• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.12
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• pp.7187-7192
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• 2014

Recently, theservice field based on the location while expanding into a variety of business areas and have generated significant revenue. In particular, the map service provides a variety of information in conjunction with such public transport directions. Therefore, this study evaluated the map service, as one of the key technologies, StreetView and LoadView photographs of panoramic photograph-support service-modules that can be supported on smart phones. For this, purpose sensors were provided to allow smart phone users to easily publish panoramic photographs. The unnecessary parts could be removed from several photos and pictures using the design technology, and the naturalness of the connection could be maintained by applying the algorithm to handle a single photograph. Finally, a system to work with smartphone panoramic photographs was configured and designed to operate a smartphone application panoramic photograph for 6 months.

• Journal of Platform Technology
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• v.9 no.1
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• pp.15-22
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• 2021

In a smart manufacturing environment, more and more devices are connected to the Internet so that a large volume of data can be obtained during all phases of the product life cycle. The large-scale industries, companies and organizations that have more operational units scattered among the various geographical locations face a huge resource consumption because of their unorganized structure of sharing resources among themselves that directly affects the supply chain of the corresponding concerns. Cloud-based smart manufacturing paradigm facilitates a new variety of applications and services to analyze a large volume of data and enable large-scale manufacturing collaboration. The manufacturing units include machinery that may be situated in different geological areas and process instances that are executed from different machinery data should be constantly managed by the super admin to coordinate the manufacturing process in the large-scale industries these environments make the manufacturing process a tedious work to maintain the efficiency of the production unit. The data from all these instances should be monitored to maintain the integrity of the manufacturing service system, all these data are computed in the cloud environment which leads to the latency in the performance of the smart manufacturing service system. Instead, validating data from the external device, we propose to validate the data at the front-end of each device. The validation process can be automated by script validation and then the processed data will be sent to the cloud processing and storing unit. Along with the end-device data validation we will implement the APM(Asset Performance Management) to enhance the productive functionality of the manufacturers. The manufacturing service system will be chunked into modules based on the functionalities of the machines and process instances corresponding to the time schedules of the respective machines. On breaking the whole system into chunks of modules and further divisions as required we can reduce the data loss or data mismatch due to the processing of data from the instances that may be down for maintenance or malfunction ties of the machinery. This will help the admin to trace the individual domains of the smart manufacturing service system that needs attention for error recovery among the various process instances from different machines that operate on the various conditions. This helps in reducing the latency, which in turn increases the efficiency of the whole system

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.1913-1934
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• 2022

The emergence of technologies like Big data analytics, Industrial Internet of Things, Internet of Things, and applicability of these technologies in various domains leads to increased demand in the underlying execution environment. The demand may be for compute, storage, and network resources. These demands cannot be effectively catered by the conventional cloud environment, which requires an integrated environment. The task of finding an appropriate service provider is tedious for a service consumer as the number of service providers drastically increases and the services provided are heterogeneous in the specification. A service broker is essential to find the service provider for varying service consumer requests. Also, the service broker should be smart enough to make the service providers best fit for consumer requests, ensuring that both service consumer and provider are mutually beneficial. A service broker in an integrated environment named Global Manager is proposed in the paper, which can find an appropriate service provider for every varying service consumer request. The proposed Global Manager is capable of identification of parameters for service negotiation with the service providers thereby making the providers the best fit to the maximum possible extent for every consumer request. The paper describes the architecture of the proposed Global Manager, workflow through the proposed algorithms followed by the pilot implementation with sample datasets retrieved from literature and synthetic data. The experimental results are presented with a few of the future work to be carried out to make the Manager more sustainable and serviceable.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.3
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• pp.89-97
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• 2021

Voice interface can not only make daily life more convenient through artificial intelligence speakers but also improve the working environment of the factory. This paper presents a voice-assisted work management system that supports both speech and speaker recognition. This system is able to provide machine control and authorized worker authentication by voice at the same time. We applied two speech recognition methods, Google's Speech application programming interface (API) service, and DeepSpeech speech-to-text engine. For worker identification, the SincNet architecture for speaker recognition was adopted. We implemented a prototype of the work management system that provides voice control with 26 commands and identifies 100 workers by voice. Worker identification using our model was almost perfect, and the command recognition accuracy was 97.0% in Google API after post- processing and 92.0% in our DeepSpeech model.

• Journal of Communications and Networks
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• v.18 no.3
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• pp.513-522
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• 2016

We propose a mechanism for monitoring load in quality of service (QoS)-enabled wireless networks and show how it can be used for network management as well as for dynamic pricing. Mobile network traffic, especially video, has grown exponentially over the last few years and it is anticipated that this trend will continue into the future. Driving factors include the availability of new affordable, smart devices, such as smart-phones and tablets, together with the expectation of high quality user experience for video as one would obtain at home. Although new technologies such as long term evolution (LTE) are expected to help satisfy this demand, the fact is that several other mechanisms will be needed to manage overload and congestion in the network. Therefore, the efficient management of the expected huge data traffic demands is critical if operators are to maintain acceptable service quality while making a profit. In the current work, we address this issue by first investigating how the network load can be accurately monitored and then we show how this load metric can then be used to provide creative pricing plans. In addition, we describe its applications to features like traffic offloading and user satisfaction tracking.

• Journal of Information Technology Services
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• v.21 no.1
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• pp.163-179
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• 2022

Two dominant phenomena in modern world; population ageing and digitalization, have led public sector organizations to heavily rely on B2C(Business-to-Consumer) mobile applications. Yet, fatal concerns and complaints have often been raised by the mobile application users, notably from social welfare sector. With the continual expansion of digital landscape as well as the growth of life expectancy, usage of mobile applications has become prevalent across the stakeholders involved in social welfare sector. 'Smart Long-Term Care (SLTC)', inter alia, is a primary example of such mobile applications, designed to support Long-Term Residential Care (LTRC) service. The main goal of SLTC is to serve more convenient and practical LTRC service for both caregivers and care receivers. To examine user satisfaction of SLTC mobile application, this study investigates existing challenges and means to improve user satisfaction. Hence, we conducted this study using two methods: in-depth interview and topic modeling. Interestingly, two research outcomes commonly indicated that 5 factors (stability, accessibility, usefulness, responsiveness, and ease of use) were found significant in affecting user satisfaction of SLTC. Our findings suggest that the aforementioned factors can be seen as potential causes of the genuinely low user satisfaction. Eventually, this work will be a stepping-stone to elevate the overall quality level of LTRC service along with the user satisfaction degree of SLTC mobile application.

• Journal of Information Technology Services
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• v.20 no.4
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• pp.95-111
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• 2021

Recently, many organizations are actively adopting VDI (Virtual Desktop Infrastructure), an IT-based business system, to build a non-face-to-face business environment for smart-work. However, most of the existing research on VDI has focused on the satisfaction of system service quality or the use of IT resources and investment for VDI introduction. However, research on effective management and utilization of factors according to the characteristics of VDI technology is urgently required. This study is an empirical research study on how VDI technology characteristics affect interactions and work performance by identifying differences in utilization factors between general organization members and IT managers, presenting standards for business utilization and management. This study proposed a model and hypothesis that the system technology characteristics for VDI use are mediated by interactions in which users respond to functions appropriate to their work. In order to verify the hypothesis, a questionnaire survey was conducted on 188 people of companies and institutions that have adopted and used VDI through a questionnaire survey. Data analysis was performed with partial least squares (PLS), a structural equation modeling (SEM) technique that uses a component-based approach to estimation. As a result of the empirical analysis, the same environmental function for performing work, N-th security, and remote access function factors for non-face-to-face work have a significant effect on interactivity, and IT managers have an additional significant effect on the management technology characteristics of resource reallocation. Has been shown to affect. The results of this study aim to minimize trial and error due to new introduction by presenting considerations for future VDI introduction through case analysis.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.3
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• pp.21-29
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• 2015

The Internet of Things (IoT) is an Infrastructure which allows to connect with each device in physical world through the Internet. Thus IoT enables to provide meahup services or intelligent services to human user using collected data from those devices. Due to these advantages, IoT is used in divers service domains such as traffic, distribution, healthcare, and smart city. However, current IoT provides restricted services because it only supports monitor and control devices according to collected data from the devices. To resolve this problem, we propose a design and implementation of personalized IoT service base on service orchestration. The proposed service allows to discover specific services and then to combine the services according to a user location. To this end, we develop a service ontology to interpret user information according to meanings and smartphone web app to use the IoT service by human user. We also develop a service platform to work with external IoT platform. Finally, to show feasibility, we evaluate the proposed system via study.

• Journal of Information Technology Services
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• v.12 no.3
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• pp.39-54
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• 2013

IT consulting is becoming a norm rather than exception in this age of smart work and information revolution. As IT consulting is one of the knowledge intensive services requiring high credence on both sides, maintaining a good trustful relationship is critical in sustenance of strategic partnership between business firms and IT service firms. Trust is known to be one of the salient constructs in service relationships. In this study, building from the social psychology literature, trust is conceptualized as two dimensions : cognitive and affective trust. Using two dimensions of trust as mediators, a research model is constructed for IT consulting specific context : relationship continuance intention as the dependent construct while expertise, service performance, reputation, relationship satisfaction and value similarity as antecedents of cognitive and affective trust. 145 data points were collected through a survey of IT service client project managers retrospectively asking their experience with IT consultants. Findings suggest that cognitive trust is associated with perceived level of expertise and service performance while affective trust with relationship satisfaction and value similarity, respectively. Interestingly, the paths from reputation are found to be statistically insignificant towards both dimensions of trust, indicating IT service context would be more practically outcome oriented than any other professional service context. Also, cognitive trust seems to maintain stronger influence on relationship continuance intention as anticipated. Implications and limitations are discussed at the end.

• Journal of Digital Convergence
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• v.18 no.12
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• pp.29-36
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• 2020

The background of this study is that machine learning administrative services are recently attracting attention as a major policy tool for non-face-to-face administrative services in the post-corona era. This study investigated the types of work expected to be effective when introducing machine learning administrative services for Seoul Metropolitan Government officials who are piloting machine learning administrative services. The research method is a machine that can be introduced by organizational unit by distributing and collecting questionnaires for Seoul administrative organizations that have performed machine learning-based administrative services for one month in July 2020 targeting Seoul public officials using machine learning-based administrative services. By analyzing the learning administration service and application service, the business characteristics of each machine learning administration service type such as supervised learning work type, unsupervised learning work type, and reinforced learning work type were analyzed. As a result of the research analysis, it was found that there were significant differences in the characteristics of administrative tasks by supervised and unsupervised learning areas. In particular, it was found that the reinforcement learning domain contains the most appropriate business characteristics for machine learning administrative services. Implications were drawn. The results of this study can be provided as a reference material to practitioners who want to introduce machine learning administration services, and can be used as basic data for research to researchers who want to study machine learning administration services in the future.