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44th International Conference on Information Systems: Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies, ICIS 2023

作者： Chen, Tianwa Demartini, Gianluca Indulska, Marta Sadiq, Shazia School of Electrical Engineering and Computer Science The University of Queensland Brisbane Australia Business School The University of Queensland Brisbane Australia

ISBN: (纸本)9781713893622

The rise of data re-purposing has resulted in an unprecedented opportunity to create new value from existing data assets. Unlike previous approaches that relied on well-understood data quality requirements, this open-ended setting demands a discovery-oriented approach. Despite a growing market of tools that assist with data exploration and profiling, data quality discovery continues to drain the time of data workers due to its cognitively demanding and contextual nature. Accordingly, we study data quality discovery through purpose-built experimental platforms that mimic typical data exploration platforms, and explore implicit sensemaking behaviours of data workers when required to write code or use available functions, by exploiting eye-tracking and log data. Our analysis of visual scanning and attention patterns reveals various sensemaking loops amongst data workers with different performance levels in different settings. Our findings provide insights for researchers and tool designers to consider how to support different data workers in data quality discovery. Copyright © 2023 Tianwa Chen, Gianluca Demartini, Marta Indulska, Shazia Sadiq.

关键词： Eye tracking

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Single-And Dual-Beam Pattern Reconfigurable Patch Antenna With Dual Switchable CP for Internet of Vehicles

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IEEE Internet of Things Journal 2025年第12期12卷 21904-21914页

作者： Wang, Shi-Tong Zhu, Lei University of Macau Faculty of Science and Technology Department of Electrical and Computer Engineering China

In this article, a novel method is proposed to facilitate the design of compact, low-profile, pattern reconfigurable antennas with fixed or switchable circular polarization (CP) for Internet of Vehicles (IoV) applications. The proposed method eliminates the need for a complex beamforming or phase-tuning network by innovatively exploiting four resonant modes of a square patch antenna. Specifically, the TM01 and TM10 modes are utilized to accomplish the single-beam CP pattern, while, the dualbeam CP pattern is achieved by combining the TM11 and TM02 modes. An electric current model is developed to investigate the far-field radiation, revealing that the radiation pattern of TM11 mode can be effectively reshaped from quad-beam to dual-beam by manipulating the surface current distribution. The complete design method is verified by an antenna prototype working at 3.5 GHz, which consists of a radiative patch, a pair of open-ended stubs, a pair of slots, and four equivalent switchable pins. Different from the conventional pin-loading method, the proposed equivalent switchable pins attain excellent CP performance during switching by compensating for the detrimental electric coupling. The prototype is fabricated and measured. Its radiation can be switched between single-beam (7.8 dBic) and dual-beam CP pattern (3.5 dBic), exhibiting an overlapped CP coverage from -123° to 73°. Furthermore, another prototype with the extended switchable CP capability is realized. Without increasing the number of p-i-n diodes, this prototype achieves four operating states with independent pattern (single-and dual-beam) and polarization (right-and left-handed CP) reconfiguration. The merits of compact size, low profile, and flexible reconfigurability make the proposed method and design cases excellent candidates for IoV applications and intelligent transportation systems (ITSs). © 2014 IEEE.

关键词： Circular polarization

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A Blueprint for Adopting Agility in Teaching, Research and Service in an engineering Department 53

A Blueprint for Adopting Agility in Teaching, Research and S...

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53rd IEEE ASEE Frontiers in Education International Conference, FIE 2023

作者： Ochoa, Omar Towhidnejad, Massood Pembridge, James J. Babiceanu, Radu F. Embry-Riddle Aeronautical University Department of Electrical Engineering and Computer Science Daytona BeachFL32114 United States

ISBN: (纸本)9798350336429

This innovate-practice, work in progress paper presents a blueprint on the adoption of agile process in an academic engineering department. The blueprint offered in this paper can be used by engineering departments to introduce an agile approach in their teaching, research, and service activities. This paper provides a framework for using Scrum as it has been implemented in the EECS department at Embry-Riddle Aeronautical University. For each of the common facets of academia, i.e., teaching, research, and service, we report on our experiences, lessons learned, and proposed approaches in adopting Scrum. Furthermore, we highlight the value added by integrating this Scrum approach, such as the increased marketability of students with agile experience, a greater accountability from students and faculty, and/or building a much stronger communities between faculty, and between faculty and students. We also discuss possible obstacles and required mitigations to facilitate adoption. Results of adopting agility in all three facets of the academic department will be reported, including how it benefits computing and engineering education and the academic department. © 2023 IEEE.

关键词： Agile Research Agile Service Agile Teaching Serum in Academia

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IoT Based Battery Monitoring System for Electric Vehicle using ESP32 2

IoT Based Battery Monitoring System for Electric Vehicle usi...

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2nd International Conference on Smart Technologies for Smart Nation, SmartTechCon 2023

作者： Usha Rani, R. Divya, G. Lakshmi Swarupa, M. Navaneetha, Kandle Department of Computer Science Engineering CVR College of Engineering Ibrahimpatnam Hyderabad India Department of Electrical and Electronics Engineering CVR College of Engineering Ibrahimpatnam Hyderabad India

ISBN: (纸本)9798350305418

Since the system is powered by the battery, it is the most vital part of any gadget. Incorrect or excessive charging or draining of the battery might damage the battery and lead to system failure, hence it is important to monitor the battery's voltage level. By far most of current electrical and electronic gear utilize a committed instrument called a battery the board framework (BMS). The battery the board framework (BMS) screens and controls the battery's fundamental capabilities such voltage, current, temperature, and auto-off. The appropriate and get treatment of lithium-particle or lithium-polymer batteries is guaranteed along these lines. More established BMS just observed the battery and notified the user when there was a problem. Thanks to IoT, however, we can now provide instantaneous alerts to far-flung targets. They may check the remaining juice from any location using their phones or computers. The goal is to demonstrate the viability of the idea's basic premise. The hardware for the battery monitoring device is developed as part of the system development. In this study, the battery status data is sent to the Arduino IoT cloud using an IoT-based battery monitoring system, node, and MCU using an ESP32 chip. Whether the battery is being charged or discharged, the Arduino IoT cloud will display the voltage and percentage of charge remaining. © 2023 IEEE.

关键词： Battery management systems (BMS) Battery Voltage Electric Vehicles Internet of Things Lithium-ion Batteries SoC measurement

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Deployment Strategy for Low-Power-Consumption Roadside Units in 5G Vehicular Networking 16

Deployment Strategy for Low-Power-Consumption Roadside Units...

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16th International Conference on Communication Software and Networks, ICCSN 2024

作者： Wang, Shuai Yang, Xinjie Ningbo University Faculty of Electrical Engineering and Computer Science Ningbo China Ningbo Arrowdeep Internet Technology Co. Ltd. Ningbo China

ISBN: (纸本)9798331506322

The low-power-consumption (LPC) operation of Roadside Units (RSUs) is of paramount importance in the 5G Vehicle-to-Infrastructure (V2I) communications within two-dimensional (2-D) Internet of Vehicles (IoV) networks. Compared with all RSUs operating at a fixed power, implementation of dynamic power transmission control and operation mode conversion of RSUs based on the actual distribution of vehicles is undoubtedly an intuitive and ideal power optimization solution. To achieve LPC RSU operations, in this paper, a novel concept of candidate communication service area (CCSA) is introduced and a power optimization strategy is established. The main idea of this strategy is to curtail the redundant coverage areas of RSUs while maintaining communications with the vehicles within the system. An enhanced Genetic algorithm (eGA) is proposed to implement this deployment strategy. Extensive simulation results show that the proposed algorithm effectively reduces the aggregate power consumption of RSUs while maintaining robust communication links between RSUs and vehicles. © 2024 IEEE.

关键词： 5G mobile communication systems

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Optimizing Real Estate Prediction - A Comparative Analysis of Ensemble and Regression Models 4th

Optimizing Real Estate Prediction - A Comparative Analysis o...

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4th EAI International Conference on Cognitive Computing and Cyber Physical Systems, IC4S 2023

作者： Prasad, Runkana Durga Varma, Vemulamanda Jaswanth Jyothi, Uppalapati Padma Shankar, Sarakanam Sai Deenakonda, Mamatha Narasimharao, Kandula Department of Computer Science and Engineering Vishnu Institute of Technology Andhra Pradesh Bhimavaram India Department of Electrical and Electronics Engineering Vishnu Institute of Technology Andhra Pradesh Bhimavaram India

ISBN: (纸本)9783031488870

Valuation is a fundamental aspect of real estate for businesses. Land and property serve as factors of production, and their value is derived from the use to which they are put. This value is influenced by the demand and supply for the product or service produced on the property. Valuation involves determining the specific amount for which a property would transact on a given date. Accurate prediction of real estate prices is crucial for investors, house owners and industry professionals. In this article, analysis of USA real estate prediction using regression and ensemble models was presented, also evaluating the best model out of all the models that have been applied. The objective of this article is to provide accurate predictions for the real estate market, by making use of Multi-Variate Regression, Random Forest Regressor, Decision Tree Regressor, XGB Regressor and CatBoost Regressor. This analysis offers valuable insights for making wise and right choices in the real estate market. © 2024, ICST Institute for computer sciences, Social Informatics and Telecommunications engineering.

关键词： Forecasting

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Human Emotions Classification Using EEG via Audiovisual Stimuli and AI

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computers, Materials & Continua 2022年第12期73卷 5075-5089页

作者： Abdullah A Asiri Akhtar Badshah Fazal Muhammad Hassan A Alshamrani Khalil Ullah Khalaf A Alshamrani Samar Alqhtani Muhammad Irfan Hanan Talal Halawani Khlood M Mehdar Radiological Sciences Department College of Applied Medical SciencesNajran UniversityNajranSaudi Arabia Faculty of Computer Science and Engineering GIK Institute of Engineering Sciences and TechnologyTopi23460Pakistan Department of Electrical Engineering University of Engineering and TechnologyMardan23200Pakistan Department of Software Engineering University of MalakandDir LowerPakistan Department of Computer Science and Information Systems College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia Electrical Engineering Department College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia Computer Science Department College of Computer Science and Information SystemsNajran UniversityNajranSaudi Arabia Anatomy Department Medicine CollegeNajran UniversityNajranSaudi Arabia

Electroencephalogram(EEG)is a medical imaging technology that can measure the electrical activity of the scalp produced by the brain,measured and recorded chronologically the surface of the scalp from the *** recorded signals from the brain are rich with useful *** inference of this useful information is a challenging *** paper aims to process the EEG signals for the recognition of human emotions specifically happiness,anger,fear,sadness,and surprise in response to audiovisual *** EEG signals are recorded by placing neurosky mindwave headset on the subject’s scalp,in response to audiovisual stimuli for the mentioned *** a bandpass filter with a bandwidth of 1-100 Hz,recorded raw EEG signals are *** preprocessed signals then further analyzed and twelve selected features in different domains are *** Random forest(RF)and multilayer perceptron(MLP)algorithms are then used for the classification of the emotions through extracted *** proposed audiovisual stimuli based EEG emotion classification system shows an average classification accuracy of 80%and 88%usingMLP and RF classifiers respectively on hybrid features for experimental signals of different *** proposed model outperforms in terms of cost and accuracy.

关键词： Electroencephalography emotion classification signal processing multilayer perceptron random forest

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ECO-Guard: An Integrated AI Sensor System for Monitoring Wildlife and Sustainable Forest Management 8th

ECO-Guard: An Integrated AI Sensor System for Monitoring Wil...

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8th International Conference on Information and Communication Technology for Competitive Strategies, ICTCS 2023

作者： Nikhilesh Krishna, Ch. Rauniyar, Avishek Kireeti Sai Bharadwaj, N. Raj, Sujay Bharath Valsan, Vipina Suresh, Kavya Ravikumar Pandi, V. Sathyan, Soumya Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Amritapuri India Department of Electrical and Electronics Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Amritapuri India

ISBN: (纸本)9789819994885

In India, 12% of wild animals are threatened with extinction, and human activity threatens more than 80% of East and Southeast Asia's wetlands. Every year, an estimated 400 people are killed by wildlife in India, with Maharashtra alone seeing 88 human deaths and 9258 cattle killings by tigers in 2020. The ECO-Guard is an intelligent device which uses the You Only Look Once (YOLO) model and various sensors and machine learning models with algorithms that support and promote forest monitoring and tourist guidance in forest areas addressing Sustainable Development Goal (SDG) 12 (Life on Land). The paper presents a linear chain-like mesh of devices speeded across bio-area which are used in correlation for intended surveillance. Each device can multimodule apps and tally their sightings automatically to analyze coherence of the situation with the forest rangers, organizations, and figures. It catches from the information, the ill substitutes like human spotting with beasts. It suggests that the advice can be further put into practice by constantly monitoring any closeness of alternatives that match to create an unfavorable combination. Also having to help detect many forest crimes, some including illegal logging, preventing, and deforestation on a large scale. This paper highlights a novel ECO-Guard, an intelligent and autonomous monitoring system which includes artificial intelligence (AI)-enhanced strategies and algorithms to conserve wildlife and forest ecosystems by integrating various hardware and software components. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Deforestation

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A Comprehensive Study of Artificial Intelligence and Cybersecurity on Bitcoin, Crypto Currency and Banking System

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Annals of Data science 2024年第1期11卷 103-135页

作者： Choithani, Tamanna Chowdhury, Asmita Patel, Shriya Patel, Poojan Patel, Daxal Shah, Manan Department of Computer Science and Engineering Indus University Gujarat Ahmedabad India Department of Electrical Engineering Nirma University Gujarat Ahmedabad India Department of Electronics and Communication Engineering Nirma University Gujarat Ahmedabad India Department of Chemical Engineering School of Technology Pandit Deendayal Energy University Gujarat Gandhinagar382426 India

In recent years cryptocurrencies are emerging as a prime digital currency as an important asset and financial system is also emerging as an important aspect. To reduce the risk of investment and to predict price, trend, portfolio construction, and fraud detection some Artificial Intelligence techniques are required. The Paper discusses recent research in the field of AI techniques for cryptocurrency and Bitcoin which is the most popular cryptocurrency. AI and ML techniques such as SVM, ANN, LSTM, GRU, and much other related research work with cryptocurrency and Bitcoin have been reviewed and most relevant studies are discussed in the paper. Also highlighted some possible research opportunities and areas for better efficiency of the results. Recently in the past few years, artificial intelligence (AI) and cybersecurity have advanced expeditiously. Its implementation has been extensively useful in finance as well as has a crucial impact on markets, institutions, and legislation. It is making the world a better place. AI is responsible for the simulation of machines that are replicas of human beings and are intelligent enough. AI in finance is changing the way we communicate with money. It helps the financial industry streamline and optimize processes from credit judgments to quantitative analysis marketing and economic risk management. The main goal of this research has been investigating certain impacts of artificial intelligence in this contemporary world. It's centered on the appeal of artificial intelligence, confrontation, chances, and its influence on professions and careers. The research paper uses AI to enable banks to generate financial resources and to provide valuable customer services. The application of the growing Indian banking sector is part of everyday life made up of several banks like RBI, SBI, HDFC, etc. and these banks have digitally implemented using chat-bots that have brought benefits to the customers. © The Author(s), under exclusive licence t

关键词： Risk assessment

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RIS-Assisted ISAC: Precoding and Phase-Shift Optimization for Mono-Static Target Detection

RIS-Assisted ISAC: Precoding and Phase-Shift Optimization fo...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Demir, Özlem Tuǧfe Björnson, Emil Tobb University of Economics and Technology Department of Electrical-Electronics Engineering Ankara Turkey Kth Royal Institute of Technology Department of Computer Science Stockholm Sweden

ISBN: (纸本)9798350351255

The reconfigurable intelligent surface (RIS) technology emerges as a highly useful component of the rapidly evolving integrated sensing and communications paradigm, primarily owing to its remarkable signal-to-noise ratio enhancement capabilities. In this paper, our focus is on mono-static target detection while considering the communication requirement of a user equipment. Both sensing and communication benefit from the presence of an RIS, which makes the channels richer and stronger. Diverging from prior research, we comprehensively examine three target echo paths: the direct (static) channel path, the path via the RIS, and a combination of these, each characterized by distinct radar cross sections (RCSs). We take both the line-of-sight (LOS) and the non-line-of-sight (NLOS) paths into account under a clutter for which the distribution is not known, but the low-rank subspace it resides. We derive the generalized likelihood ratio test (GLRT) detector and introduce a novel approach for jointly optimizing the configuration of RIS phase-shifts and precoding. Our simulation results underscore the paramount importance of this combined design in terms of enhancing detection probability. Moreover, it becomes evident that the derived clutter-aware target detection significantly enhances detection performance, especially when the clutter is strong. © 2024 IEEE.

关键词： Radar clutter

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