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Security Testing in IEEE 802.11 Wireless networks 1

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13th Computer Science Online Conference

作者： Pocarovsky, Stefan Hecl, David Gregus, Martin Letenay, Jakub Orgon, Milos Slovak Univ Technol Bratislava Inst Multimedia Informat & Commun Technol Fac Elect Engn & Informat Technol Bratislava Slovakia

ISBN: (数字)9783031703003

ISBN: (纸本)9783031702990;9783031703003

This paper discusses the possibilities of using appropriate security protocols to secure access to a wireless Wi-Fi network. Based on the described vulnerabilities and attacks on security protocols, practical possibilities of breaking the security of Wi-Fi networks protected by WPA2 and WPA3 protocols are shown by the most used attacks on a router secured by the mentioned protocols.

关键词： WiFi security WPA WPA2 WPA3

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Multidimensional and Multilingual Emotional Analysis 1

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11st World Conference on Information systems and Technologies (WorldCIST)

作者： Aparicio, Sofia Aparicio, Joao T. Aparicio, Manuela Univ Lisbon Inst Super Tecn INESC ID Rua Alves Redol 9 P-1000029 Lisbon Portugal Univ Nova Lisboa NOVA Informat Management Sch NOVA IMS Lisbon Portugal

ISBN: (数字)9783031456510

ISBN: (纸本)9783031456503;9783031456510

In order to monitor informal political online discussions and to lead a better understanding of hate speech on social media, we found that it was necessary to use sentiment quantification for languages with few training datasets. Previous studies mainly rely on languages with enough data to train a model. Several statistical and machine learning models were produced and compared in three languages (English, Portuguese and Polish). This work shows promising results when inferring sentimental dimensions, even in languages other than English.

关键词： Emotional ratings of text Affective norms Long Short-Term Memory Recurrent Neural networks Machine learning

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Learning Factories in New Business Development: A Framework Proposition 14th

Learning Factories in New Business Development: A Framework ...

引用

14th International Conference on Learning Factories (CLF)

作者： Vieira, Renan Esposito Zancul, Eduardo Schutzer, Klaus Univ Sao Paulo Polytech Sch Av Prof Luciano Gualberto 1380 BR-05508010 Sao Paulo Brazil

ISBN: (纸本)9783031653995;9783031654008

Research on Learning Factories has often been associated with education, lean manufacturing, and technology facilitation in small and medium enterprises (SMEs). Still, fewer studies are related to the potential constitution and development of new businesses in these environments, that is, to what extent Learning Factories can encourage entrepreneurial action and promote business creation and development. The present study proposes a framework for business constitution and development in Learning Factories. The literature search followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) method. It addressed Learning Factories in the context of technology facilitation, business and innovation agglomerations and networks, since these research streams have theoretical contributions to the proposed topic. Based on the theoretical foundations, a framework that supports the analysis of entrepreneurial action and organizational development in Learning Factories is proposed. The framework is then applied to analyze an initial case of a startup working in collaboration with a Learning Factory. The case relates to developing additive manufacturing processes for application in the pharmaceutical industry. The preliminary case analysis offers insight into the relationship between the startup and the Learning Factory. The startup collaboration with the Learning Factory is motivated by the ease of access to technologies and processes. Moreover, the partnership should enable knowledge transfer to the startup supporting technology development. Results include the proposed framework that can serve as a reference to other Learning Factories supporting new business development.

关键词： Entrepreneurship Startup Business constitution and development Innovation networks

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Toward Upper-Body Posture Monitoring for Upper-Limb Rehabilitation Robot 1

引用

18th International Conference on Intelligent Autonomous systems (IAS)

作者： Hwang, Yeji Kim, Jonghyun Sungkyunkwan Univ Suwon 16419 South Korea

ISBN: (数字)9783031448515

ISBN: (纸本)9783031448508;9783031448515

This paper proposes an improved upper-body monitoring method using an end-effector rehabilitation robot and an RGB-D sensor. To enhance the monitoring method, we conducted tests in different robotic environments and utilized the Jacobian to detect sensor inaccuracies. The robotic system was replaced with more commonly used structure and sustainable development. Additionally, we proposed a method for detecting sensor inaccuracies and confirmed it by predicting joint angular velocity using the *** proposed method showed improved root mean squared error compared to the elbow joint of the sensor, even in different robotic environments.

关键词： End-effector Joint angle Monitoring Jacobian Arm-model

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Cyber Safety Awareness Through a Massive Open Online Course (MOOC): Community Engagement Knowledge Transfer

Cyber Safety Awareness Through a Massive Open Online Course ...

引用

Computing Conference

作者： Kritzinger, Elmarie Univ South Africa UNISA POB 392 ZA-0003 Pretoria South Africa

ISBN: (纸本)9783031622793;9783031622779;9783031622762

The world is becoming increasingly digitised, and information communication technology (ICT) has become integrated in every part of our lives. Constant connectivity (internet access) has provided opportunities that have enriched and changed the way we do business, education environments, socialise and participate in personal activities. An environment that is growing due to constant ICT development is the education space. This impact of ICT on the educational environment made it possible to provide educational opportunities to numerous communities that were previously excluded. This exclusion of educational spaces and lifelong learning opportunities are a result of inadequate funding, transport and time constraints, access to higher education spaces and lack of prior knowledge and skills. This research investigates howelectronic learning (e-learning) can be used to facilitate knowledge sharing amongst disadvantage communities. The research explores aMassive Open Online Course (MOOC) approach with the aim to enhance knowledge sharing and cultivating an environment for lifelong learning among previous excluded communities. This research uses a case study of a cyber safety awareness community engagements project to determine if a MOOC can be used to provide quality education, knowledge and skills to committees that otherwise had no access to higher educational or further learning spaces. This research covered the design, presentation, and evaluation of a cyber safety awareness MOOC on a 0-rated (free data available) university platform in South Africa. The MOOC was evaluated by means of a pre and post questionnaire to determine its success and the extent of knowledge transfer to community members.

关键词： MOOC Cyber safety Community engagement Lifelong learning Knowledge transfer

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Real-Time Gameplay Data and Biometric Measurement Integration as a Data Source for Game User Research 20th

Real-Time Gameplay Data and Biometric Measurement Integratio...

引用

20th International Workshop on Combinatorial Image Analysis (IWCIA)

作者： Balcerzak, Adam Laczynski, Marcin Hufschmitt, Aline Gackowski, Tomasz Univ Warsaw Warsaw Poland CREC St Cyr Ecoles Coetquidan Guer France

ISBN: (纸本)9783031665936;9783031665943

This research project, conducted at the Laboratory of Media Studies, University of Warsaw in cooperation with CREC Saint Cyr Ecoles de Coetquidan, Guer, France, aims to explore the integration of automated gameplay analysis and biometric tools to enhance the game user experience. The study utilized a custom-developed first-person shooter game. Twenty-two student participants from the Faculty of Journalism and Book Studies at the University of Warsaw took part in the research. They were divided into two groups based on their gaming experience-heavy gamers and light gamers. The study focused on the emotional reactions (facetracking) of these participants during gameplay and specified in-game events. The research findings revealed that heavy gamers exhibited stronger emotional responses, particularly joy, when successfully hitting targets in the game. This suggests that game elements could be modified to enhance player satisfaction. However, the study acknowledges the absence of baseline recordings and the need for additional biometric measurements. The research demonstrates the potential of integrating automated gameplay analysis and biometric research to improve game user experiences. It offers valuable insights for game developers and highlights the significance of individual gaming backgrounds. Future work should address the limitations and refine the research procedure for wider application in the gaming industry.

关键词： game user research game analytics biometric research shooter game data integration

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A Layered Semantic Interoperability Framework for Conflict Resolution of Semantic Models in Smart Devices

A Layered Semantic Interoperability Framework for Conflict R...

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Intelligent systems Conference

作者： Mofatteh, Mohammad Yaser Pirayesh, Amir Valilai, Omid Fatahi Constructor Univ Bremen Sch Business Social & Decis Sci Campus Ring 1 D-28759 Bremen Germany KEDGE Business Sch Ctr Excellence Supply Chain & Transportat CESIT Talence France

ISBN: (纸本)9783031664304;9783031664311

In the dynamic realm of smart devices and the Internet of Things (IoT), semantic interoperability serves as the linchpin for effective communication. This article navigates through various semantic models, encompassing ontologies, RDF, and WoT, elucidating their pivotal role in mitigating conflicts among devices with disparate representations. This research proposes a conceptual model that extends the recent research studies for expanding on conflict resolution methods and proposes a conceptual model for enabling additional abstraction layers to enhance conflict detection within semantic models. This innovation aims to address conflicts stemming from divergent data formats, structural intricacies, and contextual variations. The conceptual model is exemplified through a compelling case study, illustrating its efficacy in detecting conflicts in a real-world scenario. Applications of semantic interoperability, ranging from harmonizing diverse data sources in healthcare to optimizing energy management in smart homes, underscore the practical significance of this work. By augmenting the abstraction layers of semantic models, this research contributes to the evolution of sophisticated ecosystems, empowering smart devices to proactively identify and resolve conflicts, thereby fortifying the foundation of seamless semantic interoperability.

关键词： Semantic interoperability IoT Conflict resolution Smart home Energy management

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Video Colorization Based on a Diffusion Model Implementation

Video Colorization Based on a Diffusion Model Implementation

引用

Intelligent systems Conference

作者： Stival, Leandro Torres, Ricardo da Silva Pedrini, Helio Univ Estadual Campinas Inst Comp Ave Albert Einstein 1251 Campinas SP Brazil Wageningen Univ & Res Artificial Intelligence Grp Wageningen Netherlands Norwegian Univ Sci & Technol Larsgardsvegen 2 N-6009 Alesund Norway

ISBN: (纸本)9783031663284;9783031663291

Cutting-edge techniques are being employed by researchers to develop algorithms that have the capability to automatically add color to black-and-white videos. This advancement has the potential to revolutionize our experience of historical films and provide filmmakers and video producers with a powerful new tool. These algorithms employ sophisticated deep neural networks to analyze images, identifying patterns and offering a promising avenue for extracting meaning and insights from visual data in the field of computer vision. Although current studies primarily focus on image colorization, there is a noticeable gap when it comes to videos and movies in the realm of deep machine learning techniques. Our investigation aims to bridge this gap and demonstrate that the image colorization techniques used today can also be effectively applied to videos and match the current state of the art presented at NTIRE 2023 video colorization challenge. We explored the application of diffusion models, which have gained popularity due to their ability to generate images and text. Our implementation involves utilizing a diffusion model to introduce noise in the frames, while a U-Net with self-attention layers predicts the denoised frames, thereby predicting the color of the video frames. For training purposes, we utilized the DAVIS and LDV datasets. When comparing the colorized frames with the ground truth in the test set, we observed promising results under several quality metrics, such as PSNR, SSIM, FID, and CDC.

关键词： Video colorization Deep learning diffusion models Evaluation metrics

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Malware Detection and Classification with Machine Learning Algorithms 1

引用

8th Smart Trends in Computing and Communications (SmartCom)

作者： Kumar, R. Vinoth Islam, Md Mojahidul Apon, Abir Hossain Prantha, C. S. Vel Tech Rangarajan Dr Sagunthala R&D Inst Sci & Dept Comp Sci & Engn Chennai Tamil Nadu India

ISBN: (数字)9789819713134

ISBN: (纸本)9789819713127;9789819713134

The Windows platform can be easily affected by abnormal growth of malicious software, so we need to find abnormal activities in the system and vary them effectively. Manually finding an abnormal growth of activities in the system is not possible at all times and takes time. We need to assign humans to monitor activities. To solve this problem, we have to develop an automated system for finding abnormal activities at all times without human interaction. We applied several kinds of techniques involving machine learning to quickly determine whether the algorithm models were effective and detect any abnormal system growth. Machine learning methods such as XGBoost, Naive Bayes, K-NN, Random Forest, decision tree, logistic regression, and Support Vector Machine have been utilized to detect abnormal growth in the system. We found that the XGBoost classification algorithm performs the most accurate classification among the algorithms tested. At the end of the testing, a 99.28% accurate prediction was obtained.

关键词： Malicious software Machine learning algorithms XGBoost

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Toward an Enhanced Energy-Efficiency Model Using Routing Protocol Strategy: Implementation in Wireless Sensor networks 9th

Toward an Enhanced Energy-Efficiency Model Using Routing Pro...

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9th International Congress on Information and Communication Technology (ICICT)

作者： Moulad, Lamyaa Moussaid, Laila Hassan II Univ FSJES AC Casablanca Morocco Hassan II Univ ENSEM Casablanca Morocco

ISBN: (纸本)9789819735556;9789819735563

Wireless sensor networks (WSNs) are extremely used for monitoring and collecting data from remote or hostile and harsh areas. Efficient approach is essential to ensure reliable data transmission within these components. If we adopt a holistic approach that encompasses hardware optimization, software strategies, and communication protocol choices, it is possible to maximize the lifespan of sensor nodes and ensure the reliable operation of these networks. However, it is important to strike a balance between energy efficiency and network performance to meet the specific needs of each application and that is the goal of our work. We decide to improve AODV protocol through combining it with energy-aware mechanisms and careful energy management strategies, we can significantly improve the energy efficiency of wireless sensor networks. AODV's on-demand routing strategy aligns well with energy conservation in WSNs. The protocol minimizes routing overhead by creating routes only when necessary. However, AODV does not directly address energy efficiency in data transmission, such as data aggregation or duty cycling or other strategies;the proposed model shows that the improved 'eneciency' AODV approach based on priority and load balancing minimizes extremely the energy consumption in WSN.

关键词： WSN AODV Energy efficiency Priority model Energy aware

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