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Kavitha Srinivasan, Sainath Prasanna, Rohit Midha, Shraddhaa Mohan
Pág. 1 - 20
Advances have been made in the field of Machine Learning showing that it is an effective tool that can be used for solving real world problems. This success is hugely attributed to the availability of accessible data which is not the case for many fields...
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Junoh Kim, Jisun Park and Kyungeun Cho
Considering autonomous navigation in busy marine traffic environments (including harbors and coasts), major study issues to be solved for autonomous ships are avoidance of static and dynamic obstacles, surface vehicle control in consideration of the envi...
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Rene Cruz Flores,Gabriel López Morteo
Pág. pp. 9 - 18
In this paper we present a framework (CA-Mobile Framework) for develop educational activities for collaborative learning based on mobile devices, this framework is composited by two main components: A documental reference and an API for develop mobile so...
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Chuanxiang Song, Seong-Yoon Shin and Kwang-Seong Shin
This study introduces a novel approach named the Dynamic Feedback-Driven Learning Optimization Framework (DFDLOF), aimed at personalizing educational pathways through machine learning technology. Our findings reveal that this framework significantly enha...
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Igor Ryazanov, Amanda T. Nylund, Debabrota Basu, Ida-Maja Hassellöv and Alexander Schliep
Driven by the unprecedented availability of data, machine learning has become a pervasive and transformative technology across industry and science. Its importance to marine science has been codified as one goal of the UN Ocean Decade. While increasing a...
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Amir Dirin,Marko Nieminen
Pág. pp. 37 - 51
In this paper, we propose the mLUX framework, a model based on the user-centered design (UCD) framework, which is specifically for the development of m-learning applications. We present the results of four case studies conducted to develop m-learning app...
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Stavros A. Nikou and Anastasios A. Economides
Motivation is an important issue to consider when designing learning activities, including mobile learning and assessment. While previous research provides evidence for the motivational impact of mobile learning, not many pedagogical frameworks exist for...
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Georgios Karantaidis and Constantine Kotropoulos
The detection of computer-generated (CG) multimedia content has become of utmost importance due to the advances in digital image processing and computer graphics. Realistic CG images could be used for fraudulent purposes due to the deceiving recognition ...
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Felipe Coelho de Abreu Pinna, Victor Takashi Hayashi, João Carlos Néto, Rosangela de Fátima Pereira Marquesone, Maísa Cristina Duarte, Rodrigo Suzuki Okada and Wilson Vicente Ruggiero
Complex and long interactions (e.g., a change of topic during a conversation) justify the use of dialog systems to develop task-oriented chatbots and intelligent virtual assistants. The development of dialog systems requires considerable effort and takes...
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AlsharifHasan Mohamad Aburbeian and Manuel Fernández-Veiga
Securing online financial transactions has become a critical concern in an era where financial services are becoming more and more digital. The transition to digital platforms for conducting daily transactions exposed customers to possible risks from cyb...
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Ji-Woon Lee and Hyun-Soo Kang
The escalating use of security cameras has resulted in a surge in images requiring analysis, a task hindered by the inefficiency and error-prone nature of manual monitoring. In response, this study delves into the domain of anomaly detection in CCTV secu...
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Alya Alshammari and Khalil El Hindi
The combination of collaborative deep learning and Cyber-Physical Systems (CPSs) has the potential to improve decision-making, adaptability, and efficiency in dynamic and distributed environments. However, it brings privacy, communication, and resource r...
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Haedam Kim, Suhyun Park, Hyemin Hong, Jieun Park and Seongmin Kim
As the size of the IoT solutions and services market proliferates, industrial fields utilizing IoT devices are also diversifying. However, the proliferation of IoT devices, often intertwined with users? personal information and privacy, has led to a cont...
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Yu Yao and Quan Qian
We develop the online process parameter design (OPPD) framework for efficiently handling streaming data collected from industrial automation equipment. This framework integrates online machine learning, concept drift detection and Bayesian optimization t...
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Sufyan Danish, Asfandyar Khan, L. Minh Dang, Mohammed Alonazi, Sultan Alanazi, Hyoung-Kyu Song and Hyeonjoon Moon
Bioinformatics and genomics are driving a healthcare revolution, particularly in the domain of drug discovery for anticancer peptides (ACPs). The integration of artificial intelligence (AI) has transformed healthcare, enabling personalized and immersive ...
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Shobhit Aggarwal and Asis Nasipuri
The Internet of Things (IoT) enables us to gain access to a wide range of data from the physical world that can be analyzed for deriving critical state information. In this regard, machine learning (ML) is a valuable tool that can be used to develop mode...
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Nermin Abdelhakim Othman, Manal A. Abdel-Fattah and Ahlam Talaat Ali
Because of technological advancements and their use in the medical area, many new methods and strategies have been developed to address complex real-life challenges. Breast cancer, a particular kind of tumor that arises in breast cells, is one of the mos...
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Xiaotong Cui, Hongxin Zhang, Xing Fang, Yuanzhen Wang, Danzhi Wang, Fan Fan and Lei Shu
The leakage signals, including electromagnetic, energy, time, and temperature, generated during the operation of password devices contain highly correlated key information, which leads to security vulnerabilities. In traditional encryption algorithms, th...
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Yang Chao, Chaoning Lin, Tongchun Li, Huijun Qi, Dongming Li and Siyu Chen
Aiming to investigate the problem that dam-monitoring data are difficult to analyze in a timely and accurate automated manner, in this paper, we propose an automated framework for dam health monitoring based on data microservices. The framework consists ...
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Richard Wen and Songnian Li
Many spatial decision support systems suffer from user adoption issues in practice due to lack of trust, technical expertise, and resources. Automated machine learning has recently allowed non-experts to explore and apply machine-learning models in the i...
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