• Asian Pacific Journal of Cancer Prevention
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• v.13 no.3
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• pp.767-773
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• 2012

The esophageal squamous cell carcinoma (ESCC) is an aggressive tumor with a poor prognosis. Understanding molecular changes in ESCC should improve identification of risk factors with different molecular subtypes and provide potential targets for early detection and therapy. Our study aimed to obtain a molecular signature of ESCC through the regulation network based on differentially expressed genes (DEGs). We used the GSE23400 series to identify potential genes related to ESCC. Based on bioinformatics we constructed a regulation network. From the results, we could establish that many transcription factors and pathways closely related with ESCC were linked by our method. STAT1 also arose as a hub node in our transcriptome network, along with some transcription factors like CCNB1, TAP1, RARG and IFITM1 proven to be related with ESCC by previous studies. In conclusion, our regulation network provided information on important genes which might be useful in investigating the complex interacting mechanisms underlying the disease.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.8
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• pp.1088-1094
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• 2021

This paper proposes a partial BMA (Broadcasting Multiple Access) network structure and D-ARP (Distributed Address Resolution Protocol) method in order to support full mesh routing function in the DAMA (Demand Assigned Multiple Access)-based MF-TDMA (Multi Frequency-Time Division Multiple Access) satellite system. The partial BMA network enables legacy router devices and routing protocols to be adopted in the satellite communication system, and decreases the amount of routing protocol overhead. In addition, we introduce the D-ARP method that help a spoke satellite node acquiring the MAC (Media Access Control) address from remote satellite nodes in none BMA satellite network. The D-ARP method provides the MAC address of remote nodes to each other nodes through the broadcasting-enabled satellite channel. And we lastly evaluate and analysis the network performance of the proposed approach.

• Journal of Microbiology and Biotechnology
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• v.32 no.3
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• pp.365-377
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• 2022

Mammalian target of rapamycin (mTOR) is a serine-threonine kinase member of the cellular phosphatidylinositol 3-kinase (PI3K) pathway, which is involved in multiple biological functions by transcriptional and translational control. mTOR is a downstream mediator in the PI3K/Akt signaling pathway and plays a critical role in cell survival. In cancer, this pathway can be activated by membrane receptors, including the HER (or ErbB) family of growth factor receptors, the insulin-like growth factor receptor, and the estrogen receptor. In the present work, we congregated an electronic network of mTORC1 built on an assembly of data using natural language processing, consisting of 470 edges (activations/interactions and/or inhibitions) and 206 nodes representing genes/proteins, using the Cytoscape 3.6.0 editor and its plugins for analysis. The experimental design included the extraction of gene expression data related to five distinct types of cancers, namely, pancreatic ductal adenocarcinoma, hepatic cirrhosis, cervical cancer, glioblastoma, and anaplastic thyroid cancer from Gene Expression Omnibus (NCBI GEO) followed by pre-processing and normalization of the data using R & Bioconductor. ExprEssence plugin was used for network condensation to identify differentially expressed genes across the gene expression samples. Gene Ontology (GO) analysis was performed to find out the over-represented GO terms in the network. In addition, pathway enrichment and functional module analysis of the protein-protein interaction (PPI) network were also conducted. Our results indicated NOTCH1, NOTCH3, FLCN, SOD1, SOD2, NF1, and TLR4 as upregulated proteins in different cancer types highlighting their role in cancer progression. The MCODE analysis identified gene clusters for each cancer type with MYC, PCNA, PARP1, IDH1, FGF10, PTEN, and CCND1 as hub genes with high connectivity. MYC for cervical cancer, IDH1 for hepatic cirrhosis, MGMT for glioblastoma and CCND1 for anaplastic thyroid cancer were identified as genes with prognostic importance using survival analysis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1224-1248
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• 2022

In various sensor network applications, such as climate observation organizations, sensor nodes need to collect information from time to time and pass it on to the recipient of information through multiple bounces. According to field tests, this information corresponds to most of the energy use of the sensor hub. Decreasing the measurement of information transmission in sensor networks becomes an important issue.Compression sensing (CS) can reduce the amount of information delivered to the network and reduce traffic load. However, the total number of classification of information delivered using pure CS is still enormous. The hybrid technique for utilizing CS was proposed to diminish the quantity of transmissions in sensor networks.Further the energy productivity is a test task for the sensor nodes. However, in previous studies, a clustering approach using hybrid CS for a sensor network and an explanatory model was used to investigate the relationship between beam size and number of transmissions of hybrid CS technology. It uses efficient data integration techniques for large networks, but leads to clone attacks or attacks. Here, a new algorithm called SBEA (Snowball Endurance Algorithm) was proposed and tested with a bow. Thus, you can extend the battery life of your WSN by running effective copy detection. Often, multiple nodes, called observers, are selected to verify the reliability of the nodes within the network. Personal data from the source centre (e.g. personality and geographical data) is provided to the observer at the optional witness stage. The trust and reputation system is used to find the reliability of data aggregation across the cluster head and cluster nodes. It is also possible to obtain a mechanism to perform sleep and standby procedures to improve the life of the sensor node. The sniffers have been implemented to monitor the energy of the sensor nodes periodically in the sink. The proposed algorithm SBEA (Snowball Endurance Algorithm) is a combination of ERCD protocol and a combined mobility and routing algorithm that can identify the cluster head and adjacent cluster head nodes.This algorithm is used to yield the network life time and the performance of the sensor nodes can be increased.

• Journal of Apiculture
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• v.34 no.3
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• pp.197-206
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• 2019

Pollination is an important ecosystem service involved in plant breeding and reproduction. This study analyzed the pollination network, which is the interaction between flowering plants and flower-visiting insects in the agricultural landscape. Flower-visiting insects from blossoms of flowering crops and surrounding plants were quantitatively surveyed during summer time. The pollinator species and abundance on each flowering plant were analyzed. A total of 2,381 interactions were indentified with 154 pollinators on 30 species of plants. Species richness of the pollinators was highest in Coleoptera (34%) followed by Hymenoptera (28%), Diptera (28%) and Lepidoptera (10%). Apis mellifera dominated (50%) followed by Calliphora vomitoria (5.3%) and Xylocopa appendiculata among pollinators, and remaining wild pollinators provided complex interaction. Among plants, Platycodon grandiflorum, Perilla frutescen and Fagopyrum esculentum harbored most pollinators and showed highest interaction frequencies. In the modular analysis, Apis mellifera was located as a hub-species which connect the interaction of others, implying most important role in the network. This results provide the basic information on the pollinator species associated with each crop and pollinator habitat in which plant provide the nectar, pollen and habitat resources for wild pollinators.

• The Journal of the Korea Contents Association
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• v.14 no.9
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• pp.529-537
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• 2014

To establish a foundation to objectively interpret Chosun history, we construct people network of the Chosun dynasty. The network shows scale free network properties as if most social networks do. The people network is composed of 1,379 nodes and 3,874 links and its diameter is 14. To analysis of the network dynamics, whole network that is composed of 27 king networks were constructed by adding the first king, Taejo network to the second king, Jeongjong network and then continuously adding the next king networks. Interestingly, betweenness and closeness centralities were gradually decreased but stress centrality was drastically increased. These results indicate that information flow is gradually slowing and hub node position is more centrally oriented as growing the network. To elucidate key persons from the network, k-core and MCODE algorithms that can extract core or module structures from whole network were employed. It is a possible to obtain new insight and hidden information by analyzing network dynamics. Due to lack of the dynamic interacting data, there is a limit for network dynamic research. In spite of using concise data, this research provides us a possibility that annals of the Chosun dynasty are very useful historical data for analyzing network dynamics.

• Journal of Korean Society of Transportation
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• v.32 no.2
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• pp.162-169
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• 2014

This study dealt with the airport network applying the Structural Equivalence which has used in the field of social science network. It analyzed the size of aviation market and trade exchanges. The results between blocks through the Convergence of Iteration Correlation are as follows; Block 1 (major hub airport) and Block 5 (Australian and New Zealand airports) have a strong relationship between other blocks. Block 3 (CIS region) and Block 7 (Malaysia and Indonesia) have been indicated as relatively low degree. The structural equivalence analysis can be grouped as a small number of blocks with large and complex networks and also presented a significant result according to the nature of the relationship between aviation market and the level of trade exchanges.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.7
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• pp.1548-1554
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• 2005

e-Trade could improve marine logistic industry of our country to be convenient and efficient. However, in view of management, technical problems of networks have been revealed due to rapid increase of communications including electronic data. So, in order for Korea to be a leading country in east-northern Asia and a center for marine logistic information, control methods of networks should be employed effectively among information technology needed for e-Trade. Our objective to this research is focused as follows; Firstly, we investigate each part of e-Trade network and technical problems of communication networks. Secondly, we present an efficient control method of e-Trade network handling a large amount of network traffic. In this research, we try to provide an analytic foundation to practitioners rather than to present a direction to develop a new technology of communication networks.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.13
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• pp.5493-5498
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• 2015

Due to the lack of nationwide population-based cancer registration, the total cancer prevalence in Iran is unknown. Our previous work in which we used a basic network scale-up (NSU) method, failed to provide plausible estimates of total cancer prevalence in Kerman. The aim of the present study was to estimate total and partial prevalence of cancer in southeastern Iran using an adapted version of the generalized network scale-up method. A survey was conducted in 2014 using multi-stage cluster sampling. A total of 1995 face-to-face gender-matched interviews were performed based on an adapted version of the NSU questionnaire. Interviewees were asked about their family cancer history. Total and partial prevalence were estimated using a generalized NSU estimator. The Monte Carlo method was adopted for the estimation of upper/lower bounds of the uncertainty range of point estimates. One-yr, 2-3 yr, and 4-5 yr prevalence (per 100,000 people) was respectively estimated at 78 (95%CI, 66, 90), 128 (95%CI, 118, 147), and 59 (95%CI, 49, 70) for women, and 48 (95%CI, 38, 58), 78 (95%CI, 66, 91), and 42 (95%CI, 32, 52) for men. The 5-yr prevalence of all cancers was estimated at 0.18 percent for men, and 0.27 percent for women. This study showed that the generalized familial network scale-up method is capable of estimating cancer prevalence, with acceptable precision.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.8
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• pp.3273-3277
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• 2015

Network scale up (NSU) is a novel approach to estimate parameters in hard to reach populations through asking people the number of individuals they know in their active social network. Although the method have been used in hidden populations, advantages of NSU indicate that exploration of applicability to disease like cancer might be feasible. The aim of this study was to assess the application of NSU to estimate the size of the population of breast, ovarian/cervical, prostate, and bladder cancers in the South-east of Iran. A total of 3,052 (99% response rate) Kermanian people were interviewed in 2012-2013. Based on NSU, participants were asked about if they know any people on their social network who suffered from breast, ovarian/cervical, prostate, and bladder cancers, if yes, they should enumerate them. A total of 1,650 persons living with four types of cancers (breast, ovary/cervix, prostate, and bladder) were identified by the respondents. Totally, the prevalence of people living with the four types of cancers was 228.4 per 100,000 Kermanian inhabitants. The most prevalent cancer was breast cancer, at 168.9 per 100,000, followed by prostate cancer with 116.9, ovarian/cervical cancer with 99.8, and bladder cancer with 36.3 per 100000 Kerman city population. NSU values provide a usable but not very precise way of estimating the size of subpopulations in the context of the four major cancers (breast, ovary/cervix, prostate, and bladder).