Browsing by Author "Chen, Chi-Hua"

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A Cloud-Based Recommender System - A Case Study of Delicacy Recommendation
(2011)
Chen, Chi-Hua
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Yang, Ya-Ching
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Shih, Pei-Liang
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Lee, Fang-Yi
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Lo, Chi-Chun
Delicacy recommendation services are the trend of the future. In this paper, we propose an effective decision support systems (DSS), the Cloud-Based Recommender System (CBRS), which provides the introduction and commentaries of delicacies and restaurants with relevant recommendation. CBRS provides the web content retrieval agent (WCRA) and multiple document summarization (MDS) technology to generate summary of commentaries. Finally, CBRS combines with the cloud computing for MDS to provide delicacy recommendation services. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of [CEIS 2011]
A Field Wireless Sensor System for Mangrove Ecology Environment in Taiwan: Design and Implementation
(2012)
Lin, Mei-Hsien
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Kung, Hsu-Yang
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Li, Chia-Ling
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Chen, Chi-Hua
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Lai, Wei Kuang
This study is the first investigation of using wireless sensor networks (WSNs) for Mangroves protection and observation in Taiwan. In this paper, this study proposes a natural ecology sensing system (NESS), which consists of ecological environment sensor (EES), nature resource integrated computing server (NRICS), mobile user (MU), and ecological information service system (EISS). NESS can improve the traditional long-term observation method by providing a real-time and networked surveillance system. This paper considers the practical issues of deploying ecological environment sensors in the Mangroves protection area. In additions, feasible solutions are proposed to achieve sustainable energy supply and reliable data delivery with high accuracy. We also evaluate system performance in terms of energy consumption and packet loss rate at different duty cycles, and compare lifetime and data accuracy with different energy supply sources. According to implementation results, the proposed system is efficient and feasible for Mangroves observation, protection, and surveillance. [Mei-Hsien Lin, Hsu-Yang Kung, Chia-Ling Li, Chi-Hua Chen, Wei Kuang Lai. A Field Wireless Sensor System for Mangrove Ecology Environment in Taiwan: Design and Implementation. Life Sci J 2012;9(4):5759-5767] (ISSN:1097-8135). http://www.lifesciencesite.com. 857
A Fuel-Efficient Route Plan Method Based on Game Theory
(2019-01-01)
Lo, Chi-Lun
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Chen, Chi-Hua
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Hu, Jin-Li
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Lo, Kuen-Rong
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Cho, Hsun-Jung
This study adopts a fuel consumption estimation method to measure the consumed fuel quantity of each vehicle speed interval (i.e., a cost function) in accordance with individual behaviors. Furthermore, a mobile app is designed to consider the best responses of other route plan apps (e.g., the shortest route plan app and the fast route plan app) and plan the most fuel-efficient route according to the consumed fuel quantity. The numerical analysis results show that the proposed fuel-efficient route plan app can effectively support fuel-saving for logistics industries.
A green positioning algorithm for Campus Guidance System
(2012)
Chen, Chi-Hua
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Lin, Bon-Yeh
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Lin, Chun-Hao
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Liu, Yen-Szu
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Lo, Chi-Chun
In this paper, we propose a new CGS, called the Green Campus Guidance System (GCGS). The GCGS employs the Fingerprint Position Algorithm (FPA) using Received Signal Strength (RSS) from mobile stations/user equipment through cellular networks and Location-Based Services (LBSs) for user reference. In experiments, the results show that the error of location estimation using FPA is about 9.92 m. As to power consumption, the cost per sample of GPS is 27.68 times of that of FPA. Consequently, the FPA exerts itself as a green positioning algorithm, and thus can be used to support GCGS.
A High-Efficiency Method of Mobile Positioning Based on Commercial Vehicle Operation Data
(2016-06-01)
Chen, Chi-Hua
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Lin, Jia-Hong
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Kuan, Ta-Sheng
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Lo, Kuen-Rong
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資訊管理與財務金融系註：原資管所+財金所
Commercial vehicle operation (CVO) has been a popular application of intelligent transportation systems. Location determination and route tracing of an on-board unit (OBU) in a vehicle is an important capability for CVO. However, large location errors from global positioning system (GPS) receivers may occur in cities that shield GPS signals. Therefore, a highly efficient mobile positioning method is proposed based on the collection and analysis of the cellular network signals of CVO data. Parallel- and cloud-computing techniques are designed into the proposed method to quickly determine the location of an OBU for CVO. Furthermore, this study proposes analytical models to analyze the availability of the proposed mobile positioning method with various outlier filtering criteria. Experimentally, a CVO system was designed and implemented to collect CVO data from Chunghwa Telecom vehicles and to analyze the cellular network signals of CVO data for location determination. A case study found that the average errors of location determination using the proposed method vs. using the traditional cell-ID-based location method were 163.7 m and 521.2 m, respectively. Furthermore, the practical results show that the average location error and availability of using the proposed method are better than using GPS or the cell-ID-based location method for each road type, particularly urban roads. Therefore, this approach is feasible to determine OBU locations for improving CVO.
A Network Behavior Analysis System for Cloud Computing Service
(2011-03-01)
Lin, Bon-Yeh
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Chen, Chi-Hua
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Chang, Hsu-Chia
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Lo, Chi-Chun
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資訊管理與財務金融系註：原資管所+財金所
It will be full of distributed network services and a large quantity of data in network environment. It is important to dynamically retrieve the real-time network information when the information is published in network. In the determination of Optimal Cycle for Network Information Retrieval (OCNIR), the network loading and the cost of information retrieval are higher when the retrieval frequency is higher. If the retrieval frequency is too low, the delay time of information is long. For this reasoning, the OCNIR is an important issue. However, the OCNIR for cloud computing service has not been investigated. In this paper, we provide the integration of web service techniques and Network Behavior Analysis Model (NBAM). We implement Service-Oriented Architecture (SOA) environment with Semantic Web (SW) and NBAM to accomplish a Network Behavior Analyis System (NBAS) for cloud computing service. The major contents of this research are follows: (1) the establishment of NBAM, (2) the determination of the optimal cycle for network information retrieval, and (3) the establishment of data transmission and analysis based on SOA. We develop the approach and implement the NBAS for individuals or enterprises to find out NBAM and OCNIR, test this approach in a domain with real-time data alteration, and then evaluate this approach.
A Novel Real-Time Speech Summarizer System for the Learning of Sustainability
(2015-04-01)
Wang, Hsiu-Wen
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Cheng, Ding-Yuan
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Chen, Chi-Hua
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Wu, Yu-Rou
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Lo, Chi-Chun
As the number of speech and video documents increases on the Internet and portable devices proliferate, speech summarization becomes increasingly essential. Relevant research in this domain has typically focused on broadcasts and news; however, the automatic summarization methods used in the past may not apply to other speech domains (e.g., speech in lectures). Therefore, this study explores the lecture speech domain. The features used in previous research were analyzed and suitable features were selected following experimentation; subsequently, a three-phase real-time speech summarizer for the learning of sustainability (RTSSLS) was proposed. Phase One involved selecting independent features (e.g., centrality, resemblance to the title, sentence length, term frequency, and thematic words) and calculating the independent feature scores; Phase Two involved calculating the dependent features, such as the position compared with the independent feature scores; and Phase Three involved comparing these feature scores to obtain weighted averages of the function-scores, determine the highest-scoring sentence, and provide a summary. In practical results, the accuracies of macro-average and micro-average for the RTSSLS were 70% and 73%, respectively. Therefore, using a RTSSLS can enable users to acquire key speech information for the learning of sustainability.
A Novel Speed Estimation Method Using Location Service Events Based on Fingerprint Positioning
(2011-11-01)
Lin, Bon-Yeh
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Chen, Chi-Hua
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Lo, Chi-Chun
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資訊管理與財務金融系註：原資管所+財金所
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Department of Information Management and Finance
The rise of economic growth and technology advance has led to improve the quality of traditional transport system. Intelligent Transportation System (ITS) has become more and more popular. The building and promotion of real-time traffic information system is an important part of ITS. The traffic information estimations from cellular network data are more immediately, cost-effective, and easy to deploy and maintain than traditional methods. In this paper, we propose a novel speed estimation method using Location Service (LCS) events based on Fingerprint Positioning Algorithm (FPA). In experiments, we compare the estimated positioning information and speed information with the real information obtained from Global Position System (GPS) receiver. The results show that the average errors of location determination by using FPA and the traditional cell ID based location method are 36.11 meters and 714.07 meters, respectively. For speed estimation, the average error ratio of speed estimation by using FPA and the traditional cell ID based location method are 3.39% and 85.32%, respectively. Therefore, using FPA provides better accuracies of location determination and speed estimation than using cell ID based location method defined in the LCS specification. This approach is feasible to estimate traffic information for ITS improvement.
A Real-time Campus Guidance System Based on Energy Efficient Location Determination Method
(2011)
Lin, Chun-Hao
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Liu, Yen-Szu
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Chen, Chi-Hua
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Lin, Bon-Yeh
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Lo, Chi-Chun
Recently guidance system is becoming more popular, as more people realize its benefits. There have been many developments on campus guidance system (CGS) in personal digital assistant (PDA) and smart phone. The building and promotion of the energy efficient location determination method is an important part of CGS. The cellular-based location determination using RSS from cellular network is more immediately, power-effective, and easy to deploy and maintain than traditional methods. In this paper, we design the CGS which provides the fingerprint position algorithm (FPA) using RSS from cellular networks and location-based service (LBS) for user reference. In experiments, we compare the estimated positioning information with the real information from global position system (GPS) receiver. The results show that the error of location estimation using FPA is about 9.92 meters. This approach is feasible to be applied to CGS.
A Real-time Crime Detection System Based on Lawful Interception - A Case Study of MSN Messenger
(2011)
Chen, Chi-Hua
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Chen, Wan-Jia
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Wang, Ya-Fen
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Lo, Chi-Chun
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資訊管理與財務金融系註：原資管所+財金所
In recent years, the number of online crimes (e. g., the various emerging scams and criminal schemes) has increased. Online crime suspects utilize the anonymous nature of web to disguise their identity through various methods and evade detection and surveillance from law enforcement agencies. This study proposes an effective lawful interception system, Real-time Crime Detection System (RCDS), which includes Criminal Investigation Bureau (CIB), Internet Service Providers (ISP), and Network Interception Server (NIS) to establish a legally sanctioned lawful interception process which can collect and store evidence for criminal detection in real time. We provide a case study of MSN Messenger to describe the MSN Protocol (MSNP), information flow process, and lawful interception methodologies. The RCDS can provide criminal detection and surveillance services for MSN to obtain criminal communication records in turn reducing online criminal activities. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of [CEIS 2011]
A Real-Time Pothole Detection Approach for Intelligent Transportation System
(2015-01-01)
Wang, Hsiu-Wen
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Chen, Chi-Hua
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Cheng, Ding-Yuan
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Lin, Chun-Hao
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Lo, Chi-Chun
In recent years, fast economic growth and rapid technology advance have led to significant impact on the quality of traditional transport system. Intelligent transportation system(ITS), which aims to improve the transport system, has become more and more popular. Furthermore, improving the safety of traffic is an important issue of ITS, and the pothole on the road causes serious harm to drivers' safety. Therefore, drivers' safety may be improved with the establishment of real-time pothole detection system for sharing the pothole information. Moreover, using the mobile device to detect potholes has been more popular in recent years. This approach can detect potholes with lower cost in a comprehensive environment. This study proposes a pothole detection method based on the mobile sensing. The accelerometer data is normalized by Euler angle computation and is adopted in the pothole detection algorithm to obtain the pothole information. Moreover, the spatial interpolation method is used to reduce the location errors from global positioning system (GPS) data. In experiments, the results show that the proposed approach can precisely detect potholes without false-positives, and the higher accuracy is performed by the proposed approach. Therefore, the proposed real-time pothole detection approach can be used to improve the safety of traffic for ITS.
A Real-time Traffic Information Model Using GPS-based Probe Car Data
(2011)
Chen, Wan-Jia
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Chen, Chi-Hua
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Lin, Bon-Yeh
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Lo, Chi-Chun
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資訊管理與財務金融系註：原資管所+財金所
In recent year, the rise of economic growth and technology advance leads to improve the quality of service of traditional transport system. Intelligent Transportation System (ITS) has become more and more popular. At present, the collection of real-time traffic information is executed in two ways: (1) Stationary Vehicle Detectors (VD) and (2) Global Position System (GPS)-based probe cars reporting. However, VD devices need a large sum of money to build and maintain. Therefore, we propose the linear regression model to infer the equation between vehicle speed and traffic flow. The traffic flow can be estimated from the speed which is obtained from GPS-based probe cars. In experiments, the Speed Error Ratio (SER) and Flow Error Ratio (FER) of linear regression model are 4.60% and 24.63% respectively. The estimated speed and traffic flow by using linear regression model is better than by using linear model, power law model, exponential model, and normal distribution model. Therefore, the linear regression model can be used to estimate traffic information for ITS.
A Traffic Information Estimation Model Using Periodic Location Update Events from Cellular Network
(2011)
Lin, Bon-Yeh
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Chen, Chi-Hua
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Lo, Chi-Chun
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資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
In recent years considerable concerns have arisen over building Intelligent Transportation System (ITS) which focuses on efficiently managing the road network. One of the important purposes of ITS is to improve the usability of transportation resources so as extend the durability of vehicle, reduce the fuel consumption and transportation times. Before this goal can be achieved, it is vital to obtain correct and real-time traffic information, so that traffic information services can be provided in a timely and effective manner. Using Mobile Stations (MS) as probe to tracking the vehicle movement is a low cost and immediately solution to obtain the real-time traffic information. In this paper, we propose a model to analyze the relation between the amount of Periodic Location Update (PLU) events and traffic density. Finally, the numerical analysis shows that this model is feasible to estimate the traffic density.
A TRUST MECHANISM FOR WEB SERVICES REGISTRIES DATA EXCHANGING
(2012-11-01)
Chen, Chi-Hua
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Cheng, Ding-Yuan
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Lin, Bon-Yeh
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Lu, Yin-Jung
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Lo, Chi-Chun
In recent years, Web Services (WS) have been becoming more popular, as more people realize its benefits. However, the WS-Security specification only guarantees the security on end-to-end level. We propose the architecture of Trust-based Web Services Registries Data Exchanging (TWSRDE) which is four-tier architecture composed of the users, Web Service Providers (WSP) in Simple Object Access Protocol (SOAP) server, Enhance Web Services Registry (EWSR), and extra Web Services Registries (WSReg). The EWSR provides the trust mechanism which considers physical space and concept space to infer the trust value of WS for WSReg data exchanging.
A Two-Step Approach for Classifying Music Genre on the Strength of AHP Weighted Musical Features
(2019-01-01)
Chen, Yu-Tso
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Chen, Chi-Hua
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Wu, Szu
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Lo, Chi-Chun
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資訊管理與財務金融系註：原資管所+財金所
Music is a series of harmonious sounds well arranged by musical elements including rhythm, melody, and harmony (RMH). Since music digitalization has resulted in a wide variety of new musical applications used in daily life, the use of music genre classification (MGC), especially MGC automation, is increasingly playing a key role in the development of novel musical services. However, achieving satisfactory performance of MGC automation is a practical challenge. This paper proposes a two-step approach for music genre classification (called TSMGC) on the strength of analytic hierarchy process (AHP) weighted musical features. Compared with other MGC approaches, the TSMGC has three strong points for better performance: (1) various musical features extracted from the RMH and the calculated entropy are comprehensively considered, (2) the weight of features and their impact values determined by AHP are applied on the basis of the Exponential Distribution function, (3) music can be accurately categorized into a main-class and further sub-classes through a two-step classification process. According to the conducted experiment, the result exhibits an accuracy rate of 87%, which demonstrates the potential for the proposed TSMGC method to meet the emerging needs of MGC automation.
Accuracy Analysis Mechanism for Agriculture Data Using the Ensemble Neural Network Method
(2016-08-01)
Kung, Hsu-Yang
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Kuo, Ting-Huan
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Chen, Chi-Hua
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Tsai, Pei-Yu
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資訊管理與財務金融系註：原資管所+財金所
With the rise and development of information technology (IT) services, the amount of data generated is rapidly increasing. Data from many different places are inconsistent. Data capture, storage and analysis have major challenges. Most data analysis methods are unable to handle such large amounts of data. Many studies employ neural networks, mostly specifying the number of hidden layers and neurons according to experience or formula. Different sets of network topologies have different results, and the best network model is selected. This investigation proposes a system based on the ensemble neural network (ENN). It creates multiple network models, each with different numbers of hidden layers and neurons. A model that does not achieve the accuracy rate is discarded. The proposed system derives the weighted average of all remaining network models to improve the accuracy of the prediction. This study applies the proposed method to generate agricultural yield predictions. The agricultural production process in Taiwan is more complex than those of manufacturing or other industries. The Council of Agriculture provides agricultural forecasting primarily based on the planted area and experience to predict the yield, but without consideration of the overall planting environment. This work applies the proposed data analysis method to agriculture. The method based on ENN has a much lower error rate than traditional back-propagation neural networks, while multiple regression analysis has an error rate of 12.4%. Experimental results reveal that the ENN method is better than traditional back-propagation neural networks and multiple regression analysis.
An Analytical Framework of a Deployment Strategy for Cloud Computing Services: A Case Study of Academic Websites
(2013)
Chen, Chi-Hua
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Lin, Hui-Fei
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Chang, Hsu-Chia
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Ho, Ping-Hsien
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Lo, Chi-Chun
Cloud computing has become a popular topic for exploration in both academic and industrial research in recent years. In this paper, network behavior is analyzed to assess and compare the costs and risks associated with traditional local servers versus those associated with cloud computing to determine the appropriate deployment strategy. An analytic framework of a deployment strategy that involves two mathematical models and the analytical hierarchy process is proposed to analyze the costs and service level agreements of services involving using traditional local servers and platform as service platforms in the cloud. Two websites are used as test sites to analyze the costs and risks of deploying services in Google App Engine (GAE) (1) the website of Information and Finance of Management (IFM) at the National Chiao Tung University (NCTU) and (2) the NCTU website. If the examined websites were deployed in GAE, NCTU would save over 83.34% of the costs associated with using a traditional local server with low risk. Therefore, both the IFM and NCTU websites can be served appropriately in the cloud. Based on this strategy, a suggestion is proposed for managers and professionals.
An Augmented Reality Question Answering System Based on Ensemble Neural Networks
(2017-01-01)
Chen, Chi-Hua
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Wu, Chen-Ling
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Lo, Chi-Chun
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Hwang, Feng-Jang
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資訊管理與財務金融系註：原資管所+財金所
This paper proposes a classification algorithm based on ensemble neural networks. In the training phase, the proposed algorithm uses a random number of training data to develop multiple random artificial neural network (ANN) models until those ANN models converge. Those models with lower accuracy than the threshold are filtered out. The remaining highly accurate models will be used to predict the output in the testing phase. Meanwhile, the accuracy of ANN models is presented as a weighting value in the testing phase. In the testing phase, the testing data are loaded into the selected ANN models to predict the output class. The output values are multiplied by the corresponding weighting values of ANN models. Then the weighted average of the outputs can be obtained. Finally, the predicted output is converted into the predicted class. We design an augmented reality question answering system (AR-QAS) applying and implementing the proposed algorithm on mobile devices. AR-QAS offers an interactive user interface and automatically replies according to user's queries. By comparing with the logistic regression method and the ANN method, the experiment results demonstrate that the proposed algorithm offers the highest accuracy.
An Energy Efficient Geocast Routing Protocol based on a Defer-Time Control Function for Vehicular Ad-hoc Network
(2011)
Lin, Bon-Yeh
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Chen, Chi-Hua
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Lo, Chi-Chun
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資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
The Vehicular Ad-hoc NETwork (VANET) requires a suitable routing protocol to accommodate its special characteristics (e.g., high mobility, short-lived links, and fast-changing topology). There are many routing algorithms which are developed for transmitting information more quickly and cost-effective. In this paper, we propose a routing protocol which relies on Defer-Time Control Function (DTCF) to reduce the hop count, the transmission delay, and the probability of collisions during transmission. We provide an extensive analysis of DTCFs and choose the power-law model for routing protocol optimization. The function can be adjusted dynamically according to the distribution of the neighboring nodes (vehicles) of each hop. We also propose a mechanism to prevent the selected next-hop leaves the transmission range.
An Intelligent Embedded Marketing Service System based on TV apps: Design and implementation through product placement in idol dramas
(2013-08-01)
Lin, Hui-Fei
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Chen, Chi-Hua
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傳播與科技學系
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資訊管理與財務金融系註：原資管所+財金所
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Department of Communication and Technology
Due to the increase in advertising requirements for various multi-media services, two studies were conducted to first propose an Intelligent Embedded Marketing Service System (IEMSS) and then to use this IEMSS to implement product placement strategies for idol dramas using interactive television. In study I, the IEMSS combines TV apps, multiple agents, and multi-document summarization technologies to retrieve and store information and comments about merchandise from search engines, blogs, and forums. The IEMSS involves a multi-document summarization technique that uses the TF-IDF (term frequency-inverse document frequency), the position and an artificial neural network (ANN) to automatically generate and transmit key positive comments to the user via TV apps. The experimental results show that the IEMSS has 100% accuracy, indicating that the IEMSS is capable of helping users understand the merchandise and improving purchase intentions. In study 2, a 2 (product description messages: shown vs. not shown) x 2 (online reviews: shown vs. not shown) between-subjects design was conducted to examine the effectiveness of the IEMSS in an actual application. The results of this empirical research reveal that the display of reviews of the embedded products obtained from the Internet using the IEMSS functionality provides the viewing audience of idol dramas with the opinions of others who have used the embedded product, thereby improving attitudes toward the brand and product placement and stimulating purchase intentions. In sum, the IEMSS can be successfully applied to automatic summarization for advertising. Furthermore, this approach can be considered an extension of eWOM marketing and an application of Media Richness Theory that increases the effectiveness of product placement. (C) 2013 Elsevier Ltd. All rights reserved.