Aspect] is a simple and practical aspect-oriented extension to Java With just a few new constructs, AspectJ provides support for modular implementation of a range of crosscutting concerns. In AspectJ's dynamic join point model, join points are well-defined points in the execution of the program; pointcuts are collections of join points; advice are special method-like constructs that can be attached to pointcuts; and aspects are modular units of crosscutting implementation, comprising pointcuts, advice, and ordinary Java member declarations. AspectJ code is compiled into standard Java bytecode. Simple extensions to existing Java development environments make it possible to browse the crosscutting structure of aspects in the same kind of way as one browses the inheritance structure of classes. Several examples show that AspectJ is powerful, and that programs written using it are easy to understand.

An overview of AspectJ

[서평]「The Unified Modeling Language User Guide」

What is Twitter

Recommender systems have become an important research field since the emergence of the first paper on collaborative filtering in the mid-1990s. Although academic research on recommender systems has increased significantly over the past 10years, there are deficiencies in the comprehensive literature review and classification of that research. For that reason, we reviewed 210 articles on recommender systems from 46 journals published between 2001 and 2010, and then classified those by the year of publication, the journals in which they appeared, their application fields, and their data mining techniques. The 210 articles are categorized into eight application fields (books, documents, images, movie, music, shopping, TV programs, and others) and eight data mining techniques (association rule, clustering, decision tree, k-nearest neighbor, link analysis, neural network, regression, and other heuristic methods). Our research provides information about trends in recommender systems research by examining the publication years of the articles, and provides practitioners and researchers with insight and future direction on recommender systems. We hope that this paper helps anyone who is interested in recommender systems research with insight for future research direction.

A literature review and classification of recommender systems research

The blooming trend of smart grid deployment is engaged by the evolution of the network technology, as the connected environment offers various alternatives for electrical data collections. Having diverse data sharing/transfer means is deemed an important aspect in enabling intelligent controls/governance in smart grid. However, security and privacy concerns also are introduced while flexible communication services are provided, such as energy depletion and infrastructure mapping attacks. This paper proposes a model permissioned blockchain edge model for smart grid network (PBEM-SGN) to address the two significant issues in smart grid, privacy protections, and energy security, by means of combining blockchain and edge computing techniques. We use group signatures and covert channel authorization techniques to guarantee users’ validity. An optimal security-aware strategy is constructed by smart contracts running on the blockchain. Our experiments have evaluated the effectiveness of the proposed approach.

Permissioned Blockchain and Edge Computing Empowered Privacy-Preserving Smart Grid Networks

Vehicle class is an important parameter in the process of road-traffic measurement. Currently, inductive-loop detectors (ILD) and image sensors are rarely used for vehicle classification because of their low accuracy. To improve the accuracy, the authors suggest a new algorithm for ILD using back-propagation neural networks. In the developed algorithm, the inputs to the neural networks are the variation rate of frequency and frequency waveform. The output is five classified vehicles. The developed algorithm was assessed at test sites, and the recognition rate was 91.5%. The results verified that the proposed algorithm improves the vehicle-classification accuracy compared to the conventional method based on ILD

Vehicle-Classification Algorithm for Single-Loop Detectors Using Neural Networks

Vehicle speed is an important parameter in measurements of road traffic. At present, double-loop detectors are generally used for vehicular speed measurement. However, these detectors incur errors caused by scanning time, spacing between double loops, irregular vehicle trajectories, and the presence of multiple vehicles in the detection zone. This paper suggests a new model that uses an error-filtering algorithm to improve the accuracy of speed measurements. In the field tests, all percent errors of the vehicular speeds measured by the proposed model were within the error tolerance limit (plusmn5%). Furthermore, the variance of percent errors was reduced. Therefore, it can be concluded that the proposed model significantly improves vehicle-speed-measuring accuracy

Model for accurate speed measurement using double-loop detectors

Cloud-based electronic health record (EHR) systems enable medical documents to be exchanged between medical institutions; this is expected to contribute to improvements in various medical services in the future. However, as the system architecture becomes more complicated, cloud-based EHR systems may introduce additional security threats when compared with the existing singular systems. Thus, patients may experience exposure of private data that they do not wish to disclose. In order to protect the privacy of patients, many approaches have been proposed to provide access control to patient documents when providing health services. However, most current systems do not support fine-grained access control or take into account additional security factors such as encryption and digital signatures. In this paper, we propose a cloud-based EHR model that performs attribute-based access control using extensible access control markup language. Our EHR model, focused on security, performs partial encryption and uses electronic signatures when a patient’s document is sent to a document requester. We use XML encryption and XML digital signature technology. Our proposed model works efficiently by sending only the necessary information to the requesters who are authorized to treat the patient in question.

Privacy-Preserving Attribute-Based Access Control Model for XML-Based Electronic Health Record System

With a rapid development of ubiquitous computing technology in the home and community, users can access information anytime and anywhere via personal devices such as PDA and internet mobile phone. Similarly, more flexible access control is required in the ubiquitous applications. In this paper, we propose a context-aware access control mechanism, which dynamically grants and adapts permissions to users according to the current context. We extend the role-based access control(RBAC) model to deal with the context information in ubiquitous environment. Unlike the traditional RBAC, the proposed access control mechanism can consider context information such as location, time and system resources by the context-aware agent and state checking matrix(SCM).

Context-Aware access control mechanism for ubiquitous applications

This paper proposes an SAMD (Synchronization Algorithms based on Message Digest) algorithm based on message digest in order to facilitate data synchronization between a server-side database and a mobile database The SAMD algorithm makes the images at the server-side database and the mobile database uses message digest tables to compare two images in order to select the rows needed for synchronization If the two images are different, the synchronization progresses according to synchronization policy The SAMD algorithm does not use techniques that are dependent on specific database venders; neither does it use triggers, stored procedures or timestamps The SAMD uses only the standard SQL functions for the synchronization Therefore the SAMD algorithm can be used in any combinations of server-side database and mobile database because of its independence of database vender This feature is important in order to build efficient mobile business systems because the upcoming mobile business environment has heterogeneous characteristics in which diverse mobile devices, mobile databases, and RDBMS exist

Doo-Kwon Baik

Papers

Vehicle-Classification Algorithm for Single-Loop Detectors Using Neural Networks

Model for accurate speed measurement using double-loop detectors

Privacy-Preserving Attribute-Based Access Control Model for XML-Based Electronic Health Record System

Context-Aware access control mechanism for ubiquitous applications

A database synchronization algorithm for mobile devices