检索结果-内蒙古大学图书馆

12th International Conference on Ubi-Media Computing, Ubi-Media 2019

作者： Thaipisutikul, Tipajin Chen, Yi-Cheng Hui, Lin Chen, Sheng-Chih Mongkolwat, Pattanasak Shih, Timothy K. Department of Computer Science and Information Engineering National Central University Taiwan Department of Information Management National Central University Taiwan Department of Innovative Information and Technology Tamkang University Taiwan Master's Program of Digital Content and Technologies College of Communication National ChengChi University Taiwan Faculty of Information and Communication Technology Mahidol University Thailand

ISBN: (纸本)9781728128207

Reinforcement Learning (RL) is an extraordinarily paradigm that aims to solve a complex problem. This technique leverages the traditional feedforward networks with temporal-difference learning to overcome supervised and unsupervised real-world problems. However, RL is one of state-of-the-art topic due to the opaque aspects in design and implementation. Also, in which situation we will get performance gain from RL is still unclear. Therefore, This study firstly examines the impact of Experience Replay in Deep Q-Learning agent with Self-Driving Car application. Secondly, The impact of Eligibility Trace in RNN A3C agents with Breakout AI game application is studied. Our results indicated that these two techniques enhance RL performance by more than 20 percent as compared with traditional RL methods. © 2019 IEEE.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

A System Dynamics Computer Model to Assess the Effects of Action Games on the Development of Children with Special Need 4

A System Dynamics Computer Model to Assess the Effects of Ac...

引用

4th International Conference on information management and technology, ICIMTech 2019

作者： Satria, Thomas Galih Sardjono, Wahyu Panggabean, Francisco Maruli Game Application Technology Program School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Information Systems Management Department Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9781728133331

Special needs children have a tendency to play more games than children with development in general. Game play activities are often carried out by children with special needs can be a support learning and therapy due to his players the game has interaction without having to meet with his co-star in person. Starting from these data, this study aims to create a model of the System Dynamics approach. Data collected will be simulated by variables other support. The simulation results of the model will be seen autistic children therapy behavior. The results are then analyzed to create an alternative to the existing model. The benefit of this research is to know the description of game play to treatment of children with special needs. The results of simulation showed that playing games in an average time children with autism play therapy can help improve the quality of children with autism if children with autism play the game in a long time actually showed a decrease. © 2019 IEEE.

关键词： System theory

来源：评论

学校读者我要写书评

暂无评论

Sport Science Model to Support the Professional Sports Organization Decision Making

Sport Science Model to Support the Professional Sports Organ...

引用

International Conference on information management and technology (ICIMTech)

作者： Tanty Oktavia Ford Lumban Gaol Takaaki Hosoda Arsyan Syahir School of Information Systems Bina Nusantara University Jakarta Indonesia BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Advanced Institute of Industrial Technology Tokyo Japan BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9781728170718

ISBN: (纸本)9781728170725

The role of information technology in sports organizations is important to analyze all aspects including how to win in the competition based on various internal and external factors. The approach that used to enhance the sports organizations is sports science, which is a concept that contributes to the development of athletes by collaborating in many fields and studies, such as anatomy, physiology, psychology, engineering, chemistry, etc. The approach of Sport science articulates the technology that blended on all of the approached. Currently, the use of sports technology or science in Indonesia is also very low in all sports categories. Usually, the management and coaches look at player statistics based on manual data or reports to view player statistics periodically. There is still a lack of exploration to use player statistics to be used by coaches to improve the ability of the players and the organization. This research will propose how to develop sports science with a business intelligence approach that used the Kimball data mart approach as decision support in the field of sports so that management and coaches can apply the correct approach to improve the capacity of players and organizational development. The result of this study will provide the model of sports science that can be implemented for a professional sports organization in Indonesia.

关键词： Business intelligence Decision making Tools Companies

来源：评论

学校读者我要写书评

暂无评论

Transformative Sport Science Using Social Media as a Collaboration Tool

Transformative Sport Science Using Social Media as a Collabo...

引用

International Conference on ICT For Smart Society (ICISS)

作者： Tanty Oktavia Ford Lumban Gaol Takaaki Hosoda Arsyan Syahir School of Information Systems Bina Nusantara University Jakarta Indonesia Binus Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Advanced Institute of Industrial Technology Tokyo Japan BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9781665404228

ISBN: (纸本)9781665404235

Sports science can have a significant and positive impact on coaches and athletes, as well as for the professional sports organization. According to this situation, more and more organizations are competing to implement sports science as the monitoring systems. Along with the development of technology, it becomes easier for humans to carry out their activities, including communication with each other. Advances in the field of communication technologies have led to the use of social networks to support all activity. With social media, all kinds of information that people want to search for can be found easily. Social networks have their uniqueness in their characteristics. Like LINE has free calling and video calling features, while Instagram has features like Instagram Story, where users can document their activities in the form of photos or recordings. By all the characteristics of social networks, it will support the activity of sports science. The methodology of this research focused on quantitative research based on the T-test approach. The result shows that social media involvement can significantly support collaboration in sports science, so it can increase people's motivation to interact with other participants in sport organizations.

关键词： Sports Social networking (online) Media Reliability Organizations Tools information systems

来源：评论

学校读者我要写书评

暂无评论

Based on machine learning for personalized skin care products recommendation engine

Based on machine learning for personalized skin care product...

引用

International Symposium on Computer, Consumer and Control (IS3C)

作者： Hsiao-Hui Li Yuan-Hsun Liao Yen-Nun Huang Po-Jen Cheng Bachelor's Degree Program in Chain Store Management Tainan University of Technology Tainan Taiwan Master Program of Digital Innovation Tunghai University Taichung Taiwan Research Center for Information Technology Innovation Academia Sinica Taipei Taiwan National Chung Cheng University Chiayi Taiwan

ISBN: (数字)9781728193625

ISBN: (纸本)9781728193632

With the economic development and the aging trend, the use of cosmetic products has expanded rapidly. In an ever-expanding skin care market, facial skin care product was the most popular product of skin care product. However, thousands of skin care products are available in the market. With endless options, shoppers are confronted confused and tired. Because everyone's skin condition is not the same, using unsuitable skin care products can damage the skin. Frequent problems with face skin are wrinkles, spots, acne vulgaris, pores, etc. The causes of facial lines, such as dryness, facial expressions, aging, etc., are cause different shades and different types of wrinkles. Therefore, it is very important to know your skin quality and use skin care products correctly. According to the application of different levels of image processing, it can be divided into image classification, positioning, object detection and object segmentation in the field of image vision. This paper will focus on the application of machine learning and deep learning algorithm development on human face and skin intelligence recommendation platform. That uses YOLOv4's novel object recognition algorithm to detect key features in face images, and intercept sub-images of regions of interest (ROI) as input information for multi-label models. Each sub-image detects the defective part through the YOLOv4 identifier of the second layer, and calculates the ratio of the pixel area of the local block to the main body to evaluate the correlation between feature parts and degree to establish a reference for the optimization of subsequent multi-label model. The skin condition classification uses the image processing algorithm to preprocess automatically remove, reduce noise, enhance, normalize and extract features to obtain the feature vectors of the sub-images for training the multi-label classification model. The prediction results of machine learning can provide suitable maintenance knowledge and product re

关键词： Machine learning algorithms Face recognition Maintenance engineering Feature extraction Skin Classification algorithms Engines

来源：评论

学校读者我要写书评

暂无评论

Groundwater quality assessment using few-shot learning with prototypical, Siamese, and matching networks

引用

Journal of Water Process Engineering 2025年 75卷

作者： Derdour, Abdessamed Baz, Mohammed Alzaed, Ali Bojer, Amanuel Kumsa Ghoneim, Sherif S.M. Artificial Intelligence Laboratory for Mechanical and Civil Structures and Soil University Center of Naama P.O. Box 66 Naama 45000 Algeria Laboratory for the Sustainable Management of Natural Resources in Arid and Semi-Arid Zones University Center of Naama Naama 45000 Algeria Department of Computer Engineering College of Computers and Information Technology Taif University Taif 21944 Saudi Arabia Architectural Engineering Program - Civil Engineering Department Faculty of Engineering Taif University Taif 21944 Saudi Arabia Ethiopian Artificial Intelligence Institute PO Box 40782 Addis Ababa Ethiopia Department of Electrical Engineering College of Engineering Taif University Taif 21944 Saudi Arabia

Groundwater quality assessment is critical for sustainable water resource management, especially in hyperarid regions like Adrar, Algeria, where data scarcity and environmental challenges hinder traditional monitoring methods. This study explores the application of three Few-Shot Learning (FSL) algorithms: Prototypical Networks, Siamese Networks, and Matching Networks, for groundwater quality classification using limited datasets. The dataset comprises 166 groundwater samples from the Adrar region, characterized by five quality classes: “Excellent,” “Very Good,” “Good,” “Satisfactory,” and “Unsatisfactory.” Results demonstrate that Prototypical Networks outperform other FSL algorithms, achieving 93 % accuracy with 10 support samples per class, while Siamese and Matching Networks achieve 90 % and 88 % accuracy, respectively. The study highlights the potential of FSL in addressing data scarcity, offering a cost-effective and efficient approach for groundwater quality assessment in data-scarce regions. The findings underscore the importance of FSL in complementing traditional methods, particularly in hyper arid areas where data collection is challenging. © 2025 The Authors

关键词： Accuracy evaluation Classification algorithms Data scarcity Hyperarid regions Water resource management

来源：评论

学校读者我要写书评

暂无评论

The Impact of Learning Motivation on Character-Nurturing and Competitive Game-Based Item Bank Practicing System 10

The Impact of Learning Motivation on Character-Nurturing and...

引用

10th IEEE International Conference on technology for Education, T4E 2019

作者： Peng, Jui-Chi Lai, Yu-Ling Hwang, Gwo-Haur Health and Hospitality Cardinal Tien Junior College of Healthcare and Management Yilan County Taiwan Information Management Ling Tung University Taichung City Taiwan Bachelor Program in Interdisciplinary Studies National Yunlin University of Science and Technology Yunlin County Taiwan

ISBN: (纸本)9781728142272

In Taiwan, the traditional approach in English learning can be experienced as dull and boring. As a result, it leads to a decline in learning motivation and learning effectiveness. Some scholars have pointed out that adding games into learning could enhance the learner's motivation. However, different game strategies may have different effects on learners' learning motivation. Therefore, this study explored how different types of systems (a character-nurturing game, a competitive game and traditional practice without games) impacted learners' motivation when blending those systems into learning. In order to study this issue, the researchers first developed three systems which were a character-nurturing game-based item bank practicing system, a competitive game-based item bank practicing system and an item bank practicing system without games. Then the researchers invited 125 first-graders from a junior college in northern Taiwan taking an English course, and conducted a nine-week teaching experiment. The results showed that the learners of the competitive-game group had significantly lower confidence and satisfaction than the learners of the character-nurturing-game group. © 2019 IEEE.

关键词： Blending

来源：评论

学校读者我要写书评

暂无评论

A Proposed Model for Consumer-Based Brand Equity Analysis on Social Media Using Data Mining and Social Network Analysis

引用

Journal of Relationship Marketing 2018年第2期17卷 95-117页

作者： Nogueira, Eduardo Tsunoda, Denise F. Program of Science Management and Information Technology Federal University of Parana Curitiba Parana Brazil

Online social networks have expanded their “virtual borders,” making the Internet more like an environment of social interaction than a business tool. However, even before the emergence and expansion of social media, marketing professionals were interested in identifying consumers' perceptions about brands. Thus, operational models have been proposed to facilitate such a task. Those models, however, can be expensive and inconvenient, since the models use questionnaires for data collection. To help overcome this problem, this article proposes a model for brand equity analysis from the consumer perspective expressed in social networks using opinion mining techniques and social network analysis. The application of the proposed model on data collected from Twitter made it possible to analyze five brand equity dimensions: brand awareness, brand loyalty, perceived sentiment, perceived quality, and brand associations. The results reached by the application of the model show that brand equity can be analyzed from data retrieved from virtual social networks, disclosing how consumers perceive brands in such an environment, without using questionnaires, enabling different brands in different contexts. Those data can be analyzed under both objective and replicable criteria for each of the brand equity elements that make up the model. © 2018 Taylor & Francis Group, LLC.

关键词： brand equity consumer-based brand equity data mining knowledge discovery online social network social media social network analysis

来源：评论

学校读者我要写书评

暂无评论

Roots to roofs: Farmers' perceived socio-ecological impacts of converting mango orchards to urban areas in Multan, Pakistan

引用

Environmental Challenges 2024年 15卷

作者： Hassan, Zamam Khan, Fawad Z.A. Aldosary, Adel S. Al-Ramadan, Baqer Ahmad, Ahtisham Manzoor, Syed Amir Rahman, Muhammad Tauhidur Department of Forestry & Range Management Faculty of Agricultural Sciences & Technology Bahauddin Zakariya University Multan 60000 Pakistan Department of Outreach and Continuing Education MNS University of Agriculture Multan 60000 Pakistan Institute of Plant Protection MNS University of Agriculture Multan 60000 Pakistan Department of Architecture and City Design King Fahd University of Petroleum and Minerals Dhahran 31261 Saudi Arabia Interdisciplinary Research Center for Smart Mobility and Logistics King Fahad University of Petroleum and Minerals Dhahran 31261 Saudi Arabia Geospatial Information Sciences Program School of Economic Political and Policy Sciences University of Texas at Dallas 800 Campbell Road Richardson 75080 TX United States

The process of urban growth often results in the conversion of agricultural spaces, including orchards. In Pakistan, Multan - widely known as the city of Mangoes - has seen exponential urban growth in the past couple of decades, resulting in a huge loss of Mango orchards to urban settlements. This research focuses on investigating local farmers’ motivations for selling Mango orchards to urban colonies and their perceived implications of transforming mango orchards into residential areas in Multan, Pakistan. By surveying 100 participants, the study captures insights into urban expansion trends, primary motivations behind selling agricultural land, and the social, economic and environmental consequences of such conversions. Descriptive statistics and correlation analysis (heatmap) are used to dissect the farmers perceptions on the drivers and implications of Mango orchards' conversion to housing settlements in Multan, Pakistan. Notably, 96% of respondents highlighted that orchards nearer to urban centers were predominantly targeted for conversion. Furthermore, 57% believed less productive orchards were more frequently turned into urban developments. Our correlation analysis provided clarity on the economic dimensions. Participants who felt their orchard was not a profitable venture tended to see greater economic advantages from selling their orchards. Interestingly, individuals motivated by a desire to 'improve quality of life' generally observed an improvement in their living conditions post-sale. On the environmental spectrum, concerns such as potential future temperature rises were consistently associated with several selling motivations, indicating a broad awareness of environmental consequences. This comprehensive research highlight the interplay of economic, social, and environmental factors in orchard-to-housing conversions, presenting valuable knowledge for urban development strategists and decision-makers. © 2024 The Author(s)

关键词： Environmental impact Mango orchards Multan Southern Punjab Urban expansion

来源：评论

学校读者我要写书评

暂无评论

A novel evolution-based recommendation system 12

A novel evolution-based recommendation system

引用

12th International Conference on Ubi-Media Computing, Ubi-Media 2019

作者： Chen, Yi-Cheng Chu, Yen-Lung Hui, Lin Chen, Sheng-Chih Thaipisutikul, Tipajin Weng, Kai-Ze Department of Information Management National Central University Taiwan Department of Computer Science and Information Engineering Tamkang University Taiwan Department of Innovative Information and Technology Tamkang University Taiwan Master's Program of Digital Content and Technologies College of Communication National ChengChi University Taiwan Department of Computer Science and Information Engineering National Central University Taiwan

ISBN: (纸本)9781728128207

Matrix factorization (MF) technique has been widely utilized in recommendation systems due to the precise prediction of users' interests. Prior MF-based methods adapt the overall rating to make the recommendation by extracting latent factors from users and items. However, in real applications, people's preferences usually vary with time;the traditional MF-based methods could not properly capture the change of users' interests. In this paper, by incorporating the recurrent neural network (RNN) into MF, we develop a novel recommendation system, M-RNN-F, to effectively describe the preference evolution of users over time. A learning model is proposed to capture the evolution pattern and predict the user preference in the future. The experimental results show that M-RNN-F performs better than other state-of-the-art recommendation algorithms. In addition, we conduct the experiments on real world dataset to demonstrate the practicability. © 2019 IEEE.

关键词： Recommender systems

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：