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检索条件"丛书名=Lecture Notes in Networks and Systems"

共 9495 条记录，以下是651-660 订阅

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Detecting Standard Library Functions in Obfuscated Code 1

引用

Intelligent systems Conference (IntelliSys)

作者： Shroyer, Alexander Swany, D. Martin Indiana Univ Bloomington IN 47405 USA

ISBN: (数字)9783031477249

ISBN: (纸本)9783031477232;9783031477249

Binary analysis helps find low-level system bugs in embedded systems, middleware, and Internet of Things (IoT) devices. However, obfuscation makes static analysis more challenging. In this work we use machine learning to detect standard library functions in compiled code which has been heavily obfuscated. First we create a C library function dataset augmented by obfuscation and diverse compiler options. We then train an ensemble of Paragraph Vector-Distributed Memory (PVDM) models on this dataset, and combine their predictions with simple majority voting. Although the average accuracy of individual PV-DM classifiers is 68%, the ensemble is 74% accurate. Finally, we train a separate model on the graph structure of the disassembled data. This graph classifier is 64% accurate on its own, but does not improve accuracy when added to the ensemble. Unlike previous work, our approach works even with heavy obfuscation, an advantage we attribute to increased diversity of our training data and increased capacity of our ensemble model.

关键词： Internet of things Data science Neural networks

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Case-Based Spam Filtering for Encrypted Emails 3rd

Case-Based Spam Filtering for Encrypted Emails

引用

3rd International Conference on Network Security and Blockchain Technology

作者： Chaki, Shreeja Sarkar, Anindita Khatua, Piyali Bagchi Kundu, Anirban Amity Univ Kolkata W Bengal India Univ Calcutta Kolkata W Bengal India Netaji Subhash Engn Coll Kolkata W Bengal India

ISBN: (纸本)9789819780501;9789819780518

Email has become the de facto standard for communication and attackers are taking this opportunity to send junk emails, making it difficult for recipients to distinguish between spam and not spam. In this article, our goal is to build a spam filtering framework by considering the best-known approaches. Pretty Good Privacy (PGP) is a well-known cryptography technique for secure communication via encrypted and decrypted emails. To make communication more secure, Homomorphic Encryption (HE) is used for processing emails without revealing their contents. Email Spam Filtering is another approach for classifying whether emails are spam or not spam. For deciding the suitable classifier from Support Vector Machine, Random Forest, Logistic Regression, and KNN, we consider three cases where the input data consists of the ciphertext of the email as well as the metadata of the email content. Case 1 simply performs the classification over the plaintext of the email. Case 2 performs the classification over the encrypted email without using any metadata while Case 3 considers the encrypted email as well as the metadata of the email content to perform the classification. KNN gives the best accuracy of 92.393% in plain body but it fails to give the best accuracy in the case of encrypted email. In all the cases of encrypted email, Logistic Regression gives the best accuracy compared to other classifiers with an accuracy of 83.219% in Case 2, 83.515% accuracy in Case 3.1, and 83.988% accuracy in Case 3.2, and 86.061% in Case 3.3.

关键词： Homomorphic encryption K Neighbor Logistic regression Random forest Support vector machine Pretty good privacy Spam filtering

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Advancing EEG Classification with Transformer Architecture: A Case Study on P300 Potentials for Assistive Devices

Advancing EEG Classification with Transformer Architecture: ...

引用

Intelligent systems Conference

作者： Goncalves Gomes de Novais, Victor Hugo Leal, Adriano Galindo IPT Inst Technol Res Sao Paulo SP Brazil

ISBN: (纸本)9783031663352;9783031663369

In this investigation, the Transformer architecture is applied to classify P300 event-related potentials in publicly available EEG data to augment assistive communication devices for individuals with impaired communication abilities. A detailed analysis comparing the Transformer model to established algorithms documented in the literature demonstrates its effectiveness in terms of classification accuracy, achieving a notable 95% accuracy rate, indicating its viability as a classifier for P300-based spellers. This result underlines the potential of advanced AI techniques in enhancing neurotechnology applications and suggests a new benchmark in the field. Future work will focus on refining these methods to further improve the usability and performance of assistive devices, aiming to bridge the gap between AI advancements and practical healthcare applications. This endeavour contributes to the biomedical engineering and artificial intelligence disciplines by offering insights into EEG data analysis and its implications for developing more accessible assistive technologies.

关键词： Transformer neural network EEG P300 Brain-computer interface Assistive devices LLM Artificial intelligence

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Combined Multicomponent Interventions for Older Adults in a Smart Home Living Lab 21st

Combined Multicomponent Interventions for Older Adults in a ...

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21st International Conference on Smart Technologies and Education (STE) on Smart Technologies for a Sustainable Future

作者： Segkouli, Sofia Mpaltadoros, Lampros Patenidis, Athanasios T. Alepopoulos, Vasilis Skoumbourdi, Aikaterini Grammatikopoulou, Margarita Kalamaras, Ilias Lazarou, Ioulietta Bamidis, Panagiotis Petsani, Despoina Konstantinidis, Evdokimos Santonen, Teemu Nikolopoulos, Spiros Kompatsiaris, Ioannis Votis, Konstantinos Tzovaras, Dimitrios Ctr Res & Technol Hellas CERTH Informat Technol Inst ITI Thessaloniki Greece Aristotle Univ Thessaloniki Sch Med Med Phys & Digital Innovat Lab Thessaloniki Greece European Network Living Labs Brussels Belgium Laurea Univ Appl Sci Vantaa Finland

ISBN: (纸本)9783031619045;9783031619052

Research indicates the additive effects and interrelation of physical exercise and cognitive training towards cognition maintenance and physical performance in older adults. Combined physical and cognitive interventions enabled by eHealth technologies, web applications and wearable sensors hold a great potential for the improvement of physical and cognitive status of older adults. Living laboratory strategies and mechanisms are considered effective spaces for the implementation of interventions for cognitive and/or physical training. In order to holistically capture the opportunities of the living lab environment, a feasibility study entitled "Use of nZEB Smart Home services as a controlled lab environment to guide real life case studies of older adults", has been conducted in the rapid prototyping and novel technologies' demonstration infrastructure of nZEB smart home of Information Technologies Institute (ITI). The cognitive performance and physical function of 18 users ranging from 55 years old to 70 healthy adults has been assessed in interrelation to measure the significant impact of a holistic approach in lab-based interventions. The study design methods included a) physiological monitoring during exercise, b) balance distribution assessment, c) EEG measurements duringMeditation task and d) activities of daily living execution using a Banking transaction and a Virtual Supermarket web application. The feasibility study was successful in incorporating and combining various hardware and software solutions in exercise and meditation tasks as well as in simulations of everyday activities of the participants. Processes and significant insights are presented in a preliminary analysis of the collected data.

关键词： Living labs eHealth Feasibility study Wearables Insoles

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Fuzzy Fatigue Model for Ergonomic Design of Assembly Lines Under Uncertainty

Fuzzy Fatigue Model for Ergonomic Design of Assembly Lines U...

引用

Intelligent systems Conference

作者： Ghorbani, Elham Keivanpour, Samira Sekkay, Firdaous Imbeau, Daniel Polytech Montreal Montreal PQ H3T 1J4 Canada

ISBN: (纸本)9783031664274;9783031664281

In the context of Industry 5.0, the significance of prioritizing ergonomics within manufacturing systems cannot be overstated. This paper introduces an innovative methodology, the Fuzzy Ergo-ALDP-F, which extends the traditional Ergonomic Assembly Line Balancing Problem (Ergo-ALBP) into the design stage to address imprecise task durations and ergonomic risks effectively. This approach encompasses a two-phase framework, integrating a constructive heuristic with fuzzy logic. The first phase focuses on ensuring feasibility, while the second phase is dedicated to finding the ergonomically optimum solution amongall feasible options. Our research enriches the existing knowledge by incorporating a fuzzy extension of Potvin's fatigue model. It is worth noting that integrating fuzziness in fatigue evaluation across tasks, workers, and assembly lines is a novel and pivotal aspect of ourwork. This study is rooted in the fundamental recognition that, in the long term, work-related injuries and ergonomics-related issues can impose substantial costs on production systems. Moreover, in the design phase, various types of uncertainty relating to operational aspects and ergonomics can significantly impact the optimization model. Consequently, this paper makes substantial progress in the research landscape by synergistically addressing the critical intersection of ergonomics, uncertainty, and assembly line optimization, significantly contributing to the ongoing pursuit of a safer and more efficient manufacturing environment and underlining its broader implications within the field.

关键词： Ergonomic assembly line design Knowledge-based expert system Fuzzy logic

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A Proposed Evaluation Framework of Artificial Intelligence's Business Effects on Sustainability from a Micro-enterprise Organizational Structure Type Perspective Using Fuzzy Intuitionistic Extensions 1

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International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Demircan, Murat Levent Ertan, Ibrahim Can Galatasaray Univ Istanbul Turkiye

ISBN: (数字)9783031700187

ISBN: (纸本)9783031700170;9783031700187

The increasing incorporation of Artificial Intelligence (AI) into corporate structures demands a thorough investigation of the implications for sustainability, especially in the complex environment of micro-enterprises. This study aims to provide a comprehensive assessment framework designed for examining the complex interactions between AI implementation and sustainability results, with a particular emphasis on the organizational structures characteristic of microenterprises. In order to acknowledge and account for the inherent uncertainties and imprecisions that characterize sustainability indicators in this dynamic setting, the proposed approach leans on fuzzy intuitionistic extensions. With a primary focus on sustainability issues, this study attempts to close current gaps in the academic discussion by offering a methodologically valid approach to evaluate the complex business implications of AI integration in the particular microenterprise environment. By utilizing fuzzy intuitionistic logic, the framework takes into account the natural desires and errors that come with sustainability metrics. This allows for a more realistic and nuanced representation of the complex relationships that exist between AI technologies and the organizational structures that are essential to micro-enterprises. Important components of the suggested assessment system include defining relevant sustainability aspects, creating fuzzy intuitionistic indicators relevant to micro-enterprises, and including a strict assessment process. By systematically utilizing this paradigm, our research aims to provide insightful information about the possible benefits and difficulties associated with implementing AI in micro-enterprises, so contributing to a more nuanced understanding of the technology's implications for sustainable business practices. The expected results of this study will provide fundamental information for later academic investigations and guide policy decisions intended to promote

关键词： Decision Making Artificial Intelligence Sustainability Micro-Enterprises Fuzzy Intuitionistic Extensions

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Assessment of Performance for Cloud-Native Machine Learning on Edge Devices 20th

Assessment of Performance for Cloud-Native Machine Learning ...

引用

20th International Workshop on Combinatorial Image Analysis (IWCIA)

作者： Clapa, Konrad Grudzien, Krzysztof Sierszen, Artur Tech Univ Lodz Inst Appl Comp Sci Stefanowskiego 18 PL-90537 Lodz Poland

ISBN: (纸本)9783031665936;9783031665943

This article presents the performance assessment environment for conducting experiments on an edge computing platform specifically designed for machine learning. The platform consists of a virtualised environment, including a K3s cluster and Kubeflow software. The primary objective of the study was to be able to assess the efficiency of executing Kubeflow Pipelines. To verify they usability of the environment, we run simple calculus operations in a simulated parallel computing scenario. To deliver accurate performance measurements, a benchmarking environment was set up, taking into account parameters such as the number of parallel pipelines executions and nodes. The results obtained, proved the validity of the environment, by showing the impact of cluster node count on computational time. This provides valuable insights that can guide future decision-making for optimizing the performance of machine learning pipelines on edge devices.

关键词： Machine learning Artificial intelligence Cloud computing Edge computing Internet of Things

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Analyzing the Factors Influencing the Performance of Railway Infrastructure Managers 10th

Analyzing the Factors Influencing the Performance of Railway...

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International Conference on New Technologies, Development and Application - Advanced Production Processes and Intelligent systems

作者： Kalem, Aida Brankovic, Nedzad Cabric, Nermin Kiso, Fadila Univ Sarajevo Fac Traff & Commun Sarajevo 71000 Bosnia & Herceg

ISBN: (纸本)9783031662706;9783031662713

Railway infrastructure managers play a vital role in the proper functioning of railway systems in various countries. Their success depends on many factors, including geographical, climatic, political, social, service-related, technological, and economic aspects. This research employs the TOPSIS method (Technique for Order of Preference by Similarity to Ideal Solution) to evaluate the performance of 19 European railway infrastructure managers. Variables used for ranking include area size, population, gross domestic product (GDP), modal share in passenger and freight transport, share of the managed national network, active licenses, network length, and full-time employees. This approach aims to deepen the understanding of infrastructure managers performance, considering various aspects, including geographic, economic, technological, and social factors. This comprehensive approach to analyzing railway infrastructure managers performance seeks to develop strategic guidelines for improving railway infrastructure in different countries. The application of the TOPSIS method will be instrumental in the ranking process, presuming equal importance among the considered factors. The findings of this research hold significance for advancing sustainability and efficiency within the railway sector.

关键词： railway infrastructure managers key factors performance evaluation TOPSIS method

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Evaluating and Improving Disparity Maps Without Ground Truth

Evaluating and Improving Disparity Maps Without Ground Truth

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Intelligent systems Conference

作者： Pocol, Andreea Istead, Lesley Kaplan, Craig S. Univ Waterloo Waterloo ON N2L 3G1 Canada Carleton Univ Ottawa ON K1S 5B6 Canada

ISBN: (纸本)9783031663284;9783031663291

Disparity maps are integral to the fields of computer vision and computer graphics, with many applications in robotics, path planning, computerized drawing, 3D viewing, and more. Stereo algorithms can be used to synthesize disparity maps from stereo image pairs. Unfortunately, most methods to assess disparity map quality rely on a ground-truth disparity map, which is not always available. This paper introduces a method to evaluate disparity map generation algorithms that does not require ground truth, and is instead based on the quality of the disparity maps themselves. This novel scoring metric assesses each pixel in a given disparity map and then provides an overall score for the disparity map. The score is both a visual representation-where each color encodes an error or potential error-and a numerical score. This novel scoring metric is used to compare two top-ranking disparity map generators in different scenarios. Our scoring method yields results consistent with intuition and also uncovers, and helps in resolving, an issue with one generator. Finally, RANSAC plane-fitting is used to automatically inpaint unknown regions and thereby improve the usability of disparity maps in applications such as non-photorealistic rendering, layer-based stereo methods, and warping.

关键词： Computer vision Stereoscopic 3D Disparity maps

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DeepRL-Based Robot Local Motion Planning in Unknown Dynamic Indoor Environments 6th

DeepRL-Based Robot Local Motion Planning in Unknown Dynamic ...

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6th Iberian Robotics Conference (Robot)

作者： Goncalves, Gabriel Palaio, Daniel Garrote, Luis Nunes, Urbano J. Univ Coimbra Inst Syst & Robot ISR Dept Elect & Comp Engn DEEC Coimbra Portugal

ISBN: (纸本)9783031586750;9783031586767

Robots are progressively being applied in different tasks, spanning from industrial applications to space exploration, enhancing human capabilities. Difficulties in performing many tasks such as navigation, target recognition and obstacle avoidance must be overcome. This work proposes a novel Deep Reinforcement Learning approach to solve robot motion planning in environments populated by both static and dynamic obstacles by exploiting a Dueling Double Deep Q-Network (D3QN) framework, with a costmap-based state representation, Prioritized Experience Replay (PER), reward propagation and curriculum/transfer learning. Evaluation was carried out in Gazebo simulation environments, and the presented results highlight the proposed framework's performance in both static and dynamic scenarios.

关键词： Space research

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