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检索条件"主题词=software algorithms"

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A Novel Android software for Comprehensive Ability Testing Based on HCI and Data Interaction Algorithm

A Novel Android Software for Comprehensive Ability Testing B...

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Sentiment Analysis and Deep Learning (ICSADL), International Conference on

作者： Zuyi Wang Xiaoli Wang Binbin Ren SanYa Aviation & Tourism college Sanya Hainan China

ISBN: (数字)9798350396157

ISBN: (纸本)9798350396164

This study proposes a comprehensive ability testing software based on the Android platform, taking into account human-computer interaction principles and advanced data interaction algorithms. By optimizing the user interface to achieve seamless interaction and applying complex algorithms to improve test accuracy, it comprehensively assesses multiple skills. Its adaptability to Android devices makes it widely used in fields such as education and recruitment. Experimental results show that this Android-based software development model is highly scalable and flexible, allowing developers to easily create applications with different functions. Services in the middleware layer simplify the development process, while the user interface provides an intuitive way for users to interact with the device. The use of the Linux kernel ensures the stability and efficiency of the entire system. In addition, the research also uses hybrid encryption technology, which takes full advantage of AES and RSA algorithms. The AES key is encrypted with the RSA public key, and the plain-text information is encrypted with the AES key, which maintains the security of the AES key during transmission and ensures the security of the data in transit. This unique combination of algorithms creates a more secure and reliable data encryption solution. The experiment section focuses on Android software tests and simulations and oo compile code using the NDK to download and install the Android NDK. Since make and gcc are necessary for NDK compilation, this study establishes a Linux development environment using Cygwin. Cygwin is a Unix simulation environment on Windows, which is effective for Unix/Linux-savvy developers and application porting.

关键词： Operating systems Linux software algorithms Public key Stability analysis Encryption Middleware

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Modularization in Object Oriented software: A Comparative Study

Modularization in Object Oriented Software: A Comparative St...

引用

Artificial Intelligence, Blockchain, Cloud Computing, and Data Analytics (ICoABCD), International Conference on

作者： Sandi Tendean Daniel Siahaan Anny Yuniarti Department of Informatics Institut Teknologi Sepuluh Nopember Surabaya Indonesia Universitas Widya Dharma Pontianak Pontianak Indonesia

ISBN: (数字)9798350368451

ISBN: (纸本)9798350368468

The process of software modularization is essential to comprehending complex software systems. There are a variety of implementation approaches that provide different approaches to software architectural delineation. The advancement of programming languages and techniques presents novel challenges in determining suitable approaches for creating cohesive and separate modules. In this study, modularization increases the understanding of software quality by breaking apart the source code incorporated into packages into coherent and independent groupings. This study assesses the effectiveness of various architectures that integrate clustering algorithms, i.e. Agglomerative, K-means, and K-medoids, with three word-embedding techniques, i.e. BERT, FastText, and GloVe. The evaluation was conducted on five java-based applications with varying number of packages developed by different prominent developers. The primary objective of this study is to identify the optimal combination of clustering and word embedding algorithms that could yield high cohesion and low coupling of java-class modules. The results demonstrate that the combination of K-means and FastText outperforms other architectures in terms of cohesion, with a CH Index value of 10.66 and coupling with a DB Index value of 1.76 of clustered classes. In addition, regarding accuracy and similarity with ground truth, the combination of distance-based clustering algorithms and FastText outperformed other architectures.

关键词： Couplings Source coding Object oriented modeling software algorithms Clustering algorithms Computer architecture software quality software systems Indexes Object recognition

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Adaptive Mitigation of Blackhole Attacks in Blockchain-Enhanced software Defined Networks

Adaptive Mitigation of Blackhole Attacks in Blockchain-Enhan...

引用

IEEE International Conference on Performance, Computing and Communications (IPCCC)

作者： Mehmed K. Uludag Murat Karakus Evrim Guler Suleyman Uludag Department of Computer Science and Engineering University of Michigan Ann Arbor Department of Software Engineering Ankara University Ankara Türkiye Department of Computer Engineering Bartin University Bartin Türkiye Department of Computer Science University of Michigan Flint MI USA

ISBN: (数字)9798350367942

ISBN: (纸本)9798350367959

software-Defined Networking (SDN) and Blockchain (BC) are transformative technologies reshaping network management and security, utilizing their synergies. SDN’s centralized control enhances flexibility and efficiency but introduces vulnerabilities due to its single point of control. With its decentralized and immutable ledger, BC offers a solution by distributing control and providing a tamper-proof audit trail. This paper integrates these technologies to address blackhole attacks—a critical vulnerability where compromised SDN controllers disrupt network performance. We propose Blockchain-Enhanced SDN for Adaptive Path Finding (BeS4APF) algorithm against blackhole attacks in the multidomain SDNs. The algorithm maintains a high Packet Delivery Ratio (PDR) by dynamically adjusting network paths in response to node failures. The BeS4APF algorithm presented effectively maintains a high PDR by dynamically adjusting paths in response to node failures. The methodology involves monitoring the network, detecting compromised nodes, and recalculating optimal paths using Dijkstra’s algorithm and node-disjoint path selection. Experiments with synthetic networks of varying sizes (from 60 to 120 domains) demonstrate that the algorithm successfully handles domain-compromising node attacks, maintaining high PDR even with increasing stochastic disruptions. Our preliminary results show that, while PDR slightly deviates and recovers in smaller networks, it stabilizes towards almost 100% in larger networks after initial adjustments. This work advances the integration of SDN and BC, offering a robust approach to securing modern networks against evolving stochastic attack scenarios and threats.

关键词： Measurement Adaptive systems Heuristic algorithms Prevention and mitigation software algorithms Robustness Security software defined networking Monitoring Resilience

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Resilient software Defined Satellite Networks: Combining Clustering Techniques with Efficient Routing Protocols

Resilient Software Defined Satellite Networks: Combining Clu...

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International Conference on software Defined Systems (SDS)

作者： Juliano Antonio da Silva Paulo Mendes Edison Pignaton de Freitas Graduate Program in Computer Science Federal University of Rio Grande do Sul Porto Alegre Brazil Central Research and Technology Airbus Munich Germany

ISBN: (数字)9798331518325

ISBN: (纸本)9798331518332

Low Earth Orbit satellite constellations are highly mobile and thus have time-varying network topologies. Such time-varying networks face various challenges due to intermittently available links and devices. Consequently, many routing algorithms that work well on the terrestrial Internet may not be suitable for Low Earth Orbit (LEO) constellations. This paper provides an analysis of the impact that different types of routing algorithms may have on the performance of LEO constellations. The provided study analyses not only link-state routing algorithms, as used in well-known routing protocols for LEO constellations such as Contact Graph Routing (CGR), which follows a software Defined Networking (SDN) approach, but also distance-vector algorithms, as well as the potential combination of link-state and distance-vector algorithms when network clusters are used in a LEO constellation.

关键词： Satellites Heuristic algorithms software algorithms Clustering algorithms Low earth orbit satellites Routing software Routing protocols Vectors software defined networking

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software Development for Modeling Microstructures of Polycrystalline Materials by Cellular Automata Method

Software Development for Modeling Microstructures of Polycry...

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Advanced Technology (KhPIWeek), IEEE KhPI Week on

作者： Valeriia Hritskova Oleh Semenenko Mariia Shapovalova Oleksii Vodka Department of mathematical modeling and intelligent computing in engineering National Technical University “Kharkiv Polytechnic Institute” Kharkiv Ukraine

ISBN: (数字)9798350384499

ISBN: (纸本)9798350384505

This paper deals with software package development for 3D modeling of material microstructures using the 3D cellular automata method (MatViz3D). The software package includes algorithms for modeling based on the Moore, von Neumann, radial, and probabilistic cellular automata models. It also includes a 3D scene construction module using OpenGL for visualizing microstructures, a program interface design module, and modules for calculating geometric twodimensional and three-dimensional characteristics of grains. Finally, the software package includes algorithms for comparing the obtained characteristics with experimental microstructures, using script graphs for this purpose. MatViz3D has been developed using the $\mathbf{C}++$ programming language and the OpenGL library. The program interface has been designed using the Qt framework. The algorithms for comparing the obtained characteristics with experimental microstructures have been implemented using the Python programming language and the Seaborn library.

关键词： Visualization Solid modeling Three-dimensional displays software packages software algorithms Automata Probabilistic logic Libraries Microstructure Surface treatment

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An Alternative Boosting-based software Reliability Prediction Method

An Alternative Boosting-based Software Reliability Predictio...

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Pacific Rim International Symposium on Dependable Computing

作者： Jingchi Wu Junjun Zheng Tadashi Dohi Hiroyuki Okamura Graduate School of Advanced Science and Engineering Hiroshima University Higashi-Hiroshima Japan

ISBN: (数字)9798331540746

ISBN: (纸本)9798331540753

Although a huge number of software reliability models (SRMs) have been proposed in the past literature, there is no unique SRM with satisfactory prediction accuracy, because it has been known that the best goodness-of-fit SRM to the underlying data is not always equivalent to the best prediction model for the future software fault-count process. It is common to select an appropriate SRM with highest goodness-of-fit to the underlying software fault-count data based on any information criteria such as Akaike information criterion (AIC). In this paper we focus on a prediction SRM consisting with linearly weighted combinational (LWC) non-homogeneous Poisson process (NHPP)-based SRMs, and overview an AdaBoosting-based approach by Li et al. (2012) to determine the optimal weights for the LWC NHPP-based SRMs. Next, we propose a refined AdaBoosting technique to keep the steps of original AdaBoosting, in order to present the original predictive performance of AdaBoosting in software reliability.

关键词： Accuracy Computational modeling software algorithms Predictive models Prediction algorithms software Data models software reliability

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Development of a Low-Cost Fluorescence Analyzer Based on software Filtering for Reading Fluorescence Strips

Development of a Low-Cost Fluorescence Analyzer Based on Sof...

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International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)

作者： Fang Li Zhifeng Wu Jinlai Yuan Yuyang Feng Beijing University of Chemical Technology

ISBN: (数字)9798331507398

ISBN: (纸本)9798331507404

Lateral flow assays (LFA) are paper-based rapid detection technologies that enable efficient and convenient quantitative or qualitative analysis of samples in a very short period. This research focuses on the development of a low-cost fluorescence analyzer with a unique design that successfully achieves high-precision quantitative reading of fluorescence lateral immunochromatography strips, eliminating the traditional requirements for hardware filtering, electromagnetic shielding, and other complex technologies. The critical role of Fast Fourier Transform (FFT) filter technology in processing weak positive test strip signals is thoroughly examined. Additionally, we have developed a comprehensive and reliable fluorescence characteristic peak recognition method, effectively distinguishing and quantifying the fluorescence signal on the test strip, providing robust technical support for accurate diagnosis. Tuberculosis samples were selected as test objects in this study. Comparative experiments demonstrated that the performance of the low-cost fluorescence analyzer is comparable to that of high-end commercial equipment, such as the RTR-FS100 gold standard instrument, thereby confirming its technical feasibility and application potential. The core contribution of this paper is the effective reduction of the analyzer's reliance on expensive hardware components through software algorithm optimization strategies, which significantly lowers production costs. This achievement not only paves the way for the popularization and application of immunochromatography technology but also provides an important reference for the research and development of low-cost and portable medical detection equipment, showcasing broad application prospects and social value.

关键词： Strips Filtering Fast Fourier transforms Tuberculosis software algorithms Fluorescence software Hardware Immune system Testing

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Discovery of Evolving Relationships of software Vulnerabilities

Discovery of Evolving Relationships of Software Vulnerabilit...

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IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA)

作者： Hailey Sparks Krishnendu Ghosh Department of Computer Science College of Charleston South Carolina USA

ISBN: (数字)9798350386745

ISBN: (纸本)9798350386752

Discovering the risks posed by software vulnerabilities is a challenge. software vulnerabilities are often not listed and studies have shown 50.3% of the reports do not include the list of vulnerable libraries. Thus, it becomes critical to maximize the understanding of the vulnerability reports and the trends in vulnerabilities. In this work, a novel tool is created that is able to connect the vulnerabilities with time and identify subsets of vulnerabilities that are *** the first step of the model, a text network is created from the vulnerability reports of each month in a year. Then, a temporal network is constructed from text networks. Temporal network theoretic properties are evaluated on the model to understand the vulnerability trends and the evolution of relationships amongst the vulnerabilities. The analysis leverages on the community detection algorithms on text networks. The dynamics of evolving relationships of the software vulnerabilities are extracted using biclustering algorithms, and the statistical significance of the biclusters is evaluated. Experimental results based on vulnerability reports are analyzed and presented.

关键词： Privacy Heuristic algorithms software algorithms Market research software Libraries Security Intelligent systems Detection algorithms

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Enhancing DDoS Attack Detection deploying Machine Learning in software Defined Networking Environment

Enhancing DDoS Attack Detection deploying Machine Learning i...

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Intelligent Technologies (CONIT), International Conference on

作者： Anshika Sharma Himanshi Babbar Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (数字)9798350349900

ISBN: (纸本)9798350349917

The Internet of Things, or IoT, has become essential to contemporary industrial operations due to the widespread use of devices that are connected to the Internet in industrial settings. However industrial networks are now more vulnerable to a range of cybersecurity risks, such as Distributed Denial of Service (DDoS) attacks, due to their growing connectedness. In this paper, a novel method that combines hybrid machine learning (ML) algorithms with software Defined Networking (SDN) approaches has been provided to identify DDoS attacks in the IoT space. By utilising the Edge-IIoT dataset, which incorporates information from IoT devices and SDN infrastructure, one may improve the precision and resilience of DDoS detection by combining feature extraction techniques with hybrid ML models. The suggested technique effectively detects DDoS assaults with few false positives, as seen by the experimental findings. This improves the safety stance of industrial networks against the ever-evolving threat landscape. A comparison of the suggested hybrid ML model’s accuracy, precision, recall, and F1-score has been made with the different algorithms including KNN [1], RF [2] and LR [3]. The proposed accuracy rises to 99.10%, while the accuracy rates of [1], [2] and [3] are, respectively, 97.15%, 97.99% and 98.39%.

关键词： Radio frequency Accuracy Machine learning algorithms Image edge detection software algorithms Machine learning Denial-of-service attack

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K-12 Agile Learning with Educational software and Robotics Technology

K-12 Agile Learning with Educational Software and Robotics T...

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Electronic Engineering, Information Technology & Education (EEITE), International Conference in

作者： Antonios J. Konstantaras Emmanuel Maravelakis Giorgos Giannakakis Lefteris Doitsidis Nikolaos Spanoudakis Edward Duca Department of Electronic Engineering Hellenic Mediterranean University Chania Greece Biomedicine Laboratory Foundation for Research and Technology-Hellas Heraklion Greece School of Production Engineering and Management Technical University of Crete Chania Greece Department of Mathematics and Science Education University of Malta Msida Malta

ISBN: (数字)9798350372878

ISBN: (纸本)9798350372885

This article discusses the application of agile learning Scrum sprints targeted to K-12 primary education students using educational robotics. Educational robotics are a suitable tool for learning via experimentation, trial & error and retrial, which when inflicted in a form of game-play becomes pleasantly adopted by the students. This has been conducted by implementing carefully designed cumulative sprints which are repeating a certain agile learning process that breaks a larger problem into smaller parts/milestones, designing algorithms as to how to proceed step-by step towards solving the larger overall problem. This is done by evaluating and re-evaluating the progress of every step, until an outcome has been reached and reflected upon. The aforementioned process applies both and equally to tutors and students, individually and as team members, respectfully. Results of the application of agile learning in K-12 educational robotics demonstrate the ability of young K-12 students to cope and realize educational robotics construction, system understanding and algorithm design and implementation via Scratch 3 programming.

关键词： Education software algorithms software Robots Programming profession

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