Author
Haeng-Kon Kim
Other affiliations: Catholic University of Daegu
Bio: Haeng-Kon Kim is an academic researcher from The Catholic University of America. The author has contributed to research in topics: Mobile device & Software development. The author has an hindex of 13, co-authored 201 publications receiving 784 citations. Previous affiliations of Haeng-Kon Kim include Catholic University of Daegu.
Papers published on a yearly basis
Papers
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TL;DR: This paper proposed architecture for IoT based u-healthcare monitoring with the motivation and advantages of Cloud to Fog(C2F) computing which interacts more by serving closer to the edge (end points) at smart Homes and Hospitals.
Abstract: Healthcare in the past, decision making was merely based on doctor’s personal experience, domain knowledge, patient's physical signs and symptoms and diagnostic laboratory reports. In contrast, devices or things and technologies came into existence playing significant role and helps doctors or physicians to add wisdom to their decision in healthcare monitoring. Cloud paradigm stands as the backbone for on-demand network use of a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) in U-healthcare monitoring system architectures but attached limitations which are solved by Fog(significant extension of cloud). This paper proposed architecture for IoT based u-healthcare monitoring with the motivation and advantages of Cloud to Fog(C2F) computing which interacts more by serving closer to the edge (end points) at smart Homes and Hospitals.
112 citations
TL;DR: Oral semaglutide provides significant reductions in HbA1c compared with placebo in a dose-dependent manner in Japanese patients with type 2 diabetes, and has a safety profile consistent with that of GLP-1 receptor agonist.
94 citations
TL;DR: The PIONEER 10 study aimed to evaluate the safety and efficacy of oral semaglutide versus dulagLutide in Japanese patients with type 2 diabetes, and found that the most common adverse events were infections and gastrointestinal events.
78 citations
TL;DR: This paper contributes by presenting Green IoT Agriculture and Healthcare Application (GAHA) using sensor-cloud integration model and lists out the advantages, challenges, and future research directions related to green application design.
Abstract: The application of the two trending and popular technologies, Cloud Computing (CC) and the Internet of Things (IoT) are current hot discussions in the field of agriculture and healthcare applications. Motivated by achieving a sustainable world, this paper discusses various technologies and issues regarding green cloud computing and green Internet of Things, further improves the discussion with the reduction in energy consumption of the two techniques (CC and IoT) combination in agriculture and healthcare systems. The history and concept of the hot green information and communications technologies (ICT’s) which are enabling green IoT will be discussed. Green computing introduction first and later focuses on the recent works done regarding the two emerging technologies in both agriculture and healthcare cases. Furthermore, this paper contributes by presenting Green IoT Agriculture and Healthcare Application (GAHA) using sensor-cloud integration model. Finally, lists out the advantages, challenges, and future research directions related to green application design. Our research aims to make green area broad and contribution to sustainable application world. Keyword: Green, IoT (Internet of Things), Cloud Computing, Agriculture application, Healthcare application, Sensor-Cloud
70 citations
TL;DR: The background of Internet of Things (IoT) and its application to u-healthcare is discussed and the idea of framework of IoT which works for u- healthcare is presented.
Abstract: The IoT plays an important role in healthcare applications, from managing chronic diseases at one end of the spectrum to preventing disease at the other. IoT devices can be used to enable remote health monitoring and emergency notification systems. IoT aims to provide means to access and control all kinds of ubiquitous and uniquely identifiable devices, facilities and assets. In this paper we discussed the background of Internet of Things (IoT) and its application to u-healthcare. This also presents the idea of framework of IoT which works for u-healthcare.
51 citations
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TL;DR: A review of current studies and research works in agriculture which employ the recent practice of big data analysis, showing that the availability of hardware and software, techniques and methods for big dataAnalysis, as well as the increasing openness ofbig data sources, shall encourage more academic research, public sector initiatives and business ventures in the agricultural sector.
547 citations
TL;DR: Object-oriented and process metrics have been reported to be more successful in finding faults compared to traditional size and complexity metrics and seem to be better at predicting post-release faults than any static code metrics.
Abstract: ContextSoftware metrics may be used in fault prediction models to improve software quality by predicting fault location. ObjectiveThis paper aims to identify software metrics and to assess their applicability in software fault prediction. We investigated the influence of context on metrics' selection and performance. MethodThis systematic literature review includes 106 papers published between 1991 and 2011. The selected papers are classified according to metrics and context properties. ResultsObject-oriented metrics (49%) were used nearly twice as often compared to traditional source code metrics (27%) or process metrics (24%). Chidamber and Kemerer's (CK) object-oriented metrics were most frequently used. According to the selected studies there are significant differences between the metrics used in fault prediction performance. Object-oriented and process metrics have been reported to be more successful in finding faults compared to traditional size and complexity metrics. Process metrics seem to be better at predicting post-release faults compared to any static code metrics. ConclusionMore studies should be performed on large industrial software systems to find metrics more relevant for the industry and to answer the question as to which metrics should be used in a given context.
437 citations
TL;DR: Results depict that the proposed Bayesian belief network classifier-based model has high accuracy and response time in determining the state of an event when compared with other classification algorithms, which enhances the utility of the proposed system.
Abstract: Internet of Things (IoT) technology provides a competent and structured approach to handle service deliverance aspects of healthcare in terms of mobile health and remote patient monitoring. IoT generates an unprecedented amount of data that can be processed using cloud computing. But for real-time remote health monitoring applications, the delay caused by transferring data to the cloud and back to the application is unacceptable. Relative to this context, we proposed the remote patient health monitoring in smart homes by using the concept of fog computing at the smart gateway. The proposed model uses advanced techniques and services, such as embedded data mining, distributed storage, and notification services at the edge of the network. Event triggering-based data transmission methodology is adopted to process the patient’s real-time data at fog layer. Temporal mining concept is used to analyze the events adversity by calculating the temporal health index of the patient. In order to determine the validity of the system, health data of 67 patients in IoT-based smart home environment was systematically generated for 30 days. Results depict that the proposed Bayesian belief network classifier-based model has high accuracy and response time in determining the state of an event when compared with other classification algorithms. Moreover, decision making based on real-time healthcare data further enhances the utility of the proposed system.
346 citations