• Fisheries and Aquatic Sciences
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• v.26 no.9
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• pp.569-581
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• 2023

The morphology and genetic identification of Rasbora lateristriata and Rasbora argyrotaenia between cultivated and wild populations has never been reported. This study compares morphology and cytochrome c oxidase (COI) genes between farmed and wild stock Rasbora spp. in Java and Sumatra island, Indonesia. We analyzed the truss network measurement (TNM) characters of 80 fish using discriminant function analysis statistical tests. DNA was extracted from muscle tissue of 24 fish specimens, which was then followed by polymerase chain reaction, sequencing, phylogenetic analysis, fixation index analysis, and statistical analysis of haplotype networks. Basic Local Alignment Search Tool analysis validated the following species: R. lateristriata and R. argyrotaenia from farming (Jogjakarta); Rasbora agryotaenia (Purworejo), R. lateristriata (Purworejo and Malang), Rasbora dusonensis (Palembang), and Rasbora einthovenii (Riau) from natural resources. Based on TNM characters, Rasbora spp. were divided into four groups, referring to four distinct characters in the middle of the body. The phylogenetic tree is divided into five clades. The genetic distance between R. argyrotaenia (Jogjakarta) and R. lateristriata (Malang) populations (0.66) was significantly different (p < 0.05). R. lateristriata (Purworejo) has the highest nucleotide diversity (0.43). R. argyrotaenia from Jogjakarta and Purworejo shared the same haplotype. The pattern of gene flow among them results from the two populations' close geographic proximity and environmental effects. R. argyrotaenia had low genetic diversity, therefore, increasing heterozygosity in cultivated populations is necessary to avoid inbreeding. Otherwise, R. lateristriata (Purworejo) had a greater gene variety that could be used to develop breeding. In conclusion, the middle body parts are a distinguishing morphometric character of Rasbora spp., and the COI gene is more heterozygous in the wild population than in farmed fish, therefore, enrichment of genetic variation is required for sustainable Rasbora fish farming.

• Journal of Information Processing Systems
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• v.12 no.1
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• pp.57-72
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• 2016

To provide effective communication in the wireless mesh network (WMN), several algorithms have been proposed. Since the possibilities of numerous failures always exist during communication, resiliency has been proven to be an important aspect for WMN to recover from these failures. In general, resiliency is the diligence of the reliability and availability in network. Several types of resiliency based routing algorithms have been proposed (i.e., Resilient Multicast, ROMER, etc.). Resilient Multicast establishes a two-node disjoint path and ROMER uses a credit-based approach to provide resiliency in the network. However, these proposed approaches have some disadvantages in terms of network throughput and network congestion. Previously, the buffer based routing (BBR) approach has been proposed to overcome these disadvantages. We proved earlier that BBR is more efficient in regards to w.r.t throughput, network performance, and reliability. In this paper, we consider the node/link failure issues and analogous performance of BBR. For these items we have proposed a resilient packet transmission (RPT) algorithm as a remedy for BBR during these types of failures. We also share the comparative performance analysis of previous approaches as compared to our proposed approach. Network throughput, network congestion, and resiliency against node/link failure are particular performance metrics that are examined over different sized WMNs.

• Asian Journal of Atmospheric Environment
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• v.10 no.2
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• pp.67-79
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• 2016

The forecasting of air pollution is an important and popular topic in environmental engineering. Due to health impacts caused by unacceptable particulate matter (PM) levels, it has become one of the greatest concerns in metropolitan cities like Karaj City in Iran. In this study, the concentration of $PM_{2.5}$ was predicted by applying a multilayer percepteron (MLP) neural network, a radial basis function (RBF) neural network and a Markov chain model. Two months of hourly data including temperature, NO, $NO_2$, $NO_x$, CO, $SO_2$ and $PM_{10}$ were used as inputs to the artificial neural networks. From 1,488 data, 1,300 of data was used to train the models and the rest of the data were applied to test the models. The results of using artificial neural networks indicated that the models performed well in predicting $PM_{2.5}$ concentrations. The application of a Markov chain described the probable occurrences of unhealthy hours. The MLP neural network with two hidden layers including 19 neurons in the first layer and 16 neurons in the second layer provided the best results. The coefficient of determination ($R^2$), Index of Agreement (IA) and Efficiency (E) between the observed and the predicted data using an MLP neural network were 0.92, 0.93 and 0.981, respectively. In the MLP neural network, the MBE was 0.0546 which indicates the adequacy of the model. In the RBF neural network, increasing the number of neurons to 1,488 caused the RMSE to decline from 7.88 to 0.00 and caused $R^2$ to reach 0.93. In the Markov chain model the absolute error was 0.014 which indicated an acceptable accuracy and precision. We concluded the probability of occurrence state duration and transition of $PM_{2.5}$ pollution is predictable using a Markov chain method.

• Korean Chemical Engineering Research
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• v.62 no.3
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• pp.214-224
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• 2024

Valves play an essential role in a chemical plant such as regulating fluid flow and pressure. Therefore, optimal selection of the valve size and type is essential task. Valve size and type have been selected based on theoretical formulas about calculating valve sizing coefficient (Cv). However, this approach has limitations such as requiring expert knowledge and consuming substantial time and costs. Herein, this study developed a model for predicting valve sizes and types using machine learning. We developed models using four algorithms: ANN, Random Forest, XGBoost, and Catboost and model performances were evaluated using NRMSE & R² score for size prediction and F1 score for type prediction. Additionally, a case study was conducted to explore the impact of phases on valve selection, using four datasets: total fluids, liquids, gases, and steam. As a result of the study, for valve size prediction, total fluid, liquid, and gas dataset demonstrated the best performance with Catboost (Based on R², total: 0.99216, liquid: 0.98602, gas: 0.99300. Based on NRMSE, total: 0.04072, liquid: 0.04886, gas: 0.03619) and steam dataset showed the best performance with RandomForest (R²: 0.99028, NRMSE: 0.03493). For valve type prediction, Catboost outperformed all datasets with the highest F1 scores (total: 0.95766, liquids: 0.96264, gases: 0.95770, steam: 1.0000). In Engineering Procurement Construction industry, the proposed fluid-specific machine learning-based model is expected to guide the selection of suitable valves based on given process conditions and facilitate faster decision-making.

• Preventive Nutrition and Food Science
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• v.2 no.4
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• pp.281-284
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• 1997

Heat-induced gelation is an important functional property of whey proteins. Preheating of calcium reduced whey was reported to increase gel strength. 5% whey-protein solutions were preheated at pH7 and at various temperatures(60~8$0^{\circ}C$) for 15 minutes. The amount of soluble aggregates and denaturation enthalpy of preheated whey proteins were measured. Preheating temperature was negatively correlated with denaturation enthalpy($R^2$=0.857, P=0.08) and positive with the amount of soluble aggregates($R^2$=0.921, P=0.002). Denaturation enthalpy was negatively correlated with gel strength($R^2$=0.93, P=0.002). Soluble aggregates and gel strength were positively correlated($R^2$=0.972, P=0.0003). The formation of three dimensional gel network requires controlled protein denaturation and aggregation. Since preheating leads to the partial denaturation of proteins and the formation of soluble aggregates, preheated whey proteins have a higher gel strength than non-preheated one.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.66-69
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• 2011

Many international organizations build a global communications network called the GMDSS by close cooperation, and ITU-R, IMO and IEC apply it for the modernization of the international marine radiocommunication system, but a modernization study of the GMDSS to reflect such a technique by the rapidly development of the wireless communication technology recently progresses. Such effort was submitted for adoption with WRC-12 held in 2012. This paper analyzed standardization trends for marine radiocommunication modernization discussed around ITU-R recently and analyzed research activities for frequency allocation for new technical introduction and described it.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1213-1222
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• 2021

This study is a digitalization study based on ICT technology as part of the development of innovative technologies in the new energy industry as a 2050 carbon-neutral policy. It is the development of an oneM2M-based IoT server platform that can be integrated and managed in conjunction with the external interface of each energy facility. It analyzes KEPCO's e-IoT standard specifications through the Power Research Institute's 'SPIN' and develops representative standards, LWM2M and oneM gateway platforms. OneM2M secures and analyzes the recently announced standard for Release 2 instead of the existing Release 1. In addition, the e-IoT standard oneM2M platform is developed based on R2. In addition, it selects the specifications for e-IoT gateway devices that can sufficiently implement KEPCO's e-IoT standards. In addition, a technology and system for developing a high-performance gateway device that considers future scalability were proposed.

• Journal of Information Management
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• v.31 no.4
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• pp.71-87
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• 2000

Recently, researches of mobile agent systems have done actively to enhance usability of heterogenenous environment linked via network and to solve problems of existing distributed-object computing. Though these research and development many studies have done to be applicated to many areas that are existing distributed systems as well as E-commerce, network maintenance, and information retrieval etc. This paper reviews some related issues to agent studies, comprehensive studies to enhance telecommunication functionality among agents, and future and application fields of agent.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.8B
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• pp.620-629
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• 2012

This paper proposes packet aggregation scheme for considering energy consumption of mobile devices on guaranteeing quality of voice. To our purpose, we analyze VoIP service on wireless multi-hop channel in terms of delay, packet loss and energy consumption when packet aggregation scheme is applied to VoIP service. Moreover, we induce a cost function with considering of tradeoff relation between quality of voice and energy consumption.

• Genomics & Informatics
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• v.20 no.1
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• pp.5.1-5.10
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• 2022

Non-syndromic hearing loss (NSHL) is a common hereditary disorder. Both clinical and genetic heterogeneity has created many obstacles to understanding the causes of NSHL. The present study has attempted to ravel the genetic aetiology in NSHL progression and to screen out potential target genes using computational approaches. The reported NSHL target genes (2009-2020) have been studied by analyzing different biochemical and signaling pathways, interpretation of their functional association network, and discovery of important regulatory interactions with three previously established miRNAs in the human inner ear as well as in NSHL such as miR-183, miR-182, and miR-96. This study has identified SMAD4 and SNAI2 as the most putative target genes of NSHL. But pathogenic and deleterious non-synonymous single nucleotide polymorphisms discovered within SMAD4 is anticipated to have an impact on NSHL progression. Additionally, the identified deleterious variants in the functional domains of SMAD4 added a supportive clue for further study. Thus, the identified deleterious variant i.e., rs377767367 (G491V) in SMAD4 needs further clinical validation. The present outcomes would provide insights into the genetics of NSHL progression.