• Journal of the Korean Society of Radiology
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• v.84 no.2
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• pp.504-511
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• 2023

Hemolymphangioma or hemangiolymphangioma is a rare venolymphatic vascular malformation composed of proliferations or networks of vascular spaces including the lymphatics, capillaries, veins, or arteries. The small bowel is a rare location for hemolymphangioma, and the small bowel mesentery is an even rarer site. Herein, we report a surgically confirmed large complex hemolymphangioma in the small bowel mesentery in a 55-year-old male.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.10
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• pp.1087-1092
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• 2015

It was diversified demand for a wireless network to the rapid growth of the Internet, the time and space that are not in the new level of Internet technology, limits the Ad-hoc networks are needed. Ad-hoc networks do not communicate with the central station, each of the mobile nodes included in the network communicate with each other by the relay role. In recent years, the Ad-hoc wireless networks in a variety of routing protocols and network security, research is actively underway for the authentication method, but the security of wireless Internet and Ad-hoc networks, certification is incomplete situation. This paper considers the authentication and key agreement technique applicability of the USIM card using the DSR routing protocol of the Java Card and Ad-hoc networks, we propose a secure authentication mechanism between the mobile node.

• Safety and Health at Work
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• v.10 no.4
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• pp.400-408
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• 2019

The "fourth industrial revolution" (FIR) is an age of advanced technology based on information and communication. FIR has a more powerful impact on the economy than in the past. However, the prospects for the labor environment are uncertain. The purpose of this study is to anticipate and prepare for occupational health and safety (OHS) issues. In FIR, nonstandard employment will be common. As a result, it is difficult to receive OHS services and compensation. Excessive trust in new technologies can lead to large-scale or new forms of accidents. Global business networks will cause destruction of workers' biorhythms, some cancers, overwork, and task complexity. The social disconnection because of an independent work will be a risk for worker's mental health. The union bonds will weaken, and it will be difficult to apply standardized OHS regulations to multinational enterprises. To cope with the new OHS issues, we need to establish new concepts of "decent work" and standardize regulations, which apply to enterprises in each country, develop public health as an OHS service, monitor emerging OHS events and networks among independent workers, and nurture experts who are responsible for new OHS issues.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.13
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• pp.5325-5330
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• 2014

Background: Chronic myelocytic leukemia is a disease that threatens both adults and children. Great progress has been achieved in treatment but protein-protein interaction networks underlining chronic myelocytic leukemia are less known. Objective: To develop a protein-protein interaction network for chronic myelocytic leukemia based on gene expression and to predict biological pathways underlying molecular complexes in the network. Materials and Methods: Genes involved in chronic myelocytic leukemia were selected from OMIM database. Literature mining was performed by Agilent Literature Search plugin and a protein-protein interaction network of chronic myelocytic leukemia was established by Cytoscape. The molecular complexes in the network were detected by Clusterviz plugin and pathway enrichment of molecular complexes were performed by DAVID online. Results and Discussion: There are seventy-nine chronic myelocytic leukemia genes in the Mendelian Inheritance In Man Database. The protein-protein interaction network of chronic myelocytic leukemia contained 638 nodes, 1830 edges and perhaps 5 molecular complexes. Among them, complex 1 is involved in pathways that are related to cytokine secretion, cytokine-receptor binding, cytokine receptor signaling, while complex 3 is related to biological behavior of tumors which can provide the bioinformatic foundation for further understanding the mechanisms of chronic myelocytic leukemia.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1016-1033
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• 2016

In this paper, we present a joint relay-and-antenna selection and power allocation strategy for multiple-input multi-output (MIMO) amplify-and-forward (AF) two-way relay networks (TWRNs). In our approach, we select the best transmit and receive antennas at the two sources, a best relay and a best transmit and receive antenna at the selected relay based on maximizing the minimum of the end-to-end received signal-to-noise-ratios (SNRs) under a total transmit power constraints. We obtained the closed-form solution for the optimal power allocation firstly. Then with the optimal allocation solution we found, we can reduce the joint relay-and-antenna selection to a simpler problem. Besides, the overall outage probability is investigated and a tight closed-form approximation is derived, which provides a method to evaluate the outage performance easily and fast. Simulation results are presented to verify the analysis.

• Herbal Formula Science
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• v.28 no.3
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• pp.243-254
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• 2020

Objectives : Network pharmacology analysis is commonly used to investigate the synergies and potential mechanisms of multiple compounds by analyzing complex, multi-layered networks. We used TCMSP and BATMAN-TCM databases to compare results of network pharmacological analysis between White Ginseng(WG) and Red Ginseng(RG). Methods : WG and RG were compared with components and their target molecules using TCMSP database, and compound-target-pathway/disease networks were compared using BATMAN-TCM database. Results : Through TCMSP, 104 kinds of target molecules were derived from WG and 38 kinds were derived from RG. Using the BATMAN-TCM database, target pathways and diseases were screened, and more target pathways and diseases were screened compared to RG due to the high composition of WG ingredients. Analysis of component-target-pathway/disease network using network analysis tools provided by BATMAN-TCM showed that WG formed more networks than RG. Conclusions : Network pharmacology analysis can be effectively performed using various databases used in system biology research, and although the materials that have been reported in the past can be used efficiently for research on diseases related to targets, the results are unreliable if prior studies are focused on limited or narrow research areas.

• Journal of Communications and Networks
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• v.13 no.2
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• pp.132-141
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• 2011

IEEE 802.15.4 networks are a feasible platform candidate for connecting all health-care-related equipment dispersed across a hospital room to collect critical time-sensitive data about patient health state, such as the heart rate and blood pressure. To meet the quality of service requirements of health-care systems, this paper proposes a multi-priority queue system that differentiates between various types of frames. The effect of the proposed system on the average delay and throughput is explored herein. By employing different contention window parameters, as in IEEE 802.11e, this multi-queue system prioritizes frames on the basis of priority classes. Performance under both saturated and unsaturated traffic conditions was evaluated using a novel analytical model that comprehensively integrates two legacy models for 802.15.4 and 802.11e. To improve the accuracy, our model also accommodates the transmission retries and deferment algorithms that significantly affect the performance of IEEE 802.15.4. The multi-queue scheme is predicted to separate the average delay and throughput of two different classes by up to 48.4% and 46%, respectively, without wasting bandwidth. These outcomes imply that the multi-queue system should be employed in health-care systems for prompt allocation of synchronous channels and faster delivery of urgent information. The simulation results validate these model's predictions with a maximum deviation of 7.6%.

• Journal of IKEEE
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• v.22 no.4
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• pp.1175-1179
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• 2018

In this paper, we propose recurrent CNN(Convolutional Neural Networks) for detecting seizures among patients using EEG signals. In the proposed method, data were mapped by image to preserve the spectral characteristics of the EEG signal and the position of the electrode. After the spectral preprocessing, we input it into CNN and extracted the spatial and temporal features without wavelet transform. Results from the Children's Hospital of Boston Massachusetts Institute of Technology (CHB-MIT) dataset showed a sensitivity of 90% and a false positive rate (FPR) of 0.85 per hour.

• Journal of information and communication convergence engineering
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• v.10 no.4
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• pp.337-342
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• 2012

The medical industries are integrated with information technology with mobile devices and wireless communication. The advent of mobile healthcare systems can benefit patients and hospitals, by not only providing better quality of patient care, but also by reducing administrative and medical costs for both patients and hospitals. Security issues present an interesting research topic in wireless and pervasive healthcare networks. As information technology is developed, many organizations such as government agencies, public institutions, and corporations have employed an information system to enhance the efficiency of their work processes. For the past few years, healthcare organizations throughout the world have been adopting health information systems (HIS) based on the wireless network infrastructure. As a part of the wireless network, a mobile agent has been employed at a large scale in hospitals due to its outstanding mobility. Several vulnerabilities and security requirements related to mobile devices should be considered in implementing mobile services in the hospital environment. Secure authentication and protocols with a mobile agent for applying ubiquitous sensor networks in a healthcare system environment is proposed and analyzed in this paper.

• Journal of Oral Medicine and Pain
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• v.47 no.2
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• pp.107-108
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• 2022

Artificial intelligence (AI) refers to the use of machines to mimic intelligent human behavior. It involves interactions with humans in clinical settings, and augmented intelligence is considered as a cognitive extension of AI. The importance of AI in healthcare and medicine has been emphasized in recent studies. Machine learning models, such as genetic algorithms, artificial neural networks (ANNs), and fuzzy logic, can learn and examine data to execute various functions. Among them, ANN is the most popular model for diagnosis based on image data. AI is rapidly becoming an adjunct to healthcare professionals and is expected to be human-independent in the near future. The introduction of AI to the diagnosis and treatment of oral diseases worldwide remains in the preliminary stage. AI-based or assisted diagnosis and decision-making will increase the accuracy of the diagnosis and render treatment more precise and personalized. Therefore, dental professionals must actively initiate and lead the development of AI, even if they are unfamiliar with it.