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检索条件"主题词=software algorithms"

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SecureML: Machine Learning-Powered Malware Detection

SecureML: Machine Learning-Powered Malware Detection

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International Conference on Advances in Information Technology (ICAIT)

作者： Animay Awasthi Mohd Ahsan Vanusha D Delsi Robinsha S Department of ComputingTechnologies School of Computing SRM Institute of Science and Technology Kattankulathur Tamilnadu India Department of Computing Technologies Faculty of Engineering and Technology School of Computing SRM Institute of Science and Technology Kattankulathur Tamilnadu India

ISBN: (数字)9798350383867

ISBN: (纸本)9798350383874

As malware threats become increasingly complex, the development of advanced detection systems is necessary to protect digital assets. SecureML Using Machine Learning presents an innovative approach to combat the escalating threat of malicious software by leveraging machine learning algorithms. This research paper outlines the design, implementation, and evaluation of SecureML, emphasizing its effectiveness in detecting both known and novel malware strains. Through comprehensive feature selection techniques and algorithmic comparison, SecureML identifies crucial features and selects the Random Forest algorithm as the most effective for malware detection, achieving an impressive accuracy rate of 99.40% on the test set. The system's low false positive and false negative rates validate its robustness and reliability in accurately distinguishing between benign and malicious files. SecureML demonstrates significant potential in bolstering cybersecurity defenses and safeguarding digital assets against evolving malware threats.

关键词： Resistance Machine learning algorithms Accuracy software algorithms Feature extraction Malware Robustness

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Task Planning for Hybrid Space-Ground Debris Removal Based on Simulated Annealing Algorithm

Task Planning for Hybrid Space-Ground Debris Removal Based o...

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IEEE International Conference on Unmanned Systems (ICUS)

作者： Yanlai Zhao Yuehui You Fei Cheng Tianxi Liu Weige Zhu Cheng Wei School of Astronautics Harbin Institute of Technology Harbin China Shanghai Academy of Spaceflight Technology Shanghai China

ISBN: (数字)9798350384185

ISBN: (纸本)9798350384192

The research investigated the task planning problem of space debris removal in Space-Ground mixed zones using multiservice satellites based on the simulated annealing algorithm. The optimization algorithm module of the self-developed SpaceSim software at Harbin Institute of Technology's School of Astronautics was utilized to compute the trajectory adjustment velocity pulses for the service satellites and to display the orbital maneuvering process directly within the software, resulting in clear optimization outcomes for the debris removal tasks. For scenarios involving satellite disintegration, the simulated annealing algorithm optimized the multi-orbit Lambert algorithm to determine the required velocity pulse magnitude for each service satellite to clear each target space debris. This process established a velocity pulse matrix, which was further processed using dynamic programming algorithms. In cases where specific space debris positions posed challenges, an emergency satellite launch method was employed to facilitate debris removal at target locations.

关键词： Visualization Satellites Space debris Heuristic algorithms software algorithms Clustering algorithms Simulated annealing software Planning Optimization

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Advancing Vascular Dementia Diagnosis Through Salp Swarm Optimized Convolutional Neural Network

Advancing Vascular Dementia Diagnosis Through Salp Swarm Opt...

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International Conference on Computation System and Information Technology for Sustainable Solutions (CSITSS)

作者： Nivedita Manohara Mathkunti U Ananthanagu Vidya N Abdulpur D. Mangaiyarkarasi Anitha S Department of Computer Science & Engineering Alliance School of Advanced Computing Alliance Univerisity Bengaluru Karnataka India Department of Electrical Engineering Dr.D.Y Patil Pratishthan's College of Engineering Kolhapur Maharastra India Computer Science & Engineering Vel Tech Rangarajan Dr.Sangunthala R&D Institute of Science and Technology Avadi India Department of Artificial Intelligence & Machine Learning Sri Sairam College of Engineering Anekal (VTU) Bengaluru Karnataka India

ISBN: (数字)9798331505462

ISBN: (纸本)9798331505479

Vascular Dementia (VD) is a form of cognitive impairment seen in individuals, restricting from problems with blood vessels supplying the brain. These issues lead to strokes or reduced blood flow and gradually lead to the development of vascular dementia. Since it tends to progress slowly, diagnosis often comes after significant brain damage making prevention is crucial. Early identification of risk factors are vital to mitigate the risk of irreversible cognitive decline associated with vascular dementia. Accordingly, this research proposes an optimized neural network model for predicting vascular dementia at its earlier to improve the quality of life. The initial stage in this research involves preprocessing, where the input data is cleaned and normalized. These steps ensure that the vascular dementia dataset is cleaned of inconsistencies and prepared with normalized features for accurate analysis and modeling. Following preprocessing, relevant data features are selected using the chi-square approach, making the classification task easier. Finally, classification is performed utilizing a Convolutional Neural Network (CNN) and for fine-tuning of CNN parameters Salp Swarm Optimization (SSO) Algorithm is implemented. The execution of proposed work is processed using Python software and the outcome reveals superior performance in terms of accuracy and precision. Thereby the proposed method provides better performance with an accuracy of 94.5%, contrasted to existing methods in predicting VD.

关键词： Accuracy software algorithms Data preprocessing Predictive models software Classification algorithms Convolutional neural networks Biological neural networks Dementia Python

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Island-Oriented Multi-Energy Reef Pan Power Plant and Its Application - Layout Optimization Study and Capacity Exploration

Island-Oriented Multi-Energy Reef Pan Power Plant and Its Ap...

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Electrical Engineering (CIYCEE), IEEE China International Youth Conference on

作者： Weijie He Fanrong Wei Xiangning Lin Samir M. Dawoud The State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan China The Department of Electrical Power and Machines Engineering Tanta University Tanta Egypt

ISBN: (数字)9798331530174

ISBN: (纸本)9798331530181

In response to the problem of unreasonable power supply layout on islands, this paper fully evaluates the status of wind/light/wave energy resources in the island and its surrounding reef area scenarios. Then, based on bladeless wind turbines, floating solar panels and oscillating float wave energy capture devices, an integrated construction layout plan for multi-energy reef power stations was proposed. And with the maximum annual total power generation as the objective function, a layout optimization and capacity exploration model was established. The CPLEX mixed integer programming algorithm was used to solve the model example. The example results show that the construction layout plan proposed in this paper is reasonable and feasible, and has unique advantages in island scenarios.

关键词： Renewable energy sources Power supplies Layout software algorithms software Wind turbines Solar panels Wave energy conversion Power generation Optimization

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Exploring the Security Landscape of Underwater Positioning and Navigation Systems: An Attack Surface Analysis

Exploring the Security Landscape of Underwater Positioning a...

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Conference on Local Computer Networks (LCN)

作者： Hosam Alamleh Bilge Karabacak Computer Science University of North Carolina Wilmington Wilmington North Carolina Congdon School of Supply Chain University of North Carolina Wilmington Wilmington North Carolina

ISBN: (数字)9798350388008

ISBN: (纸本)9798350388015

Underwater positioning and navigation systems are vital for maritime operations but face significant security threats like spoofing, jamming, interception, sensor manipulation, and algorithm exploitation. This paper categorizes underwater navigation techniques (acoustic, GPS buoys, multi-sensor fusion, vision-based, hybrid) and analyzes their potential attack surfaces. To mitigate these threats, a multi-layered defense strategy is proposed, encompassing cryptographic authentication, secure communications, physical security, sensor redundancy, data validation, image authentication, and algorithm robustness. Specific countermeasures against jamming, spoofing, interception, sensor attacks, and algorithm attacks are discussed. A holistic approach integrating secure software practices, anomaly detection, and fusion technique diversity is emphasized to fortify system resilience against advanced persistent threats, ensuring maritime safety and security. This research contributes to understanding security vulnerabilities and providing a comprehensive mitigation framework for enhancing the resilience of underwater navigation systems.

关键词： Prevention and mitigation software algorithms Authentication Termination of employment Underwater navigation Robustness Cryptography

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Optimal Allocation of Distributed Generation and Electric Vehicles Charging Stations in A Part of The Egyptian Electrical Network Using Manta Ray Foraging Optimization

Optimal Allocation of Distributed Generation and Electric Ve...

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International Middle-East Power System Conference, MEPCON

作者： Zenhom M. Zenhom Tarek A. Boghdady Essam Aboul Zahab Shady H. E. Abdel Aleem Electric Engineering Department Ahram Canadian University Giza Egypt Electric Engineering Department Cairo University Giza Egypt Electric Engineering Department Institute of Aviation Engineering and Technology Giza Egypt

ISBN: (数字)9798350379648

ISBN: (纸本)9798350379655

Fossil fuels are burned in conventional transportation vehicles, which release greenhouse gases into the atmosphere. The expanding population requires the quick creation of an alternative way of transportation. Since they emit less pollutants into the environment, Electric Vehicles (EVs) will be the foundation of transportation systems of the future. On the other hand, it is impossible to overlook the negative effects of EV charging station demands on the Distribution Network (DN). This paper introduces a suggested approach to determine the optimal allocation of Electric Vehicles Charging Stations (EVCS) and Distributed Generation (DG) units simultaneously to minimize total losses and voltage deviation and maximize Electric Vehicles Hosting Capacity (EV-HC). However, a constant load type is assumed in most DG and EVCS allocation studies, three different time-varying load models are considered in this work to evaluate the proposed technique robustness. When compared to other optimization techniques, the Manta Ray Foraging Optimization (MRFO) algorithm shows better performance in solving the optimization problem. MatLab software is utilized to simulate and test the suggested method on a real 59-bus DN in Cairo.

关键词： Uncertainty software algorithms Transportation Voltage Charging stations Robustness Distributed power generation Resource management Optimization Load modeling

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Improve The Efficiency and Code Quality Using A Framework Based On Big Data

Improve The Efficiency and Code Quality Using A Framework Ba...

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Communications and Information Technologies (GCCIT), Global Conference on

作者： Aarati Chavan Uruj Jaleel Nisha Auti Department of Computer Science and Engineering Kalinga University Raipur Department of Computer Science and Engineering Bharati Vidyapith Pune

ISBN: (数字)9798350388916

ISBN: (纸本)9798350388923

The primary objective of utilizing recommendation frameworks is to pick up the efficiency of the designer by prescribing documents to alter. Now days use of recommendation systems while developing software increasing in order to speed up the process of software development by software developers. Data Collection will be depended on Primary and Secondary resources. The data will be accumulated from the subjective research will turn into the reason for the plan of quantitative examinations. We utilized Mylyn data. Mylyn records association follows from the Obscuration IDE and files them in the Overshadowing Bugzilla framework. In the present study, we will be utilized a non-probability testing procedure that is accommodation inspecting. Convenience sampling is typically utilized for gathering an extensive number of data. Distinctive kinds of systems can be utilized to assess diverse research results and make a sound decision for a given overview data. In this examination, data will be investigated utilizing distinctive quantitative and subjective methods.

关键词： Productivity Collaborative filtering software algorithms Programming software Information and communication technology History Recommender systems Testing software development management

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Task Offloading in Cloud-Edge Collaborative Environment Based on Deep Reinforcement Learning and Fuzzy Logic

Task Offloading in Cloud-Edge Collaborative Environment Base...

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software Engineering and Artificial Intelligence (SEAI), IEEE International Conference on

作者： Xiaojun Wu Lulu Wang Sheng Yuan Wei Chai School of Software Engineering Xi'an Jiaotong University Xi’an China

ISBN: (数字)9798350374346

ISBN: (纸本)9798350374353

Cloud-edge collaborative computing is a key technology towards delay-sensitive and computation-intensive applications in future cellular networks. This paper considers the combination of edge computing and cloud computing, and studies the problem of task offloading in an “End-Edge-Cloud” collaborative architecture optimized for Quality of Experience (QoE) and system stability. To this end, this paper proposes a dual experience pool task offloading algorithm based on deep reinforcement learning and fuzzy logic (FDRL-DEP). Considering dynamic offloading requests and time-varying communication conditions, this paper models the problem as a Markov process and applys Dueling Deep Q-Network (Dueling DQN) to implement it. And this paper designs a two-stage fuzzy logic controller to improve the instability of Dueling DQN to the system when the parameters are not optimized. Via extensive simulation and theoretical analyses, this paper shows the effectiveness of the proposed FDRL-DEP framework on improving QoE and system stability.

关键词： Fuzzy logic Training Cloud computing software algorithms Collaboration Deep reinforcement learning Stability analysis

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Real-Time Task Scheduling using Bio-Inspired algorithms: A Comparative Study of ACO, PSO, and GWO

Real-Time Task Scheduling using Bio-Inspired Algorithms: A C...

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software, Systems and Information Technology (SSITCON), International Conference on

作者： Surekha Paneerselvam Department of Electrical and Electronics Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (数字)9798350352931

ISBN: (纸本)9798350352948

This work investigates the use of bio-inspired algorithms in real-time task scheduling, whereby their capabilities are explored in intelligent computing to enhance performance optimization. Three influential bio-inspired algorithms, including Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), and Grey Wolf Optimization (GWO), are employed in the real-time task scheduling process. The dataset utilized includes $\mathbf{6, 8 0 0}$ periodic task sets, with each set including 9 tasks. The evaluation of the proposed algorithms is based on two primary metrics: success ratio, which quantifies the proportion of activities finished within their established time limits, and CPU utilization factor, which evaluates the effectiveness of processor utilization. The success ratio and CPU utilization were evaluated based on low, high and very high CPU load on ACO, PSO and GWO. Based on the observations, it is observed that GWO performed significantly better than ACO and PSO. The empirical findings illustrate the efficacy of bioinspired algorithms in augmenting job scheduling for real-time systems, therefore providing significant insights into their suitability for optimizing system performance.

关键词： Machine learning algorithms Processor scheduling Heuristic algorithms System performance software algorithms Prediction algorithms Dynamic scheduling software systems Real-time systems Optimization

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Fortifying Cloud Data Security with the Maritime Search and Rescue Algorithm

Fortifying Cloud Data Security with the Maritime Search and ...

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Data Science and Information System (ICDSIS), IEEE International Conference on

作者： K M Monica Parameswaran T J. Swapna S. Prabu S. Kaliappan School of Computer Scienceand engineering VIT University Chennai India Department of Computer science and Engineering School Of Engineering and Technology CMR University lakeside campus Bangalore India Department of Computer science and Engineering Veltech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai Tamilnadu India Department of ECE Mahendra Institute of Technology Namakkal India Division of Research and Development Lovely Professional University Phagwara Punjab India

ISBN: (数字)9798350381665

ISBN: (纸本)9798350381672

Cloud computing has fundamentally transformed the accessibility and payment models of services within distributed system environments. In response to heightened security concerns, cloud service providers offer diverse resources spanning Infrastructure, software, Platform, and Database services, supported by security measures such as Service Level Agreements (SLAs), access control rules, and cryptographic methods. This paper introduces a novel data encryption technique, termed Data Security in Cloud Computing using Maritime Search and Rescue Algorithm (DSCC-MSRA). By integrating an enhanced cypher block chaining algorithm with logical substitution and the Maritime Search and Rescue Algorithm (MSRA) for key generation, this method provides a unique approach to encryption. Through rigorous optimization and analysis, it has undergone significant refinement, with comparisons against industry-standard algorithms showcasing its efficacy. The primary objective is to elevate encryption procedures and introduce complexity to cryptanalysis, ultimately enhancing data security in cloud computing.

关键词： Cloud computing Ciphers Databases software algorithms software Encryption software measurement

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