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检索条件"任意字段=6th IAPR International Conference on Pattern Recognition in Bioinformatics"

共 1869 条记录，以下是81-90 订阅

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Fingerprint and Face Authentication Portable Digital Electronic Voting Machine 6

Fingerprint and Face Authentication Portable Digital Electro...

引用

6th international conference on Electronics and Electrical Engineering Technology (EEET)

作者： Cagape, Brandon Sage Lisondato, John Carlo Maboloc, Princess Diane Bacus, John A. Univ Mindanao Elect Engn Program Coll Engn Educ Davao Philippines

ISBN: (纸本)9798350395600;9798350395594

the paper presents the Electronic Voting Machine (EVM) device to facilitate digital elections with the use of Raspberry Pi as its brain. It is developed to reduce paper wastage and prevent fraud and ghost voting in contrast to the Paper Ballot System. the EVM is designed to authenticate the voter through fingerprint or face authentication. the face authentication method is incorporated with an anti-spoofing technique. Local Binary pattern Histograms (LBPH) and Haar-Cascade Classifier models were used to detect and recognize faces and eye-blink counters for anti-spoofing. Both authentications were combined and incorporated into the voting graphic user interface (GUI), programmed through Python and its libraries to create the EVM, wherein the voter must authenticate through fingerprint or face recognition if they failed the prior method. the accuracy tests resulted in an overall 80% and 95.56% accuracy for fingerprint and face authentication, respectively. the antispoofing technique resulted in an overall accuracy of 100%. the mock elections of 20 voters conducted to test the functionality of the EVM resulted in an 80% fingerprint authentication success rate, while 100% of the remaining 20% passed the face authentication. those who failed the fingerprint authentication proceeded to face authentication, resulting in an overall 100% success rate in the authentication of all voters. the database results matched the receipt of the voters, demonstrating the device's overall efficiency of 100%. In conclusion, the paper proposes an efficient and secure EVM that ensures fair and transparent digital elections.

关键词： Electronic Voting Machine Local Binary pattern Histogram (LBPH) Haar-Cascade Classifier Anti-Spoofing Raspbian OS FirebaseDB

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Visualizing NASDAQ Composite Index Historical Data Using Tableau 6th

Visualizing NASDAQ Composite Index Historical Data Using Tab...

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6th international conference on Computational Intelligence in pattern recognition, CIPR 2024

作者： Safuan, Halawati Abd Jalil Nyein, Chit Ko Ko Riskhan, Basheer Ashfaq, Farzeen School of Computing and Informatics Albukhary International University Alor Setar Malaysia School of Computer Science SCS Taylors University Subang Jaya Malaysia

ISBN: (纸本)9789819780891

the study explores the visualization and analysis of historical data for the NASDAQ Composite Index (^IXIC) using Tableau. It examines trends in daily closing prices and volume distribution and compares performance with the NYSE index. Findings reveal significant fluctuations in the NASDAQ index over 22 years, suggesting potential future price changes. Forecasted graphs offer insights into potential economic decline and recovery, highlighting the dynamic nature of the market. Volume distribution analysis identifies periods of heightened trading activity. Comparative performance analysis emphasizes different trends observed in the NASDAQ and NYSE indices. Due to market unpredictability and external influences, additional research is crucial for validation. this study showcases the value of data visualization and analysis in finance through Tableau. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Inflation

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pattern recognition Assisted Translation Training System 6

Pattern Recognition Assisted Translation Training System

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6th international conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2022

作者： Jin, Ling Lijiang College of Guangxi Normal University Guangxi Guilin541004 China

ISBN: (数字)9781665469418

ISBN: (纸本)9781665469418

the pattern recognition and computer-assisted translation teaching under the school-enterprise cooperation mode is centered on computer-assisted translation technology, and the implementation of networked interactive translation teaching will help translation students improve translation quality and efficiency, become familiar with the construction of smart undergraduates, and form project management Ideas, including the choice of CAT software, the combined application of CAT and corpus technology in translation teaching, the setting of CAT technology modules, etc., in order to promote the application and development of CAT technology in undergraduate translation training. © 2022 IEEE.

关键词： Project management

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conference Committees

Conference Committees

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pattern recognition and Artificial Intelligence (PRAI), international conference on

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Design of an Edge Detected CMOS Image Sensor for an Intelligent pattern recognition 6

Design of an Edge Detected CMOS Image Sensor for an Intellig...

引用

6th international conference on Information Technology, InCIT 2022

作者： Lee, Hohyeon Kim, Soo Youn Song, Minkyu Dongguk University Dept. of Semiconductor Science Seoul100-715 Korea Republic of

ISBN: (纸本)9781665489126

Normally, a pattern recognition has been studied in the field of digital signal processing with digital codes. Even though it has very accurate results, it needs a lot of power consumption, very long operating time, and huge hardware bundles. In this paper, an edge detected CMOS image sensor for an intelligent pattern recognition is proposed. Further, an efficient edge detection algorithm is also described. With the new techniques, a low power and high speed pattern recognition is available in the field of CMOS image sensor. the image sensor is composed of photodiodes, a two-step single-slope 8-bit analog-to-digital converter, static random memories, and etc. the testing sensor has been implemented with an 180nm technology. It has a very excellent measured results, compared to other published chips. © 2022 IEEE.

关键词： Image sensors

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Intrusion Detection on Industrial Networks Using Neuromorphic Computing 6

Intrusion Detection on Industrial Networks Using Neuromorphi...

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6th international conference on Electrical, Control and Instrumentation Engineering, ICECIE 2024

作者： Mehrabi, Ali Van Schaik, Andre International Centre for Neuromorphic Systems Western Sydney University Australia

ISBN: (纸本)9798350380040

Cyber-attacks on Industrial Control Systems (ICS) present critical risks to operational stability, public safety, and national security. As industrial networks become more integrated and interconnected, their susceptibility to sophisticated cyber threats increases. Traditional security measures often fall short in detecting evolving attack patterns. this paper investigates the application of neuromorphic computing, which emulates the human brain's pattern recognition capabilities, as an innovative approach to intrusion detection in industrial networks. We introduce a hardware-based Spiking Neural Network (SNN) engineered to monitor and analyze communication packets in real time, detecting anomalies indicative of potential intrusions. the neuromorphic approach offers a promising solution to the growing challenge of cyber-attacks in critical infrastructure. the proposed system is implemented on an FPGA, focusing initially on monitoring key packet types such as LLDP, ARP, UDP, TCP, and Profibus RT, with scalability to accommodate additional protocols. the results demonstrate the efficacy of this SNN-based intrusion detection system in providing real-time, efficient, and accurate monitoring of industrial networks. © 2024 IEEE.

关键词： Network intrusion

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Fault Diagnosis in Power Transmission Line using Decision Tree and Random Forest Classifier 6

Fault Diagnosis in Power Transmission Line using Decision Tr...

引用

IEEE 6th international conference on Condition Assessment Techniques in Electrical Systems (IEEE CATCON)

作者： Chakravarty, Somesh Lahiri Maiti, Abhijnan De, Abhinandan Indian Inst Technol BHU Dept Elect Engn Varanasi 221005 Uttar Pradesh India Indian Inst Engn Sci & Technol Dept Elect Engn Sibpur 711103 W Bengal India

ISBN: (纸本)9781665473804

Fault diagnosis includes both detection of the type of fault that has occurred as well as locating the fault on a vast stretch of transmission network. there exists wide scope of application of Artificial Intelligence (AI) and Machine Learning (ML) based pattern recognition techniques in fault detection. the method proposed in this paper attempts to correctly identify the location of fault, type of fault and the faulty phase of transmission line in the form of an encoded 13bit binary number. this number is then decoded and appropriate remedial measures are taken to isolate the fault. In this paper, Decision Tree (DT) and Random Forest based classification techniques have been proposed for fault diagnosis in a radial transmission line. Python platform has been used to simulate the proposed fault classifiers and implemented on a developed SIMULINK model of a 100 km long radial transmission line. the proposed method delivered fault recognition accuracy in the range of 95 - 100% under different fault scenarios.

关键词： pattern recognition Decision Tree Random Forest Fault diagnosis Transmission

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Big Data and Reinforcement Learning, Emg Clustering 6

Big Data and Reinforcement Learning, Emg Clustering

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6th international conference on Contemporary Computing and Informatics, IC3I 2023

作者： Naaz, Rohaila Bajpai, Yashi Kumar Verma, Pushpendra Balaji, N.V. Ramesh, P.N. Aher, Vijaya N. Teerthankar Mahaveer University Uttar Pradesh Moradabad India Invertis University Department of Computer Science & Engineering Uttar Pradesh Bareilly India School of Computer Science and Applications IIMT University Uttar Pradesh Meerut India Karpagam Academy of Higher Education Department of Computer Science Tamilnadu Coimbatore India Karpagam Institute of Technology Department of Computer Science Engineering Tamilnadu Coimbatore India Vishwakarma Institute of Information Technology E & TC Maharashtra Pune India

ISBN: (纸本)9798350304480

the need of creating improved that are better equipped to manage 'big data'has significantly grown due to the growing volume of data in electromyographic signal study. As a result, increasingly sophisticated created. this essay starts with a succinct overview of the key driving forces behind the expansion of big data age, then moves on to discuss the recent development of current shared data sets. After that, we cover current research and advancements in pattern recognition techniques that can be used for big data analytics. these new signal analysis approaches may be classified into two primary categories engineering utilizing a potential large specific focus on 'deep learning'. Finally, suggestions for further pattern research are presented and explored. © 2023 IEEE.

关键词： Big data Classification accuracy Convolutional neural networks (CNN) Deep learning Electromyographic signal study EMG clustering EMG pattern recognition Feature engineering High-density surface EMG pattern recognition techniques Recurrent neural network (RNN) Reinforcement learning Surface EMG

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6th international conference on Information Technology, InCIT 2022

6th International Conference on Information Technology, InCI...

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6th international conference on Information Technology, InCIT 2022

ISBN: (纸本)9781665489126

the proceedings contain 97 papers. the topics discussed include: sequential frequency estimation using auxiliary particle filter;gamification of donation app: what affect donators’ decision?;a self-augmentation transfer learning network for image deraining;towards employee-driven idea mining: concept, benefits, and challenges;the classification of edible-nest swiftlets using deep learning;disambiguation of web search terms based on clustering using page rank and distance between words;adaptive noise cancellation using a fully connected network: a lesson learned;research on self-driving based on dynamic recognition of traffic signs;data clustering using particle swarm optimization for pairwise microarray bioinformatics data;system design of a toxic waste management system empirical study for Chiang Rai province;shape recognition using unconstrained pill images based on deep convolution network;beauty face: an android application for cosmetic consumers to try on and receive product recommendation;and in-memory synchronization platform for electronic toll collection via computer network of the expressway in thailand.

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An Analysis of Sequential pattern Mining Approach for Progressive Database by Deep Learning Technique 6

An Analysis of Sequential Pattern Mining Approach for Progre...

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6th international conference on Intelligent Computing and Control Systems, ICICCS 2022

作者： Jamshed, Aatif Mallick, Bhawna Bharti, Rajendra Kumar Uttarakhand Technical University Veer Madho Singh Bhandari Department of Cse Uttarakhand Dehradun India Meerut Institute of Engineering and Technology Dean Academics Uttar Pradesh Meerut India Bipin Tripathi Kumaon Institute of Technology Department of Cse Uttrakhand Dwarahat India

ISBN: (纸本)9781665410359

In the disciplines of enterprise, electronic commerce, bioinformatics, and other related subjects, sequential form mining is one of the most broadly utilized approaches. Traditional techniques are unable to accurately mine massive amounts of data due to their inherent limitations. thus, the suggested study makes use of Deep Structured Learning-based Sequent form mining to reduce the complexity associated with dealing with large amounts of data. Data in application sectors like banking and e-commerce are prone to dynamic changes, increasing non-stationarity. To convert the data to a stochastic/time series format, employing wavelet analysis has been suggested. A modified Long Short-Term Memory (LSTM) was also built to increase mining precision. By removing old data from a progressive database, the recommended technique extracts the sequential pattern. To demonstrate the robustness of the suggested work, the execution time of the proposed work is compared to that of traditional algorithms. © 2022 IEEE.

关键词： Database systems

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