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Mix ISO 9241 and Design Thinking for a Collaborative Interface Design Process 8th

Mix ISO 9241 and Design Thinking for a Collaborative Interfa...

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8th International Conference on computer-Human Interaction Research and Applications-CHIRA-Annual

作者： Ouedraogo, Wendgounda Francis Otto Guericke Univ Magdeburg Fac Comp Sci Univ Platz 2 D-39106 Magdeburg Germany

ISBN: (纸本)9783031838446;9783031838453

Skills and experiences of individuals are different in the use of intelligent systems. Designing and implementing a user interface that meets user habits can be a major asset to the acceptance of these systems. Usability aspects must therefore be placed at the heart of interactive technological solutions. This assumes active involvement of potential end users in collaborative design processes. The ISO 9241 - Human-centered design for interactive systems standards - offers a framework in parts 110, 112, and 210. Design Thinking, which is a non-linear methodology, supports an approach for the practical implementation of this ISO 9241 tool. The results obtained and the evaluation that followed encourage this process using these tools and methods to place potential end users at the heart of the interactive platform development process.

关键词： ISO 9241 Design Thinking User Interface Collaborative Design Process Interactions Principles

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Phase Difference Ranging Study Based on MF R-Mode Signals 5th

Phase Difference Ranging Study Based on MF R-Mode Signals

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5th China Intelligent Robotics Academic Conference

作者： Linghu, Yifan Hu, Qing Wu, Ze Cao, Jingyun Li, Hao Sun, Xiaowen Wang, Xiaoye Dalian Maritime Univ Dalian Peoples R China

ISBN: (纸本)9789819616138;9789819616145

Marine navigation technology is essential for ensuring navigation safety. With the rapid advancement of technology, ship navigation technology has undergone significant evolution from initial ephemeris navigation to the modern Global Navigation Satellite System (GNSS). However, GNSSs suffer from vulnerabilities and susceptibility to interference, prompting researchers to seek more reliable backup systems. As a terrestrial navigation system, the ranging mode (RMode) provides a highly accurate alternative. In particular, the medium-frequency (MF) differential GNSS (DGNSS) R-Mode signal has attracted attention for its ability to correct signal delay and calibration. This study simulates theMFDGNSS R-Mode signal for phase difference ranges. The time difference derived from the phase difference can be controlled within 10 ns, and the ranging accuracy can be controlled within 27 m. The simulation results further validate the effectiveness of MF DGNSS R-Mode signals in enhancing the reliability of marine navigation.

关键词： MF R-Mode phase difference of arrival (PDOA) ranging

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Advanced Machine Learning and Features Based Data Analytics of Electricity Consumption in USA and India 4th

Advanced Machine Learning and Features Based Data Analytics ...

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4th International Conference on Advanced Network Technologies and Intelligent Computing-ANTIC-Annual

作者： Shukla, Adwitiya Univ Toledo Dept Elect Engn & Comp Sci Toledo OH 43606 USA

ISBN: (纸本)9783031837951;9783031837968

This study presents a comprehensive comparative analysis of electricity consumption patterns of USA and India, using a variety of basic and advanced Machine Learning (ML) techniques. ML can accurately predict and forecast the energy demand, allowing for more efficient management of energy grids. Herein, we utilized multiple basic and advanced ML models, including XGBoost, Convolutional Neural Networks, Long Short-Term Memory (LSTM) networks, Transformer models, and Reinforcement Learning (RL) for electricity demand modeling. All ML models were evaluated for accuracy of electricity consumption prediction over short-term and long-term periods. Additional datasets of climate, economic indicators, and renewable energy metrics were also incorporated to enhance the prediction accuracy. Results show that the Transformer models outperformed all other models, due to their ability to accurately capture long-range temporal dependencies for both countries. LSTM networks also demonstrated robust performance, particularly for India, where frequent electricity demand fluctuations are more prevalent. XGBoost performed well for short-term predictions, owing to its capability to handle non-linear relationships between the drivers. Furthermore, RL provided an innovative solution for electricity usage planning and management. This paper presents key insights for energy policymakers and companies on improving grid efficiency, integrating renewable energy sources, future planning and pricing policies.

关键词： Machine learning Electricity consumption Predictive modeling Features

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The Use of Artificial Intelligence in Governance: A Systematic Review

The Use of Artificial Intelligence in Governance: A Systemat...

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4th International Conference on Advanced Research in Technologies information Innovation and Sustainability-ARTIIS-Annual

作者： Castilla Barraza, Jaime Gabriel Romero-Rubio, Salvador Abraham Univ Privada Norte Univ Tecnol Peru Lima Peru Univ Autonoma Sinaloa Culiacan Rosales Culiacan Rosales Sinaloa Mexico

ISBN: (纸本)9783031834349;9783031834356

In the last decade, Artificial Intelligence (AI) has begun to play a fundamental role in the transformation of different areas of human endeavor, including public management. This article explores recent advances in the application of AI in public management, examines the associated challenges and analyzes the future prospects of this disruptive technology. In this understanding, a bibliographic portfolio of 3.124 articles was prepared, produced between 2019 and 2023, with which a systematic review of the literature was carried out and bibliometric networks were created with the VOSviewer software. Thus, specific use cases are explored in areas such as decision making, public service delivery and resource management. It is concluded that, if these challenges are addressed, AI has the potential to boost efficiency, transparency and citizen participation in public administration.

关键词： Internet governance Intelligent algorithm Public administration information technology Digitalization

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"Charting the Future of Public Procurement: Insights from the First Round of a Delphi Study on Emerging Technologies in the EU Context" 5th

"Charting the Future of Public Procurement: Insights from th...

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5th 5th Olympus - International Conference on Supply Chain

作者： Aristotelis, Mavidis Dimitrios, Folinas Int Hellen Univ Katerini Greece

ISBN: (纸本)9783031693434;9783031693441

This paper presents the initial findings from the first round of a Delphi study, a method chosen for its proven efficacy in fostering iterative consensus-building among a panel of experts under conditions of anonymity, aimed at developing a technology roadmap for integrating emerging technologies into public procurement in alignment with European Union strategic goals. The study engages a panel of experts to identify and assess the potential impact of cutting-edge technologies in revolutionising procurement processes. The methodology section details the selection of experts and the survey's design, ensuring a comprehensive understanding of the current landscape and future possibilities. The results from this round offer valuable insights into the consensus and diverse opinions on various technologies such as artificial intelligence, Blockchain, and data analytics. These findings highlight the key areas of agreement and debate among experts and shed light on the challenges and opportunities inherent in adopting these technologies within the EU framework. The paper discusses the implications of these results for the subsequent rounds of the Delphi study and outlines preliminary conclusions that begin to shape a strategic technology roadmap. This study is pivotal in guiding policymakers and stakeholders towards effective and innovative procurement strategies, ensuring alignment with the broader objectives of the European Union.

关键词： Delphi study Emerging technologies Public procurement European Union

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Enhancement in AOMDV Routing Protocol to Overcome Congestion Problem in MANET 5th

Enhancement in AOMDV Routing Protocol to Overcome Congestion...

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5th International Conference on Computing science, Communication and Security

作者： Iticha, Misgana M. Gemeda, Ketema A. Tadesse, Samuel S. Wallaga Univ Coll Engn & Technol Nekemte Ethiopia Adama Sci & Technol Univ Adama Ethiopia Jimma Univ Jimma Inst Technol Jimma Ethiopia

ISBN: (纸本)9783031751691;9783031751707

Mobile Ad hoc Networks (MANETs) face significant challenges due to the absence of centralized management, particularly in handling congestion issues. In this context, nodes experiencing congestion often advertise themselves as the fastest route to the desired destination node, resulting in multiple packet losses and compromising the integrity, reliability, and availability of the network. To address these concerns, researchers have proposed various approaches to enhance the Ad-hoc On-demand Multipath Distance Vector (AOMDV) routing protocol. This paper investigates the integration of congestion management protocols into MANETs to enhance the performance of AOMDV. We introduce an enhanced version called Congestion Overcome AOMDV (COAOMDV), which incorporates congestion management protocols. A comparative analysis is conducted between COAOMDV and traditional AOMDV procedures, with a focus on mitigating the consequences of congested nodes and improving the overall performance of MANETs. To tackle congestion-related challenges, the proposed technique utilizes higher sequence numbers to identify crowded nodes. The evaluation of these protocols is carried out using NS2.35, considering varying simulation durations and node sizes. Key performance metrics such as throughput, packet delivery ratio, packet loss, and average end-to-end latency are measured and compared between the protocols. The findings of this research demonstrate the effectiveness of the proposed COAOMDV technique in managing congestion problems in MANETs. The results indicate significant improvements in the performance of the AOMDV protocol when congestion management protocols are integrated. By addressing the challenges associated with congested nodes, this research contributes to enhancing the integrity and reliability of MANETs.

关键词： Mobile Ad hoc Networks congestion management AOMDV COAOMDV performance evaluation

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Deep Feature Fusion Framework for Alzheimer's Disease Staging Using Neuroimaging Modalities 1st

Deep Feature Fusion Framework for Alzheimer's Disease Stagin...

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1st MICCAI Meets Africa Workshop

作者： Gamal, Aya Elattar, Mustafa Selim, Sahar Nile Univ Med Imaging & Image Proc Res Grp Ctr Informat Sci Giza Egypt Nile Univ Sch Informat Technol & Comp Sci Giza Egypt

ISBN: (纸本)9783031791024;9783031791031

Alzheimer's Disease (AD) is a significant neurodegenerative disorder. Detecting AD early is essential for effective management and improving the quality of life for both patients and their families. Recent advancements in medical imaging technology have introduced neuroimaging-based methods for early AD diagnosis. However, the challenges in early AD detection suggest that using a single modality dataset in deep learning (DL) studies, particularly neuroimaging, might not yield precise predictions of AD progression compared to integrating data from multiple imaging modalities. Utilizing information from multi-modal data fusion can enhance the detection of subtle changes and biomarkers, leading to more reliable and accurate diagnosis. In our study, we develop an automated multimodal system that integrates MRI and PET images at an intermediate fusion level, facilitating the early diagnosis of Alzheimer's disease. This fusion approach eliminates the need for extensive preprocessing steps that are typically required in image fusion methods. Our proposed methodology outperforms previous studies in differentiating between individuals with Alzheimer's disease and cognitively normal (CN) individuals, achieving an AUC score of 97.67% and an accuracy (ACC) of 95.24%.

关键词： Alzheimer's Disease Neuroimaging Features 3D Image Classification

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Non-negative Tensor Representation and Unsupervised Classification of Object Pose in Continuous Image Sequences 4th

Non-negative Tensor Representation and Unsupervised Classifi...

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4th International Conference on Artificial Intelligence Logic and Applications

作者： Ying, Zhihao Zhao, Yang Pei, Jihong Yang, Xuan Shenzhen Univ Coll Elect & Informat Engn Shenzhen Guangdong Peoples R China Guangdong Prov Key Lab Intelligent Informat Proc Shenzhen Guangdong Peoples R China Shenzhen Univ Coll Comp Sci & Software Engn Shenzhen Guangdong Peoples R China

ISBN: (纸本)9789819603534;9789819603541

The analysis of video data in machine learning classification tasks has become a significant topic in both research and application areas. The accurate classification of video data by frame sets, particularly when the content contains objects that are in a state of dynamic change, represents a significant and complex undertaking. With regard to the temporal phase of video, the thesis proposes an unsupervised classification method based on non-negative tensor factorization (NTF). In order to transform the video data into low-dimensional data that can be classified by unsupervised clustering, the non-negative tensor factorization method is used to reduce the dimension of the input tensor, resulting in the generation of a non-negative rank-1 tensor combination. Following dimensionality reduction, the extracted features are divided into clusters through Mean Shift, thereby facilitating classification and recognition of video sequences. Experiments on the Coil-100 dataset of item image sequences at different angles and other dynamic pose-changing videos demonstrate the effectiveness of the method.

关键词： Video timing division Non-negative tensor factorization Unsupervised learning

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IoT - Enabled Tool for Static and Dynamic Analysis of Hand Strength 4th

IoT - Enabled Tool for Static and Dynamic Analysis of Hand S...

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4th International Conference on Advanced Network Technologies and Intelligent Computing-ANTIC-Annual

作者： Bhatnagar, Jay R. Iyer, Ravi Prakash Sharma, Jiya Bhatnagar, Tanay K. Graph Era Univ Dept Comp Sci & Engn Dehra Dun Uttarakhand India KREA Univ Dept Comp Sci & Engn Sricity India Shiv Nadar Inst Gurugram India

ISBN: (纸本)9783031837821;9783031837838

There is increasing evidence regarding the dependence of human health on actions performed using hands. In this paper, we propose an IoT-enabled framework for measuring hand strength based on pressure sensed from finger-tapping and finger-grip, also referred to as Finger-Tap and Grip Gram (FTGG). It performs sensing with the help of Clinical Mouse connected to IoT board which analyzes the static voltage from finger-grip and dynamic voltage from fingertapping. The finger-grip strength is estimated using pressure differences between Tight and Hold postures for 20 s observation collected from 40 humans of diverse age groups. Similarly, finger-tapping is monitored by averaging the max and min voltages from Thumb, Middle, and Little fingers for 10 s window. We classify finger-tapping into High tap and Low tap based on the pressure transferred from fingertip to piezo discs. Experimental Analysis for FTGG using 40 users yields the following results: finger-grip strength is markedly different between identified user groups, tap strengths recorded for both groups varies across all three fingers, tap strength is highest for Thumb followed by Middle and Little finger, correlation monitored in the finger-grip data for mature group is higher than the young group, cross-correlation monitored for finger-tap strength data between young and mature groups is typically low. The IoT-enabled FTGG setup demonstrated in this paper holds promise in commercial usage entailing the monitoring and diagnosis of clinical issues related to hand strength.

关键词： Clinical Mouse Hand Strength Finger-Tapping Finger-Grip IoT Analytics

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Impact of Virtual Reality on Cultural Heritages: Development of Mobile VR Tour of the Museum Site of Chandigarh, India 4th

Impact of Virtual Reality on Cultural Heritages: Development...

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4th International Conference on Advanced Network Technologies and Intelligent Computing-ANTIC-Annual

作者： Jangra, Shinnu Singh, Gurjinder Mantri, Archana Chitkara Univ Chitkara Univ Inst Engn & Technol Rajpura Punjab India Anurag Univ Hyderabad Telangana India

ISBN: (纸本)9783031837890;9783031837906

The integration of Virtual Reality (VR) into museum preservation has opened newavenues for enhancing visitor's engagement and education. This study explores the impact of VR technology on the Le-Corbusier Museum of Chandigarh, with a specific aim on the development of a mobile VR system for the Museum of Chandigarh, India. The research aims to develop an immersive, interactive experience that allows participants to explore the museum's exhibits in a virtual environment, thereby extending the museum's scope to a global audience. A total of 80 participants were participated in this research and equally divided into two groups: The mobile-VR version, and the non-VR version, to compare and evaluate the effectiveness of the VR system on the participants in terms of immersion level. The obtained results indicated overall immersion score of mobile VR was 3.94 (SD = 0.657), and the non-VR score was 3.54 (SD = 0.352) which indicates the designed mobile VR system is highly effective in the context of involvement and immersion as compared to non-VR groups. A significant difference was identified between both the groups using ANCOVA and the post hoc test. Additionally, this research also represented the significant difference between both versions based on the gender groups and prior knowledge of participants about the museum. Based on the results indicated the developed VR system is more effective as compared to non-VR tours of museums. The study also examines participant's interactions with the virtual museum, using the effectiveness of VR in promoting the cultural narratives of Chandigarh's promote heritage.

关键词： Virtual Museum User Experience Immersion 3D Modeling Preservation

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