Urban Rainwater Management and Protection Through Optimization for Multiple Goals - L Yong (Journal of Digital Information Management, 2024)
With the continuous acceleration of urbanization, urban rainwater management has become an increasingly important issue. In the process of urbanization, the increase in impervious area and insufficient drainage systems have led to an increase in rainwater runoff and a risk of water quality deterioration. This article explores the application of multi-objective optimization in landscape urban rainwater design and defense. Against the backdrop of accelerating urbanization, rainwater management has become an important issue. By introducing multi-objective optimization methods, the aim is to seek a more comprehensive and effective rainwater design solution to address the impact of urbanization on rainwater.

A Novel Algorithm for Generating pseudo Random Number- - Gangyi Hu; Weili Kou; Sumeth Yuenyong; Jian Qu (Journal of Digital Information Management, 2020)
This paper proposes a pseudo random number generation algorithm based on cellular neural networks. It used the hyper-chaos characteristics of the cellular neural networks and sets the appropriate parameters to generate the pseudo random number. The experimental results show that, compared with other similar algorithms, this algorithm has the characteristics of simple operation, low complexity, large key space, and good randomness. It can meet the needs of secure communication and network information security, which has good application prospects.

Effective Evaluation of XML Queries in a Visual Environment- - Weimin He; Teng Lv; Ping Yan (Journal of Digital Information Management, 2019)
Since its emergence in 1997, Extensible Markup Language (XML) has become a standard data format for data exchange among a variety of web applications. In this paper, we present a framework to effectively evaluate XML queries in a visual environment. We have developed a system termed VXPath, which is a visual XPath query evaluator that allows the user to evaluate various XPath queries by clicking the nodes in an expanding tree instead of typing the whole XPath queries manually. Our system GUI is built on top of Microsoft .NET Windows Forms Applications. We have implemented most XPath axes in our system, including child, descendant, self, parent, ancestor, following-sibling, preceding-sibling, predicate and so on. In order to handle large size XML documents, instead of loading the whole XML document into memory, we developed an effective algorithm to extract a concise data synopsis called structural summary from the original XML document to avoid the loading overhead for large XML documents. We evaluated our system over the data from XMark and DBLP and our system can handle large XML documents up to gigabytes.

Effective Evaluation of XML Queries in a Visual Environment - Weimin He (Journal of Digital Information Management, 2019)

Application of the Fiber Image Detection Algorithm Based on the Grey System Theory and Directed Graph - Xiaodong Wang; Jianhui Yang (Journal of Multimedia Processing and Technologies, 2018)

Assimilation of Business Intelligence (BI) and Big Data Analytics (BDA) Towards Establishing Organizational Strategic Performance Management Diagnostics Framework: A Case Study- - Mailasan Jayakrishnan; Abdul Karim Mohamad; Mokhtar Mohd Yusof (Journal of Digital Information Management, 2018)
In this research paper, we had observed and proposed the characteristic of Big Data Analytics (BDA) and Business Intelligence (BI) in observing the voluminous picture of organizational strategic performance management diagnostics framework. In our study, we are interested in handling BDA and BI as a dynamic research that had enabled organizations to invade and generate greater knowledge formation and decision-making. Our research goal is to advance a real world understanding of emerging knowledge derived from organizing big data scenarios and BI framework development. In order, to overcome the ambiguity scenarios of BDA, we propose a framework that involve the present BDA and BI stages with their analytic features in designing the organizational strategic performance management framework. The outcome will be a design of a typical strategic performance management application – the organizational strategic diagnostic dashboard.

Assimilation of Business Intelligence (BI) and Big Data Analytics (BDA) Towards Establishing Organizational Strategic Performance Management Diagnostics Framework: A Case Study - Mailasan Jayakrishnan; Abdul Karim Mohamad; Mokhtar Mohd Yusof (Journal of Digital Information Management, 2018)

Major Issues in Adoption of Electronic Health Records - Myongho Yi (Journal of Digital Information Management, 2018)

Major Issues in Adoption of Electronic Health Records- - Myongho Yi (Journal of Digital Information Management, 2018)
The use of Electronic Health Records (EHRs) is not new, but the implementation and provision of their services are. Despite the positive aspects and promising features of EHRs use in medical and healthcare practices, there are many issues that need to be identified and addressed to expedite the adoption rate of EHRs. The objective of the study is to examine major issues which hinder EHR adoption and to present identified solutions.

A Noise-Robust Image Encryption Algorithm Based on Hyper Chaotic Cellular Neural Network - Gangyi Hu; Sumeth Yuenyong; Jian Qu; Jian Rong; Weili Kou (Journal of Digital Information Management, 2018)

A Noise-Robust Image Encryption Algorithm Based on Hyper Chaotic Cellular Neural Network- - Gangyi Hu; Sumeth Yuenyong; Jian Qu; Jian Rong; Weili Kou (Journal of Digital Information Management, 2018)
We propose an image encryption algorithm based on a 6-dimensional chaotic cellular neural network (CNN) that is robust to noise/missing pixels in the cipher image. We performed parameter search on the templates of the CNN in order to discover the parameters that leads to 6D chaotic evolution of the state, and then used the resulting chaotic sequence as the basis of encryption. The encryption process itself consists of shuffling the positions of image pixels based on the numerical value of the chaotic sequence; the second half of the encryption process consists of changing the shuffled image pixel values by performing XOR operation between the pixel values and the numerical value of the chaotic sequence. By using simple operations like sorting and XOR in the encryption process, the algorithm is robust to noise/ missing pixels in the cipher image. We illustrate this by comparing the robustness against 3 recently proposed chaos-based image encryption algorithms. The results show that our algorithm is competitive with the state-ofthe-art in term of encryption security, and superior in term of robustness.

Dynamic parse approach of ladder diagram based on binary logic tree on the soft PLC system - Yang, G.; Yang, J.; Li, S. (Journal of Digital Information Management, 2017)

A novel digital image classification algorithm via low-rank sparse bag-of-features model - Zou, X.-M.; Sun, H.-J.; Yang, S.; Zhu, Y. (Journal of Digital Information Management, 2016)

A novel recommendation strategy for user-based collaborative filtering in intelligent marketing - Yi, J.; Zhang, L.; Phelan, C.A. (Journal of Digital Information Management, 2016)

Research on power dispatching automation system for data management of power plant substation - Li, H.; Zhu, Q.; Yang, F. (Journal of Digital Information Management, 2016)

Risk evaluation of information exchange among nodes under P2P net work environment - Yingjun, H.; Xiaoyang, W. (Journal of Digital Information Management, 2016)

Sentence-level opinion analysis for Chinese news documents based on sentiment information of social tags - Yeh, J.-Y.; Chen, S.-Y. (Journal of Digital Information Management, 2016)

Study on the classification of negative sentiment Weibo messages in the post-disaster situation - Bai, H.; Yu, G.; Tian, X.Y. (Journal of Digital Information Management, 2016)

Application of a NewmAnt-MinerPRAlgorithm in Classification Rule Mining - Yang, L.; Li, K.S.; Zhang, W.S.; Wang, Y.; Ke, Z.X. (Journal of Digital Information Management, 2015)

Denoising and segmentation of digital feather image using mean shift algorithm - Yue, H.; Cai, K.; Luo, B.; Jin, Y.; Zeng, Z. (Journal of Digital Information Management, 2015)

A feature selection method to handle imbalanced data in text classification - Chang, F.; Guo, J.; Xu, W.; Yao, K. (Journal of Digital Information Management, 2015)

Power station flue gas desulfurization system based on automatic online monitoring platform - Liu, X.; Ma, C.; Yang, X.; Yang, C.; Diao, Y. (Journal of Digital Information Management, 2015)

Recognizing Discrepant Traffic Data Based on Least Square Support Vector Machine - Yao, C.; Gu, J. (Journal of Digital Information Management, 2015)

Research on Application of Digital Literature Archives Management Based on XML Database System - Yang, Y. (Journal of Digital Information Management, 2015)

Adaptive fuzzy PID control for servo motor direct-drive pump control system - Zheng, J.-M.; He, M.-J.; Liu, E.-D.; Yuan, Q.-L.; Xiao, J.-M.; Tang, A.-F. (Journal of Digital Information Management, 2014)
The direct-drive pump control system has been gradually applied to the industrial control field due to its high control precision, fast response, small throttle loss and compact structure. This paper adopts the fuzzy PID control method to resolve the hydraulic cylinder position servo control of direct-drive pump control system. The system model and fuzzy PID control algorithm was established by using AMEsim/Simulink joint simulation platform. The step response and Sine tracking performance of the system with PID and fuzzy PID control algorithms was investigated by simulation. At the same time, the performance of PID and fuzzy PID control was studied on the self-developed electro-hydraulic servo control experiment table. The results show that the adaptive fuzzy PID control can greatly improve the performance of the PID control, and has the characteristics of fast response, short rise time, small time delay and overshoot.
Cited By (since 1996):1Export Date: 10 July 2014
Keywords: Adaptive fuzzy PID control; AMESim/simulink; Direct-drive pump control system; Labview; Position servo control

Research on application of image encryption technology based on chaotic of cellular neural network - Li, G.-D.; Zhao, G.-M.; Xu, W.-X.; Yao, S.-Z. (Journal of Digital Information Management, 2014)
This paper gives a brief introduction of the basic knowledge of Cellular Neural Networks and proposes an image encryption algorithm based on Cellular Neural Networks. The algorithm is based on the unique characteristics of Cellular Neural Networks by using a chaotic system of 5-D CNN as the key source. On this basis, The paper puts forward an image pixel scrambling algorithm based on Logistic chaotic sequence, which realize the image encryption. In this paper, encryption algorithms are programmed and stimulated. The results show that encryption image is the characters of higher pixels' scrambling degree, small correlation between adjacent pixels, strong anti attack, higher security.
Keywords: Cellular Neural Network (CNN); Chaotic System; Image Encryption

Research on the Application of SIFT Algorithm in UAV remote sensing image feature extraction - Yuan, D.; Cui, X.; Xu, W.; Hong, X.; Yu, S. (Journal of Digital Information Management, 2014)
UAV remote sensing is characterized by fast speed and flexibility and applied widely. The extraction and matching for feature point of UAV image is a foundational work in the application of UAV remote sensing. SIFT is a currently widely used feature point extraction algorithm that keeps invariant as the scale changes. It is also invariant as image changes in other aspects. Meanwhile it maintains certain stability to noise and light changes. SIFT is a kind of compute-intensive mission and usually takes much time. The author made parallel processing for SIFT algorithm and good accelerator ratio has been achieved on the premise of ensuring good result of feature point extraction and matching.
Keywords: Content processing; Feature point extraction; SIFT; UAV; Video frame processing

A SEIR model epidemic of virus on the online social network - Min, Y.; Qianmu, L.; Yaoliang, S. (Journal of Digital Information Management, 2014)
Vigorous development of computer technology has made computers play an integral role in people's lives, but at the same time propagation of the virus on a computer network also cost a great loss to the people. So the research on the mechanism of computer virus propagation and pointing out the key factors in the propagation of the virus has a significant influence on the prevention of computer virus and can also promote the development of relevant policies. The paper researched the influence of the user re-login frequency, the average number of friends on the user's friend list and the initial spread rate of the virus on the social networks during the epidemic of the propagation of the computer virus. By the means of mathematical analysis, an SEIR model to describe the epidemic of the virus on the online social network is established in this paper. The research shows that the re-login frequency of the user and the average friend number of the user would make a significant influence on the virus propagation. The two factors enhance the risk of a virus outbreak in the social network, at the same time.
Keywords: Complex network; Computer virus; Epidemic spreading; Social Network; Social networks; Transmission factor; Virus propagation

Exception detection for web service composition using improved bayesian network - Chen, Y.; Ying, S.; Zhang, L.; Wu, J. (Journal of Digital Information Management, 2013)
New application systems generated by composition of web services dynamically have become a development trend in network environment. However, since a variety of external services are invoked with different quality of service during processing, the problem of how to keep the execution stable must be addressed in order to improve the reliability and availability of the combination of services. In this paper, an approach of exception detection is presented for web service composition by improved Bayesian network. Firstly, the topological structure of Bayesian network is established, where the causal relationships between underlying web services are mapped to Bayesian network in service combination process. The conventional Bayesian network algorithm is improved to satisfy the demand of better conversion from nodes in web service composition to nodes in Bayesian network. Secondly, the parameter setting in Bayesian network is explored for determining the prior probability of service nodes and the conditional probability of service output node. Thirdly, the algorithm of the improved exception detection model is introduced, with the aim of locating the web services that cause exceptions in the execution of composite services. Lastly, a case study is given and the results analysis is also conducted. The results show that the presented approach not only considers the uncertainty during exception detection, but also can identify the exception web services in the process.
Keywords: Bayesian network; Exception handling; Web service; Web service composition

Fair virtual bandwidth allocation model in virtual data centers - Yuan, Y.; Wang, C.-R.; Wang, C. (Journal of Digital Information Management, 2013)
Network virtualization opens a promising way to support diverse applications over a shared substrate by running multiple virtual networks. Current virtual data centers in cloud computing have flexible mechanisms to partition compute resources but provide little control over how tenants share the network. This paper proposes a utility-maximization model for bandwidth sharing between virtual networks in the same substrate network. The aim is to improve the fairness of virtual bandwidth allocation for multi tenants, especially for virtual links which share the same physical link and carry nonfriendly traffic. We first given a basic model and then proved the model can be split into many sub models which can run on each rack-switch port. In the sub model, every physical link is associated with a fairness index constraint in maximize utility calculating. The goal is to limit the differences among the bandwidth allocation of the virtual links which share the same physical link. Experimental results show that the virtual bandwidth allocation between tenants is more reasonable.
Keywords: Bandwidth allocation; Multi-tenant; Network virtualization; Virtual data centers

Hierarchical clustering analysis method based on the grid with obstacle space - Shan, D.; Yang, Z. (Journal of Digital Information Management, 2013)
The advantage of grid-based clustering method is its fast processing speed. The speed of clustering algorithm and the number of data objects is unrelated. To discover any size and shape of the clusterÿit is by the number of units on each dimension in the data space. In this method, the amount of data and computation time does not matter, calculations and data entry of the order does not matter, does not require the number of k-means algorithm to pre-specified cluster and so on. Clustering problem with obstacle constraints has very strong practical value in the spatial clustering analysis, and has become a research hotspot in recent years. Under the condition of existing obstacles constraints, the vast majority of the spatial clustering algorithm can't effectively solve the problem of irregular obstructions. Thus it has a greater impact on the accuracy of the algorithm clustering results, and reduces the efficiency of the algorithm. To solve this problem, an obstacle constraint space grid-based hierarchical clustering algorithm, which is GSHCO algorithm, is proposed. The algorithm inherits the advantages of gridbased clustering algorithm, by defining the concept of barriers to grid to deal effectively with the obstacles of arbitrary shape, to achieve the purpose of found clusters of arbitrary shape; At the same time, the algorithm uses a hierarchical strategy which can effectively reduce the complexity of the algorithm with obstacles clustering and the algorithm is improved operating efficiency. The experimental results show that the GSHCO algorithm can deal with obstacles constrained clustering, and with higher performance and better clustering quality.
Keywords: Cluster ensemble; Grid spatial clustering; Multi-scale clustering; Spatial cluster analysis

A hybrid method to deformation force of high-speed cold roll-beating forming - Yang, M.-S.; Li, Y.; Yuan, Q.-L. (Journal of Digital Information Management, 2013)
High-speed cold roll-beating forming technique is a new near-net plastic forming method that the intermittent high-speed roll-beating is used to achieve dynamic impact local loading, and that is fast, transient, high impact, large deformation of the complex forming process. For this forming process, the main stress method is employed to derive an analytic formula for the deformation force. Taking into account the main stress method can not reflect impact factors such as high-speed transient roll beating in process of this analytic solution, then the ABAQUS/Explicit is applied to simulate for highspeed cold roll- beating. The regression analysis is used to correct for the analytic formula based on simulation results, which makes the analytic formula more accurate reflection of deformation force of the different technological parameters of high-speed cold roll-beating. The forming experiments are carried out with self developed high-speed cold roll-beating experimental equipment and the experimental of deformation force is measured to verify the correctness of the corrected analytic formula.
Cited By (since 1996):1Export Date: 10 July 2014
Keywords: Cold roll-beating; Deformation force; Experimental verification; Slab method

Improved image fusion algorithm for detecting obstacles in forests - Yan, L.; Yu, Z.; Han, N.; Liu, J. (Journal of Digital Information Management, 2013)
The harvester has been widely used in forestry operations. However the existence of obstacles in forests, such as stones, animals, human and clustered trees, may leads to safety accident and decreases the operating efficiency of the harvester. Therefore it becomes vital to show the obstacles accurately to provide guidance for the harvester. In this paper, an improved image fusion algorithm based on Contourlet transform and pulse coupled neural network (PCNN) is proposed to enhance the fused images' clarity and capture more abundant information of the reality. As for comparison, algorithms, such as wavelet transform, Principal Component Analysis (PCA) and PCNN are simulated to evaluate the proposed algorithm. Visible and infrared thermal image are captured in forest in this experiment. The experimental results demonstrate that the proposed algorithm outperform the mentioned methods by the objective criteria of Entropy, Average gradient and Standard deviation.
Keywords: Contourlet transform; Image fusion; Improved algorithm; Obstacles in forests; Pulse coupled neural network

Information sharing in supply chain: A review - Yang, Z.; Zhang, L. (Journal of Digital Information Management, 2013)
The importance of information sharing in supply chain management is a matter of consensus between practitioners and researchers. Information sharing can increase supply chain efficiency by reducing inventories and smoothing production. Studies from different and recognised authors are reviewed, compiled and analyzed in three aspects. First, the types of shared information in supply chain are summarized. After, the value of different shared information and the factors which affect its value are presented. Moreover, the methodologies used in literature are detailed. The paper concludes with some future directions for theory construction and empirical research.
Keywords: Information sharing; Literature review; Supply chain network; Supply chains management

The modeling of genetic and Tabu search algorithm based BP neural network in the risk analysis of investment - Yang, L.; Yunlong, D. (Journal of Digital Information Management, 2013)
There are many parameters which affect the economic benefit indicators for evaluation and they are all uncertain. Because of the parameters' uncertainty, evaluation indicators values of economic benefit in project investment are also uncertain. In these years, more and more BP Neural network based models are established to evaluate the risk of investment for its characters of wide information distribution and strong fault tolerance. However, the internal defect of local minima problem in this model will greatly discount the effects of evaluation if the training data are not proposed selected. To solve this problem of traditional BP neural network, an optimization algorithm that combines the advantages of genetic algorithm (GA) and Tabu Search (TS) is proposed. The training process is divided into two phases in order to search promising parameters of the BP neural network in favor of better evaluation and analysis of the investment. In the first phase, the initial parameters are first searched by GA algorithm by taking advantage of its various searches of the solutions, and the best parameters are selected by Tabu search algorithm in the second phases. After calculation of practical data, it proves that the new algorithm has better convergence rate and predictive accuracy, which make the evaluation and risk analysis of the investment faster and more accurate.
Cited By (since 1996):2Export Date: 10 July 2014
Keywords: BP Neural Network; Genetic Algorithm; Investment Evaluation; Risk Analysis; Tabu Search Algorithm

A new shuffled frog leaping algorithm with space zoomed factor and gravity attractor - Tang, D.; Yang, J. (Journal of Digital Information Management, 2013)
Shuffled frog leaping algorithm is a new kind of swarm intelligence optimization algorithm. Due to the local search of the basic shuffled frog leaping algorithm which is the only by the worst frog to search and jump, searching ability of which was limited; therefore it had the low precision, slow convergence speed and easy premature convergence etc. Therefore, in order to enhance the ability of the local searching, this paper presented a gravity attractor, all the frogs in the same memeplexe could find the best position under its guidance. Considering the transboundary problems in the frog searching for food process, we introduced a space zoomed factor which made the frog out of the searching space could also be put into the searching space, and the social position relation was not changed, thus it improve the search ability of the SFLA. Through the standard function for testing, and compared with the standard SFLA algorithm and szAPSO algorithm, the experimental results show that the improved algorithm not only improves the convergence speed of the algorithm, enhance the searching capability of the algorithm, but also has better stability.
Keywords: Gravity attractor; Search strategy; Shuffled frogleaping algorithm; Space zoomed factor; Swarm intelligence optimization

Optimization and application of support vector machine based on SVM algorithm parameters - Yan, H.-F.; Wang, W.-F.; Liu, J. (Journal of Digital Information Management, 2013)
The hospital customer classification is very important for the integration and allocation of hospital resources, can greatly enhance the market competitiveness of the hospital. Support Vector Machine (SVM) is an approach to solve classification problem by using optimization method. Selecting different kernel parameters can construct different classifiers, meanwhile parameters decide their learning and generalization ability. In order to solve the limitation of selecting parameters by experience, so the particle swarm (PSO) pattern search algorithm is proposed to search optimal parameters and take them into the practice of hospital customer classification; The PSO mode search algorithm is to combine the advantages of PSO algorithm and pattern search algorithm, PSO mode search algorithm has strong global search capability and good advantage of local convergence. The result of experiment shows that this method is not only efficient, but also to search the optimal parameters achieving a high accuracy, which is an effective method of SVM parameter optimization.
Keywords: Customer data classification; Kernel parameters selection; Particle swarm pattern search; Support vector machine

Robustness analysis of social network based on a dynamic model - Wu, H.; Ying, S.; Jia, X.; Zhang, L.; Chen, X. (Journal of Digital Information Management, 2013)
Due to the high vulnerability of today's social systems against disruptions, it has become critical to measure and manage the robustness of social networks. In this study the relationship between social network's topology and its robustness in the presence of cascading failures is examined. In the attempt to help practice in increasing the robustness of social systems, the concept of the robustness of social systems is discussed and defined first. And then we propose a new dynamic model of social systems to investigate the robustness of social systems. We theorize that network characteristics such as average path length, node degree, and size of the largest connected component in social networks and so on. Based on the model, a good evaluation method is proposed to investigate the robustness of social networks against the cascading failures of component nodes. Finally, the damage degree of social networks considering cascading failures is investigated through our model. The simulation results confirm that there is a positive relationship between the robustness of social systems and social system performance, while a negative relationship between the topology structure and the robustness of social systems. By the dynamic model, we not only identify the potential key nodes, but also obtain the parameter value which can make the social network reach strongest robustness level. Our work develops a new methodology to the real world application. This research is helpful to increase the robustness of such complex systems and tackle the optimization problem of them.
Keywords: Disruptions; Graph Theory; Network Damage Degree; Robustness; Social Network Analysis

Spanning tree method for minimum communication costs in grouped virtual mapreduce cluster - Yang, Y.; Long, X.; Shi, B. (Journal of Digital Information Management, 2013)
Today, MapReduce and virtual cluster are sharp swords for this big data and cloud computing era. To combine these two emerging technologies, it brings feasible-scalability, easy-management, fast-deployment and high-efficiency with the system. As every sword has two sides, the I/O bottleneck of virtualization technologies may seriously impacts on the performance of MapReduce cluster which deals with I/O-intensive applications. In this paper, we analyze the combination advantages and disadvantages of virtualization technology of MapReduce cluster. We also analyze the communication model for both of them and build a communication costs model. Then, we propose a novel algorithm of minimum-weight spanning tree to construct a lower communication costs virtual MapReduce cluster. With the help of constructing minimum-weight spanning tree, we find out a method to select local-master and group the cluster. Theoretical simulation and experiment results demonstrate that our method can greatly reduce communication costs. The performance improvement is up to ~40.4% respectively.
Keywords: Cloud computing; Mapreduce; Spanning tree; Virtual machine

The statistical analysis of family names of donators for wenchuan - Yufan, L.; Qinghua, C. (Journal of Digital Information Management, 2013)
It is analyzed that the family names of personal donators who donated through China Construction Bank Corporation to Chinese Red Cross Foundation for the WenChuan earthquake. The distribution of family names, the first 100 family names and their shares, the probability of the same family names as well as the Gini coefficient are all given in this paper. A heavy disproportion is showed in the distribution, that is to say a small part of family names occupy the absolutely large proportion while most of them are rare. This character is similar to power-law that has been observed in many demonstrations about family names. However, the Kolmogorov-Smirnov test fails to support the hypothesis. Instead, part of the data shows an exponential characteristic. As an innovative sampling method, the discussion may help to know the family name's distribution of China.
Keywords: Distribution; Exponential; Powerlaw; The family name

Study on computer audit based on OLAP technology - Yanjun, T. (Journal of Digital Information Management, 2013)
It has become increasingly difficult for the traditional audit information system to find out the necessary audit information from the mass data generated in the large scale application of accounting computerization and ERP software, etc. For the current massive financial and operation information data of enterprises, a new audit model is necessarily explored to satisfy the requirements on massive information audit. Dynamic on-line analysis and audit information system can provide a brand new train of thought to conduct rapid and efficient audit in mass data. Under such a backdrop, selective introduction of the computer audit mode based on OLAP from Western Countries has become the necessity for the current audit development of our country. The computer audit based on OLAP technology mainly conducts multi-angle data observation, finding suspicious audit data, and create an audit data model in advance; it mainly includes five parts, i.e. data model subsystem, audit online analysis processing subsystem, auditing business management subsystem, expertise experience library subsystem and audit alarm subsystem.
Keywords: Computer Audit; Data model; OLAP; Subsystem CLC Number; TP311.13 F239

A comparison of pattern classification approaches for structural damage identification - Qingqing, Z.; Qifeng, Z.; Yongpeng, N.; Fan, Y.; Jiayan, L.; Run, T.; Minda, L. (Journal of Digital Information Management, 2012)
A structural damage identification approach based on wavelet packet decomposition (WPD) and random forests (RF) was proposed and compared with other pattern classification approachs. The main procedure involves extracting energy features from vibration acceleration data through wavelet packet decomposition and then using these features as input for a RF classifier. The experiment was carried on an 8-storey steel shear building model in the case verification. The results show that the proposed method is effective for structure damage detection and can achieve a higher accuracy than other commonly used methods.
Keywords: Extraction algorithms; Pattern matching; Sensor identificaiton; Wavelet packet decomposition

Investigating factors influencing non-use and abandonment of microblogging services - Guo, Y.; Goh, D.H.-L.; Ilangovan, K.; Jiao, S.; Yang, X. (Journal of Digital Information Management, 2012)
This study explores the reason for non-usage and abandonment of microblogging. While previous studies mainly focused on individual behaviors associated with the use of social media, this research identifies why people do not use, or terminate their microblogging accounts. Studying the reasons for non-usage and abandonment is important as it helps organizations devise strategies to counteract this behavior by addressing nonusers' concerns. First, focus group interviews were conducted to uncover non-usage reasons. The elicited reasons were then used to construct a survey instrument and administered. Our results suggests that preference for other technologies, privacy concern and time constraints are the top three reasons contributing to the non-use and abandonment of microblogging accounts. The paper also proposes potential improvements to microblogs to attract more users.
Keywords: Abandonment; Focus Group; Microblogging; Non-use; Social media; Social networks; Survey

A novel RDB-SW approach for commodities price dynamic trend analysis based on web mining - Zhu, Q.; Zhou, P.; Cao, S.; Yan, Y.; Ding, J. (Journal of Digital Information Management, 2012)
In order to improve the accuracy of price forecasting for dynamic trend analysis on imperfect data by web extracting, a novel repair data algorithm based on dichotomy backfilling is proposed in this paper. The price forecasting algorithm based on the Sliding Window (SW) is utilized to verify the validity of Repair Dichotomy Backfilling (RDB) algorithm. Experiments demonstrated that the mean absolute errors can be achieved to 5.31 percent average. Furthermore, the price forecasting algorithm based on original data and that based on RDB data are explored to compare their accuracy. Experiments demonstrated the reduction of mean absolute errors in the price dynamic trend analysis verification model. The average MAE on original data is 2.38 percent when the average MAE on RDB data is 2.31 percent. Experiment results proved that the proposed RDB-SW approach is meaningful and useful to analyze and to research the price market on imperfect data by Web extracting.
Cited By (since 1996):5Export Date: 10 July 2014
Keywords: Dichotomy backfilling; Disturbance factor; Imperfect data; Price forecast algorithm; Sliding window

Research and practice of characteristic teaching resources sharing and interactive platform - Yun, W. (Journal of Digital Information Management, 2012)
By using advanced cloud computing, virtualization and distributed video load balance technology, the paper constructs an interactive platform which shares the teaching resources. On the one hand it provides a beyond time and space, free and equal interactive teaching and learning platform for the teachers and students. On the other hand it offers teaching resources Networked storage, utilization, communication and show space. Dispersive resources will be classified automatically and integrated modularly in order to perform Characteristic and high-quality multimedia resource database and media teaching characteristic of material database.
Keywords: Characteristic teaching resource; Interactive platform; Sharing

Research on face recognition based on wavelet transform and PCA-ANN - Yuanzhi, W.; Xiao, L. (Journal of Digital Information Management, 2012)
This paper mainly studies the basic theory and technology on the identification of people's faces. The better methods are chosen and a new method is proposed. It integrates three elements (Wavelet Transform, Principal Component Analysis, Artificial Neural Networks), and the method can recognize faces more effectively. Meanwhile, this method lessens the effect of light on face appearance. Experimental result indicates that our new face recognition system is effective in the aspects of both correct ratio and speed of distinguishing.
Keywords: Face recognition; Feature extraction; Principal component analysis; Radial basis function neural network

A retrieval method based on language model considering neighboring contents - Tamura, K.; Hatano, K.; Yadohisa, H. (Journal of Digital Information Management, 2012)
The World Wide Web (WWW) has a massive number of Web pages, so that it is difficult for users to get useful information. In recent years, however, it is said that the probabilistic language model can help to improve retrieval accuracies of some kinds of search engines. The probabilistic language model has statistical background and can adapt previous text information retrieval model. However, we cannot directly adapt the probabilistic language model to Web search engines, because data on the Web has a hyperlink environment while the probabilistic language model can only text information on it. In this paper, we propose a novel approach for searching Web pages considering a Web page as well as its neighboring oneson the hyperlink environment.
Keywords: Hyperlink Analysis; Language Model; Web search

Story segmentation of xinwenlianbo based on three-level criterion of content analysis - Yang, J.-C. (Journal of Digital Information Management, 2012)
To detect the story boundary (SB) of Xinwenlianbo precisely, this paper proposes a method of three-level criterion story segmentation (SS) based on content analysis. For the story with anchorperson, this paper uses penny distance to judge whether the anchorperson gotten by video feature is true or not to look for SB; for the story without anchorperson, this paper looks for the SB by judging the shot change point occurs in the silence region. The experiment results show that the method can improve 6.98% precision comparing with only using video feature in anchor detection and the error range can be decreased from 1.5 ~2.5 seconds to 0 ~0.5 second in SB without anchor by silence detection, which settles the problem of no precision boundary and video frame lost corresponding to silence for only using silence .The final precision of SS reaches 93.12%.
Keywords: Content analysis; Penalty distance; Story segmentation; Three-level criterion; Xinwenlianbo

Editorial - Yuxin, M.; Xu, L. (Journal of Digital Information Management, 2011)

Password based anonymous authentication with private information retrieval - Nakamura, T.; Inenaga, S.; Ikeda, D.; Baba, K.; Yasuura, H. (Journal of Digital Information Management, 2011)
This paper focuses on authentication with three types of entities: a user who sends an authentication request, a service provider who receives and verifies the request, and a database who supplies the service provider with information for verifying the request. This paper presents novel authentication protocols that satisfy the following important properties: (1) secure against replay attacks and (2) the database cannot identify which user is authenticating. First, we show a protocol which satisfies Properties (2). Second, we show a protocol which satisfies Properties (1) and (2). A key idea of our authentication protocols is to use private information retrieval (PIR) [Chor et al. J. ACM, 1998].
Keywords: Anonymity; Authentication; Privacy protection; Private information retrieval

An approach for matching schemas of heterogeneous relational databases - Karasneh, Y.; Ibrahim, H.; Othman, M.; Yaakob, R. (Journal of Digital Information Management, 2010)
Schema matching is a basic problem in many database application domains, such as data integration. The problem of schema matching can be formulated as follows, "given two schemas, Si and Sj, find the most plausible correspondences between the elements of Si and S j, exploiting all available information, such as the schemas, instance data, and auxiliary sources" [24]. Given the rapidly increasing number of data sources to integrate and due to database heterogeneities, manually identifying schema matches is a tedious, time consuming, error-prone, and therefore expensive process. As systems become able to handle more complex databases and applications, their schemas become large, further increasing the number of matches to be performed. Thus, automating this process, which attempts to achieve faster and less labor-intensive, has been one of the main tasks in data integration. However, it is not possible to determine fully automatically the different correspondences between schemas, primarily because of the differing and often not explicated or documented semantics of the schemas. Several solutions in solving the issues of schema matching have been proposed. Nevertheless, these solutions are still limited, as they do not explore most of the available information related to schemas and thus affect the result of integration. This paper presents an approach for matching schemas of heterogeneous relational databases that utilizes most of the information related to schemas, which indirectly explores the implicit semantics of the schemas, that further improves the results of the integration.
Keywords: Biomedical database; Database integration; Heterogeneous; Schema matching

Bidirectional recommendation technology for web digital texts - Wada, Y.; Matsuzawa, S.; Yamaguchi, M.; Dohi, S. (Journal of Digital Information Management, 2010)
Recently, e-learning systems have begun to be used in companies and education institutions. The spread of e-learning is mainly due to development of the learning management system (LMS), which includes SCORM and WebCT. Therefore, the introduction of learning the web digital web digital texts have become much simpler. The increase of contents of the web digital texts has realized a wider range of learning. As a result, we are concerned that learners will be confused with selecting the best learning web digital texts. In our research, we are developing a bidirectional recommendation system that extracts the relationship among learning the web digital texts with historical logs and recommends an effective web digital text for learners. In this paper, we first discuss the design of the bidirectional recommendation system, and second, we show its evaluation results. Finally, we conclude that our recommendation system is useful for learners.
Keywords: Bidirectional recommendation; Collaborative filtering

Extraction of characteristic description for analyzing news agencies - Ishida, S.; Ma, Q.; Yoshikawa, M. (Journal of Digital Information Management, 2010)
News agencies report news from different viewpoints and with different writing styles and these differences often ap pear in their article descriptions. We propose a method to extract characteristic descriptions on certain entities (persons, locations, organizations, etc.) in news agency articles. For a given entity, a description is one tuple (called an SVO tuple) consisting of that entity and other words or phrases appearing in the same sentence on the basis of their SVO (Subject (S), Verb (V) and Object (O)) roles. We extract characteristic descriptions of entities by computing the fre quency and inverse agency frequency of each description. By arranging characteristic descriptions chronologically, we were able to ascertain the left-or right-leanings of news agencies and how those leanings varied with the passage of time.
Keywords: News agencies; News analysis; Text characteristics; Text description; Word frequency analysis

File replication method based on demand forecasting of file download in P2P networks - Kobayashi, M.; Kageyama, J.; Shibusawa, S.; Yonekura, T. (Journal of Digital Information Management, 2010)
In peer-to-peer (P2P) networks that support file-sharing services, the level of access demand can vary widely between different files. Since fewer nodes store files for which there is a lower demand, these files are more likely to be lost from the P2P networks if users leave the network or delete the files. File loss can cause users to seek alternatives to P2P services, and lead to degradation in service quality. We propose and evaluate a replication method based on demand forecasting that aims to prevent the loss of low-demand files. In this method, the number of file replicas to be placed is determined based on the forecast demand for the file, so that the loss of low-demand files is likely prevented by placing replicas at nodes that frequently use P2P services. Based on simulation results, we compared our proposed method with basic replication methods in terms of the number of files and the amount of storage used. Our experimental results show that the proposed method prevents file loss by preserving lowdemand files over extended periods of time. We also confirmed that the node storage resources consumed by this method are efficiently used.
Keywords: P2P file sharing; P2P networks; Replication

Multi-objective optimization in service systems - Gonsalves, T.; Yamagishi, K.; Itoh, K. (Journal of Digital Information Management, 2010)
Muti-objective optimization deals with the simultaneous optimization of two or more conficting objective functions in real-life systems. This paper deals with the multi-objective optimization in service systems. The goal of service systems is to provide cost-efficient service to customers, while at the same time, reducing the customer waiting time for service. In general, a low cost in system operation leads to longer waiting times, while a higher cost in system operation leads to shorter waiting times. The two objectives - service cost (operational cost) and waiting time (customer satisfaction) are, therefore, conficting in nature. We use the novel Multi-Objective Particle Swarm Optimization (MOPSO) algorithm to optimize the two conficting objective functions simultaneously. MOPSO is a fairly recent swarm intelligence meta-heuristic algorithm known for its simplicity in programming and its rapid convergence. The multi-objective optimization procedure is illustrated with the example of a practical service system. MOPSO produces a family of well-spread Pareto fronts for the two objective functions in the practical service system.
Keywords: Multi-Objective Particle Swarm Optimization; Service cost; Service systems; Simulation optimization

A new authentication scheme for session initiation protocol - Lee, C.-C.; Yang, C.-C.; Huang, S.Y. (Journal of Digital Information Management, 2009)
he Session Initiation Protocol (SIP) is a signaling protocol that controls communication sessions such as conferencing, telephony, and instant messaging in the Internet community (RFC2543). Before a user gets to use an SIP service provided by a server, an authentication process must be finished. However, there are some security problems with SIP authentication yet to be solved, such as server spoofing, off-line password guessing attacks, and the use of the password table. In this article, we shall propose a new authentication scheme for SIP that does not need the password table.
Cited By (since 1996):2Export Date: 10 July 2014
Keywords: Authentication; Security; Session initiation protocol

Information hiding on lossless data compression - Yoshioka, K.; Sonoda, K.; Takizawa, O.; Matsumoto, T. (Journal of Digital Information Management, 2008)
We address a new class of Information hiding on lossless data compression. In our model, secret information is embedded into a compressed data (e.g. ZIP) in a way that the compressed data can still be decompressed by regular decompression process (e.g. UNZIP). The entity with secret key can extract the secret information from the compressed data. In this paper, we formally define the above model of information hiding on lossless data compression. Then, we focus on a particular compression method, namely LZSS, which is used in ZIP/LHA. We propose a new method, called IH-LZSS, which controls the trade-off between the maximum embeddable data size and compression rate. Some experimental results are also shown.
Cited By (since 1996):1Export Date: 10 July 2014
Keywords: Information hiding; Lossless data compression; LZSS; Tamper detection; ZIP

Robust video watermarking based on dual-plane correlation for immunity to rotation, scale, translation, and random distortion - Atomori, Y.; Echizen, I.; Dainaka, M.; Nakayama, S.; Yoshiura, H. (Journal of Digital Information Management, 2008)
A robust video watermarking method is described that can embed watermarks immune to not only rotation, scaling, and translation but also to random geometric distortion and any of their combinations. It can detect watermarks without any search for canceling the effect of random distortion. Rotation, scale, and translation are canceled by searching for the angle, size, and origin of the original picture. The search for the angle and size is combinatorial but is independent of the search for the origin. That is, the angle and size of the target picture can be restored without restoring the picture's origin. Furthermore, the search for the origin is divided into horizontal and vertical searches that can be carried out independently. The number of searches is thus drastically reduced, making the processing speed high enough for practical application. Experimental evaluation using actual video samples demonstrated that the proposed method can embed watermarks immune to all four types of transformations.
Cited By (since 1996):5Export Date: 10 July 2014
Keywords: Random distortion; RST; Survivability; Video watermarking

Route navigation method for disabled access GIS in consideration of abilities and psychologies - Izumi, S.; Kobayashi, G.; Yoshida, T. (Journal of Digital Information Management, 2008)
This paper aims to propose a route navigation method for disabled access GIS. We focused the disabled's psychologies as well as their physical conditions. This paper represents quantization of physical and psychological burden of the disabled persons inflicted by various barrier factors. Also it represents estimation of total burden of a route to determine the optimum route. The route is represent ed by graph theory and route navigation method which is based on Dijkstra algorithm is applied. We extend the algorithm to make it possible to provide information on obstacles even when there are no accessible routes available to destination. The result of this study is being implemented and published as 3D Web Disabled Access GIS.
Cited By (since 1996):1Export Date: 10 July 2014
Keywords: Dijkstra algorithm; Disabled GIS access; Route navigation

Smoke detection for early fire-alarming system based on video processing - Wang, D.-J.; Chen, T.-H.; Yin, Y.-H.; Chen, T.-Y. (Journal of Digital Information Management, 2008)
The paper presents a smoke-detection method for early fire-alarming system based on video processing. The basic strategy of smoke-pixel judgment is composed of two decision functions: a chromaticitybased decision function in static characteristic and a diffusion-based decision function in dynamic characteristic. The chromatic decision rule is deduced by grayish color of smoke and the dynamic decision rule is dependent on the diffusion attribute of smoke. To give an appropriate alarm, a fuzzy scheme is introduced to enhance the reliability of alarming by checking if the quantity of smoke extracted increases with the checking time. Experimental results show that the proposed method can provide an early alarm at a lower false alarm rate before the fire burns up, and hence is very attractive for the important places, social security, commercial applications, and so on.
Cited By (since 1996):3Export Date: 10 July 2014
Keywords: Fire-alarming; Fuzzy scheme; Image processing; Smoke detection; Smoke pixels

Multi-source remote sensing classification based on Mallat fusion and residual error feature selection - Cao, D.; Yin, Q.; Guo, P. (Journal of Digital Information Management, 2007)
Classification of multi-source remote sensing images has been studied for decades, and many methods have been proposed or improved. Most of these studies focus on how to improve the classifiers in order to obtain higher classification accuracy. However, as we know, even if the most promising method such as neural network, its performance not only depends on the classifier itself, but also has relation with the training pattern (i.e. features). On consideration of this aspect, we propose an approach to feature selection and classification of multi-source remote sensing images based on Mallat fusion and residual error in this paper. Firstly, the fusion of multi-source images can provide a fused image which is more preferable for classification. And then a featureselection scheme approach based on fused image is proposed, which is to select effective subsets of features as inputs of a classifier by taking into account the residual error associated with each land-cover class. In addition, a classification technique base on selected features by using a feed-forward neural network is investigated. The results of computer experiments carried out on a multisource data set confirm the validity of the proposed approach.
Keywords: Feature selection; Mallet fusion; Multi-source classification; Neural network; Residual error

Editorial - Chbeir, R.; Yetongnon, K. (Journal of Digital Information Management, 2006)

How to enhance competitive advantage of digital content industries? - A case study of Taiwan - Yeh, S.-W.; Shiue, Y.-C.; Horng, D.-J. (Journal of Digital Information Management, 2006)
On account for the rising of XDSL construction in Taiwan recent years, hundred of thousands people have become interested in digital content. Digital content is a creative industry, accompanied with emergence of rapid changed technologies and innovative business models, the government all over the world would be devoted to promoting the competitive advantage in digital content industries. From perspective of "digital independence", online game is regarded as the most cultural and innovative among them. While designing the online games architecture researchers provide due importance to technology. However, the present paper place emphasis on human element in architecture related to online games. The Taiwan experience is used to construct the online game architecture.
Keywords: Digital content; Online games; Taiwan digital industry