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Networking and Communications (ICNWC), international conference on

作者： Sakthimohan M Sundravadivelu K Amuthaguka D Tamil Selvan S Elizabeth Rani G Dudekula Rahul Department of ECE KalaignarKarunanidhi Institute of Technology Coimbatore Tamilnadu India Department of Computer Science Madurai Kamaraj University Madurai Tamilnadu India Department of Computer Applications Kalasalingam Academy of Research and Education Krishnankoil Tamil Nādu India Department of CSE (AIML) KalaignarKarunanidhi Institute of Technology Coimbatore Tamilnadu India

ISBN: (数字)9798350365269

ISBN: (纸本)9798350365276

For applications of signal processing that are both economical and computationally intensive, efficient arithmetic circuits are required. High-reliability and portable circuits are required for electronic appliances including pagers, laptops, and notebook computers. Power dissipation has grown in relevance with the introduction of high-performance chips for effective chip design. To achieve high throughput and low power dissipation, it is now more important than ever to investigate efficient design methodologies. In the past few years, high-performance VLSI design has become more and more dependent on low power and fast circuits. An Adder and a Multiplier are the basic components of an Arithmetic & Logic Unit (ALU). An adder, is an essential unit of every ALU, performs the addition function. And a multiplier is created using this adder as a foundational element. Thus, any DSP application such as FFT or others must use multiplication as a fundamental building block. Subsequently, new strategies for planning arithmetic circuits are expected to come from the results that are wanted concerning area, power, and time. The significant objective is to make a high-performance adder and Multiplier that can work at a clock recurrence of 2 GHz. Pass transistors, transmission gates, and traditional correlative metal oxide semiconductors are utilized in the design of the proposed hybrid full adder. The aforementioned adder has been used to construct the Braun multiplier architecture for multiplication operations. Additionally, it is computed how much power and propagation delay each circuit dissipates on average. And Synopsis - PrimeSim Tool was used to complete the entire design. Our proposed system Braun Multiplier with Hybrid Full Adder achieved a very significant reduction in delay, by 80%. This translates to a potential operating frequency of around 6.7 GHz.

关键词： Very large scale integration Signal processing programming Throughput Power dissipation Delays Transistors

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Integrating Artificial Intelligence in Early Childhood Education: A Review of Current Practices and Future Directions

Integrating Artificial Intelligence in Early Childhood Educa...

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Artificial Intelligence in Education and Industry 4.0 (IDICAIEI), DMIHER international conference on

作者： Anjali Rai Sharath Hullumani V Moh’d Irshad Qureshi Raghuveer Raghumahti Gurjeet Kaur Department of Neurophysiotherapy Ravi Nair Physiotherapy College Wardha India Department of Pediatrics Physiotherapy Ravi Nair Physiotherapy College Wardha India Ravi Nair Physiotherapy College Wardha India

ISBN: (数字)9798331528713

ISBN: (纸本)9798331528720

Background-With the rapid technological development in the world with Artificial intelligence in Early childhood education (AIED) and development is a new focus in digital literacy education research. Despite its expanding importance, AI literacy is mostly unexplored in early childhood education (ECE), as AI courses for young children have only recently emerged. It is vital to establish AI competencies in the next generation and educate them on properly engaging with numerous toolkits and curricula to enable young children to learn about AI by creating, programming, training, interacting, and using AI. Methods-Previous studies on AI in education have primarily focused on curriculum design for kindergarten, secondary, and university levels and toolkits like social robots, addressing challenges and opportunities. However, research on AI in early childhood education (ECE) remains limited. This study evaluates various research designs, pedagogical approaches, and interventions, exploring how different AI tools help young children to know how to foster AI literacy in terms of concepts, practices, and perspectives. Results-The selected articles published from the year 2019 to 2024 which studied AI in Education and Development, Current research, technology, and applications in AI education have shown that activity-based learning is more effective than other modes of learning and has potential educational benefits. This study also looked at how well children comprehended AI ideas according to their age and gender, in addition to their direct involvement with social robots and AI courses. Conclusion-It highlights the potential and importance of AI literacy in ECE, that young children can quickly grasp AI concepts through interactive activities with a social robot, suggesting that hands-on exploration effectively enhances AI literacy. Future research should focus on expanding the curriculum to include more comprehensive materials and adapting it for diverse educational contex

关键词： Training Pediatrics Reviews Navigation Education Social robots Medical services Artificial intelligence Next generation networking programming profession

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Java and the Power of Multi-Core Processing

Java and the Power of Multi-Core Processing

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2nd international conference on Complex, Intelligent and Software Intensive Systems (CISIS 2008)

作者： Peter Bertels Dirk Stroobandt ELIS Department Ghent University Belgium Belgium ELIS Department Ghent University Belgium

The new era of multi-core processing challenges software designers to efficiently exploit the parallelism that is now massively available. Programmers have to exchange the conventional sequential programming paradigm for parallel programming: single-threaded designs must be decomposed into dependent, interacting tasks. The Java programming language has built-in thread support and is therefore suitable for the development of parallel software, but programming multi-threaded applications is a tedious task. Therefore we are working on a framework and tool support to alleviate the burden of threads, synchronisation and locking, based on process networks. This paper describes our initial ideas for this new programming model.

关键词： Java Magnetic cores Parallel processing Software Parallel programming programming System recovery

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Data Driven Solution to Market Equilibrium via Deep Reinforcement Learning

Data Driven Solution to Market Equilibrium via Deep Reinforc...

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Power Science and Technology (ICPST), IEEE international conference on

作者： Lin Wen Jianxiao Wang Li Lin Yang Zou Feng Gao Qiteng Hong School of Electrical and Electronic Engineering North China Electric Power University Beijing China National Engineering Laboratory for Big Data Analysis and Applications Peking University Beijing China Department of Industrial Engineering and Management College of Engineering Peking University Beijing China Department of Electronic and Electrical Engineering University of Strathclyde Glasgow United Kingdom

ISBN: (数字)9798350349030

ISBN: (纸本)9798350349047

Equilibrium analysis is an effective tool to analyze the operation efficiency of the electricity market, but how to efficiently solve the power market equilibrium model with multiagent participation remains to be further studied. The traditional model transformation method has low computational efficiency and poor ability to deal with strong uncertainty. The optimality and convergence of the solution are not fully guaranteed. Therefore, this paper intends to use a multi-agent deep reinforcement learning algorithm to reach a fast solution to the market equilibrium model. Here we take the interaction between multiple virtual power plants (VPPs) and the upstream power grid as an example. A bi-level mathematical programming with equilibrium constraints (MPEC) is constructed. The upper level aims to minimize the cost of running the VPPs, the lower level aims to minimize the cost of running the power grid. A multi-agent reinforcement learning algorithm is employed to solve the MPEC based on deep deterministic policy gradient (DDPG), which is a data-driven, selflearning and model-free approach without the modeling and computational complexity caused by existing methods. Finally, an example of iteration between an IEEE-30 node power grid system and a VPP is given to verify the rationality and effectiveness of the proposed algorithm.

关键词： Analytical models Costs Uncertainty Computational modeling Virtual power plants Deep reinforcement learning Power grids

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AI and the Future of Work in Logistics: A Delphi Study on Workforce Transformation

AI and the Future of Work in Logistics: A Delphi Study on Wo...

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Artificial Intelligence in Education and Industry 4.0 (IDICAIEI), DMIHER international conference on

作者： Shailesh Kediya Vandana Mohanty Mubina Saifee Rajani Kumar Lalit Agrawal Aarti Kulkarni School of Logistics and Supply Chain Management Symbiosis Skills and Professional University Pune India Yashaswi's IIMS Pune India Department of Business Administration Jhulelal Institute of Technology Nagpur India Green Heaven Institute of Management and Research Nagpur India Department of Computer Science and Applications Ramdeobaba University Nagpur India Central Institute of Business Management Research and Development Nagpur India

ISBN: (数字)9798331528713

ISBN: (纸本)9798331528720

AI being used in transportation is going to change the future of work by changing how people work together and how things are done. This Delphi study looks at how AI is changing transportation, focused on how it changes the work force and what the geopolitical effects are. This study combines ideas to shed light on how things are changing by carefully looking at the opinions of experts and predicted trends. When AI is used in transportation, big improvements are expected, such as more efficient operations, the ability to make predictions, and the ability to make decisions on its own. It is expected that these new ideas will make the supply chain more efficient, cut costs, and lower risks, making the whole system more flexible and strong. Along with these possibilities, though, there are worries about how AI will change established jobs and the need for more skills to fully use AI's potential. Key results show that experts agree on one thing: AI is the key to making all business tasks more efficient. One of the main benefits of AI is that it can automate boring chores like managing supplies, finding the best routes, and planning for future upkeep. Also, AI-powered data give you information in real time, which helps you make better decisions and adapt to changes in the market. The study finds important changes that need to happen in the workforce because of AI usage. It talks about the rise of new job categories, like AI system teachers, data scientists, and AI ethicists that need skills from a lot of different fields, like being good with technology and knowing a lot about the subject.

关键词： Ethics Technological innovation Costs Supply chains Transportation Real-time systems Stakeholders Artificial intelligence Robots programming profession

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User-Land Work Stealing Schedulers: Towards a Standard

User-Land Work Stealing Schedulers: Towards a Standard

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2nd international conference on Complex, Intelligent and Software Intensive Systems (CISIS 2008)

作者： Jorg Wagner Armin Jahanpanah Jesper Larsson Traff NEC Laboratories Europe NEC Europe Limited UK

Multicore processors are currently hitting the market at enormous speed. Multi-processing in all its variants is seen as the way into the future of computational systems and imply parallelism for future applications. The basics of software development are changing when going parallel. One key concept to ensure scalability of today's applications for the future is the idea of using work stealing scheduling systems to ensure load balancing, and re-writing existing software is necessary to exploit that style of programming. The numerous work stealing concepts however differ in form of implementation, interfaces and supported systems. Handling this diversity of systems makes the already complicated process of going parallel even worse. We present a simple but complete work stealing scheduler (TPI -^sTask Processing Interface) as an example and formulate the requirements to a basic work stealing interface as a first step to an open standard proposal.

关键词： Pediatrics Program processors programming Load management Libraries Processor scheduling Software

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Proposing University Students Learning Approach –Learning and Playing via Facebook

Proposing University Students Learning Approach –Learning a...

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2015 2nd international conference on Education,Management and Computing Technology(ICEMCT 2015)

作者： Ming-Kuei Yeh Sarah Hsueh-Jui Liu Zih-Ping Ho Dept.of Information Management "National Taipei U.Business" Taipei City Department of Applied English Kainan University Taoyuan City Business Intelligence Research Center "National Taipei U.Business" Taipei City

Game enhanced learning（GEL） or computer aids education（CAE） presupposes that game-like applications and computer-based tools enable to improve learners’ cognitive and social skills. However, there is a limited amount of relevant literature and empirical studies available to provide a better understanding of how the fuzzy mathematical model is applied in an English-as-a-foreign-language（EFL） learning context. This research is intended to propose a decision-making model on the university EFL students’ approach to learning through playing games on Facebook. This study administered an online questionnaire to the university students, and then mined their opinions, in an attempt to build a possible learning approach and analyzing model. The issue of whether CAE combining games motivates university students to learn is explored by employing the fuzzy decision-making model which was applied within this case study. The results indicated a positive relationship between learning and playing games via Facebook as university students playing games on Facebook would enhance learning the subject of English, especially in enhancing learning motivation. This research suggests that it is necessary to apply this fuzzy model in other courses in order to make comparisons. It also suggests that teachers should design simple games for their lessons to enhance their students’ learning motivation.

关键词： computer aid education CAE fuzzy decisionmaking model dynamic programming Facebook and internet game English-as-a-foreign language flipped education

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Development of Telecardiology Monitor using Internet of Things

Development of Telecardiology Monitor using Internet of Thin...

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international conference on Electronics, Communication and Aerospace Technology

作者： L. Priya S. Aarthi S. M. Preethi P. Elakiya Jothi R. Aruna M. Anitha Department of Biomedical Engineering Department of Biomedical Engineering PSG College of Technology

ISBN: (纸本)9781538609668

Electrocardiography (ECG) is the recording of the electrical activity of the heart with the help of the electrodes placed on the skin. The transmission of the ECG signal is very helpful in the field of Telemedicine. This will help the doctors to view the patient's ECG who is living in the remote region. Other applications are ambulance monitoring, Intensive Care Unit (ICU) patient monitoring, home patient monitoring, etc, where Internet of Things (IoT) plays a major role in the transmission of medical data and information. In existing wireless technology like Global System for Mobile Communication (GSM), Satellite, Bluetooth, zigbee, etc., communication of data, installation and other practical difficulties are quite complex. But in IoT even long distance communication is made that much easier when compared to other methods.

关键词： Electrocardiography Internet of Things Microcontroller unit Texas Instrument Application programming Interface

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2022 the 4th international conference on Modeling, Simulation, Optimization and Algorithm[ICMSOA 2022], 12 November, 2022

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Journal of Physics: conference Series 2023年第1期2508卷 011001页

作者： Zhao, Yichuan Shang, Yilun Xu, Jinyang Luo, Zongwei Ma, Ying Sun, Hui Lu, Peng Ma, Shouchen Liu, Bin Zhu, Quanxin Wang, Zhixiao Zhao, Yingxue Wang, Lulu De Moura Ramos, José Joaquim Dararutana, Pisutti Onat, Altan Ismail, Zul-Atfi Yenilmez, Ismail Ye, Kyaw Zaw Vladimir, Gorbunov Xue, Yu Razmiki, Goharik Petrosyan Chen, Ning Popva, Nina Doulamis, Anastasios Hu, Jie Lo, Man-Fung Metrolho, José Carlos Jiskani, Izhar Mithal Ivancu, Larisa Ma, Quanjin Chubato, Wondaferaw Yohannese Ghani, Noraida Abdul Memon, Imran Das, Pratibhamoy Banerjee, Subhabrata Wang, Haijing Zeng, Weili Georgia State University United States Northumbria University United Kingdom Shanghai Jiao Tong University China China Xiamen University of Technology China Academy of OPTO-Electronics Chinese Academy of Science China Central South University China Henan Polytechnic University China Nanjing Medical University China Hunan Normal University China Xi'an University of Technology China University of International Business and Economics China Shenzhen Technology University China Department of Computer Science University of A Corua Spain Royal Thai Army Chemical Department Thailand Eskisehir Technical University Turkey School of Environmental Engineering Universiti Malaysia Perlis Malaysia Department of Statistics Science Faculty Eskisehir Technical University Eskisehir Turkey Ministry of Defense Myanmar National Research University of Electronic Technology Russia Nanjing University of Information Science and Technology China Armenian State Pedagogical University Armenia Xian Polytechnic University China St.Petersburg Polytechnic University Russia Greece University of Massachuttes United States The Hong Kong Polytechnic University Hong Kong Polytechnic Institute of Castelo Branco Portugal China University of Mining and Technology China Politehnica University of Timisoara Romania Universiti Malaysia Pahang Malaysia Southwest JiaoTong University China Universiti Sains Malaysia Malaysia Zhejiang University China Department of Mathematics Indian Institute of Technology Patna India Department of Electronics and Communication Engineering Institute of Engineering and Management Kolkata India School of Information and Electronic Engineering Zhejiang University of Science and Technology Hangzhou China College of Civil Aviation Nanjing University of Aeronautics and Astronautics Nanjing China

ABOUT ICMSOA2022Organized by Yaseen Academy, 2022 The 2nd international conference on Modeling, Simulation, Optimization and Algorithm (ICMSOA 2022), which was planned to be held during 11-13 November, 2022 at Sanya, Hainan Province, China. Due to the travel restrictions caused by covid, the participants joined the conference online via Tencent Meeting at 12 November, 2022. The conference looks for significant contributions to related fields of Modeling, Simulation, Optimization and Algorithm. The aim of the conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the *** FOR PAPERSPlease make sure your submission is in related areas of the following general topics. The topics include, but are not limited to:Simulation modeling theory and technology, Computational modeling and simulation, System modeling and simulation, Device/VLSI modeling and simulation, Control theory and applications, Military Technology Simulation, Aerospace technology simulation, Information engineering simulation, Energy Engineering Simulation, Manufacturing Simulation, Intelligent engineering simulation, Building engineering simulation, Electromagnetic field simulation, Material engineering simulation, Visual simulation, Fluid mechanics engineering simulation, Manufacturing simulation technology, Simulation architecture, Simulation software platform and Intelligent Optimization Algorithm, Dynamic programming, Ant Colony Optimization, Genetic Algorithm, Simulated Annealing Algorithm, Tabu Search Algorithm, Ant Colony System Algorithm, Hybrid Optimization Algorithm in other related *** conference was begun at 10:00am, ended at 17:30am, 12 November, 2022. There were 77 participants in total, 2 keynote speakers and 17 invited oral speakers, Assoc. Prof. Jinyang Xu from Shanghai Jiaotong Univeristy in China and Dr. Victor Koledov from Innowledgement GmbH in Germany delivered their key

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