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In this paper, we implement the SIFT(Scale-Invariant Feature Transform) algorithm for feature point extraction using a many-core processor, and analyze the performance, area efficiency, and system area efficiency of the many-core processor. In addition, we demonstrate the potential of the proposed many-core processor by comparing the performance of the many-core processor with that of high-performance CPU and GPU(Graphics Processing Unit). Experimental results indicate that the accuracy result of the SIFT algorithm using the many-core processor was same as that of OpenCV. In addition, the many-core processor outperforms CPU and GPU in terms of execution time. Moreover, this paper proposed an optimal model of the SIFT algorithm on the many-core processor by analyzing energy efficiency and area efficiency for different octave sizes.

Most modern computer systems employ cache systems in order to alleviate the access time gap between processor and memory system. The power dissipated by the cache systems becomes a significant part of the total power dissipated by whole microprocessor chip. Therefore, power reduction in the cache system becomes one of the important issues. Partial tag cache is the system for the least power consumption. The main power reduction for this method is due to the use of small partial tag matching, not full tag matching. In this paper, we first analyze the previous regular partial tag cache systems and propose a new address matching mechanism by using locality buffer and address compression. In simulation results, the proposed model shows 18% power reduction in average, still providing same performance level, compared to regular cache.

ECU(Electric Control Unit) on the important features of the vehicle is equipped, ECU between sending and receiving messages is connected to one of the internal network(CAN BUS), but this network easily accessible from the outside and not intended to be able to receive attacks from an attacker, In this regard, the development of tools that can be used in order to verify the possibility of attacks on attacks from outside, However, the time costs incurred for developing tools and time to analyze from actual car for CAN messages to be used in the attack to find. In this paper, we want to solve it, propose a method to generate test cases required for the attack is publicly available tool called Sulley and it explains how to find the CAN messages to be used in the attack. Sulley add the CAN messages data generated library files in provided library file and than Sulley execute that make define and execute file conform to the CAN communication preferences and create message rules. Experiments performed by the proposed methodology is applied to the actual car and result, test cases generated by the CAN messages fuzzing through Sulley send in the car and as a result without a separate tool developed was operating the car.

In this paper, a photovoltaic switch is suggested that is operated by solar module, a substitute for CdS(Cadmium Sulfide) of most existing automatic switches and thus is powered by its renewably charged battery, and its usability is investigated through various experiments. At first the characteristics of CdS and the operation principle of the existing automatic switch are investigated, and then the characteristics of solar module are examined. These preparatory research shows the possibility of substitution of solar module instead of CdS in light activated switch. Secondly the suggested photovoltaic switch's circuit is designed, implemented and then its experimental comparison data shows the possibility for the replacement of the existing switch to the suggested switch, and furthermore its superiorities.

Classification result by comprehensive analysis of rhythm section and heartbeat unit makes a reliable diagnosis of heart disease possible. In this paper, based on feature-points of ECG signals,rhythm analysis for constant section and heartbeat unit is conducted using rule-based classification and SVM-based classification respectively. Rhythm types are classified using a rule base deduced from clinical materials for features of rhythm section in rule-based classification, and monotonic rhythm or major abnormality heartbeats are classified using multiple SVMs trained previously for features of heartbeat unit in SVM-based classification. Experimental results for the MIT-BIH arrhythmia database show classification ratios of 68.52% by rule-based method alone and 87.04% by fusion method of rule-based and SVM-based for 11 rhythm types. The proposed fusion method is improved by about 19% through misclassification improvement for monotonic and arrangement rhythms by SVM-based method

This paper proposes a method of automatically predicting the vanishing point for the purpose of detecting the road region from natural images. The proposed method stably detects the vanishing point in the road environment by analyzing the dominant orientation of the image and predicting the vanishing point to be at the position where the feature components of the image are concentrated. For this purpose, in the first stage, the image is partitioned into sub-blocks, an edge sample is selected randomly from within the sub-block, and RANSAC is applied for line fitting in order to analyze the dominant orientation of each sub-block. Once the dominant orientation has been detected for all blocks, we proceed to the second stage and randomly select line samples and apply RANSAC to perform the fitting of the intersection point, then measure the cost of the intersection model arising from each line and we predict the vanishing point to be located at the average point, based on the intersection point model with the highest cost. Lastly, quantitative and qualitative analyses are performed to verify the performance in various situations and prove the efficiency of the proposed algorithm for detecting the vanishing point.

The multimedia data of game affects the immersion of the game depending on its quality. It is difficult to design the evaluation criteria of artistic quality of the data. But, in a technical point of view, it is possible to evaluate its quality. Thus, the design of evaluation standard can ensure the reliability and objectivity of quality. However, multimedia data quality evaluation metrics had not yet been designed. Therefore, in this study, we extracted quality evaluation elements of Game Multimedia Data, and verified the reliability of the elements. And we defined detailed evaluation items of each element, developed Multimedia Data Quality Evaluation Metrics. We expect that the results of this study will serve as a guide in the development of high-quality games, have a positive impact on the growth of the game industry.

In this paper, the golf club head hit the golf ball moves at a constant velocity, then move in the same direction at a constant velocity of the golf club head, the velocity of the golf ball was hitting and flying the golf ball is calculated. If velocity is different before you hit the golf ball, each of the velocity of the golf ball is calculated. The purpose of this paper is to make it easy to find out the velocity of a club's head, the mass of a golf ball, the velocity or the direction of a golf ball after impact in playing golf. The results of the experiment are represented in tables and figures. And we also propose the comparison analysis between our research and other traditional ones, the implications, and futhur studies in the future. The results of this study, unlike other studies, it was can be seen that measurements of several factors superior to the measurement of the velocity of the golf ball .

Recently, the need for outsourcing sensitive data has grown due to the wide spreading of cost-effective and flexible cloud service. However, there is a fundamental concern in using such service since users have to trust external servers. Therefore, searchable encryption can be a very valuable tool to meet the security requirements of data outsourcing. However, most of work on searchable encryption focus only on privacy preserving search function and relatively lacks research on encryption mechanism used to actually encrypt data. Without a suitable latter mechanism, searchable encryption cannot be deployed in real world cloud services. In this paper,we analyze previously used and possible data encryption mechanisms for multi-user searchable encryption system and discuss their pros and cons. Our results show that readily available tools such as broadcast encryption, attribute-based encryption, and proxy re-encryption do not provide suitable solutions. The main problem with existing tools is that they may require separate fully trusted servers and the difficulty in preventing collusion attacks between outsiders and semi-trusted servers.

In these days, the smart devices are being developed and used repeatedly. But almost E-learning System did not provide these smart devices environment and user's E-learning space is changing from Single-screen environment to multi-Screen environment. Accordingly we configure smart E-learning space based on multi-screen and integrate the multi-media contents for the Smart E-learning service. We present the synchronization techniques to make the multi-screen environment for smart space with Timed Link and design the Timed Button to relate each Screen which is using multi-media e-learning contents.

Data quality management is extremely important. In this study, we proposed data standardization for effective quality management of enterprise-owned data about distributed goods and validated its effectiveness by case study. For the standardization of data, we designed data category and data dictionary. Additionally, we categorized data and identified its attributes for data category design, and we developed design process for data dictionary and built the dictionary of word, term, domain and code for data dictionary design. And then we proposed output documents which have to be written for data standardization. Proposed data standardization approach is validated its efficiency by quantitative and qualitative measurement. and as a result the data quality of the data standardization improved 24% and the data quality of the consistency of the data dictionary improved 7%.

Uncertainty in Context-aware computing is mainly a consequence of the complexity of context acquisition mechanisms and context processing. The presence of uncertainty may harm the users’confidence in the application, rendering it useless. This paper describes a three-phase strategy to manage uncertainty by identifying its possible sources, representing uncertain information, and determining how to proceed, once uncertain context is detected. The level of effort that is necessary to eliminate the uncertainty of context information affects the reliability of the system,because Sensor network system have no intervention of humans. In this paper, We applied proposed method to the development for the sensor network system, Uncertainty management can be applied a part of the system development life-cycle. It confirmed that result of testing show that detection performance is stable.

This paper proposes a linear-time algorithm that has been designed to obtain an accurate solution for Dominating Set (DS) problem, which is known to be NP-complete due to the deficiency of polynomial-time algorithms that successfully derive an accurate solution to it. The proposed algorithm does so by repeatedly assigning vertex ν with maximum degree △(G) among vertices adjacent to the vertex υ with minimum degree δ(G) to Minimum Independent DS (MIDS) as its element and removing all the incident edges until no edges remain in the graph. This algorithm finally transforms MIDS into Minimum DS (MDS) and again into Minimum Connected DS (MCDS)so as to obtain the accurate solution to all DS-related problems. When applied to ten different graphs, it has successfully obtained accurate solutions with linear time complexity O(n). It has therefore proven that Dominating Set problem is rather a P-problem.

In this paper, I propose and evaluate the method that classifies emotional type of characters with their emotional words. Emotional types are classified as three types such as positive, negative and neutral. They are selected by classification of emotional words that characters speak. I propose the method to extract emotional words based on WordNet, and to represent as emotional vector. WordNet is thesaurus of network structure connected by hypernym, hyponym, synonym, antonym,and so on. Emotion word is extracted by calculating its emotional distance to each emotional category. The number of emotional category is 30. Therefore, emotional vector has 30 levels. When all emotional vectors of some character are accumulated, her/his emotion of a movie can be represented as a emotional vector. Also, thirty emotional categories can be classified as three elements of positive, negative, and neutral. As a result, emotion of some character can be represented by values of three elements. The proposed method was evaluated for 12 characters of four movies. Result of evaluation showed the accuracy of 75%.

Although a series of studies shows the fact that a company's reputation could affect its sales rate and stock price, due to the increased use of SNS, the research related to the online measurement method for the corporate reputation has been relatively insufficient. This study explores a design for a method to quantify the corporate reputation value by reconstructing the discussions in literature review. Concretely, this study divides the corporate reputation value into the corporate identity information and the corporate awareness information, which includes the following five sub-categories: ① the quality of product and service; ② the employment environment; ③ the corporate vision; ④ the social responsibility; and ⑤ the business achievement. Additionally, for the corporate identity assessment, this study considers the following six factors:① Agreeableness (Goodness), ②Capability (Ability), ③Enterprise (Rise), ④Chic (Class), ⑤Ruthlessness (Authority), and ⑥Informality. Based on these categories and factors, this study develops a technique quantifying the corporate reputation value by selecting ‘word items’ for the reputation search, and after conducting a frequency analysis in a survey. Also, to verify the result, this study exemplifies the reputation of three SI companies in Korea which could be utilized by using the commercialized reputation service. This study firstly attempts the corporate reputation measurement by classifying the identity and the awareness (corporate image and communication) upon a company in detail and enables its real applicabilities by proposing a formula to measure the reputation scores which can be utilized by verified word items from a frequency analysis

As the number of Smartphone users increases, mobile advertising market has been expanding rapidly. In line with this, the ways to evaluate mobile advertising effectiveness are diversified, and engagement is one of the crucial qualitative and multi-dimensional evaluation methods of mobile advertising. Thus, the purpose of this study is to identify key antecedents and consequences of mobile advertising engagement, and examines the structural relationships among those research variables. Informativeness and personalization were selected as antecedents of engagement, trust and e-WOM intention were selected as consequences of engagement based on the review of previous studies. Data collected from survey was used to assess research hypotheses. Results show that informativeness and personalization have significant and positive effects on engagement, and engagement influences on trust and e-WOM intention. In addition, trust is proven to be positively related to e-WOM intention.

Though the number of food franchises has been increased these days, there has not been less success for food franchise than failure. One of the several failures is the distrust between franchisor and franchisee factors because the franchisee thought its franchisor does not make its accounts and operations transparent. In order to resolve it, the large business food franchise has used the ERP system, however, small business franchise has run a very simple information system, which is linked to POS system and consists of simple functions to insert or inquire the result of data on sales and order etc to identify the status of both franchisor and franchisee because of financial difficulties and manpower shortage. Thus, small business franchise needs the cost management between them with low cost for efficient business administration. In this study, we suggest the data reference model (DRM) which covers the cost management system and is able to be linked to any POS system. The DRM is a framework whose primary purpose is to enable information linking and reuse across the any POS-based information systems via the classification, structure, model, exchange and management of data.

Association rule mining is a popular data mining technique with a wide range of application domains, and aims to extract the cause-and-effect relations between the discrete items included in transaction data. However, analysts sometimes have trouble in interpreting and using the plethora of association rules extracted from a large amount of data. To address this problem, this paper aims to propose a novel approach called HTM for extracting the interesting association rules from given transaction data. The HTM approach consists of three main steps, hierarchical clustering,table-view, and mosaic plot, and each step provides the analysts with appropriate visual representation. For illustration, we applied our approach for analyzing the mass health examination data, and the result of this experiment reveals that the HTM approach help the analysts to find the interesting association rules in more effective way.

This study was conducted to identify the effect of a flight attendant's uniform quality on uniform satisfaction and on selecting an airline. To do that, uniform components were first classified into three factors esthetics, functionality, and symbolization. Then the differences of respondents’perception were tested according to the demographics of respondents. Finally the causal relationships among three uniform components, uniform satisfaction and select airline were examined. For the empirical study, the questionnaire data were collected from college and university student studying cabin crew service. The result of this study showed that the perceptions of students who study cabin crew service were significant on according some demographics information, esthetics, functionality and symbolization factors affecting uniform satisfaction, which had the positive effect on selecting an airline. These results suggested practical implications for cabin crew’s uniform. These result include important managerial implications for the airlines. Also there was some limitation on a hypothesis of study and the further study were needed

The purpose of this paper is to study the effects of the competitiveness of intermediate goods and enterprise’s core competency on customer value and enterprise performance. And it is the first time to investigate the intermediate product competitiveness with the variable of interest to recent corporate values and corporate customers with business performance by exploring their relationships. Intermediate products, which the competitiveness of products that target structure is introduced for the first time, and the relationships between intermediate goods competitive and product reliability, intermediate goods competitive and product innovation are studied in this paper. Further research on integral, modular, valuable, durability, by measuring parameters such as product innovation and product reliability are also conducted. Eight hypotheses are introduced for statistical hypothesis testing. Employees and typical intermediate products in electronic companies in China and South Korea are investigated. SPSS and AMOS models are applied to perform the statistical analysis. Analysis of the proposed models is fit to an acceptable level. Research results and limitations are discussed, and useful conclusions are drawn