• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.3
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• pp.41-51
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• 2006

Clustering is to group similar objects into clusters. Until now there are a lot of approaches using Self-Organizing feature Maps (SOFMS) But they have problems with a small output-layer nodes and initial weight. For example, one of them is a one-dimension map of c output-layer nodes, if they want to make c clusters. This approach has problems to classify elaboratively. This Paper suggests one-dimensional output-layer nodes in SOFMs. The number of output-layer nodes is more than those of clusters intended to find and the order of output-layer nodes is ascending in the sum of the output-layer node's weight. We un find input data in SOFMs output node and classify input data in output nodes using Euclidean distance. The proposed algorithm was tested on well-known IRIS data and TSPLIB. The results of this computational study demonstrate the superiority of the proposed algorithm.

• Journal of Korean Institute of Industrial Engineers
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• v.31 no.3
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• pp.257-264
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• 2005

This paper suggests a heuristic algorithm for the clustering problem. Clustering involves grouping similar objects into a cluster. Clustering is used in a wide variety of fields including data mining, marketing, and biology. Until now there are a lot of approaches using Self-Organizing Feature Maps(SOFMs). But they have problems with a small output-layer nodes and initial weight. For example, one of them is a one-dimension map of k output-layer nodes, if they want to make k clusters. This approach has problems to classify elaboratively. This paper suggests one-dimensional output-layer nodes in SOFMs. The number of output-layer nodes is more than those of clusters intended to find and the order of output-layer nodes is ascending in the sum of the output-layer node's weight. We can find input data in SOFMs output node and classify input data in output nodes using Euclidean distance. We use the well known IRIS data as an experimental data. Unsupervised clustering of IRIS data typically results in 15 - 17 clustering error. However, the proposed algorithm has only six clustering errors.

• ETRI Journal
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• v.37 no.2
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• pp.359-368
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• 2015

In this paper, we investigate the capture effect through experiments conducted with Iris nodes equipped with AT86RF230 radio transceivers. It is shown that the first arriving packet in a collision can capture the radio channel for equal power transmissions and may be decoded depending on the amount of overlap. A new 3-packet-capture scenario is introduced and implemented. To be able to understand the impact of capture on the throughput performance of wireless sensor networks, we present an analysis of the capture coefficient using our practical results. For real-world implementations, the throughput of pure ALOHA considering a finite number of users is presented in analytical form. The capture coefficient is then applied to pure ALOHA as a case study. Using analytical and practical implementations of the capture effect on ALOHA, a very good match in channel throughput performance enhancement is demonstrated over the non-capture effect case. TinyOS-2.x is used to program the nodes and to observe data exchange on a computer through a base station.

• Infection and chemotherapy
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• v.50 no.4
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• pp.350-356
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• 2018

In acquired immunodeficiency syndrome (AIDS) patients, immune reconstitution inflammatory syndrome (IRIS) due to Mycobacterium avium complex (MAC) infection is one of the most difficult IRIS types to manage. We report an unusual case of MAC-associated IRIS. At first the patient was diagnosed human immunodeficiency virus (HIV) infection after he was admitted with pneumocystis pneumonia. After starting antiretroviral therapy he presented unmasked IRIS with MAC infection. Next, he was hospitalized with continuous loose stools and new-onset fever. Investigation included computed tomography (CT), which showed homogeneous enhancement and enlargement of the lymph nodes (LN), elevation of ferritin (>1,650 ng/mL) and lactate dehydrogenase (306 IU/L) levels, and F- fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) scan, which showed increased FDG uptake. These findings were highly indicative of lymphoma. We performed laparoscopic biopsy of the mesenteric LN, and the biopsy culture grew MAC. So we made a diagnosis of MAC-associated. Therefore, IRIS must be considered as a possible diagnosis when AIDS patients develop new symptoms or exhibit exacerbations of existing symptoms. Furthermore the biopsies should be conducted.