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检索条件"主题词=Software Algorithms"

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Risks of Digital Transformation: Review of Machine Learning algorithms in Credit Card Fraud Detection

Risks of Digital Transformation: Review of Machine Learning ...

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International Informatics and software Engineering Conference (UBMYK)

作者： Güneş Gürsoy Asaf Varol College of Engineering and Natural Sciences Maltepe University Istanbul Turkey

ISBN: (纸本)9781665407601

In addition to the advantages of the digital world, there are also disadvantages, which can harm people. With the spread of credit cards with the digital transformation, banks have become the targets of malicious hackers. In this study, firstly, information about artificial intelligence and digital transformation is given. In related studies, some machine learning methods such as Random Forest, Naive Bayes, K-Nearest Neighbor, Logistic Regression, Support Vector Machines, Decision Tree, Artificial Neural Networks, Multilayer Perceptron and Ensemble Learning have been used to detect credit card fraud and their algorithm performance has been demonstrated.

关键词： Support vector machines Machine learning algorithms Digital transformation software algorithms Predictive models Prediction algorithms Credit cards

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Creating the Future: Augmented Reality, the next Human-Machine Interface

Creating the Future: Augmented Reality, the next Human-Machi...

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International Electron Devices Meeting (IEDM)

作者： Michael Abrash Facebook Reality Labs Research Redmond WA USA

ISBN: (纸本)9781665425735

XR, consisting of Virtual Reality (VR) and Augmented Reality (AR) together, will be the next general computing platform, dominating our relationship with the digital world for the next 50 years, much as personal computing has dominated the last 50. XR will be the way people work, play, and connect. VR headsets will create deeply immersive new experiences and will enable the richest Metaverse experiences. Always-available AR glasses will be with us when we're on the go, letting us act with extremely low latency and friction, allowing us to use virtual entities of all sorts to annotate our world, share with others, and communicate, and extending our perceptions, memory, and cognition with an Artificial Intelligence (AI) assistant that truly understands our context and our personal needs. Both will be centered around people rather than technology, allowing us to connect more strongly than ever before, and providing a contextually personalized interface that is far more intuitive and natural than anything that exists today. However, VR and particularly AR are at a very early stage, and need a great deal of innovation and development, across multiple technologies, before they can offer the level of performance that would cause billions of people to make XR a part of their everyday lives. Those technologies include optics, projectors, display systems, graphics, audio, hand tracking, eye tracking, face tracking, body tracking, world mapping and reconstruction, contextual understanding, sensors, interaction, and AI. VR headsets operate within tight power, weight, and thermal budgets, and AR glasses will need to operate within extraordinarily tight budgets; for AR glasses, the constraints include light weight, very low power, and all-day comfort and all-day operation in a socially acceptable form factor,. Breakthroughs are needed in every one of the areas listed above, and in almost every case, innovative, highly customized semiconductor technologies will be needed to achiev

关键词： Headphones Technological innovation Three-dimensional displays Thermal factors software algorithms Glass Thermal sensors

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ResNet Approach for Coding Unit Fast Splitting Decision of HEVC Intra Coding

ResNet Approach for Coding Unit Fast Splitting Decision of H...

引用

IEEE International Conference on Data Science in Cyberspace (DSC)

作者： Yixiao Li Lixiang Li Zirui Zhuang Yuan Fang Yixian Yang State Key Laboratory of Networking and Switching Technology Information Security Center Beijing University of Posts and Telecommunications Beijing China National Engineering Laboratory for Disaster Backup Recovery Beijing China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781665418164

High Efficiency Video Coding (HEVC) has achieved substantial improvement over its predecessor H264/AVC in terms of compression ratio by about 50%. In intra coding, HEVC implies a quad-tree structure to partition a Coding Unit (CU), which brings more encoding flexibility and lower bitrates. However, it is quite time-consuming to find the optimal one with the minimum encoding cost from massive CU partitioning structures. Based on ResNet method, this paper proposes a fast CU splitting decision approach for HEVC intra coding to decide whether early termination is applicable. The proposed approach is applied to CUs of depth 0, 1 and 2. The CU partitioning strategy is viewed as a recursive dichotomy problem and solved with ResNet models. Compared with HEVC reference software HM16.7 of all-intra configuration, the encoding time saving of the proposed approach is averaged about 48.03% on sequence BQTerrace with 3.3% BD-rate increase.

关键词： software algorithms Rate-distortion Data science Encoding software Partitioning algorithms Feeds

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Reconstruction of Furnace Temperature Field by Ultrasonic Transducer

Reconstruction of Furnace Temperature Field by Ultrasonic Tr...

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International Conference on Electronic Measurement and Instruments, ICEMI

作者： Fenjin Chao Shaohong Wang Fuqiang Zhou Zeyi Zhao Lei Chen Xiaoli Xu Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science & Technology University Beijing China

ISBN: (纸本)9781665444927

There are many deficiencies in contact temperature measurement, which can not provide a good guarantee for economy, efficiency and safety. Ultrasonic sensor temperature measurement technology has a good effect on the real-time monitoring of complex temperature field. This study takes the boiler furnace as the research object and the reconstruction of the temperature field in the furnace as the research purpose. Based on the finite element method, a single peak symmetrical temperature field model of the furnace is established on COMSOL platform to simulate the propagation of sound waves in the furnace, calculate the flight time according to the cross-correlation algorithm, and restore the temperature field of the furnace temperature field model by using the least square method and interpolation algorithm. The results show that the maximum relative error of flight time and theoretical flight time obtained by cross-correlation algorithm is 0.85%, and the average absolute error of reconstructed temperature field and single peak symmetric temperature field is 31K, which has a good reconstruction effect.

关键词： Temperature measurement Temperature sensors Interpolation Analytical models Furnaces software algorithms Acoustics

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FPGA Implementation of Arbiter PUFs for ideal Cryptographic Key Generation

FPGA Implementation of Arbiter PUFs for ideal Cryptographic ...

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International conference of Electronics, Communication and Aerospace Technology (ICECA)

作者： Komma Anitha Kiran Kumar Gopathoti J Rajeswari Sankararao Majji Tulasi Radhika Patnala Damaraju Sri Sai Satyanarayana Prasad V Potluri Siddhartha Institute of Technology Vijayawada India Institute of Aeronautical Engineering Hyderabad India Lecturer in ECE Government Polytechnic for women Kakinada India GRIET Hyderabad India Developer Shanax Technologies Hyderabad India Scholar Chalmers University of Technology Goteborg Sweden

ISBN: (纸本)9781665435253

It is critical in today's security-conscious environments and communications to create unique identities, and this can be done with software or hardware. Hardware can create a reliable and unique identity with less complexity than software because software requires more complex algorithms to keep the secret hidden from the adversaries. PUF is the name of one such basic circuit. Even when made using a nominally identical process, no two physical objects are exactly the same. When presented with a binary input, a PUF circuit responds with a binary, device-unique output. A PUF circuit is designed to be sensitive to manufacturing process variations. PUF as a hardware primitive is used as an authentication device in the real-world practical application scheme. The proposed IoT node-to-node mutual authentication algorithm does not require a server or a trusted third party. FPGA boards are used to implement the algorithm's main modules, such as the Nonce generation logic and the unclonable response generation logic. In spite of identity theft, PUF-based authentication schemes have the assurance that malicious parties cannot replace the intended PUF-based node.

关键词： Protocols software algorithms Authentication software Hardware software reliability Cryptography

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Reinforcement Learning Based Penetration Testing of a Microgrid Control Algorithm

Reinforcement Learning Based Penetration Testing of a Microg...

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IEEE Annual Computing and Communication Workshop and Conference (CCWC)

作者： Christopher Neal Hanane Dagdougui Andrea Lodi José M. Fernandez Polytechnique Montreal Montreal Canada

ISBN: (数字)9781665414906

ISBN: (纸本)9781665430586

Microgrids (MGs) are small-scale power systems which interconnect distributed energy resources and loads within clearly defined regions. However, the digital infrastructure used in an MG to relay sensory information and perform control commands can potentially be compromised due to a cyberattack from a capable adversary. An MG operator is interested in knowing the inherent vulnerabilities in their system and should regularly perform Penetration Testing (PT) activities to prepare for such an event. PT generally involves looking for defensive coverage blind spots in software and hardware infrastructure, however the logic in control algorithms which act upon sensory information should also be considered in PT activities. This paper demonstrates a case study of PT for an MG control algorithm by using Reinforcement Learning (RL) to uncover malicious input which compromises the effectiveness of the controller. Through trial-and-error episodic interactions with a simulated MG, we train an RL agent to find malicious input which reduces the effectiveness of the MG controller.

关键词： Conferences software algorithms Reinforcement learning Microgrids Batteries State of charge Penetration testing

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Implementation of Fuzzy Logic on Microcontroller for Quails Coop Temperature Control

Implementation of Fuzzy Logic on Microcontroller for Quails ...

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International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)

作者： Nisa Rizqiya Fadhliana Sayekti Harits Suryawan Ariyadi Program Studi Informatika Institut Teknologi Kalimantan Balikpapan Indonesia Program Studi Teknik Informatika Fakultas Sains dan Teknologi Universitas Muhammadiyah Kalimantan Timur Samarinda Indonesia

ISBN: (纸本)9781665401524

Quail (cortunix cortunix japonica) is a type of poultry that is quite popular for its eggs and meat as an alternative protein source. However, for tropical climates such as Indonesia, there are challenges faced by quail farmers, namely heat stress. One way that can be a solution to deal with these challenges is to regulate the room temperature in the quail cage. This study aims to design an automatic temperature control system for quail cages using a microcontroller embedded with a fuzzy algorithm to determine the action to be taken to adjust the temperature and humidity of the air in the quail cage. The prototype developed in this research is tested by comparing the output simulation of the microcontroller with the simulation performed using Matlab software.

关键词： Heating systems Temperature dependence Microcontrollers Atmospheric modeling Simulation software algorithms Humidity

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Improving Gene Expression Prediction of Cancer Data Using Nature Inspired Optimization algorithms

Improving Gene Expression Prediction of Cancer Data Using Na...

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International Conference on Computational Science and Computational Intelligence (CSCI)

作者： Payal Patel Kalpdrum Passi Chakresh Kumar Jain Department of Mathematics and Computer Science Laurentian University Sudbury Ontario Canada Department of Biotechnology Jaypee Institute of Information Technology Noida India

ISBN: (纸本)9781665458429

Cancer being one of the most vital diseases in the medical history needs adequate focus on its causes, symptoms and detection. Various algorithms and software have been designed so far to predict the cancer at cellular level. The most crucial aspect for sorting the cancerous tissues is the classification of such tissues based on the gene expression data. Gene expression data consists of high amount of genetic data as compared to the number of data samples. Thus, sample size and dimensions are a major challenge for researchers. In this work, four different types of cancer microarray datasets are analyzed viz., breast cancer, lung cancer, leukemia and colon cancer. The analysis of the cancer microarray datasets was done using various nature-inspired algorithms like Grasshopper Optimization (GOA), Particle Swarm Optimization (PSO), and Interval Value-based Particle Swarm Optimization (IVPSO). To study the accuracy of the prediction, five different classifiers were used: Random Forest, K-Nearest Neighborhood (KNN), Neural Network, Naïve Bayes and Support Vector Machine (SVM). The Grasshopper Optimization (GOA) outperforms in accuracy compared to the other two optimization algorithms with SVM classifier on leukemia, lung and breast cancer datasets selecting the best genes/attributes to correctly classify the dataset.

关键词： Support vector machines software algorithms Prediction algorithms Breast cancer Classification algorithms Gene expression Particle swarm optimization

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REDO: A Reinforcement Learning-based Dynamic Routing Algorithm Selection Method for SDN

REDO: A Reinforcement Learning-based Dynamic Routing Algorit...

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IEEE Conference on Network Function Virtualization and software Defined Networks (NFV-SDN)

作者： Ahmed Al-Jawad Ioan-Sorin Comşa Purav Shah Orhan Gemikonakli Ramona Trestian Middlesex University London UK Swiss Distance University of Applied Sciences Brig Switzerland

ISBN: (纸本)9781665439848

The current increase in the Internet traffic along with the global crisis have accelerated the roll-out of the next generation 5G network and key enabling technologies. In this context, addressing the end-to-end Quality of Service (QoS) provisioning in order to guarantee a sustainable service delivery to the end-users became of paramount importance. Some of the enabling technologies that could play a key role in this regard are software Defined Network (SDN) and Machine Learning (ML). This paper proposes REDO, a Reinforcement lEarning-based Dynamic rOuting algorithm selection method that decides on the conventional routing algorithm to be applied on the traffic flows within a SDN environment. REDO will dynamically select the most appropriate routing algorithm from a set of centralized routing algorithms (MHA, WSP, SWP, MIRA) that maximizes the reward function from the network. The proposed REDO solution is implemented and evaluated using an experimental setup based on Mininet, Floodlight controller and Open vSwitch switches. The results show that REDO outperforms other state-of-the-art solutions.

关键词： Machine learning algorithms Heuristic algorithms software algorithms Packet loss Quality of service Routing Control systems

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A Comparative Study on the Drum Sound Recognition algorithms Based Deep Learning

A Comparative Study on the Drum Sound Recognition Algorithms...

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software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD-Winter), ACIS International Winter Conference on

作者： Sang Wook Lee Jae Hyuk Heo Sung Taek Lee Soongsil University Seoul South Korea

Drums are difficult to recognize not only because the sounds overlap when many instruments are played simultaneously, but also the notes and beats vary depending on how they are played. This study compared the Recurrent Neural Network (RNN) algorithm that analyzes the sequence of time and the Conversion Neural Network (CNN) algorithm that analyzes data in image form to compare which machine learning algorithms show better performance for drum sound recognition. Through this, this research wanted to study which algorithm to recognize musical instruments is appropriate, and contribute to the area of Music Information Retrieval (MIR).

关键词： Machine learning algorithms Recurrent neural networks Instruments software algorithms Music Music information retrieval software engineering

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