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14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Samaraweera, S.A.R.P. Siriwardana, S.M.D.N. Fernando, W.D.V. Rajakarunaratne, D.N. Sri Lanka Institute of Information Technology Dept. of Computer Systems Engineering Malabe Sri Lanka

ISBN: (纸本)9798350335095

Maritime cyber-terrorist attacks have become a major concern to the entire world in recent decades. Everyone should be more aware of marine strategies to prevent cyberterrorist attacks, both locally and globally. This study investigates how Sri Lanka and the Sri Lanka Navy (SLN) may successfully address maritime security concerns by utilizing current resources and developing a marine strategy to counter such maritime cyber-terrorism assaults. The literature review in this thesis primarily evaluates the level of understanding in Sri Lanka concerning when marine cyber terrorism strikes may occur. Furthermore, this thesis investigates if Sri Lanka has any maritime rules and regulations. The use of such laws and regulations will concentrate on how they can increase their expertise. © 2023 IEEE.

关键词： Cybersecurity

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Optimizing Engagement Dynamics in E-Learning Environments with Insights and Strategic Approaches 3

Optimizing Engagement Dynamics in E-Learning Environments wi...

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3rd International Conference on Creative Communication and Innovative Technology, ICCIT 2024

作者： Cholisoh, Novi Anugrah, Rio Wahyudin Fazri, Muhammad Faizal Wahid, Syahrul Mu'Arif Pramudya, Reza Dani University of Raharja Dept. of Information Management Tangerang Indonesia Pandawan Sejahtera Indonesia Dept. of Computer Systems Tangerang Indonesia Bosindo Dept. of Business Intelligence Tangerang Indonesia Sesindo Dept. of Digital Business Tangerang Indonesia Pandawan Sejahtera Indonesia Dept. of Information Technology Tangerang Indonesia

ISBN: (纸本)9798350367492

This study explores the factors influencing student engagement in e-learning and proposes strategies for improvement. It incorporates a mixed-method approach, combining quantitative data from a learner survey with qualitative insights from interviews and focus groups involving educators and students. The survey investigates technological, pedagogical, and personal factors that impact engagement, while qualitative data provide deeper insights into experiences and perceptions. The findings underscore that student engagement in e-learning is shaped by the quality of digital content, opportunities for interaction, feedback mechanisms, and individual learner characteristics. Personalized learning experiences and robust support systems emerge as crucial for enhancing engagement. The study recommends practical strategies to strengthen e-learning engagement, including adopting adaptive learning technologies, promoting collaborative learning communities, and providing targeted support for diverse learner needs. These insights contribute to optimizing engagement within digital learning environments. © 2024 IEEE.

关键词： Contrastive Learning

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Customs Fraud Detection Method Based on Artificial Intelligence and Data Analytics 4

Customs Fraud Detection Method Based on Artificial Intellige...

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4th International Conference on Electrical, computer, Communications and Mechatronics Engineering, ICECCME 2024

作者： Gancheva, Veska Popov, George Nakov, Ognyan Raynova, Kamelia Popova, Antoaneta Technical University of Sofia Dept. of Programming and Computer Technologies Sofia Bulgaria Technical University of Sofia Dept. of Cybersecurity Sofia Bulgaria University of Sofia Dept. of Computer Systems Technical Sofia Bulgaria Technical University of Sofia Dept. of Information Technologies in Industry Sofia Bulgaria

ISBN: (纸本)9798350391183

Because of the increased market opening and massive data collection brought about by globalization, the need of maintaining control over customs procedures has increased. However, the integration and processing of customs data are complicated by its extreme imbalance. Finding autonomous, computationally sophisticated solutions for customs handling is therefore crucial. The study described in this paper aims to propose an artificial intelligence-based method for customs fraud detection through data analytics. A machine learning-based approach for detecting customs fraud is proposed. The research methodology includes data preprocessing, data analytics, combining results, and deriving precise solutions from results obtained. The aim is to extract meaningful information from a dataset. For the purpose of classifying customs fraud, seven algorithms for machine-learning-kNN, SGD, Constant, Logistic Regression, Random Forest, Neural Network, and Naive Bayes-Are chosen and empirically assessed. © 2024 IEEE.

关键词： Adversarial machine learning

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Human Body Action Recognition based on 3D Feature Fusion over RGB Scenes 11

Human Body Action Recognition based on 3D Feature Fusion ove...

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11th International Conference on information Technology, ICIT 2023

作者： Nsour, Heba Mustafa, Zaid Al-Sendah, Maria Al-Balqa Applied University Dept. of Computer Science Albalqa Jordan Al-Balqa Applied University Dept. of Computer Information Systems Albalqa Jordan Kuwait

ISBN: (纸本)9798350320060

Human body action recognition (HBAR) is an important area of research in machine learning and image processing due to its vast range of applications. Similarly, estimating various components of human anatomy from RGB scenes are essential to human action tracking. The present study involves the implementation of human key body point detection for pose estimation. During abstracted silhouettes and vital human points, the proposed system has extracted two main features, such as 3D features and distance features. Once the relevant attributes have been incorporated, executing precise tasks and strategies is critical to achieving maximum features. Therefore, we used the t- SNE-based data refinement technique for optimal feature selection. Finally, for training, a classification model random forest is utilized. The presented system is verified on a recognized benchmark dataset, i.e., the UCF sports database. The experimental settings have revealed that our proposed system has attained better performance and outperformed other present state-of-the-art methods regarding mean recognition rate. © 2023 IEEE.

关键词： Stochastic systems

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Automatic Coding at Scale: Design and Deployment of a Nationwide System for Normalizing Referrals in the Chilean Public Healthcare System 5

Automatic Coding at Scale: Design and Deployment of a Nation...

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5th Workshop on Clinical Natural Language Processing, ClinicalNLP 2023. held at ACL 2023

作者： Villena, Fabián Rojas, Matías Arias, Felipe Pacheco, Jorge Vera, Paulina Dunstan, Jocelyn Center for Mathematical Modeling Department of Computer Sciences University of Chile Chile Center for Mathematical Modeling University of Chile Chile Dept. of Statistics and Health Information Chilean Ministry of Health Chile Dept. Computer Science & IMC Pontifical Catholic University of Chile Chile

ISBN: (纸本)9781959429883

The disease coding task involves assigning a unique identifier from a controlled vocabulary to each disease mentioned in a clinical document. This task is relevant since it allows information extraction from unstructured data to perform, for example, epidemiological studies about the incidence and prevalence of diseases in a determined context. However, the manual coding process is subject to errors as it requires medical personnel to be competent in coding rules and terminology. In addition, this process consumes a lot of time and energy, which could be allocated to more clinically relevant tasks. These difficulties can be addressed by developing computational systems that automatically assign codes to diseases. In this way, we propose a two-step system for automatically coding diseases in referrals from the Chilean public healthcare system. Specifically, our model uses a state-of-the-art NER model for recognizing disease mentions and a search engine system based on Elasticsearch for assigning the most relevant codes associated with these disease mentions. The system's performance was evaluated on referrals manually coded by clinical experts. Our system obtained a MAP score of 0.63 for the subcategory level and 0.83 for the category level, close to the best-performing models in the literature. This system could be a support tool for health professionals, optimizing the coding and management process. Finally, to guarantee reproducibility, we publicly release the code of our models and experiments. © 2023 Association for Computational Linguistics.

关键词： Search engines

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Mobile Health Intervention System in Optimizing Healthcare Delivery for Cardiac Patients 5

Mobile Health Intervention System in Optimizing Healthcare D...

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5th International Conference on Advancements in Computing, ICAC 2023

作者： Prabashana, R.P.K. Nanayakkara, G.A.J.W. Wanniachchi, W.K.D.C. Arampath, S.B.A.M.B.S. Rajapaksha, Samantha Harshanath, S.M.B. Sri Lanka Institute of Information Technology Dept. of Computer Systems Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Dept. of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350358131

The advent of mobile health (mHealth) technologies has ushered in a new era in healthcare delivery, transforming the way cardiac patients receive medical care and support. This research paper explores the role of a mobile health intervention system in optimizing healthcare delivery for cardiac patients. The prevalence of heart attacks has necessitated innovative solutions to enhance patient outcomes and reduce the burden on healthcare systems. The proposed mHealth intervention system leverages the ubiquity of mobile devices to provide real-time monitoring, personalized interventions with environment prediction, and seamless communication between patients and healthcare providers. Through a comprehensive review of existing literature and empirical studies, this paper examines the impact of the mHealth intervention system on patient engagement, adherence to treatment plans, early detection of cardiac events, and overall quality of care. The integration of wearable device, CardioCare mobile application, and telemedicine platforms creates a holistic approach to cardiac care, empowering patients to actively participate in their health management and enabling healthcare professionals to make informed decisions. The potential benefits, challenges, and ethical considerations surrounding the implementation of this system are discussed. © 2023 IEEE.

关键词： Wearable technology

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A Taxonomic Classification of Insider Threats: Existing Techniques, Future Directions & Recommendations

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Journal of Cyber Security and Mobility 2023年第2期12卷 221-252页

作者： Rauf, Usman Mohsen, Fadi Wei, Zhiyuan Dept. of Math. & Computer Science Mercy College NY United States Information Systems Group Bernoulli Institute for Mathematics Computer Science and Artificial Intelligence University of Groningen Groningen9712 CP Netherlands

In the last two decades, the number of rapidly increasing cyber incidents (i.e., data theft and privacy breaches) shows that it is becoming enormously difficult for conventional defense mechanisms and architectures to neutralize modern cyber threats in a real-time situation. Disgruntled and rouge employees/agents and intrusive applications are two notorious classes of such modern threats, referred to as Insider Threats, which lead to data theft and privacy breaches. To counter such state-of-the-art threats, modern defense mechanisms require the incorporation of active threat analytics to proactively detect and mitigate any malicious intent at the employee or application level. Existing solutions to these problems intensively rely on co-relation, distance-based risk metrics, and human judgment. Especially when humans are kept in the loop for access-control policy-related decision-making against advanced persistent threats. As a consequence, the situation can escalate and lead to privacy/data breaches in case of insider threats. To confront such challenges, the security community has been striving to identify anomalous intent for advanced behavioral anomaly detection and auto-resiliency (the ability to deter an ongoing threat by policy tuning). Towards this dimension, we aim to review the literature in this domain and evaluate the effectiveness of existing approaches per our proposed criteria. According to our knowledge, this is one of the first endeavors toward developing evaluation-based standards to assess the effectiveness of relevant approaches in this domain while considering insider employees and intrusive applications simultaneously. There have been efforts in literature towards describing and understanding insider threats in general. However, none have addressed the detection and deterrence element in its entirety, hence making our contribution one of a kind. Towards the end of this article, we enlist and discuss the existing data sets. The data sets can help

关键词： Machine learning

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(POSTER) Insights from Executing TinyML Models on Smartphones and Microcontrollers 19

(POSTER) Insights from Executing TinyML Models on Smartphone...

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19th Annual International Conference on Distributed Computing in Smart systems and the Internet of Things, DCOSS-IoT 2023

作者： Singh, Harman M. Agashe, Shrishailya Jain, Shreyans Ghosh, Surjya Challa, Aditya Danda, Sravan Sen, Sougata Bits Pilani K K Birla Goa Campus Dept. of Computer Science and Information Systems India

ISBN: (纸本)9798350346497

In this paper, we empirically compare the system-level performances of executing a machine learning task on a resource-constrained IoT device and compare its performance to offloading the task to a more capable device, a smartphone. Our results indicate that although the resource-constrained device cannot run complex machine learning models, they can provide reasonable accuracy using similar models that can load on their memory. For running simpler models on the microcontroller, the best case accuracy for the machine learning task was 94.32% (SD: 1.7%). Furthermore, local computation resulted in almost 50% lesser current draw as compared to the offloading. These observations make a case for adopting an adaptive approach to ensure that applications meet the energy-accuracy-latency balance. © 2023 IEEE.

关键词： Microcontrollers

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Architecture development of middleware and API for IOT-based Red Onion farming

Architecture development of middleware and API for IOT-based...

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2023 International Seminar on Application for Technology of information and Communication, iSemantic 2023

作者： Steven, Alvin Suharnawi Alzami, Farrikh Saputra, Filmada Ocky Megantara, Rama Aria Andono, Pulung Nurtantio Universitas Dian Nuswantoro Dept. of Information Systems Indonesia Universitas Dian Nuswantoro Dept. of Information Engineering Indonesia Universitas Dian Nuswantoro Faculty of Computer Science Indonesia

ISBN: (纸本)9798350339215

IoT plays a crucial role in transforming the agricultural industry by offering diverse use cases starting from crop monitoring and precision farming to yield optimization. The fundamental reason why the agricultural community benefits immensely from IoT is due to its capacity to gather real-time data straight from their fields. Farming requires considerable attention, and wireless sensor networks enable farmers to deploy IoT devices throughout various parts of their farm so they can obtain information on soil moisture levels, temperature, humidity, among other essential parameters that are integral for effective agriculture management. This gathered data empowers farmers with accurate weather forecasts through machine learning techniques which assist them in making informed decisions related to planting or harvesting of crops - vital components critical for successful outcomes towards better yields. Moreover, middleware architectures/APIs developed specifically for IOT-based red onion farming utilize cloud computing services wherein these enlightening patterns generated get stored safely using analytics tools & automated systems. These intensify insights derived as it simplifies accessing important metrics aiding ease while analyzing historical trends advantageously helping make prudent future course corrective measures concerning planting/harvesting schedules based entirely on solid empirical evidence combined with artificial intelligence ensuring unprecedented efficiency gains and higher returns than previously achievable without technology guidance. © 2023 IEEE.

关键词： Crops

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Design of a Graduate level Software Engineering Program with a Product Perspective and a Product Management Specialization 35

Design of a Graduate level Software Engineering Program with...

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35th IEEE International Conference on Software Engineering Education and Training, CSEE and T 2023

作者： Pawar, Pravin Balasubramaniam, Sundar Ramachandran, Anita Bits Pilani Dept. of Computer Science & Information Systems Pune India Independent Consultant Bangalore India

ISBN: (纸本)9798350322026

While Software Engineering practice in the industry had matured well over the second half of the twentieth century, the first two decades of this millennium have witnessed disruptive growth of the field arising out of the evolution of new problem domains (e.g., intelligent applications and data management) as well as diverse deployment patterns (e.g., cloud, mobile and embedded devices). More subtle and impactful for practitioners is the change in perspective and approach-from a project-driven lifecycle to a product-driven lifecycle of software. Academic programs have kept up with the former set of changes as evidenced in curricular aspects or components such as DevOps, Mobile Application Development, Cloud-Native Application Development, Data Engineering, Big Data systems, Software Engineering for AI, etc. But there is a distinct lack of representation of the product perspective or approach and the emerging role of Product Management in typical University-level Software Engineering programs and curricula. We propose to address this gap by identifying-and then incorporating into a curriculum-the following:(i)requirements and features of a Software Product Life Cycle,(ii)practices of a product-driven approach to Software Engineering, and(iii)competencies of a Software Product *** show how these aspects can be addressed by a graduate level Software Engineering program with an optional specialization in Software Product Management targeted at practicing Software Engineers. We present the design of such a program in sufficient detail along with validation from industry and comparison with other programs. © 2023 IEEE.

关键词： Curricula

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