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32nd International Symposium on Algorithms and Computation, ISAAC 2021

作者： Nilsson, Bengt J. Orden, David Palios, Leonidas Seara, Carlos Żyliński, Pawel Department of Computer Science and Media Technology Malmö University Sweden Physics and Mathematics Department Universidad Alcalá Spain Department of Computer Science and Engineering University of Ioannina Greece Departament of Mathematics Universitat Politècnica de Catalunya Barcelona Spain Institute of Informatics University of Gdańsk Poland

ISBN: (纸本)9783959772143

Given a set S of regions with piece-wise linear boundary and a positive angle α ◦, we consider the problem of computing the locations and orientations of the minimum number of α-floodlights positioned at points in S which suffice to illuminate the entire x-axis. We show that the problem can be solved in O(n log n) time and O(n) space, where n is the number of vertices of the set S. © Bengt J. Nilsson, David Orden, Leonidas Palios, Carlos Seara, and Pawel Żyliński.

关键词： Floods

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Federated Learning for Privacy-Preserving Healthcare Data Analysis in the Age of Cybersecurity Threats 1

Federated Learning for Privacy-Preserving Healthcare Data An...

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1st International Conference on Artificial Intelligence for Innovations in Healthcare Industries, ICAIIHI 2023

作者： Sravan, P. Saranya, S. Deepika, N.M. Nijhawan, Ginni Alawadi, Ahmed Hussien M.v, Suresh Kumar School of Cs & Ai Sr University Telanagan Warangal India Dr. N.G.P. Institute of Technology Department of Computer Science and Engineering Coimbatore India Institute of Aeronautical Engineering Dundigal Hyderabad India Lovely Professional University Phagwara India The Islamic University Najaf Iraq Research Scholar College of Law Koneru Lakshmaiah Education Foundation Green Fields Andhra Pradesh Vaddeswaram Guntur522302 India

ISBN: (纸本)9798350330915

This examination explores joined picking up gathering appraisals, unequivocally United Averaging (FedAvg), Weighted Consolidated Averaging (FedAvg-W), Bound together Learning with Adaptable Learning Rate (FedAdapt), and Secure Combination for Brought Learning (SecAgg), inside the space of assertion saving clinical benefits data assessment. The reason for the organized assessments was to assess their performance in terms of accuracy, evidence coverage and communication speed. This article provides a comparative evaluation to help practitioners select the most appropriate algorithm for clinical reasoning applications. The results show that FedAvg-W achieves much higher accuracy than other algorithms especially when used in locations with varying data attributes implying that it can adapt to the changes. In relation to this, a method called FedAdapt mixes quickly while maintaining high accuracy by way of dynamically changing learning rate limits with respect to particular instances of distribution information. A secure aggregation framework based on homomorphic encryption guarantees exact compliance. The review provides subtle experiences into space-related works, such as health informatics and federated learning. On one hand, SecAgg fulfills a basic requirement for ensuring and preserving medical benefits data while on the other side, FedAdapt's flexibility concerns the anticipated scalability of clinical evaluation applications. © 2023 IEEE.

关键词： Federated Learning Healthcare Data Analysis Homomorphic Encryption Privacy Preservation

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Internet of Things Assisted Remote Health and Safety Monitoring Scheme Using Intelligent Sensors

Internet of Things Assisted Remote Health and Safety Monitor...

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Advances in Computing, Communication and Applied informatics (ACCAI), International Conference on

作者： V. RamKumar S. Shanthi K. Suresh Kumar S. Kanageswari S. Mahalakshmi R. Anusuya Department of ECE R.M.K. Engineering College Chennai Department of ECE CARE College of Engineering Tiruchirappalli Department of MBA Panimalar Engineering College Chennai Department of Computer Science Loyola College Chennai Department of Computer Science and Design R.M.K Engineering College Chennai Department of CSE Modern Institute of Technology and Research Centre Alwar Rajasthan

The Internet of Things (IoT) in telemedicine creates an enormous data volume that must be processed, analyzed, and stored. Risk to one's health is no longer mitigated by one's chronological age, thanks to today's hectic schedules and unexpected ways of living. The Internet of Things has made it easier to provide continuous remote health checks on patients outside of the hospital or clinic, or even in their own homes. Detectors record data on a variety of patient health factors, and the Internet of Things saves and displays this data on a website that also allows for remote monitoring. When the potential of IoT technology is taken into consideration, the challenges that patients with physical instability have while trying to regularly contact a doctor in person can be circumvented. The microcontroller's role in this project is that of a data relay. This system presents a new method for health service activities by using sensors to monitor a person's vitals and the network to alert concerned family members or physicians in the case of an *** attached buzzer in the controller will sound when there is a change in detector output, alerting the career. A microcontroller is used to monitor the patient's condition; this controller communicates with an LCD display and a wireless LAN to send out alert messages. The patient's heart rate, blood pressure, and temperature will all be displayed in the cloud in instantaneously, and a warning will be sent to the physician via the Internet of Things if the sensor recognizes an abnormality. In order to comprehend how the sensors worked, a comprehensive analysis of the data was collected with regard to fluctuations in physical and environmental activity.

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An Exploratory Investigation into Sustaining Cybersecurity Protection Through the Implementation of SETA

An Exploratory Investigation into Sustaining Cybersecurity P...

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International Conference on Emerging Trends in Networks and computer Communications (ETNCC)

作者： Abdullah Mahfuzul Huda Mohammed Brayyich Noor Hanoon Haroon Abdul Azeem Khan Rajan Verma University Institute of Computing Chandigarh University Punjab India College of Computing and Informatics Saudi Electronic University Riyadh KSA College of Technical Engineering National University of Science & Technology Dhi Qar Iraq Department of Computer Technical Engineering Technical Engineering College Al-Ayen University Thi-Qar Iraq Faculty of Islamic Technology Negara Brunei Darussalam Division of Research and Development Lovely Professional University Phagwara KKR & KSR Institute of Technology & Sciences Guntur Andhra Pradesh

ISBN: (数字)9798350353266

ISBN: (纸本)9798350353273

Most modern businesses run their competitive operations online. Cybersecurity is crucial to commercial operations. No cybersecurity defensive solution is universal. Standard security strategy involves using hardware and software to counter known security threats that may become stronger over time. Attackers and security professionals fight constantly. A security approach based primarily on tools is untenable. However, some firms skip employee awareness training, resulting in biased cybersecurity breach decisions. This study objectively analyzes key factors that help enterprises and organizations deploy Security Education, Training, and Awareness (SETA) to find ways to maintain such protection. A dataset of UK corporate cybersecurity breach surveys is used to perform performance testing on eight supervised learning models. The entire research uses the model's built characteristics that are excellent at recognizing SETA-adopting enterprises and organizations. The trial shows that awareness is vital when organizations use SETA. Many firms don't know how to safeguard employees from cybersecurity risks when they use online products and services, such as external web services.

关键词： Training Surveys Radio frequency Analytical models Web services Standards organizations Information security computer security Protection Testing

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Advances in lithium niobate photonics:development status and perspectives

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Advanced Photonics 2022年第3期4卷 40-82页

作者： Guanyu Chen Nanxi Li Jun Da Ng Hong-Lin Lin Yanyan Zhou Yuan Hsing Fu Lennon Yao Ting Lee Yu Yu Ai-Qun Liu Aaron J.Danner National University of Singapore Department of Electrical and Computer EngineeringSingapore A*STAR(Agency for Science Technology and Research)Institute of MicroelectronicsSingapore Huazhong University of Science and Technology School of Optical and Electronic InformationWuhan National Laboratory for OptoelectronicsWuhanChina Nanyang Technological University Quantum Science and Engineering CentreSingapore

Lithium niobate(LN)has experienced significant developments during past decades due to its versatile properties,especially its large electro-optic(EO)*** example,bulk LN-based modulators with high speeds and a superior linearity are widely used in typical fiber-optic communication ***,with everincreasing demands for signal transmission capacity,the high power and large size of bulk LN-based devices pose great challenges,especially when one of its counterparts,integrated silicon photonics,has experienced dramatic developments in recent *** long ago,high-quality thin-film LN on insulator(LNOI)became commercially available,which has paved the way for integrated LN photonics and opened a hot research area of LN photonics *** allows a large refractive index contrast,thus light can be confined within a more compact *** with other properties of LN,such as nonlinear/acousto-optic/pyroelectric effects,various kinds of high-performance integrated LN devices can be demonstrated.A comprehensive summary of advances in LN photonics is *** LN photonics has experienced several decades of development,our review includes some of the typical bulk LN devices as well as recently developed thin film LN *** this way,readers may be inspired by a complete picture of the evolution of this *** first introduce the basic material properties of LN and several key processing technologies for fabricating photonics *** that,various kinds of functional devices based on different effects are ***,we give a short summary and perspective of LN *** hope this review can give readers more insight into recent advances in LN photonics and contribute to the further development of LN related research.

关键词： lithium niobate etching photonics integrated optics nanotechnology devices.

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MLCardiovascularPrediction: Machine Learning-Based Cardiovascular Disease Prediction

MLCardiovascularPrediction: Machine Learning-Based Cardiovas...

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Mobile, Intelligent, and Ubiquitous Computing Conference (MIUCC), International

作者： Diaa Salama AbdElminaam Magda M. Madbouly Magdy Abd-elghany Zeid Ibrahim Abd Elatif Gomaa Laith Abualigah Faculty of Computer Science Misr International University Cairo Egypt Faculty of Computers and Artificial Intelligence Benha University Benha Egypt Faculty of Computer and Data Science Alexandria University Alexandria Egypt Computer Science Department Alobour high institute for computer and informatics Cairo Egypt Computer Science Department Al al-Bayt University Mafraq Jordan Department of Electrical and Computer Engineering Lebanese American University Byblos Lebanon Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman Jordan MEU Research Unit Middle East University Amman Jordan School of Computer Sciences Universiti Sains Malaysia Pulau Pinang Malaysia School of Engineering and Technology Sunway University Malaysia Petaling Jaya Malaysia

Like most diseases that affect a human's life, car-diovascular disease is dangerous and unwanted for anyone who has heard of it as it brings a high risk of death. In today's world, most deaths are caused by heart disease as it could come from age, heritage, smoking, and many factors that could seem normal, and it doesn't matter what part of the world you are in. There must be a way to know or predict if this person is at high risk of cardiovascular disease. This paper and project talk about six algorithms: K-Nearest-Neighbour (KNN), Decision Tree (DT), Naive Bayes, Neural Network, Logistic Regression, and Support Vector Machine (SVM). The results came between 60% to 70% in one dataset and from 80 % to 90 % in the second. Still, they mostly favor the Neural Network algorithm as it can learn and model around complex relationships. The SVM showed different outputs between the two datasets as one is significantly larger than the other, possibly due to the outliers in both datasets being different and more complex in the larger one. Cardiovascular disease can be very dangerous, but finding and discovering it soon can be a lifesaver. These algorithms also can help find and predict it, as it was shown with not just decent, but good and respectable success rates for each one.

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Visualizing Quantum Circuit Probability estimating computational action for quantum program synthesis

arXiv

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arXiv 2023年

作者： Bach, Bao Gia Kundu, Akash Acharya, Tamal Sarkar, Aritra Faculty of Computer Science and Engineering Ho Chi Minh City University of Technology Viet Nam Viet Nam Joint Doctoral School Silesian University of Technology Gliwice Poland Institute of Theoretical and Applied Informatics Polish Academy of Sciences Gliwice Poland Independent Researcher Bengaluru India Quantum Machine Learning Research group Quantum Computing Division QuTech Netherlands Quantum Intelligence Research team Department of Quantum & Computer Engineering Delft University of Technology Netherlands

This research applies concepts from algorithmic probability to Boolean and quantum combinatorial logic circuits. A tutorial-style introduction to states and various notions of the complexity of states are presented. Thereafter, the probability of states in the circuit model of computation is defined. Classical and quantum gate sets are compared to select some characteristic sets. The reachability and expressibility in a space-time-bounded setting for these gate sets are enumerated and visualized. These results are studied in terms of computational resources, universality and quantum behavior. The article suggests how applications like geometric quantum machine learning, novel quantum algorithm synthesis and quantum artificial general intelligence can benefit by studying circuit probabilities. © 2023, CC BY-NC-SA.

关键词： Machine learning

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NTIRE 2023 Quality Assessment of Video Enhancement Challenge

NTIRE 2023 Quality Assessment of Video Enhancement Challenge

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2023 IEEE/CVF Conference on computer Vision and Pattern Recognition Workshops, CVPRW 2023

作者： Liu, Xiaohong Min, Xiongkuo Sun, Wei Zhang, Yulun Zhang, Kai Timofte, Radu Zhai, Guangtao Gao, Yixuan Cao, Yuqin Kou, Tengchuan Dong, Yunlong Jia, Ziheng Li, Yilin Wu, Wei Hu, Shuming Deng, Sibin Xiao, Pengxiang Chen, Ying Li, Kai Zhao, Kai Yuan, Kun Sun, Ming Cong, Heng Wang, Hao Fu, Lingzhi Zhang, Yusheng Zhang, Rongyu Shi, Hang Xu, Qihang Xiao, Longan Ma, Zhiliang Agarla, Mirko Celona, Luigi Rota, Claudio Schettini, Raimondo Huang, Zhiwei Li, Ya'nan Wang, Xiaotao Lei, Lei Liu, Hongye Hong, Wei Chuang, Ironhead Lin, Allen Guan, Drake Chen, Iris Lou, Kae Huang, Willy Tasi, Yachun Kao, Yvonne Fan, Haotian Kong, Fangyuan Zhou, Shiqi Liu, Hao Lai, Yu Chen, Shanshan Wang, Wenqi Wu, Haoning Chen, Chaofeng Zhu, Chunzheng Guo, Zekun Zhao, Shiling Yin, Haibing Wang, Hongkui Meftah, Hanene Brachemi Fezza, Sid Ahmed Hamidouche, Wassim Déforges, Olivier Shi, Tengfei Mansouri, Azadeh Motamednia, Hossein Bakhtiari, Amir Hossein Aznaveh, Ahmad Mahmoudi Shanghai Jiao Tong University China Eth Zürich Switzerland University of Würzburg Germany Department of Tao Technology Alibaba Group China Kuaishou Technology China Interactive Entertainment Group of Netease Inc Guangzhou China Transsion China Hefei University of Technology China Department of Informatics Systems and Communication University of Milano - Bicocca Italy Xiaomi Inc. China China Ji Liang University China FreeTech Advanced Research Center KKCompany Taiwan ByteDance China Mgtv China Fuzhou University China Shopee Information Technology Co. Ltd. S-Lab Nanyang Technological University Singapore Hunan University China Hangzhou Dianzi University China Insa Rennes Cnrs Ietr - Umr 6164 Rennes France National Higher School of Telecommunications and Ict Oran Algeria Buaa Department of Electrical and Computer Engineering Faculty of Engineering Kharazmi University Tehran Iran High Performance Computing Laboratory School of Computer Science Institute for Research in Fundamental Sciences Tehran Iran Cyberspace Research Institute Shahid Beheshti University Tehran Iran

ISBN: (纸本)9798350302493

This paper reports on the NTIRE 2023 Quality Assessment of Video Enhancement Challenge, which will be held in conjunction with the New Trends in Image Restoration and Enhancement Workshop (NTIRE) at CVPR 2023. This challenge is to address a major challenge in the field of video processing, namely, video quality assessment (VQA) for enhanced videos. The challenge uses the VQA Dataset for Perceptual Video Enhancement (VDPVE), which has a total of 1211 enhanced videos, including 600 videos with color, brightness, and contrast enhancements, 310 videos with deblurring, and 301 deshaked videos. The challenge has a total of 167 registered participants. 61 participating teams submitted their prediction results during the development phase, with a total of 3168 submissions. A total of 176 submissions were submitted by 37 participating teams during the final testing phase. Finally, 19 participating teams submitted their models and fact sheets, and detailed the methods they used. Some methods have achieved better results than baseline methods, and the winning methods have demonstrated superior prediction performance. © 2023 IEEE.

关键词： Image enhancement

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An algorithmic study in the vector model for wireless power transfer maximization

arXiv

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arXiv 2021年

作者： Katsidimas, Ioannis Nikoletseas, Sotiris Raptis, Theofanis P. Raptopoulos, Christoforos Institute of Informatics and Telematics National Research Council Pisa Italy Department of Computer Engineering and Informatics University of Patras Patras Greece Computer Technology Institute and Press Diophantus Patras Greece

Rapid technological advances in the domain of Wireless Power Transfer (WPT) pave the way for novel methods for power management in systems of wireless devices and recent research works have already started considering algorithmic solutions for tackling emerging problems. However, many of those works are limited by the system modelling, and more specifically the one-dimensional abstraction suggested by Friis formula for the power received by one antenna under idealized conditions given another antenna some distance away. Different to those works, we use a model which arises naturally from fundamental properties of the superposition of energy fields. This model has been shown to be more realistic than other one-dimensional models that have been used in the past and can capture superadditive and cancellation effects. Under this model, we define two new interesting problems for configuring the wireless power transmitters so as to maximize the total power in the system and we prove that the first problem can be solved in polynomial time. We present a distributed solution that runs in pseudo-polynomial time and uses various knowledge levels and we provide theoretical performance guarantees. Finally, we design three heuristics for the second problem and evaluate them via simulations. © 2021, CC BY-NC-ND.

关键词： Energy transfer

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AI-based Object Detection for Assisting the Visually Impaired People

AI-based Object Detection for Assisting the Visually Impaire...

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Mobile Computing and Sustainable informatics (ICMCSI), International Conference on

作者： Syed Sameer Parul Madan Sathish Kannan Vijay Jagdish Upadhye Harshal Patil S. Rajkumar Project Engineer Department of Science and Technology Karnataka State Council for Science and Technology (KSCST) Indian Institute of Science (IISc) Campus Bengaluru Karnataka India Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun Uttarakhand India Department of VLSI Microelectronics Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai Tamil Nadu India Deputy Director Research and Development Cell Department of Microbiology Parul Institute of Applied Sciences Parul University Waghodia Gujarat India Computer Science and Engineering Symbiosis Institute of Technology Symbiosis International (Deemed University) Pune Maharashtra India Department of Mechanical Engineering Faculty of Manufacturing Institute of Technology Hawassa University Ethiopia

In recent decades, vision problems have become more common. One significant barrier is that people who are visually impaired generally require assistance performing their daily tasks. As a result, developing a technological solution to this challenge is critical. Implementing an automatic object identification system can enable visually impaired people to roam independently. The study employs two Artificial Intelligence (AI) models, a Region-based Fully Convolutional Network (RFCN) and a Mask Region-based Convolutional Neural Network (Mask RCNN), to detect objects and assess their performance. The evaluation demonstrates RFCN's outstanding performance with an impressive Mean Average Precision (mAP) score of 0.825. The Raspberry Pi processor is used as a vital component in the process of hardware development. The RFCN model is integrated into the processor to aid in the identification of objects collected by the system's pi-camera. The detected objects are communicated to users via auditory feedback. The hardware system also includes an ultrasonic sensor, which provides distance information for the detected objects. This full hardware solution is specifically developed to help visually impaired people overcome mobility issues in both indoor and outdoor settings. The suggested system seeks to improve the autonomy and safety of visually impaired individuals in their day-to-day activities by seamlessly mixing advanced technologies such as AI and embedded systems.

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