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Many studies have been conducted to investigate into an university students to entrepreneurial activities. This paper aims to examine structural relationship between startup programs aided by university what reflected in GEM(Global Entrepreneurship Monitor) model and was establishing entrepreneurial intention of current university students. Total of 364 suitable sample data were used to empirical analysis hypotheses. The results of the hypothesis test through analysis of the structural model are summarized as follows. First, among the factors of universities’ startup support systems, entrepreneurial education, entrepreneurial consulting has a positive effect on entrepreneurial intention. But entrepreneurial fund had a negative influence upon entrepreneurial intention. Second, entrepreneurship has the partial mediating effect on the relationship between entrepreneurial education and entrepreneurial intention, and on the relationship between entrepreneurial consulting and entrepreneurial intention. Third, entrepreneurial education has more influence than entrepreneurial consulting. This implies that more attention needs to be paid to the new business, focusing on entrepreneurial education and strengthening entrepreneurial consulting for start-ups.

The immediate recognition of abnormal temperatures in the furnace system is very important for timely disaster control. Conventional abnormal temperature detection techniques typically use pre-programmed thresholds to identify abnormal patterns from a stream of temperature data in a statistical manner. Therefore, it is not suitable for use in a heating furnace system in which abnormal patterns must be detected in real time. Hierarchical Temporal Memory (HTM) is one of the machine learning models with excellent ability to analyze patterns of stream data. This model is a new machine intelligence technique that uses unsupervised continuous learning using Cortical Learning Algorithm (CLA), which is a time-based learning algorithm, and Spare Distributed Representation (SDR), which stores temporal and spatial patterns. This HTM, which is distinguished from existing deep learning or artificial neural network model, is capable of real-time continuous prediction from input of stream data and can be used to recognize abnormal states in various fields. HTM can be used as a robust model to detect abnormalities in successive temperature data in a heating furnace system because the furnace system continues to generate temperature stream data with a certain pattern over time. Here we developed an HTM-based, unsupervised, real-time anomaly detection system for heating furnaces. Performance evaluation shows that the suggested system can perform excellent abnormal real-time detection.

Continuous cyber threats are on the rise for critical information from public institutions and private companies. However, the attacks by hackers are not predictable and continue to evolve, and there is a limitation in current security test methods to develop a reliable information system because of time and cost issues. As a new way to strengthen information system security, this study suggests a security test method with utilizing crowd SW testing technique, which is attracting attention as a new software testing methodology. Crowd SW security testing has the advantage of detecting the fault and strengthening security verification on various systems through a large number of people’s participation. It can also be a solution to the time and cost problems posed by existing security testing. Utilizing the method in security test contribute to the improvement of information systems’ reliability and quality through checking security vulnerabilities. In order to activate the cloud SW security test, it is necessary to apply the security test for each stage of development and to test public and leakage organizations. If crowd SW security testers are fostered at the national level, it will contribute to strengthening SW security and solving the manpower shortage problem of SW testing industry.

Korea has achieved remarkable economic growth in the past decades, and its income and cultural level have also greatly increased. However, support for cultural arts projects has been relatively recent and is still insufficient. As a result, the government, local governments, and public foundations are expanding support for performance projects. However, in order for public sector support to be effective, the performance project must have its own competitiveness. In particular, in order for a specific performing arts project to be maintained over the long term, it must have business feasibility. However, it seems that research on the development of the system to develop the success factor of the performance business and the feasibility analysis is still lacking. Therefore, in this study, we try to develop performance evaluation system of performance by deducing success factors and importance of musical performance project. For this purpose, success factors of musical performance project were selected through precedent research and expert interview. In the next step, AHP analysis was conducted on the experts, and the importance of each success factor was calculated. As a final step, a systematic diagram of a system that can evaluate business feasibility by building an integrated database based on the results of the analysis conducted earlier is presented. The results of the AHP analysis showed that the performances were the most important among physical factors, social factors, performance factors, and administrative factors. In the sub items, the reliability of the performer, the concept of performance, and the support of the local government were high. Based on these results, we propose a system to improve the feasibility of musical performances through quantitative research and qualitative research.

The learning motivation is the most basic factor for learning. The instructor should design the teaching and learning courses to motivate learners for successful teaching and learning. Most students at specialized high schools find it difficult to learn or give up in advance because of lack of basic learning qualities. The teaching and learning strategies for these students should focus on improving the attractiveness rather than improving efficiency and effectiveness of teaching and learning. The attractiveness of learning is closely related to the motivation of learning. Many studies have shown that teaching and learning methods applied with learning motivation models improve learners' academic performance. However, some studies have shown that although teaching and learning methods applied with this model has significant effects on improving academic performance in cognitive learning areas, it does not have a significant effects on enhancing academic performance in functional learning areas. In addition, many studies have shown that pair programming has a significant effect on improving learners' academic performance. These results are analyzed to have a positive effect on improving the programming ability through communication and feedback with the partner, as learning enjoyment continues and self-efficacy increases. In this study, we designed and evaluated a strategy for inducing learning motivation for Web programming classes at specialized high school in the commercial and information affiliation. The results of the study have shown that the learning-motivation strategy creates learning interests and self-learning desires by learners. However, this strategy was analyzed to fail to induce learners’ awareness of purpose and constant desire to learn.

Nowadays, network technology is changing rapidly in the environment of cloud computing and Internet of Things, but there are still many difficulties in providing dynamic correspondence and efficient services when illegal attacks occur. In particular, attackers with high-end attack techniques will try to use the IP spoofing attack. For IP spoofing attacks, it is based on the connection path of the client to detect and correspond. This is based on traceback, after the normal path information is generated, the client connection information is compared and analyzed. But the benchmark detection method in the process of connection intelligence analysis will make OTP (One Time Password) occur frequently, resulting in low service availability. In order to improve this problem, this paper takes traceback information , and uses the Euclidean law calculation method (Euclidean Distance) and the security model put forward by phases of encryption method. Based on this, abnormal path intelligence in the simple comparison process, the different path information of block first policy can complement. After analyzing the changing path information, also implement phases of encryption. Then, the process of decryption is used to certify whether service is needed.

With the proliferation of mobile internet and social media, the simultaneous use of online and offline channels by customers is facilitating the emergence of new shopping behaviors. Omni-channel retailing has been given a considerable attention in recent literature. Although lots of research was devoted to understanding consumers' omni-channel adoption, few studies have discussed the customer's online behaviors and offline behaviors simultaneously in an omni-channel context. By applying activity theory(AT) perspective, this study aims to create insight into omni-channel customers’ service on customers’ behavior in online/offline context. Activity theory has emerged as a new philosophical framework for conceptualizing human activities. Since AT paradigm provides useful supplement to human information processing, AT could provide guide to understand consumer's activity. Drawing upon AT, this study adopts AT to compare consumer activity in online and offline context and to apply it to practical research. From online customer’s point of view, contradictions between object to save costs and rules related to concern about delivery costs can be generated in the process of making a decision about where they will purchase. Meanwhile, from offline customer’s perspective, contradictions between object to save efforts and rules related to less variety can be generated in the process of shopping offline.

This paper aims to introduce the concept of competing operations in flow shop and investigate the characteristics of the flow shop scheduling problem with competing operations. While different operations have different processing orders in traditional flow shop scheduling problem, some operations can be processed in arbitrary order in practical shop floors. In other words, the processing orders of given operations are fixed in traditional flow shop scheduling problem, however, this paper considers flow shop scheduling problem where some operations have variable processing orders. Such operations are defined as competing operations in this paper, and flow shops with competing operations require additional decisions on routing policies. In this context, we aim to propose several routing policies that can be applied to flow shops with competing operations, and to evaluate their performances in dynamic environment by applying simulation technique. Simulation experiments are performed by using a simulation model for a simple flow shop wich 2 competing operations, which is built by applying a commercial 3D factory simulation software called FlexSim. The experiment results reveal that the performances of proposed routing policies are dependent on the processing times of competing operations. Especially, routing policies based on the total processing time of predecessors have shown promising performances. This implies that the routing policies in flow shops with competing operations should be carefully designed with consideration of model parameters.

The biggest advantage of computer based education is providing differential learning considering each learner’s situation. Recently, adaptive learning system to support individualized learning has been actively studied. This study is about the adaptive learning system considering learners' individual achievement. This paper examines an adaptive learning system applying van Hiele’s learning theory in order to support differential leveled learning in geometrical figures for elementary students. We classified learners’ level of knowledge into three levels; lower level, middle level and upper level through the online test. We provide the leveled appropriate courses for the geometrical figures learning. A PHP script language is used to implement for learning algorithm and to manipulate the database. Finally, a Flash is used to present for adaptive learning object. The learning achievement of our proposed adaptive learning system will be increased because the learning system is constructed using the figure learning teaching strategies proposed by proven van Hiele’ theory. Futhermore, the adaptive learning system considering learners’ knowledge level will increase not only learning effects but also learning motivation by providing proper leveled learning and content. This study contributed to realize an adaptive learning system that takes into account the learner's knowledge level. And we showed how mathematical theory can connect with an adaptive learning system.

In this study, we investigated the sense of high fear according to height with virtual body model in a virtual environment using non - transmissive head mounted display in relation to the reality of high-rise building's virtual reality contents. For this purpose, the virtual reality contents about watching down from the high-rise building and the user 's virtual body model which is composed of the lower body shape were produced. For the ergonomic evaluation, 18 stimulations were performed according to the six random heights and the presence of the virtual body after the presentation of the reference stimulus about 10m height in the virtual environment. In addition, a variance analysis was performed on the results of each factor, and a sub-test based on the Bonferroni correction was performed. As a result of the analysis, in the result of the height sense, the average view point of the virtual body display condition was evaluated to be higher than the condition of the virtual body notation or object display under all conditions according to the change of the viewpoint of height. This suggests that the user has a strong sense of presence as if he or she is in the virtual reality space. And, as a result of the analysis of the fear of a of heights, a significant difference was found in the main effect of virtual body display (F (1,29) = 10.201, p <0.05). In addition, the significance was confirmed by simple interaction (F (1,29) = 5.444, p <0.05) in the virtual body display and the virtual body display condition. Through this, it is confirmed that the expression of the user 's virtual body improves the reality of the head mounted display contents.

Interest in IoT technology is increasing these days, and core of IoT technology is sensor network technology. Although ZigBee network is widely used in IoT-sensor network, it is vulnerable to various security threats such as wiretapping of sensor information, abnormal packet flow, data forgery and denial of service attack. However, ZigBee IoT-sensor networks should operate in resource environments with limited computing capabilities. Therefore, it is imperative that IoT-sensor network security technologies be researched for lightweight design. In this paper proposed an algorithm for mutual authentication of IoT-sensor networks based on a trust assessment model that enables safe IoT-sensor network construction even with small security operations. The proposed trust-based authentication algorithm is designed with direct trust relationships between ZC-Sensor nodes belonging to the ZigBee Pico-Net and performs a trust assessment between nodes based on probability calculation and logic calculation. In addition, the proposed mutual authentication algorithm can support confidentiality, anonymity, mutual authentication and freshness in terms of security safety of the IoT-sensor network and increase the lightweight-ness of the existing authentication methods. And it will be possible to extend safety and survival period of IoT-sensor network by reducing the use of limited batteries in sensor nodes.

Recent smart factories use OPC as their common communication mode to collect data from the manufacturing facilities. Data collected from OPC Server can be used for monitoring facilities, remote control, data sharing between facilities and equipment using OPC Client. However, the OPC client of OPC Classic is based on COM/DCOM, and has difficulty in firewall setup and security problems when communicating with remote clients. Additionally, the expansion of OPC server data to other platforms is required by the emergence of smart phones, but COM/DCOM is dependent on Windows platform. In this article, we have designed and implemented a remote data communication server/client using WCF as a way to demonstrate functions similar to the OPC UA communication system in the early OPC DA communication system. We have developed a system that can transfer collected data from PLC to remote WCF client, which data gets collected through OPC communication that is for automatic control and monitoring of industrial plant using WCF server. This study is the implementation of a model that can integrate and control PLC data from distributed production sites. This study introduces a model that can be applied to a system that has a limitation to introduce OPC UA, and it implements a method to collect and manage centralized PLC data of distributed production sites.

Apps such as games for younger children may have negative effects if they are overused, but the coloring app provides a menu to help young children develop emotions while maintaining cleanliness. Until recently, mid- to large-sized restaurants have provided paper-based coloring and playing tools, but are now disappearing due to tooling costs and the presence of colored pencil wastes on the hands of young children. So, instead of this tool, we want to develop an app that contains a color play function for the purpose of using it in a restaurant. In this study, rather than simply providing the function of coloring, it provides the picture drawing interface screen corresponding to the emotional state of the child. To do this, we constructed five types of children's emotional state knowledge base and inferred the child's emotional state through simple questions. Then, pallets and sketches with colors corresponding to five classes were prepared so that children could play coloring games. The coloring app provides brushes and file management functions of various thicknesses like other apps. The result of this study can be used not only as a restaurant but also as a coloring game which can be used as fun for children in various places, and it is expected to contribute greatly to emotional development by providing colors according to emotional state.

Recent Information Communication Technology has been rapidly developed compare to the previous years. With the development of computer technology, many researches of intelligent systems are studied that the recognition of human’s emotion is applied to the intelligent computer response. In the 4th industrial revolution, new service type will be implemented by the new way that supports the convenience to the human focused to the user’s emotion. Emotional information and communication technology will develop the interactive communication through the recognition of user’s emotion. The information communication technology recognizes the human’s face into the mobile phone or computer camera and, from the emotion of the human, the system responses intelligent action. This research, first acquires the user’s image and recognizes the emotion through the trained data with the machine learning. The proposed this study classifies seven emotions of game players with competitive action using mobile phone. The classified emotions of players are applied to the game’s rule and interactive game pattern. This intelligent method applied to the real game and the result shows the players response and the future studies.

In this paper, we propose a location-based simplified oceanographic surveying system. The simplified oceanographic observation system consists of a device for observing the ocean wave and a monitoring server for storing information based location. The simplified type of ocean wave surveying equipment is a small type, and it can be easily installed and deployed on ships and light buoys. Ocean wave observation equipment consists of a data logger, acceleration sensor, GPS and WCDMA module. The oceanic wave observation equipment operates at low power and physically cuts off power by using RTC when not observing. The power supply uses an external power source and can be used by attaching it to a ship or light buoy which is capable of using power at sea. The simple marine digger uses GPS to provide the ability to notify the date, time, and location to registered contact when a ship or light buoy is missing. We can also use a smartphone-based application to map the location of simplified marine peat observation devices. Therefore, it is possible to visit the equipment more quickly when leaving. Generally, large equipment, such as coastal wave buoy and weather buoy is mainly used to measure the crest, but the simple type ocean wave height observation equipment developed by us is small and can be easily installed in desired places. It is the most important factor in oceanographic observation and is proved through experiments that it is possible to measure the accurate wave height with the small type observation equipment developed in this paper. In addition, we can collect location information, wave-height and weather information, and corresponding dates through location based monitoring server.

In this paper, we propose a servo-motor-based system for verifying and calibrating a device for measuring the height and direction of ocean wave. Internationally, there are many devices that measure the height and direction of ocean wave, but there is no standard data and verification device. Generally, companies develop wave measurement equipment in their manufacture, but we do not know how they produce their products. In this paper, we try to calibrate the measurement devices using two servo-motors for the wave and divergence of various devices. Each servomotor controls the wave height and the wave direction. The wave can be calibrated up to 2m and the wave direction can be calibrated in 360° direction. Besides, we develop a separate monitoring device for the calibration process which can compare and analyze the waveform in real time. Consequently, we carry out a comparative analysis experiment between the waveguide measuring device and the calibrating device. Subsequently, the accuracy of the device is confirmed by comparing and analyzing the result graph value of the comparative analyzing device. Direction is the element to confirm the direction of wave. It does not measure speed and height, but it compares and analyzes the direction values between 0°~360° direction. In addition, the verification process is conducted using the results of comparative analysis. Our calibration device can produce long-waves and short-waves of ocean wave height. Our calibrator has been designed to calibrate up to 40Kg of equipment. In South Korea, each company has its ocean wave height and calibrating device, but they can not reproduce long-wave and shortwave. Furthermore, our calibrating device can be applied to ocean wave research and various fields.

Recently, many companies or organizations are introducing cloud services for managing digital records. Cloud services can dramatically reduce the cost of archiving and managing digital records, and provide a foundation for resilient management of digital records, depending on the business environment. Many companies and organizations outsource management of digital records to the cloud. Generally, companies sign SLA contracts when outsourcing computing systems to the cloud. This means that they will pay for the usage of the service while expecting cloud service more or less quantitative level. Customers who request cloud record management services want to be assured that their records are kept in trust in the cloud while meeting records requirements. The cloud record management service provider wants to know which quality items or criteria associated with records should be used to manage records. To establish a cloud record management service SLA, customers and service providers must be aware of each other's interrelationships, make a clear statement of their requirements and expectations, and agree on them. Because cloud services pay for service usage and satisfaction, the SLA must be defined for the purpose so that the customer and service provider can provide services that are mutually satisfactory. This paper describes the requirements for ensuring the quality of cloud record management services and the quality items and classification schemes and key indicators and values required for establishing SLAs.

To distinguish a smartphone user, some studies have been researched to analyze various human activities of natural daily life and classify users without using an additional step, such as using fingerprints or iris. However, it is not sufficient to analyze the diversity of human activities, the analysis per subject and the experiments using techniques that were better in previous related studies. In this paper, we propose a method that classifies users with various human activities by experimenting with a public data set of six activities data collected from thirty subjects using acceleration and gyroscope sensor in smartphone and with seven classification techniques that are better to existing research results. As a result of the comparison experiment with seven classification techniques, AdaBoost showed good results in the experiment in which the user classifies all of the six activities. Next, Adaboost showed the good results in laying, sitting and standing according to each activity by using the top four techniques which were better performance in classification of all activities. In walking, walking downstairs and walking upstairs, we could find out higher accuracy than the previous three activities, and SVM showed relatively excellent accuracy. Especially, the accuracy of user classification using walking upstairs is the highest. The results of this experiment are expected to become an important basis for the development of technologies that naturally and continuously classify users in everyday life.

In order to improve the bandwidth and increase the antenna efficiency, it is proposed that the surface wave and the lateral wave excitation are reduced. The theoretical analysis of the common mode of the patch leads to the design procedure of the antenna, and the reduction of the surface wave and the side wave is confirmed by the simulation result using the software. In the design of microstrip patch antenna presented in this paper, the antenna losses are therefore contained by controlling those quality factors which can have significant impact on bandwidth for given permittivity and substrate thickness. The gain of bandwidth product is a constant, therefore an effort has been made to improve the bandwidth of the patch antenna while ensuring desired radiation pattern. The effect of cover layer on impedance matching, Q factor hence bandwidth and frequency correction is discussed. The electric field and magnetic field components of the TE wave and the TM wave were analyzed using boundary condition between two materials, and the surface impedance was obtained. A method has been proposed to reduce the diffraction and mutual coupling at the edge of the substrade. An electromagnetic bandgap model for surface wave reduction is proposed and the efficient etching method and bandgap cell model is also introduced.