deep learning approaches. This research introduces the use of Deep Block Convolutional Neural Networks (DB-CNNs) as a unique method for detecting skin cancer. The suggested DBCNN model was trained and tested using a large dataset consisting of photos of various skin lesions. DB-CNNs are built to take advantage of the hierarchical characteristics of skin lesions, capturing the complex patterns and textures that are essential to a correct diagnosis. The model makes use of a chain of convolutional layers, supplemented with blocks trained to extract features and establish spatial relationships. By combining these modules, the network can better identify nuances in skin lesion features, leading to more precise diagnoses. This study explores several data preparation techniques, such as image enhancement and normalization, to determine whether any of them may strengthen the model's robustness and generalizability. © 2023 IEEE.

关键词： Deep Block Convolutional Neural Networks Medical Imaging Normalization Skin cancer detection

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Data Mining Methods for Internet of Things: A Survey 6

Data Mining Methods for Internet of Things: A Survey

引用

6th International Conference on Contemporary Computing and Informatics, IC3I 2023

作者： Saxena, Aditi Taluja, Resham Sararswat, Manish Shalini, N. Krishna, Om Kumar, Pushpendra GLA University Dept of Electronics and Communication Engineering Mathura India Graphic Era Deemed to Be University Department of Mechanical Engineering Dehradun India Lloyd Institute of Engineering and Technology Greater Noida India Institute of Aeronautical Engineering Dept of Computer Science and Engineering Hyderabad India Lloyd Law College Greater Noida India Lloyd Institute of Management and Technology Greater Noida India

ISBN: (纸本)9798350304480

It is fascinating to think about all the many ways in which information, intellect, and knowledge may be used in human existence. Because of the lightning-fast pace at which technology is advancing, it is now essential to amass a large quantity of data in order to forecast and investigate potential developments in the field of artificial intelligence. In order to identify new information inside databases, it is necessary to apply strategies and procedures taken from a variety of information systems specializations. The practice of data mining entails not only the finding of new information but also the extraction of information that may be put to beneficial use. In recent years, considerable advances have been made in decision-making abilities in a variety of contexts, including expert systems, artificial agent networks, and machine intelligence. These businesses include companies in the fields of commerce, education, architecture, and building construction, among others. The approach that was taken in this piece was derived from an analysis of the data mining strategies and developments that have seen the greatest amount of adoption across a variety of business sectors over the course of the last five years. These patterns and modes of operation were investigated. Throughout the course of this enquiry, the processes and patterns described above were scrutinized. The use of text mining as a tool for database analysis, the enhancement of worker productivity in the industrial sector, and the application of data mining for instructional practices are only a few instances of what has been learnt in the area of education. One other illustration of this would be the use of text mining as a technique for image recognition. It was also found in the fields of trade and industry. © 2023 IEEE.

关键词： Data Mining Data Mining Processes Data Mining Techniques Database Database Management Systems

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Electric Vehicle Charging Scheduling: A Review and Optimization Framework

Electric Vehicle Charging Scheduling: A Review and Optimizat...

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2024 International Conference on Sustainable Computing and Integrated Communication in Changing Landscape of AI, ICSCAI 2024

作者： Singh, Arunesh Kumar Chaturvedi, D.K. Kumar, Mukesh Kumar, Rohit Naseerudin, Ibraheem Department of Electrical Engineering Jamia Millia Islamia New Delhi India Department of Electrical Engineering Dayalbagh Educational Institute Agra India Lloyd Institute of Engineering & Technology Greater Noida India

ISBN: (纸本)9798350355338

With the increasing adoption of electric vehicles (EVs) worldwide, the efficient management of electric vehicle charging infrastructure has become imperative. The EV adoption is primarily hindered by large waiting period of charging. Electric vehicle charging scheduling plays a vital role in minimizing charging costs, reducing average waiting time, optimizing energy utilization, and ensuring grid stability. This research paper provides a comprehensive review of existing literature on EV charging scheduling and proposes an optimization framework to enhance the performance of charging infrastructure. The proposed framework incorporates various factors, such as user preferences, grid constraints, and renewable energy (RE) integration, to develop efficient and sustainable charging schedules. © 2024 IEEE.

关键词： Charging stations

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Innovative Empirical Approaches for Behavioural Finance Research 6

Innovative Empirical Approaches for Behavioural Finance Rese...

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6th International Conference on Contemporary Computing and Informatics, IC3I 2023

作者： Katyal, Mahira Arora, Deepika Rao, A. Kakoli Dhyani, Deepak Lloyd Institute of Engineering & Technology Uttar Pradesh Greater Noida India Uttar Pradesh Noida India

ISBN: (纸本)9798350304480

An interdisciplinary subject matter referred to as behavioral finance, which mixes psychology and economics, has shed focus on the intricacies of human being's actions inside the economic marketplace. Even though they're beneficial, traditional conventional methods often fall short of capturing the complex and illogical components of decision-making which can be at the coronary heart of behavioral finance phenomena. This research paper examines present-day empirical techniques that provide new vantage factors and better comprehension of behavioral finance. We begin by means of intensive observation of the literature to discover any gaps or restrictions in the methods currently being used in research. Then, we present a huge range of current empirical methodologies, such as neuro-finance, experiential economics, huge records evaluation, and blockchain strategies. With the use of those methods, we may also explore investor behavior, sensory evaluation, and marker dynamics in new ways. This study demonstrates the changing nature of behavioral finance research, which is defined by cutting-edge empirical strategies that make use of big data, neuro-finance, experimental techniques, and cross-disciplinary cooperation. © 2023 IEEE.

关键词： behavioral finance ig data ML neuro-economics neuro-finance textual analysis time-series analysis VR

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Spinal Cord Disease Identification Using Transfer Learning Techniques 10

Spinal Cord Disease Identification Using Transfer Learning T...

引用

10th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer engineering, UPCON 2023

作者： Mittal, Ruchi Malik, Varun Goyal, S.B. Yadav, Suman Avdhesh Srivastava, Arun Pratap Sankhyan, Akhil Chitkara University Institute of Engineering and Technology Chitkara University Punjab India City University Faculty of Information Technology Malaysia Amity School of Engineering and Technology Amity University Department of Computer Science and Engineering Greater Noida India Lloyd Institute of Engineering & Technology Greater Noida India Lloyd Law College Greater Noida India

ISBN: (纸本)9798350382471

Spinal cord diseases pose a significant challenge in the medical field due to their complex nature and diverse manifestations. Early and accurate diagnosis is crucial for effective treatment and management. With the advent of deep learning techniques, the field of medical image analysis has witnessed remarkable advancements. Transfer learning, a subset of deep learning, has gained prominence for its ability to leverage pre-trained models on new tasks with limited labeled data, making it ideal for medical image classification tasks. In this study, we propose a novel approach for the identification of spinal cord diseases using transfer learning techniques, specifically employing a modified ResNet (Residual Neural Network) architecture. In order to train incredibly deep networks while avoiding the vanishing gradient issue, ResNet makes use of a deep structure and skip connections. This modification aims to extract subtle features that are crucial for accurate disease classification. A huge collection of spinal cord pictures, including both diseased and healthy instances, is used to train the suggested model. The model's capability to generalize and correctly diagnose spinal cord disorders is enhanced by the use of a pre-trained ResNet backbone, which draws on information gathered from a wide variety of datasets. © 2023 IEEE.

关键词： Medical Image Analysis Modified ResNet Architecture Spinal Cord Diseases Transfer Learning

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Parking Slot Estimation and Occupancy Prediction using LSTM and CNN 6

Parking Slot Estimation and Occupancy Prediction using LSTM ...

引用

6th International Conference on Contemporary Computing and Informatics, IC3I 2023

作者： Rai, Anjani Kumar Madan, Parul Khan, Irfan Vani, V Divya Singh, Rajeev Singh, Narendra Institute of Engineering & Technology GLA University Mathura India Graphic Era Deemed University Department of Computer Science & Engineering Dehradun India Lloyd Institute of Engineering and Technology Greater Noida India Institute of Aeronautical Engineering Department of Computer Science and Engineering Hyderabad India Lloyd Law College Greater Noida India

ISBN: (纸本)9798350304480

Artificial intelligence has been one of the most widely used technologies in the fields of healthcare, transportation, traffic systems, and weather forecasting. The usage of artificial intelligence It gives the accuracy of the model and enhances the model's performance. slightly compared to the conventional methods. Finding a free space or parking This is a novel area where computer vision techniques have been used predominantly. The involution of a convolutional neural network-based computer vision system has now been accelerated. These traffic monitoring and parking systems are intelligent systems. With the service application layer This particular model is As an enhanced detective interference system, which is proposed Using cloud data, locate the available parking spots. We use several machine learning models to predict parking occupancy. But this state of art under this particular horizon of research is not a search for parking spaces. Using machine learning, the data has been categorised into the different sections, like importing the data, visualising the data. Prediction and training and validation. Our proposed model has been compared with the state of the art and is proven with an accuracy of 93.2%, which is better than all the proposed models. © 2023 IEEE.

关键词： AI computer vision machine learning parking slot simulation

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Solar Wireless Electric Vehicle Charging System 6

Solar Wireless Electric Vehicle Charging System

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6th International Conference on Contemporary Computing and Informatics, IC3I 2023

作者： Kumar, Rakesh Laxminarayanamma, K. Gori, Yatika Deepak, A. Tiwari, Kripanshu Kumar, Pushpendra GLA University Department of Computer Engineering & Applications Mathura India Institute of Aeronautical Engineering Department of Information Technology Hyderabad India Graphic University Department of Mechanical Engineering Dehradun India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Lloyd Institute of Engineering and Technology Greater Noida India Lloyd Institute of Management and Technology Greater Noida India

ISBN: (纸本)9798350304480

The drastic changes in solar-based devices are changing and they are solar-based for charging electric vehicles and other appliances. Electric vehicles are used for reducing pollution through which the machines are dedicatedly designed in the way to reduce pollution. Electric vehicles brilliantly hit the roads to introduce the main factor of technology. The production of electric vehicles is increased and mainly manufactured to increase the demand for vehicles in the current era. The main motive of the solar-based approach is to reduce the cost consumption and helps the user to achieve a more fertile amount of fuel for traveling. The sensors and the microcontrollers are used to increase the capacity of the vehicle powering time and maintain the process of vehicle ambiance. Electricity-based vehicles are proven to reduce the stress on the environment and help to increase the power of the traveling time with more ambiance and the controlled nature of the devising units. The main aim of the system is to help the controller to reduce the maintenance cost and retardation time of the circuitry to help the manufacturer to reduce the cost and increased the effectiveness of the system. The controlled nature of the system and the failure ranges are reduced and mainly proctored to increase the sector value. The main aim of the system is revealed through the process of communication through the demanding system of maintenance through the networking protocol. © 2023 IEEE.

关键词： Microcontroller Motor Power voltaic cell Solar battery Watts's charger

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Attentional Deep Learning novel approach for Facial Expression Recognition 6

Attentional Deep Learning novel approach for Facial Expressi...

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6th International Conference on Information Systems and Computer Networks, ISCON 2023

作者： Khan, Nizamuddin Singh, Ajay Vikram Agrawal, Rajeev Amity Institute of Information Technology Amity University UP Noida India Lloyd Institute of Engineering and Technology UP G. Noida India

ISBN: (纸本)9798350346961

The use of intelligent human-computer interaction, which recognises human emotion based on facial expressions, is significant and has a big impact on people's daily lives and work. One of the most important applications of computer vision is the recognition of facial expressions. However, there are certain issues with the present research on facial emotion identification, such as the network model's limited capacity for generalisation and the recognition system's weak level of robustness. In this article, we provide a method for feature extraction that blends convolutional neural networks for facial emotion identification attentional deep networks. It can be demonstrated that this network performs better at emotion recognition than the current mainstream facial emotion detection models by the experimental simulation of the most challenging data set FER-2013.. © 2023 IEEE.

关键词： Emotion Recognition

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