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International Conference on Science technology Engineering and Management (ICONSTEM)

作者： Manoj Hudnurkar Kartik Singh Suhas Ambekar Geeta Sahu Harshil Yecho Symbiosis Centre for Management & Human Resource Development (SCMHRD) Symbiosis International (Deemed University) Pune India Department of Information Technology and Data Science Vidyalankar School of Information Technology (VSIT) (University of Mumbai) Mumbai India

ISBN: (数字)9798350365092

ISBN: (纸本)9798350365108

The spread of the Metaverse has created new moral and legal challenges, especially when it comes to protecting against fraud. This study explores the legal complexities surrounding Ethereum-specific metaverse transactions and provides guidance on how to identify and address fraudulent activity. The focus of this investigation is the field of fraud detection in the Ethereum environment. Current methods of detecting fraud, such as Blockchain analysis and machine learning-based algorithms, are carefully examined. Next, a new approach to fraud detection is put out, which is predicated on a collection of seven machine learning algorithms: K-Nearest Neighbours (KNN), Decision Tree, Support Vector Machine (SVM), Random Forest, KNN, XGBoost (XGB), and Artificial Neural Network (ANN). The results of this study are carefully outlined, demonstrating the accuracy, recall, F1 score, and precision that each of the previously listed algorithms demonstrated. Moreover, this article lays out possible directions for further research, including the incorporation of group approaches and the investigation of creating characteristics to strengthen fraud detection abilities. This academic paper provides a significant and novel insight into the identification of fraudulent activity in Ethereum transactions, highlighting the potential benefits of using machine learning algorithms for this kind of discernment.

关键词： Support vector machines Machine learning algorithms Accuracy Metaverse Artificial neural networks Fraud Decision trees

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Key factors of an innovative organization to adapt to changing global management

Key factors of an innovative organization to adapt to changi...

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IEEE International Conference on Industrial Engineering and Engineering Management

作者： Te-Jeng Chang Pi-Shan Hsu Chien-Pen Chuang Wen-Shion Chang Department of Industrial Education National Taiwan Normal University Taipei Taiwan Department of Human Resource Development Ching Kuo Institute of Management and Health Keelung Taiwan Jinwen University of Science and Technology Taipei Taiwan

ISBN: (纸本)9781424426294

A top priority of global management is to manage change, which requires establishing an innovative organization to be responsive to change. Traditional and matrix organizations lack an effective horizontal structure to construct core elements required for organizational learning. An innovative organization is required to implement those core elements such as self-actualization, self-development, social acceptation, shared vision and transformational leadership. Managerial innovation is achieved by incorporating organizational learning within the innovative organization. The alignment of the core elements required for organizational learning with the key factors of an innovative organization enables an environment inspiring individuals¿ passion and initiative to manage change. Factors critical to the successful deployment of an innovative organization are presented in this study in terms of volunteer assignment, multi-task competence, autonomous community, employee entrusted authority, floating authorization and peer-group decision making.

关键词： Innovation management human resource management technology management Environmental management Technological innovation Globalization Educational technology Authorization Decision making Chaos

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Predicting Delays for Truck Delivery Logistics: An application of AI and ML

Predicting Delays for Truck Delivery Logistics: An Applicati...

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International Conference on Science technology Engineering and Management (ICONSTEM)

作者： Manoj Hudnurkar Kuriakose M. Renji Suhas Ambekar Geeta Sahu Kavitha Mary Joseph Symbiosis Centre for Management & Human Resource Development (SCMHRD) Symbiosis International (Deemed University) Pune India Department of Information Technology and Data Science Vidyalankar School of Information Technology (VSIT) (University of Mumbai) Mumbai India

ISBN: (数字)9798350365092

ISBN: (纸本)9798350365108

Supply chain management has a lot of logistical challenges, which can significantly affect the efficacy and efficiency of logistics operations as a whole. Machine learning techniques are increasingly popular because they can evaluate vast data volumes and produce precise predictions. Logistics management must include the forecast of delays in the supply chain. It entails anticipating delays in logistics operations, which can assist logistics managers in effectively planning and allocating resources. This paper summarizes the logistics delay prediction in truck delivery systems and identifies some opportunities and problems. The article also suggests a framework for predicting logistics delays based on machine learning methods and assesses the framework's effectiveness using actual data. Thus, the research uses machine learning and AI approaches to anticipate logistics delays. The study gathered information on previous logistical operations and determined the major causes of delays. Then, models for predicting logistical delays were used using machine learning techniques, such as Artificial Neural Networks (ANN), decision trees, random forests, and support vector machines. Our findings demonstrate that these methods have an accuracy rate of up to 97.6 % in predicting logistics delays. Also, we discovered that the Adaboost classifier model performed better than the other models in accuracy and precision. Our study offers insightful information on the application of machine learning methods for anticipating logistics delays, which can assist supply chain managers and logistics firms in better organizing and manage their operations to cut down on delays and increase overall effectiveness.

关键词： Costs Accuracy Machine learning algorithms Supply chains Machine learning Predictive models Real-time systems

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The silent power - applications of research in medical X-ray combining with photography and digital graphic design

The silent power - Applications of research in medical X-ray...

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20th ACM International Conference on Multimedia, MM 2012

作者： Tsai, Shih-Ting Chen, Ming-Hsiu Mia Chang, Chi-Cheng Kuo, Yu-Hung Lawry, Miranda Ting, Yi-Shu Graduate Institute of Design Science Tatung University No.40 Sec. 3 Jhongshan N. Rd. Jhongshan District Taipei City 104 Taiwan Department of Technology Application and Human Resource Development National Taiwan Normal University 162. HePing East Road Taipei Taiwan School of Drama Fine Art and Music Faculty of Education and Arts University of Newcastle University Drive Callaghan NSW 2308 Australia Department of Nuclear Medicine and Molecular Imaging Center Chang Gung Memorial Hospital No.5 Fusing St. Gueishan Township Taoyuan 333 Taiwan

ISBN: (纸本)9781450310895

X-ray is a kind of secret power, it is usually used on the medicine, and it can be perspective human body and some items which are not metals. In the graphic art and design filed, digital photography is the common method for creating image, go through this method and the after effect editing, so many alluring images are presented for the audience;however, these images which are created by digital photography only can present the externals. The internal world is always as a secret region, we maybe know what it is, but we couldn't comprehend how it is like, thus, x-ray is the best way to understand what the internals is. In this research, medical contrast is used with lily flower, let the flower absorb the contrast for 12 hours, and the contrast will winding through the whole flower, then exposure the flower by x-ray, therefore, because of wavelength of radiation and contrast, we can see the internal of stem and leaves. The second method is used on human body. One of the authors is model in this part, and takes photo with same view and angle by digital camera and medical x-ray;consequently, the audience could see the internal and external view of models' body at the same time. On the basis of this research project, the intended outcome is going to bring authors some new vision, and after go through the whole project, authors wish some new imaginative ideas would be created in the testing procedure, therefore we could obtain new thoughts and experience from this project, and the x-ray combining design could let us know this silent power could be so different and it can be used not just in medicine, and delivering more ideas and methods to the other designers;artists and researchers who are interested on the same topic in design. © 2012 Authors.

关键词： Photography

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An agent-based personalized multimedia Jukebox for mobile devices using consumption sentiment 2

An agent-based personalized multimedia Jukebox for mobile de...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Won-Ik Park Miseon Choi Young-Kuk Kim Department C E Chungnam National University Daejeon South Korea Human Resource Development Consortium for Next Generation Software in Information Technology Chungnam National University Daejeon South Korea

ISBN: (纸本)9781424443147

This paper classifies the user's purchase pattern into four types of behavior, and proposes an agent-based personalized multimedia Jukebox that provides a personalized service on the client side. The proposed Jukebox assists the efficient management of numerous multimedia contents stored in a personal desktop computer, and provides personalized multimedia contents to the mobile device based on a push service type.

关键词： Content management Mobile computing humans Pattern analysis Electronic mail Multimedia systems Scalability Taxonomy Computer architecture

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A Hybrid Cache Cohrency Scheme for Ubiquitous Mobile Clients

A Hybrid Cache Cohrency Scheme for Ubiquitous Mobile Clients

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International Conference on Convergence Information technology

作者： Miseon Choi Wonik Park Young-Kuk Kim Human Resource Development Consortium for Next Generation Software in Information Technology Chungnam National University Daejeon South Korea Department of Computer Engineering Chungnam National University Daejeon South Korea

ISBN: (纸本)9780769530383

We propose a new cache coherency scheme named HCCS(hybrid cache coherency scheme) to facilitate ubiquitous data access of mobile clients. To cope with the limitations of ubiquitous computing environments, it integrates the cache invalidation scheme using broadcast channel into the publish/subscribe-based data synchronization scheme using two-way communication channel. We present novel algorithms and system architecture for the HCCS. By integrating two schemes, the HCCS provides substantial benefits: allows updates on the mobile client which are restricted in the cache invalidation scheme using broadcast channel and disconnected operations, improves the scalability. The HCCS scheme also gives proper support to the short disconnection of mobile clients, dynamically adapts to changes of disconnection period of the mobile clients.

关键词： Wireless networks Mobile computing Broadcasting Ubiquitous computing Scalability Information technology Transaction databases Pervasive computing Communication channels Bandwidth

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Examining the relationship between learning organization characteristics and change adaptation, innovation, and organizational performance

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human resource development Quarterly 2005年第2期16卷 185-212页

作者： Kontoghiorghes, Constantine Awbrey, Susan M. Feurig, Pamela L. Department of Human Resource Management and Organizational Behavior Cyprus International Institute of Management Cyprus Department of Human Resource Development Oakland University Rochester MI United States Information Technology NAFTA Change Management Division DaimlerChrysler Corporation Sterling Heights MI United States

The main purpose of this exploratory study was to examine the relationship between certain learning organization characteristics and change adaptation, innovation, and bottom-line organizational performance. The following learning organization characteristics were found to be the strongest predictors of rapid change adaptation, quick product or service introduction, and bottom-line organizational performance: open communications and information sharing;risk taking and new idea promotion;and information, facts, time, and resource availability to perform one's job in a professional manner.

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Understanding the Stress of Online Learning Among University Students 12

Understanding the Stress of Online Learning Among University...

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12th IEEE International Conference on Engineering Education, ICEED 2023

作者： Rosli, Mohd Shafie Saleh, Nor Shela Ali, Azlah Md. Bakar, Suaibah Abu Alshammari, Sultan Hammad Johar, Siti Sarawati School of Education Universiti Teknologi Malaysia Faculty of Social Sciences and Humanities Johor Bahru Malaysia Universiti Tun Hussein Onn Malaysia Center for General Studies and Co-Curicular Department of Social Science Batu Pahat Malaysia School of Human Resource Development & Psychology Universiti Teknologi Malaysia Faculty of Social Sciences and Humanities Johor Bahru Malaysia College of Education University of Hail Department of Educational Technology Hail Saudi Arabia

ISBN: (纸本)9798350307429

As the pandemic Covid-19 erupted worldwide in 2020, the entire world rapidly adopted online education as a means of sustaining the education system in universities and schools. However, the majority of students were unfamiliar with these methods, as they were accustomed to traditional classrooms. Some students may prefer online education over traditional education, but online education stress remains a persistent issue. This study investigated the stress encountered by students during online learning sessions. 220 university students participated in this quantitative correlational study. On the basis of 11 items developed and tested using Confirmatory Factor Analysis, a questionnaire consisting of three constructs of online learning stress, financial capacity, and positive perception of online learning was developed and administered. The data were subsequently evaluated using the Structural Model in order to comprehend the relationships between the variables. The model was discovered to have a high level of fitness and validity. Positive perceptions of online learning were discovered to predict student stress negatively. The financial capacity of students to purchase the necessary devices for online learning sessions had no effect on their stress levels. However, financial capacity is the antecedent of how positively students viewed online learning for themselves. This suggests that for online education to be successful, it is crucial to consider the students' perceptions by evaluating their access to all the devices and technologies associated with online learning. © 2023 IEEE.

关键词： Students

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A Cloud-Based UV Monitoring System for Remote Real-Time UV Exposure Tracking 4

A Cloud-Based UV Monitoring System for Remote Real-Time UV E...

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4th International Conference on Smart Electronics and Communication, ICOSEC 2023

作者： Dankan Gowda, V. Prasad, V. Nuthan Prasad, K.D.V. Prasad, V.K. Satya Mahajan, Yogesh Suneetha, Sampathirao Bms Institute of Technology and Management Department of Electronics and Communication Engineering Karnataka Bangalore India M S R i T Department of Electronics and Communication Engineering Karnataka Bangalore India Symbiosis Institute of Business Management Hyderabad India Pune India Symbiosis International University Symbiosis Centre for Management and Human Resource Development Maharashtra Pune India Andhra University College of Engineering Andhra University Department of Computer Science and Systems Engineering Andhra Pradesh Visakhapatnam India

ISBN: (纸本)9798350300888

Due to the widespread nature of sun-related health risks, sophisticated UV monitoring systems are urgently needed. This research study introduces a cloud-based UV monitoring system with the intent of remotely tracking and analyzing UV exposure in real time. The system incorporates a network of UV sensors deployed in various locations, continuously collecting UV radiation data. These sensors are linked to a cloud system, which allows for easy sharing and processing of collected data. As a result, we're working to perfect a cutting-edge device that can monitor vitamin D absorption, measure cumulative UV exposure, and warn of impending danger. Extensive studies have demonstrated the benefits of UV exposure for both general health and protection against the newly discovered coronavirus. However, finding a happy medium is important because too much sun exposure can cause cancer, lupus flares, and cataracts. The proposed model gives users the ability to set their own daily UV exposure limits, taking into account clinically validated thresholds for various skin tones. The developed sensor module is able to measure the UV index with high precision even in bright sunlight because it closely mimics the skin erythema spectrum. © 2023 IEEE.

关键词： Ultraviolet radiation

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Earlier peak photosynthesis timing potentially escalates global wildfires

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National Science Review 2024年第09期11卷 171-180页

作者： Gengke Lai Jialing Li Jun Wang Chaoyang Wu Yongguang Zhang Constantin M.Zohner Josep Pe?uelas Quansheng Ge International Institute for Earth System Sciences Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing University Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural ResourcesSchool of Geography and Ocean Science Nanjing University The Key Laboratory of Land Surface Pattern and Simulation Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Huangshan National Park Ecosystem Field Scientific Observation and Research Station of the Ministry of Education Jiangsu International Joint Carbon Neutrality Laboratory Nanjing University Department of Environmental Systems Science Institute of Integrative BiologyETH Zurich CSIC Global Ecology Unit CREAF-CSIC-UAB CREAF Cerdanyola del Vallès

More intense fire weather due to climate change is implicated as a key driver of recent extreme wildfire events. As fuel stock, the role of vegetation and its phenology changes in wildfire dynamics, however is not fully appreciated. Using long-term satellite-based burned areas and photosynthesis observations, we reveal that an earlier peak photosynthesis timing(PPT) potentially acts to escalate subsequent wildfires, with an increase in the global average burned fraction of 0.021%(～2.20 Mha) for every additional day of PPT advancement. Satellite observations and Earth System modeling consistently show that this fire escalation is likely due to intensified drought conditions and increased fuel availability associated with the climate feedback arising from earlier PPT. Current fire-enabled dynamic global vegetation models can reproduce the observed negative correlation between PPT and burned area but underestimate the strength of the relationship notably. Given the continued PPT advancement owing to climate change, the bioclimatic effects of vegetation phenology change suggest a potentially pervasive upward pressure on future wildfires.

关键词： vegetation photosynthesis phenology wildfire climate feedback Earth System model

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