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检索条件"任意字段=Proceedings of the 6th International Conference on Algorithms, Computing and Systems"

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Development model of evaluation of knowledge management systems implementation in government organization 6

Development model of evaluation of knowledge management syst...

引用

6th international conference on Information Management and Technology, ICIMTech 2021

作者： Sardjono, Wahyu Retnowardhani, Astari Budianto, Wahyu Rahmasari, Aninda Bina Nusantara University BINUS Graduate Program - Master of Information Systems Management Information Systems Management Department Jakarta11480 Indonesia Bina Nusantara University Faculty of Humanities International Relations Department Jakarta11480 Indonesia

ISBN: (纸本)9781665449373

Employees' performance has a crucial role in running a company. thus, any efforts that aim to improve employee's performance is vital to be conducted and evaluated. thus, the purpose of writing this paper is to assess the Knowledge Management systems (KMS) evaluation model implemented at Government Organization and then find the factors and indicators that can improve employees' performance. this study is a survey that collected the data through a summative evaluation by using a questionnaire. the collected data were analyzed quantitatively using descriptive and inferential statistics. the results obtained from the processes carried out indicate that human, process, and technology variables have a positive influence on employee performance variables. So, through the results of this study, it can be concluded that the three main variables in the implementation of KMS can have a positive influence on improving employee performance in government institutions. © 2021 IEEE.

关键词： Knowledge management

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Object Detection and Optical Character Recognition for Automated Malaysia Driving License and Road Tax Document Details Retrieval

Object Detection and Optical Character Recognition for Autom...

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IEEE Symposium on Computers & Informatics (ISCI)

作者： Chun Hong Lam Chian Wen Too Whee Yen Wong Toong Hai Sam Beh Hooi Ching Hoo Meei Hao Department of Computing Universiti Tunku Abudul Rahman Kajang Malaysia Faculty of Business and Communications INTI International University Nilai Seremban Malaysia Department of Computing Universiti Tunku Abdul Rahman Kajang Malaysia

ISBN: (数字)9798350353853

ISBN: (纸本)9798350353860

In the realm of automated document information extraction, Object Detection and Optical Character Recognition (OCR) approaches signify a pivotal leap forward. these advancements use machine learning and computer vision to quickly and precisely extract important data from a variety of document formats, including road tax and Malaysian driving license. Object Detection algorithms, with the help of platforms like Roboflow, can identify and localize key elements within documents, simplifying the dataset creation process for further analysis. Meanwhile, OCR technologies, such as Google Vision API, facilitate text and data extraction from images or scanned documents. this combination allows organizations to streamline document handling, eliminate manual processes, and reduce human errors associated with traditional data input methods. Moreover, sophisticated image classification techniques enhance document processing capabilities by improving the accuracy and reliability of extracted information. this integrated approach not only optimizes document management workflows but also sets the stage for developing advanced autonomous and assisted document technologies. As automated driving systems evolve, the seamless integration of Object Detection and OCR has the potential to revolutionize document handling through automated workflows and precise data extraction.

关键词： Accuracy Roads Optical character recognition Finance Object detection Licenses Information retrieval

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New Framework for Authentication and key Establishment to Secure 6LoWPAN Networks 8

New Framework for Authentication and key Establishment to Se...

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8th international conference on Electrical Engineering and Informatics, ICEEI 2021

作者： Alshrif, Fatma Foad Sundararajan, Elankovan A. Ahmad, Rami Alkhatib, Yousef Universiti Kebangsaan Malaysia Faculty of Information Science Technology Bangi Malaysia Sebha University The School of Information Technology Sebha Libya

ISBN: (纸本)9781665405560

this paper describes a design of a lightweight authentication solution for the 6LoWPAN based Wireless Sensor Network. 6LoWPAN nodes are classified as constrained devices with limited memory and computing power. therefore, since confidential data is shared in various fields through a public channel, the underlying resources are vulnerable to security threats. Moreover, constrained devices make it impossible to secure information using traditional resource-intensive encryption algorithms such as biometric, username, and password. therefore, a variety of symmetric cryptographic and public key-based authentication methods have been proposed to address such issues. Conversely, the solutions still suffer from large communication and computational overhead problems and do not resist some known attacks. Our proposed framework aims to reduce computing and communication costs by using lightweight authentication-based symmetric key management. It employs a hash-based method, pre-distribution key, track sequence, nonce, and symmetric Lici-2 algorithm in both phases (establishment and authentication). this proposal framework is expected to resist attacks as exemplified by to reply and man in the middle. © 2021 IEEE.

关键词： Authentication

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Message from conference Chairs

Message from Conference Chairs

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Big Data, Cloud computing, Data Science & Engineering (BCD)

Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.

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proceedings - 2021 IEEE/ACM conference on Connected Health: Applications, systems and Engineering Technologies, CHASE 2021

Proceedings - 2021 IEEE/ACM Conference on Connected Health: ...

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6th IEEE/ACM international conference on Connected Health: Applications, systems and Engineering Technologies, CHASE 2021

ISBN: (纸本)9781665439657

the proceedings contain 37 papers. the topics discussed include: machine learning prediction of TBI from mobility, gait and balance patterns;improve image-based skin cancer diagnosis with generative self-supervised learning;RT-ACL: identification of high-risk youth patients and their most significant risk factors to reduce anterior cruciate ligament reinjury risk;detection and analysis of interrupted behaviors by public policy interventions during COVID-19;information extraction from patient care reports for intelligent emergency medical services;high-confidence data programming for evaluating suppression of physiological alarms;EDA-based data stream pattern analysis and peak detection algorithm for substance users;and sensor-based human activity recognition for elderly in-patients with a Luong self-attention network.

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Enhancing Credit Card Fraud Detection with Hybrid Sampling and Machine Learning Models

Enhancing Credit Card Fraud Detection with Hybrid Sampling a...

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international conference on Advancements in Computational Sciences (ICACS)

作者： Irfan Ahmad Muhammad Waleed Asad Ullah Muhammad Usman Jamil Maynooth International Engineering College Faculty of Science and Engineering Maynooth University Ireland Fuzhou Department of Information Technology Government College University Faisalabad Pakistan Department of Computer Science Staffordshire University United Kingdom School of Mechanical and Electrical Engineering Chuzhou University Chuzhou China

ISBN: (数字)9798331533038

ISBN: (纸本)9798331533045

Financial institutions face increasing challenges regarding credit card fraud incidents because fraud data lacks balance between legitimate and fraudulent transactions. the unbalanced nature of fraud data poses challenges to detection methods because it remains difficult to identify fraud successfully. this research examines different sampling approaches which will enhance model efficiency in identifying fraudulent activities. the research examines two individual methods-Random Undersampling (RUS) and Synthetic Minority Oversampling Technique (SMOTE)-alongside three hybrid approaches, including RUS + Random Oversampling (ROS), RUS + SMOTE, and RUS + SMOTE Tomek, to determine the optimal strategy for enhancing detection accuracy. Several machine learning models, including Random Forest, Logistic Regression, XGBoost, AdaBoost, LightGBM, and Neural Networks, were evaluated, with a specific focus on the impact of hyperparameter optimization in boosting model efficiency. Comparative analysis revealed the superiority of hybrid sampling techniques, particularly RUS + SMOTE, in reducing false positives and negatives. LightGBM exhibited the best performance, achieving a Matthews Correlation Coefficient (MCC) of $\mathbf{0. 8 5}$, underscoring its effectiveness in fraud detection tasks. this research provides valuable insights for enhancing fraud detection systems and offers recommendations for future improvements in sampling strategies and model optimization.

关键词： Logistic regression Machine learning algorithms Computational modeling Neural networks Credit cards Boosting Hyperparameter optimization Fraud Random forests Optimization

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Validity Analysis of Simulation-based Testing concerning Free-space Detection in Autonomous Driving 6

Validity Analysis of Simulation-based Testing concerning Fre...

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6th international conference on Vehicle Technology and Intelligent Transport systems (VEHITS)

作者： Reway, Fabio Drechsler, Maikol Wachtel, Diogo Huber, Werner TH Ingolstadt CARISSMA Ingolstadt Germany

ISBN: (纸本)9789897584190

Automated vehicles must perceive their environment and accordingly plan a safe trajectory to navigate. Camera sensors and image processing algorithms have been extensively used to detect free-space, which is an unoccupied area where a car can safely drive through. To reduce the effort and costs of real test drives, simulation has been increasingly used in the automotive industry to test such systems. In this work, an algorithm for free-space detection is evaluated across real and virtual domains under different environment conditions: daytime, night time and fog. For this purpose, an algorithm is implemented to ease the process of creating ground-truth data for this kind of test. Based on the evaluation of predictions against ground-truth, the test results from the real test scenario are compared with its corresponding virtual twin to analyze the validity of simulation-based testing of a free-space detection algorithm.

关键词： Automated Driving Testing Validation Simulation

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Iberian conference on Information systems and Technologies, CISTI

Iberian Conference on Information Systems and Technologies, ...

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16th Iberian conference on Information systems and Technologies, CISTI 2021

ISBN: (纸本)9789895465910

the proceedings contain 367 papers. the topics discussed include: shared dock-less vehicle location distribution dataset visualizer;fostering inclusive education through universal instructional design;determinants of e-voting acceptance in Chile: an approach based on the UTAUT model;the role of marketing in the development of digital touchpoints;physical unclonable functions based hardware obfuscation techniques: a state of the art;web accessibility on online platforms for the tourism sector in Portugal;world-class universities, a dynamic multivariate analysis through international rankings;UNAME tool: automatic generation of computer resources monitoring scripts;agile governance guidelines for software development SMEs;on the evaluation of machine learning algorithms for hyperspectral image classification on a heterogeneous computing device;partitional clustering based on PCA method for segmentation of products;and nice payer - a software platform for registering debtors with past due debts.

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25th international conference on Tools and algorithms for the Construction and Analysis of systems conference series, TACAS 2019 held as part of the 22nd European Joint conferences on theory and Practice of Software, ETAPS 2019

25th International Conference on Tools and Algorithms for th...

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25th international conference on Tools and algorithms for the Construction and Analysis of systems conference series, TACAS 2019 held as part of the 22nd European Joint conferences on theory and Practice of Software, ETAPS 2019

ISBN: (纸本)9783030174644

the proceedings contain 22 papers. the special focus in this conference is on Tools and algorithms for the Construction and Analysis of systems conference series. the topics include: Shepherding hordes of markov chains;optimal time-bounded reachability analysis for concurrent systems;minimal-time synthesis for parametric timed automata;Environmentally-Friendly GR(1) Synthesis;stocHy: Automated Verification and Synthesis of Stochastic Processes;synthesis of symbolic controllers: A parallelized and sparsity-aware approach;iRank: A variable order metric for deds subject to linear invariants;binary decision diagrams with edge-specified reductions;effective entailment checking for separation logic with inductive definitions;Digital Bifurcation Analysis of TCP Dynamics;the mCRL2 Toolset for Analysing Concurrent systems: Improvements in Expressivity and Usability;verifying safety of synchronous fault-tolerant algorithms by bounded model checking;measuring masking fault-tolerance;PhASAR: An Inter-procedural Static Analysis Framework for C/C++;automatic analysis of consistency properties of distributed transaction systems in maude;multi-core On-the-Fly Saturation;Specification and efficient monitoring beyond STL;VyPR2: A framework for runtime verification of python web services;constraint-Based Monitoring of Hyperproperties;tail probabilities for randomized program runtimes via martingales for higher moments;computing the expected execution time of probabilistic workflow nets.

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Optimal Space Lower Bound for Deterministic Self-Stabilizing Leader Election algorithms 25

Optimal Space Lower Bound for Deterministic Self-Stabilizing...

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25th international conference on Principles of Distributed systems, OPODIS 2021

作者： Blin, Lélia Feuilloley, Laurent Le Bouder, Gabriel Sorbonne Université Université d’Evry-Val-d’Essonne CNRS LIP6 UMR 7606 4 place Jussieu Paris75005 France Univ. Lyon Université Lyon 1 LIRIS UMR CNRS 5205 LyonF-69621 France Sorbonne Université CNRS INRIA LIP6 UMR 7606 4 place Jussieu Paris75005 France

ISBN: (纸本)9783959772198

Given a boolean predicate Π on labeled networks (e.g., proper coloring, leader election, etc.), a self-stabilizing algorithm for Π is a distributed algorithm that can start from any initial configuration of the network (i.e., every node has an arbitrary value assigned to each of its variables), and eventually converge to a configuration satisfying Π. It is known that leader election does not have a deterministic self-stabilizing algorithm using a constant-size register at each node, i.e., for some networks, some of their nodes must have registers whose sizes grow with the size n of the networks. On the other hand, it is also known that leader election can be solved by a deterministic self-stabilizing algorithm using registers of O(log log n) bits per node in any n-node bounded-degree network. We show that this latter space complexity is optimal. Specifically, we prove that every deterministic self-stabilizing algorithm solving leader election must use Ω(log log n)-bit per node registers in some n-node networks. In addition, we show that our lower bounds go beyond leader election, and apply to all problems that cannot be solved by anonymous algorithms. © Lélia Blin, Laurent Feuilloley, and Gabriel Le Bouder.

关键词： Topology

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