• Journal of Information Processing Systems
• /
• v.7 no.4
• /
• pp.707-716
• /
• 2011

It is important that desktop grids should be able to aggressively deal with the dynamic properties that arise from the volatility and heterogeneity of resources. Therefore, it is required that task scheduling be able to positively consider the execution behavior that is characterized by an individual resource. In this paper, we implement a log analysis system with REST web services, which can analyze the execution behavior by utilizing the actual log data of desktop grid systems. To verify the log analysis system, we conducted simulations and showed that the resource group-based task scheduling, based on the analysis of the execution behavior, offers a faster turnaround time than the existing one even if few resources are used.

• Journal of Advanced Navigation Technology
• /
• v.19 no.6
• /
• pp.552-557
• /
• 2015

Recent performed by recognizing a user's location, various services have been tailored focus on short-range wireless communication technology. A beacon in which is attracting attention as next-generation technology. Beacon is a terminal by utilizing the frequency of the non-audible area can not be bluetooth and human sending and receiving terminals and information, Apple recently iBeacon like a low-power Bluetooth (BLE; bluetooth low energy) based beacon showing a tendency to rise into the mainstream there. Services using a beacon is basically installs the terminal in a certain place indoor. It is characterized by providing the user the services to catch the user's position, even automatically take a separate action. Various types of location-based service provided by the target interior space began to attract attention. A variety of location-based services are provided in the interior space in order to be successfully deployed and provide guidance to the interior space, the movement route and the like are essentially required to build various types of information. In this paper, for efficient indoor positioning by varying the signal strength of the beacon in such areas were measured and analyzed.

• Journal of Korea Multimedia Society
• /
• v.18 no.9
• /
• pp.1091-1097
• /
• 2015

Internet-of-Things (IoT) becomes one of the most promising future paradigms, which foresees enormous amounts of interoperable things and heterogeneous services. The goal of IoT is to enable all things connected and brings all kinds information and services to people. However, such a great deal of information may lead to cognitive overload or restrain in productivity of people. Thus, it is a necessity to build intelligent mechanisms to assist people in accessing the information or services they needed in a proactive manner. Most of previous related mechanisms are built on well-defined web services and lack of consideration of constrained resources. This paper suggests a services composition method by adapting a hierarchical model, which is a graph-based model composed of four layers: Context Layer, Event Layer, Service Layer and Device Layer. With a such multi-layer graph, service composition can be achieved by the iteration of layer by layer. Then, to evaluate the effectiveness of this proposed hierarchical model, a real-life emergency response dataset is applied and the experimental results are composed with the general probabilistic method and indicate that the proposed method is help for compositing multiple services while considering given context and constrained resources.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.45 no.4
• /
• pp.79-85
• /
• 2022

Various non-face-to-face services are being activated due to the influence of the Corona 19 virus around the world. However, unlike the rapid development of delivery services, social awareness of delivery services is causing many problems. Therefore, in this study, we analyze the quality attributes of delivery services from the consumer's point of view, and based on the results, we try to derive a direction for service improvement. In this study, quality factors were established through interviews and surveys with actual consumers, and quality attributes were classified through the Kano model and Timko's customer satisfaction coefficient. "Attractive" is ('Ease of ordering, Accurate delivery to the designated place'), "One Dimensional" is ('Variety of payment methods, Accurate delivery on time, Accurate delivery of ordered food, Degree of non-deformation of packaging conditions, etc., Convenience of use time'), "Must be" is ('Kindness of the delivery person'), "Reverse" is ('provision of services, service response to order discrepancies'). This study has academic significance in that it compensated for the disadvantage of not being able to interpret the mathematical meaning of the Kano model with Teamco's customer satisfaction coefficient. It also has practical implications in that it provides an indirect clue to future improvement directions.

• Journal of Information Technology Services
• /
• v.18 no.3
• /
• pp.143-154
• /
• 2019

The purpose of this study is to explore innovative adaptation of IT systems worldwide to support process-focus assessment. To this end, the study presents four cases from Australia, Singapore, the U.S.A., and Korea to inform educational policy and technology researchers and practitioners. Based on comparing the four chosen cases as benchmarks, the study concluded that IT systems and technologies can expedite and improve school interventions to enhance student learning in terms of time and quality. Also, educational big data and learning analytics can be used to systematically monitor and communicate individual student's progress among school stakeholders (i.e., teachers, students, parents, and administrators). Lastly, the study made some suggestions to support process-focused assessment in schools as following : 1) A more evidence-based, systems approach is needed to integrate the curriculum, instruction, and assessment to bridge the gap between educational policy and school practice; 2) It is critical to create ICT-friendly school environments so that meaningful data could be collected, analyzed, and stored from individual students and school units; 3) Teacher professional development is another area that needs special considerations and support to successfully implement process-focused assessment in schools.

• Journal of Internet Computing and Services
• /
• v.17 no.4
• /
• pp.61-68
• /
• 2016

In this paper, an implementation method of augmented reality (AR) technology using Web 3.0 information services in the field of disaster response is proposed. The structure and characteristics of semantic web-based Web 3.0 are realized and a AR based mobile visual search (MVS) applied in the disaster sites is described. Based on Web 3.0 and AR MVS, a semantic web ontology oriented configuration scheme for disaster-related information and the communication scheme of information provided by AR technology are proposed. For the purpose of providing disaster-related and customized information to the disaster response site quickly and accurately, a method of leveraging Web 3.0 information services in AR technology is presented.

• International Journal of Advanced Culture Technology
• /
• v.8 no.4
• /
• pp.263-270
• /
• 2020

The growth of the mobile app markets has made it popular among people who recommend relevant information about restaurants. The recommendation service app based on AI Chatbot is that it can efficiently manage time and finances by making it easy for restaurant consumers to easily access the information they want anytime, anywhere. Eating out consumers use smartphone applications for finding restaurants, making reservations, and getting reviews and how to use them. In addition, social attention has recently been focused on the research of AI chatbot. The Chatbot is combined with the mobile messenger platform and enabling various services due to the text-type interactive service. It also helps users to find the services and data that they need information tersely. Applying this to restaurant recommendation services will increase the reliability of the information in providing personal information. In this paper, an artificial intelligence chatbot-based smartphone restaurant recommendation app using personalization information is proposed. The recommendation service app utilizes personalization information such as gender, age, interests, occupation, search records, visit records, wish lists, reviews, and real-time location information. Users can get recommendations for restaurants that fir their purpose through chatting using AI chatbot. Furthermore, it is possible to check real-time information about restaurants, make reservations, and write reviews. The proposed app uses a collaborative filtering recommendation system, and users receive information on dining out using artificial intelligence chatbots. Through chatbots, users can receive customized services using personal information while minimizing time and space limitations.

• Journal of Digital Convergence
• /
• v.20 no.3
• /
• pp.117-129
• /
• 2022

In the perspective of value-based adoption mode, this study empirically examined the factors that affect the intention of users of Fintech payment services to stop using them. A survey of college students who are familiar with digital devices, have no objection to payment and settlement services, and have high service access. A total of 148 questionnaires were analyzed using SPSS and SmartPLS. The study results show that perceived benefits, complexity, and security concerns are significant factors influencing the discontinue intention of Fintech payment services. Among them, the perceived benefit showed the most significant influence. Based on the results of this study, Fintech providers will be able to build a service environment to provide continuous benefits for maintaining long-term relationships with users, improve systems to secure various uses, and reduce users' negative perceptions of security. Recently, the use of services by the elderly has increased, so it is necessary to expand the scope of this study to target various age groups in future research.

• Information Systems Review
• /
• v.22 no.4
• /
• pp.75-92
• /
• 2020

As population and generation structures change, more and more customers tend to avoid facing relation due to the development of information technology and spread of smart phones. This phenomenon consists with efficiency and immediacy, which are the consumption patterns of modern customers who are used to information technology, so offline network-oriented distribution companies actively try to switch their sales and services to untact patterns. Recently, untact services are boosted in various fields, but beauty products are not easy to be recommended through untact services due to many options depending on skin types and conditions. There have been many studies on recommendations and development of recommendation systems in the online beauty field, but most of them are the ones that develop recommendation algorithm using survey or social data. In other words, there were not enough studies that classify segments based on user information such as skin types and product preference. Therefore, this study classifies customer segments using machine learning technique K-prototypesalgorithm based on customer information and search log data of mobile application, which is one of untact services in the beauty field, based on which, untact marketing strategy is suggested. This study expands the scope of the previous literature by classifying customer segments using the machine learning technique. This study is practically meaningful in that it classifies customer segments by reflecting new consumption trend of untact service, and based on this, it suggests a specific plan that can be used in untact services of the beauty field.

• International journal of advanced smart convergence
• /
• v.9 no.3
• /
• pp.183-191
• /
• 2020

Today, taking photos using smartphones has become an essential element of modern people. According to these social changes, modern people need a larger storage capacity, and the number of unnecessary photos has increased. To support the storage, cloud-based photo storage services from various platforms have appeared, and many people are using the services. As the number of photos increases, it is difficult for users to find the photos they want, and it takes a lot of time to organize. In this paper, we propose a cloud-based photo management service that facilitates photo management by classifying photos and recommending unnecessary photos using deep learning. The service provides the function of tagging photos by identifying what the subject is, the function of checking for wrongly taken photos, and the function of recommending similar photos. By using the proposed service, users can easily manage photos and use storage capacity efficiently.