Earticle

This study analyzes the changes in the framework of personal information protection in Korea. To investigate these changes, press releases from the Ministry of the Interior were collected. Through text mining and correspondence analysis, the words were examined over the course of eight years (from 2008 to 2015). All verbal expressions were classified by time: ① framework build-up (from 2008 to 2011), ② framework transition (2012), and ③ framework adjustment (from 2013 to 2015). The analytical results show that the personal information protection system was not stuck with the residue of the past or replaced by a new system; it was a gradual change with coexisting elements and new framework components. This study also demonstrates a more objective way to do periodization than relying on subjectivity.

Privacy is the word which can listen everywhere in the data mining for data preserving. It should be provided the security to the data in many ways. Privacy should be provided to the sensitive data and micro data. Hence more number of existing techniques has been introduced to provide sensitive data. Many third party service providers are showing interest to release the data which is collected for research purpose. Existing systems like k-anonymity, l-diversity and t-closeness are already existed but they can’t provide better privacy measures. Each existing method carries different types of problems. The t-closeness is the more flexible privacy model called (n,t)-closeness will provide the better privacy and usage. Proposed Closeness measures require Probability distribution that is assessed using Earth Mover’s Distance (EMD) measurement. In this paper, the graph based algorithm graph-EMD. Compare with tree-EMD, graph EMD performs more flexible. The number of unknown variables is reduced to O (N) from O (N2) of the original EMD. In this paper, with Graph-EMD is implemented and show the performance and efficiency.

This study aims to seek optimal combination of advertising copies and images to maximize advertising effects on customers. To check how much our proposed method has impacts on customers, we adopted a physiological technique like eye-tracking method to secure more object analysis of the customers' response to the advertising copies and images that we have designed for this study. Exhaustive literature survey exhibits that there are no studies seeking appropriate combination of advertising copies and images so that customers may respond in a physiologically positive way. For this purpose, we organized heterogeneous stimuli and homogeneous stimuli to make appropriate stimuli, where heterogeneous stimuli consist of either emotional copies and rational images, or rational copies and emotional images. Homogeneous stimuli are designed to consist of either emotional copies and emotional images, or rational copies and rational images. 80 respondents were invited to our experiments, and their physiological responses were measured in a form of cognitive load and need-for-cognition. Eye-tracking methods were used to induce fixation length data from the analysis of participants’ eye-movement with the stimuli. Participant’s cognitive load increased more when they were exposed to heterogeneous stimuli, while participant’s fixation length changed significantly only when there exists interaction effect between cognitive load and need-for-cognition in response to the stimuli.

Open Source Software, OSS, is a software that can freely use, copy, release, about source code using algorithm, function and product. People are not only expected to use OSS which will play important roles in Cloud computing, big data, Internet of the Things and mobile era because unrestricted OSS’s advantage, but increasing interest of OSS value valuation. However, OSS has a characteristic of everybody that can release and share using source codes so it can’t estimate. Now, there is no standard and/or mensuration about OSS value valuation. Therefore, in this paper will estimate OSS values and compare commercial software price assessments with values on sale. Also this adapted study methods suggest a result of software values to compare analysis including suggested standard value valuation models for estimate software values. In this paper, expect that the suggested methods would help to various Open source way value valuation.

Manual identification of defected objects consumes time and effort. These leading researchers try to find out an automatic infected objects detection systems to reduce these denigrate issues, which affects trade business fields, as an example, infected fruits or vegetables in agricultural field. This paper presents an image segmentation method based on affinity propagation (AP) clustering algorithm for detecting infected part in fruits or vegetables. Results show that this methodology is good comparing to K-means algorithm, which gives good results. Nevertheless, AP outperforms that does not need pre-specify cluster number, which is needed in K-means. Some deficiencies occur when using traditional AP, but using sparse version of AP overcomes most of these deficiencies. Extra feature of AP that it works better than K-means as cluster number is increasing or complexity of infected objects is amplifying. AP works better than K-means in widespread and various sized defected regions. Another contribution in this paper, choosing adequate color space provides preferable results. Experimental results clarify that NTSC or YCbCr color space are more stable to act as image color space since they enhance Silhouette values rhythmically. However, methodology presented in this paper needs to collaborate with other image techniques, as indexed color techniques and lossless compression methods, to overcome operation speed problem. In addition, more enhancements are anticipated when using adaptive AP, as it introduces solutions through adaptive damping, adaptive preference scanning and adaptive escaping oscillations.

With the rapid spread of smartphones, there have been diverse changes in the IT industry to activate the use of smartphones. Among them, the importance of smartphone-embedded softwares is getting greater. There have been a lot of studies about the service factors affecting on the users’ choice of phone. But, the influence of smartphone-embedded S/Ws on the cost has been rarely researched, though the softwares have become a hot issue in the IT industry along with the rapid expansion of smartphone users. Therefore, this study researches the cost factors of smartphone-embedded S/Ws and makes the simulation test with them by using the business dynamics to check the influence of S/Ws on the smartphone cost.

In recent years, the applications of cloud computing technology has been increased significantly. Multi-tenant property of cloud computing allows data sharing between clients. The multi-tenant data management system breaks the cost of hardware, software and professional services among a large number of tenants and thus reduces per-tenant cost. A multi-tenant database system should provide high performance with small storage space and excellent scalability. One major challenge is to reach a database scheme with high-quality. In this paper, we offer a compatible ADAPTED database schema based on genetic algorithms, and compare it with similar schema. Simulation results show that the proposed approach (GA-ADAPT) besides considering criteria of quality of service, provides higher performance comparing the previous ones in terms of selection time of the important features and the average response time to the tenants.

Intelligent product is a product which is intellectualized with robotic technology and can be designed as behavior assistance type or behavior inducement type. In order to investigate an effective design method for an intelligent product, we explored the effect of intelligent product types on user’s perception according to usage contexts, which were either tedious and monotonous physical task or social consciousness related task. We executed two experiments to explore appropriate intelligent product types in each usage context. In the first study, we compared which type of intelligent products is suitable to the tedious and monotonous physical task. In the second study, we investigated a proper type of intelligent product in the usage context which is related to social consciousness. The results showed that in usage context related to tedious and monotonous physical task, the participants evaluated behavior assistance type is smarter, more useful and more positive, and also had stronger intention to purchase than behavior inducement type. By contrast, when the usage context of the intelligent product is related to social consciousness, the participants evaluated behavior assistance type is more useful and more positive, and also had stronger intention to purchase than behavior assistance type. These results suggested that for effective intelligent product design, designers need to consider intelligent product types along with usage context.

Network function virtualization (NFV) virtualizes entire classes of network functions into building blocks of software. A virtualized network function (VNF) can consist of one or more virtual machines to provide communication services. Service Function Chaining (SFC) provides the ability to define an ordered list of virtualized network functions while considering multiple computing constraint conditions such as CPU, memory, and bandwidth. In a cloud data center network, the various virtualized network functions can reside in multiple physical machines and a certain chain of VNFs must be carefully considered to provide an optimal path. Such an optimization problem with multiple constraints is known as an NP-hard optimization problem. We propose a metaheuristic method to provide an optimal chain of VNFs using a genetic algorithm while considering multiple constraints. This paper aims to provide a path with well-balanced computing resources in a cloud data center network environment.

The police stations have adequate importance in the society to control the law and order situations of the country. In Pakistan, police stations manage criminal records and information manually. We have previously developed and improved a desktop application for the record keeping of the different registers of the police stations. The data of police stations is sensitive and that need to be handled within secured and fully functional software to avoid any unauthorized access. For the proper utilization of the newly developed software, it is necessary to test and analyze the system before deployment into the real environment. In this paper, we have performed the testing of an application. For this purpose, we have used Ranorex, automated testing tool for the functional and performance testing, and reported the results of test cases as pass or fail.

Petri net minimum-cycle-time analysis methods have been widely used in system design in order to verify user requirements in the early design stages of software development. The minimum-cycle-time analysis process builds a Petri net model of the design, finds the minimum positive T-invariant and all of the independent minimal support S-invariants S, calculates the resource-time product, for each s an element of S calculates the product of S-invariant and the resource-time product, and returns the maximum of these products. If a computer system is complex, its Petri net model contains so many transitions and places that a full comprehension of the model becomes extremely difficult. In order to address this problem, hierarchical Petri nets have been developed. However, all of the existing hierarchical Petri net methods have only dealt with liveness, boundedness, reversibility, and other similar things. None of these methods addresses the minimum cycle time. This paper introduces a Minimum-Cycle-Time analysis process for Hierarchical Petri nets (MCTH).

Revocation of a private key is an indispensable factor if user-operation aspects, such as an information management system in a cloud computing environment, are considered. Although there is a public key infrastructure (PKI)-based certificate revocation list in the private key revocation function, the revocation function of a PKI cannot be applied to functional encryption as it is. The cloud environment has limitations, such as no smooth access privilege change, and re-allocation that uses the existing proxy re-encryption. To solve the problem, functional encryption that is suitable for the cloud used as external storage, and for which revocation is possible, was proposed. This study proposes medical data management based on functional encryption that can restrict access privileges to the users concerned, if data access privileges stored within a health cloud are terminated. If many users exist in the health cloud environment, communications volume and computation requirements are expected to increase enormously due to the packet processing load of a trusted third party. Therefore, a revocation function is executed by postponing the revocation function for a certain period of time (D) for efficient retention and management of a revocation list, and by increasing key numbers when a specific time arrives. A system and protocol must be configured in which the first ciphertext is converted into a secondary ciphertext so that the revocation of access privileges to data stored in the health cloud server can be made, and a user whose access privileges were revoked cannot conduct secondary decryption.

In this research study, one of the most crucial automotive engineering problems is intended to be solved. The necessity of tire pressure monitoring system is beyond doubt. Such systems are now provided relying on expensive sensors. In this study an indirect tire pressure monitoring system is proposed, utilizing identification techniques, which will reduce the cost of monitoring considerably in comparison to direct types, while keeping it just as reliable as the conventional types. A comprehensive study on system’s parameters was undertaken by MATLAB-IDENTIFICATION toolbox, in order to find a proper method to estimate tire pressure indirectly. The best method was chosen among five well-known estimation methods, including Space State, AR, ARMA, NLARX and Wiener-Hammerstein. It was shown, the best method to estimate the pressure of a properly inflated tire is NLARX with a 94.51% precision while the best estimation for an under-inflated tire pressure is ARMA with a 92.3% accuracy.

Images represent a large share of web site contents. Image contents allow users to perceive information using vision, but visually handicapped people cannot perceive the information unless substitute texts that can replace vision are provided. Therefore, in this paper, the Web accessibility compliance status was compared between domestic and overseas sites around their compliance with substitute texts for images. The results indicate that the general Web accessibility compliance rates of domestic and overseas websites have not increased compared to 2013. However, the compliance with substitute texts for images in domestic sites was found to be continuously increasing, whereas it decreased in overseas sites.

This study would like to find out influential factors in brand image by SNS original data sources and then builds ontology by relative and associated words. According to previou theoretical studies and trend monitors survey, an ontology built brand image’s influential factors and finds out associated brand images from car blogs, and Twitter’s terms. The ontology collects original data from Twitter in Korea. By using a Korean analyzer to process, it can select key words from its original data source and then those key words make density based on K-means clustering. Korean and German cars were selected for comparison. Then, based on these process, the major six image factors are selected; image, symbol, trademark, quality, price, and country of origin. With the use of clustering analysis, the two Korean cars and two German cars’ brands show different. Finally, this study found out correlations between brand image of cars and consumer’s purchasing intention.

Mobile connection is a rising commodity wherein the demand for it is growing. Because of this, the mobility support for Internet devices is an important factor, since mobile and Internet-based computing is on the rise. Ever since the mobile connectivity was launched years ago, the number of devices designed for such purpose also has also raised sky high. Mobile connection is on a scale that it needs to be further enhanced further because of the massive traffic it handles. Being connected to everything is the utmost importance on mobile connectivity. In this paper a thorough look on the MIPv6 protocol will be discussed, how MIPv6 works as a protocol and problems encountered in this protocol and the developments that were made.

E-Business is situated to as having connections everywhere like purchasing and advertising goods 24 hours/7 days a week, may it be through your desktop or mobile phones. It’s not surprising that businesses have a need to reach a mobile audience since competition online is dedicated to making your websites more visible and reachable for the users. Mobile promotes the entire business life cycle as of today. We present Mobile First Strategy approach in meeting your customer where a customer is looking for you in a manner appropriate to the screen the customer is using to interact with you. To be more dedicated in making your sites as reachable as possible because if you don’t require a mobile-friendly site for your audience to be satisfied with your service, chances are, they might consider a more responsive one. Understanding the adaptation of mobile first strategy and the rise of mobile users that contributes to a successful e-business will help increase the recognition of agriculture products.