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arXiv 2024年

作者： Wen, Jinbo Kang, Jiawen Xiong, Zehui Du, Hongyang Yang, Zhaohui Niyato, Dusit Shen, Meng Jiao, Yutao Zhang, Yang The College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics China The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The Department of Electrical and Electronic Engineering University of Hong Kong Hong Kong The College of Information Science and Electronic Engineering Zhejiang University China The School of Computer Science and Engineering Nanyang Technological University Singapore The School of Cyberspace Science and Technology Beijing Institute of Technology China The College of Communications Engineering Army Engineering University of PLA China

Web 3.0 is regarded as a revolutionary paradigm that enables users to securely manage data without a centralized authority. Blockchains, which enable data to be managed in a decentralized and transparent manner, are key technologies for achieving Web 3.0 goals. However, Web 3.0 based on blockchains is still in its infancy, such as ensuring block freshness and optimizing block propagation for improving blockchain performance. In this paper, we develop a freshness-aware block propagation optimization framework for Web 3.0. We first propose a novel metric called Age of Block Information (AoBI) based on the concept of age of information to quantify block freshness. AoBI measures the time elapsed from the freshest transaction generation to the completion of block consensus. To make block propagation optimization tractable, we classify miners into five different states and propose a block propagation model for public blockchains inspired by epidemic models. Moreover, considering that the miners are bounded rational, we propose an incentive mechanism based on the evolutionary game for block propagation to improve block propagation efficiency. Numerical results demonstrate that compared with other block propagation mechanisms in public blockchains, the proposed scheme has a higher block forwarding probability, which improves block propagation efficiency and decreases the minimum value of average AoBI. Copyright © 2024, The Authors. All rights reserved.

关键词： Blockchain

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Minimizing Classification Errors in Imbalanced Dataset Using Means of Sampling

Minimizing Classification Errors in Imbalanced Dataset Using...

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7th International Conference on Advances in Visual informatics, IVIC 2021

作者： Khan, Ijaz Ahmad, Abdul Rahim Jabeur, Nafaa Mahdi, Mohammed Najah College of Graduate Studies Universiti Tenaga Nasional Kajang Malaysia Information Technology Department Buraimi University College Al-Buraimi Oman College of Computing and Informatics Universiti Tenaga Nasional Kajang Malaysia Computer Science Department German University of Technology Muscat Oman Institute of Informatics and Computing in Energy Universiti Tenaga Nasional Kajang Malaysia

ISBN: (纸本)9783030902346

Classification, a significant application of machine learning, labels each instance of the dataset into one of the predefined classes. Problems occur when the number of instances in the classes is not uniform. The exceptional lyuneven class distribution gives rise to class imbalancing issues which tend to demote the overall performance of the classifier. A set of data-level algorithms are available which are applied to adjust the class distribution. The class imbalancing emerges frequently in datasets from educational domains where the number of students with unsatisfactory performance general appears in low number comparing to the students with satisfactory outcomes. This paper applies a set of data-level sampling algorithms over a dataset taken from an educational domain. It underlines the consequences rising from classification with imbalanced dataset. This research confirms that a classification model achieving higher accuracy may not appear effective in correct identification of instances in minority class. Classification with an imbalance dataset may produce low recall, precision and F-Measure for classes with lower number of instances. The performance of classification model improves with application of data level algorithm. However, it highlights the supremacy of oversampling algorithm over undersampling algorithms. © 2021, Springer Nature Switzerland AG.

关键词： Students

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Low-cost IoT-Based sensors dashboard for monitoring the state of health of mobile harbor cranes: Hardware and software description

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Heliyon 2024年第22期10卷 e40239页

作者： Awad, A.H. Alsabaan, Maazen Ibrahem, Mohamed I. Saraya, M.S. Elksasy, M.S.M. Ali-Eldin, Amr M.T. Abdelsalam, Mohamed M. Computers Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura 35516 Egypt Department of Computer Engineering College of Computer and Information Sciences King Saud University Riyadh 11543 Saudi Arabia School of Computer and Cyber Sciences Augusta University Augusta 30912 GA United States Faculty of Engineering Delta University for Science and Technology Gamasa 7731168 Egypt

A cost-effective IoT-based real-time data acquisition and analysis hardware system was developed to enhance the performance of the mobile harbor cranes using a combination of a cost-effective quality control monitoring sensor dashboard (proximity sensors, angle position sensor, weight sensor, vibration sensor, and wind sensor), embedded microcontroller (Arduino), and embedded computer (Raspberry Pi). Hardware was operated using a specially developed novel Quality Control and Data Acquisition Multiprocessing software (QC-DAS). The QC-DAS can automatically collect and save real-time data of the sensors in a large-capacity SD card, monitor the state of health of the hardware, and transmit the real-time data of the sensors and the working state of the crane to an IoT server. The novelty of the QC-DAS design is that each function is encapsulated in a predefined module that is “immersed” in a message transmission medium. Modules interact by sending and receiving various signals through this medium. Modularity makes system design simpler, faster, and flexible. Thanks to modularity, users may incorporate their data processing modules when new sensors are added to match the system's needs. Thanks to modularity the DC-DAS can operate quality control hardware for any mobile cranes. There are several constraints in the quality control data acquisition system used by the Damietta Port Authority in Damietta, Egypt, SESCO TRANS company which cause the loading and unloading process to be slowed down. As a result, the SESCO TRANS company upgraded its quality control data acquisition system using the QC-DAS. The hardware was deployed for six months, during which the collected data was used to verify the crane's performance. The vibration produced by the slewing of the crane was monitored and compared with the bearing fault frequency limits, during the operation the wind speed was monitored and compared with the critical wind speed to stop the crane operation automatically, and the pa

关键词： IoT Low-cost Mobile harbor Crane Raspberry pi

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High isolation and gain metamaterial based MIMO antenna for 5G millimiter wave applications

High isolation and gain metamaterial based MIMO antenna for ...

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Circuit, systems and Communication (ICCSC), International Conference on

作者： Ouafae Elalaouy Bilal Aghoutane Mohammed El Ghzaoui Sudipta Das Jaouad Foshi Hanan El Faylali Faculty of Sciences and techniques Errachidia University of Moulay Ismail Errachidia Morocco Department of Computer Science Informatics Systems and Optimization Laboratory Faculty of Sciences IbnTofail University Kenitra Morroco Faculty of Sciences Dhar El Mahraz Sidi Mohamed Ben Abdellah University Fes Morocco Department of Electronics and Communication Engineering IMPS College of Engineering and Technology Malda W.B India

ISBN: (数字)9798350365306

ISBN: (纸本)9798350365313

In the contemporary era, harnessing millimeter-wave frequencies emerges as a compelling strategy to fulfill the swift data transfer requirements for $\mathbf{5 G}$ communications. Consequently, this study involves designing a metamaterial-based multiple-input multiple-output (MIMO) antenna with a focus on achieving high isolation and gain within the millimeter-wave spectrum. The suggested MIMO is printed on a Rogers RT5800 measuring $18 \times 38 \times 0.8 \mathrm{~mm}^{3}$. The single antenna element demonstrates a broad frequency coverage from 27.2 to $\mathbf{2 8. 7 2} \mathbf{G H z}$. To elevate the antenna’s effectiveness, a two-port MIMO configuration is implemented by introducing a second antenna element parallel to benchmark antenna. However, the isolation between the two elements is deemed satisfactory. To address this, a $4 \times 1$ metamaterial unit cell is introduced, significantly enhancing isolation from 31 dB to 39 dB at 28 GHz. Furthermore, it improves the gain by 0.5 dBi at 28 GHz, elevating it from 8.5 to 9 dBi. The collective features of the suggested two ports MIMO antenna, encompassing its compactness and simplicity, position it as an excellent option for upcoming portable and shrink devices in Internet of Things uses.

关键词： Performance evaluation Mutual coupling Millimeter wave devices Millimeter wave measurements Metamaterials Millimeter wave integrated circuits Broadband antennas

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Improving Smart Healthcare Safety and Security Using Kinect 1st

Improving Smart Healthcare Safety and Security Using Kinect

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1st International Conference on Cybersecurity in Emerging Digital Era, ICCEDE 2020

作者： Singh, Vijai Saxena, Neetesh Pathak, Drashti Saini, Garima Bhatnagar, Divya Department of CSE G.L. Bajaj Institute of Technology and Management Gr Noida India School of Computer Science and Informatics Cardiff University Wales United Kingdom Department of CSE IMS Engineering College Ghaziabad India

ISBN: (纸本)9783030848415

Modern healthcare operating rooms are cumbersome, especially in the current pandemic of Coronavirus (COVID-19) to manage the safety and security of the patients and the staff. Conditions in a modern operating room are like, a patient’s medical diagnosis or x-ray or the MRI images are the vital resources to be considered. In general, the doctors are impelled to scrub out their hands every time they scroll through or examine the images in mid-operation. To avoid departing the operating table, several doctors put their faith in assistants or nurses and ask to examine the system that can be clumsy and disappointing and can rise the gathering in the room itself. To overcome this problem and emphasizing the use of the touchless smart healthcare system in medical diagnosis we have developed an application for the same. We propose and demonstrate a gesture and speech-based system to help staff to deal with such critical conditions. The proposed system is composed of two main parts: the healthcare operating software and sensor Microsoft Kinect. Test results conclude the efficiency of the viewing system in terms of time complexity, and the value and the safety of the recording system have increased. © 2021, Springer Nature Switzerland AG.

关键词： Diagnosis

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Active RIS-Aided Massive MIMO With Imperfect CSI and Phase Noise

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IEEE Transactions on Wireless Communications 2025年

作者： Peng, Zhangjie Zhu, Jianchen Pan, Cunhua Zhang, Zaichen Da Costa, Daniel Benevides Elkashlan, Maged Karagiannidis, George K. Shanghai Normal University College of Information Mechanical and Electrical Engineering Shanghai200234 China Southeast University National Mobile Communications Research Laboratory Nanjing210096 China Interdisciplinary Research Center for Communication Systems and Sensing Department of Electrical Engineering Dhahran31261 Saudi Arabia Queen Mary University of London School of Electronic Engineering and Computer Science LondonE1 4NS United Kingdom Aristotle University of Thessaloniki Department of Electrical and Computer Engineering Greece Artificial Intelligence and Cyber Systems Research Center Lebanon

As a recently proposed reconfigurable intelligent surface (RIS) architecture, active RIS has drawn considerable interest. The important feature of the active RIS is its ability to strengthen the impinging signals to mitigate the multiplicative fading effect inherent in passive RIS-aided systems. Herein, we explore the performance of an active RIS-aided uplink multi-user massive multiple-input multiple-output (MIMO) system, considering the phase noise at the RIS. Furthermore, a two-timescale scheme is utilized, where the base station (BS) beamforming is designed based on the instantaneous aggregated channel state information (CSI), while the statistical CSI is used for designing the phase shifts of the active RIS. In addition, the linear minimum mean square error (LMMSE) estimator is adopted to estimate the aggregated channel, which combines both the cascaded and direct channels. According to the estimated channel, a closedform expression for the lower bound of achievable rate is derived. Based on the theoretical expressions, the power scaling laws for the considered system are also investigated. Specifically, when each user’s transmit power is proportionally reduced by the quantity of BS antennas M or RIS elements N, we find that the amplified thermal noise causes the lower bound of the achievable rate to approach zero as M or N tends to infinity. Moreover, an optimization approach based on a genetic algorithm (GA) is introduced to obtain the optimal phase shifts for maximizing the achievable rate. Numerical results reveal that the active RIS can greatly enhance the performance of the massive MIMO system compared to its passive counterpart. © 2002-2012 IEEE.

关键词： Genetic algorithms

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N-Gram-Based Machine Learning Approach for Bot or Human Detection from Text Messages 22

N-Gram-Based Machine Learning Approach for Bot or Human Dete...

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6th International Conference on Intelligent systems, Metaheuristics and Swarm Intelligence, ISMSI 2022

作者： Kavadi, Durga Prasad Sanaboina, Chandra Sekhar Patan, Rizwan Gandomi, Amir Department Of Information Technology B V Raju Institute Of Technology Narsapur Telangana India Department Of Computer Science And Engineering University College Of Engineering Kakinada Jawaharlal Nehru Technological University Kakinada India Decentralized Science Lab College Of Computing And Software Engineering Kennesaw State University MariettaGA30060 United States Faculty Of Engineering And Information Systems University Of Technology Sydney UltimoNSW Australia

ISBN: (纸本)9781450396288

Social bots are computer programs created for automating general human activities like the generation of messages. The rise of bots in social network platforms has led to malicious activities such as content pollution like spammers or malware dissemination of misinformation. Most of the researchers focused on detecting bot accounts in social media platforms to avoid the damages done to the opinions of users. In this work, n-gram based approach is proposed for a bot or human detection. The content-based features of character n-grams and word n-grams are used. The character and word n-grams are successfully proved in various authorship analysis tasks to improve accuracy. A huge number of n-grams is identified after applying different pre-processing techniques. The high dimensionality of features is reduced by using a feature selection technique of the Relevant Discrimination Criterion. The text is represented as vectors by using a reduced set of features. Different term weight measures are used in the experiment to compute the weight of n-grams features in the document vector representation. Two classification algorithms, Support Vector Machine, and Random Forest are used to train the model using document vectors. The proposed approach was applied to the dataset provided in PAN 2019 competition bot detection task. The Random Forest classifier obtained the best accuracy of 0.9456 for bot/human detection. © 2022 ACM.

关键词： Feature Selection

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The Application of Effective Machine Learning Tools in Digital Marketing for Enhancing Brand Presence and Image Among the Fast-Moving Consumer Goods in the Developing Countries 2

The Application of Effective Machine Learning Tools in Digit...

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2nd International Conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2022

作者： Nirmal, Ekanath Sitaram Narang, Pravin Rajeswari, T.S. Usman, Mohammed Subha, B. Jadhav, Vandana Sandeep Arts Commerce and Satral College Savitribai Phule Pune University Department of Political Science Pune India Dr v N Bedekar Institute of Management Studies Department of Management India Koneru Lakshmaiah Education Foundation Department of English AP Vaddeswaram India College of Economics Management and Information Systems University of Nizwau Department of Management Oman Kristu Jayanti College Department of Management Bengaluru India School of Computer Sciences and Engineering Sandip University Nashik India

ISBN: (纸本)9781665437899

By using updated information techniques to digital marketing activities, increasing technological progress generates competitive edge over its rivals. By extracting insights from massive amounts of data obtained, machine learning (ML) can forecast future trends and assist decision-making. This feature has a significant impact on and accelerates an organisational future decision-making process. Machine learning regarding digital clients helps understand him properly by categorising the vast cache of data generated every day into many sectors and analysing it to develop patterns. There is no apparent boundary between digital and non-digital technology. Digital technology has an impact on human behaviour. Image processing and machine learning are widely employed to change a company's operations. Both input and output have an impact on the machine's learning abilities, which are constantly improving. The research given here relies on three diverse groups' decision and implementation of machine learning-driven analytical tools: 'marketing agencies', 'media businesses', and 'advertisers'. This research paper has considered method such as secondary qualitative method to collect both statistical and evidence-based information. © 2022 IEEE.

关键词： Decision making

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Thermo-mechanical energy storage technologies:Innovations,challenges and future directions

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能源前沿（英文） 2025年第2期19卷 115-116页

作者： Yao Zhao Mingjia Li Kai Wang Adriano Sciacovelli Chris Qin Steven Lecompte André D.Thess College of Smart Energy Shanghai Jiao Tong UniversityShanghai 200240China Shanghai Non-carbon Energy Conversion and Utilization Institute Shanghai Jiao Tong UniversityShanghai 200240China School of Mechanical Engineering Beijing Institute of TechnologyBeijing 100081China Institute of Refrigeration and Cryogenics Zhejiang UniversityHangzhou 310027China Key Laboratory of Refrigeration and Cryogenic Technology of Zhejiang Province Zhejiang UniversityHangzhou 310027China Department of Civil and Mechanical Engineering Technical University of DenmarkKongens Lyngby 2800Denmark School of Engineering and Computer Science Washington State UniversityVancouverWA 98686USA Department of Electromechanical Systems and Metal EngineeringGhent UniversityGhent 9000Belgium Institute of Engineering Thermodynamics German Aerospace Center(DLR)Stuttgart 70569Germany University of Stuttgart Stuttgart 70569Germany

Thermo-mechanical energy storage(TMES)technologies are increasingly recognized as essential solutions for enhancing the efficiency and stability of energy systems,particularly in the integration of renewable energy *** technologies leverage the conversion between thermal,electrical and mechanical energy to store and release energy,providing an effective tool to address the intermittency and variability of renewable sources such as wind and *** editorial explores the fundamental principles,innovations,challenges,and future research directions of TMES technologies,with a focus on developments in compressed-air energy storage(CAES),liquid-air energy storage(LAES),Carnot battery/pumped-thermal energy storage(PTES),and carbon dioxide energy storage(CDES).

关键词： technologies future storage energy challenges directions innovations mechanical thermo

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Navigating Real-World Challenges: A Quadruped Robot Guiding System for Visually Impaired People in Diverse Environments 24

Navigating Real-World Challenges: A Quadruped Robot Guiding ...

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Proceedings of the CHI Conference on Human Factors in Computing systems

作者： Shaojun Cai Ashwin Ram Zhengtai Gou Mohd Alqama Wasim Shaikh Yu-An Chen Yingjia Wan Kotaro Hara Shengdong Zhao David Hsu Computer Science National University of Singapore Singapore NUS-HCI Lab Department of Computer Science National University of Singapore Singapore Xinya College Tsinghua University China Mechanical Engineering Veermata Jijabai Technological Institute India Yale-NUS College Singapore Institute of Psychology Chinese Academy of Sciences China School of Computing and Information Systems Singapore Management University Singapore NUS-HCI Lab National University of Singapore Singapore

ISBN: (纸本)9798400703300

Blind and Visually Impaired (BVI) people find challenges in navigating unfamiliar environments, even using assistive tools such as white canes or smart devices. Increasingly affordable quadruped robots offer us opportunities to design autonomous guides that could improve how BVI people find ways around unfamiliar environments and maneuver therein. In this work, we designed RDog, a quadruped robot guiding system that supports BVI individuals’ navigation and obstacle avoidance in indoor and outdoor environments. RDog combines an advanced mapping and navigation system to guide users with force feedback and preemptive voice feedback. Using this robot as an evaluation apparatus, we conducted experiments to investigate the difference in BVI people’s ambulatory behaviors using a white cane, a smart cane, and RDog. Results illustrated the benefits of RDog-based ambulation, including faster and smoother navigation with fewer collisions and limitations, and reduced cognitive load. We discuss the implications of our work for multi-terrain assistive guidance systems.

关键词： assistive technology navigation orientation and mobility robot guide dog visual impairment

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