• Title/Summary/Keyword: Network Segregation

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Rationalization of Network Segregation for Continuity of Financial Services Following COVID-19

  • Choi, Manyong;Kwak, Jin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.11
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    • pp.4163-4183
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    • 2021
  • As measures for protecting users and ensuring security of electronic financial transactions, such as online banking, financial institutions in South Korea have implemented network segregation policies. However, a revision of such domain-centered standardized network segregation policies has been increasingly requested because of: 1) increased demand for remote work due to changes resulting from COVID-19 pandemic; and 2) the difficulty of applying new technologies of fintech companies based on information and communications technologies (ICTs) such as cloud services. Therefore, in this study, problems of the remote work environment arising from the network segregation policy currently applied to the financial sector in South Korea and those from the application of new ICTs such as fintech technology have been investigated. In addition, internal network protection policies of foreign financial sectors, such as those of the United States, United Kingdom, European Union, and Russia, and internal network protection policies of non-financial sectors, such as control systems, have been analyzed. As measures for the effective improvement of the current network segregation policy, we propose a policy change from domain-based to data-centric network segregation. Furthermore, to resolve threats of hacking at remote work, recently emerging as a global problem due to COVID-19 pandemic, a standard model for remote work system development applicable to financial companies and a reinforced terminal security model are presented, and an alternative control method applicable when network segregation is not applied is proposed.

Functional Requirements to Increase Acceptance of M-Learning Applications among University Students in the Kingdom of Saudi Arabia (KSA)

  • Badwelan, Alaa;Bahaddad, Adel A.
    • International Journal of Computer Science & Network Security
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    • v.21 no.2
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    • pp.21-39
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    • 2021
  • The acceptance of smartphone applications in the learning field is one of the most significant challenges for higher education institutions in Saudi Arabia. These institutions serve large and varied sectors of society and have a tremendous impact on the knowledge gained by student segments at various ages. M-learning is of great importance because it provides access to learning through a wide range of mobile networks and allows students to learn at any time and in any place. There is a lack of quality requirements for M-learning applications in Saudi societies partly because of mandates for high levels of privacy and gender segregation in education (Garg, 2013; Sarrab et al., 2014). According to the Saudi Arabian education ministry policy, gender segregation in education reflects the country's religious and traditional values (Ministry of Education, 2013, No. 155). The opportunity of many applications would help the Saudi target audience more easily accept M-learning applications and expand their knowledge while maintaining government policy related to religious values and gender segregation in the educational environment. In addition, students can share information through the online framework without breaking religious restrictions. This study uses a quantitative perspective to focus on defining the technical aspects and learning requirements for distributing knowledge among students within the digital environment. Additionally, the framework of the unified theory of acceptance and use of technology (UTAUT) is used to modify new constructs, called application quality requirements, that consist of quality requirements for systems, information, and interfaces.

How Chromosome Mis-Segregation Leads to Cancer: Lessons from BubR1 Mouse Models

  • Lee, Hyunsook
    • Molecules and Cells
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    • v.37 no.10
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    • pp.713-718
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    • 2014
  • Alteration in chromosome numbers and structures instigate and foster massive genetic instability. As Boveri has seen a hundred years ago (Boveri, 1914; 2008), aneuploidy is hall-mark of many cancers. However, whether aneuploidy is the cause or the result of cancer is still at debate. The molecular mechanism behind aneuploidy includes the chromosome mis-segregation in mitosis by the compromise of spindle assembly checkpoint (SAC). SAC is an elaborate network of proteins, which monitor that all chromosomes are bipolarly attached with the spindles. Therefore, the weakening of the SAC is the major reason for chromosome number instability, while complete compromise of SAC results in detrimental death, exemplified in natural abortion in embryonic stage. Here, I will review on the recent progress on the understanding of chromosome missegregation and cancer, based on the comparison of different mouse models of BubR1, the core component of SAC.

The Effect of Cognitive Impairment on the Association Between Social Network Properties and Mortality Among Older Korean Adults

  • Eunji Kim;Kiho Sung;Chang Oh Kim;Yoosik Youm;Hyeon Chang Kim
    • Journal of Preventive Medicine and Public Health
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    • v.56 no.1
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    • pp.31-40
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    • 2023
  • Objectives: This study investigated the effect of cognitive impairment on the association between social network properties and mortality among older Korean adults. Methods: This study used data from the Korean Social Life, Health, and Aging Project. It obtained 814 older adults' complete network maps across an entire village in 2011-2012. Participants' deaths until December 31, 2020 were confirmed by cause-of-death statistics. A Cox proportional hazards model was used to assess the risks of poor social network properties (low degree centrality, perceived loneliness, social non-participation, group-level segregation, and lack of support) on mortality according to cognitive impairment. Results: In total, 675 participants (5510.4 person-years) were analyzed, excluding those with missing data and those whose deaths could not be verified. Along with cognitive impairment, all social network properties except loneliness were independently associated with mortality. When stratified by cognitive function, some variables indicating poor social relations had higher risks among older adults with cognitive impairment, with adjusted hazard ratios (HRs) of 2.12 (95% confidence interval [CI], 1.34 to 3.35) for social nonparticipation, 1.58 (95% CI, 0.94 to 2.65) for group-level segregation, and 3.44 (95% CI, 1.55 to 7.60) for lack of support. On the contrary, these effects were not observed among those with normal cognition, with adjusted HRs of 0.73 (95% CI, 0.31 to 1.71), 0.96 (95% CI, 0.42 to 2.21), and 0.95 (95% CI, 0.23 to 3.96), respectively. Conclusions: The effect of social network properties was more critical among the elderly with cognitive impairment. Older adults with poor cognitive function are particularly encouraged to participate in social activities to reduce the risk of mortality.

Self-rated Health and Global Network Position: Results From the Older Adult Population of a Korean Rural Village

  • Youm, Yoosik;Sung, Kiho
    • Annals of Geriatric Medicine and Research
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    • v.20 no.3
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    • pp.149-159
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    • 2016
  • Background: Since the mid-20th century, the ways in which social networks and older adults' health are related have been widely studied. However, few studies investigate the relationship between self-rated health and position in a complete social network of one entire Korean rural village. This study highlights use of a complete network in health studies. Methods: Using the Korean Social Life and Health Project, the population-based data of adults aged 60 or older and their spouses in one myeon in Ganghwa island (Ganghwa-gun, Incheon, Korea), Incheon, Korea (with a 95% response rate), this study built a $1,012{\times}1,012$ complete social network matrix of the village. The data were collected from 2011 to 2012, and 731 older adults were analyzed. The ordered logistic models to predict self-rated health allowed us to examine social factors from socio-demographic to individual community activities, ego-centered network characteristics, and positions in a complete network. Results: From the network data, 5 network components were identified. Even after controlling for all other factors, if a respondent belonged to a segregated component, the probability that he or she reported good health dropped substantially. Additionally, high in-degree centrality was connected to greater self-rated health. Conclusion: This finding highlights the importance of social position not only from the respondents' point of view but also from the entire village's perspective. Even if a respondent maintained a large social network, when all of those social ties belonged to a segregated group in the village, the respondent's health suffered from this segregation.

Amazon product recommendation system based on a modified convolutional neural network

  • Yarasu Madhavi Latha;B. Srinivasa Rao
    • ETRI Journal
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    • v.46 no.4
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    • pp.633-647
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    • 2024
  • In e-commerce platforms, sentiment analysis on an enormous number of user reviews efficiently enhances user satisfaction. In this article, an automated product recommendation system is developed based on machine and deep-learning models. In the initial step, the text data are acquired from the Amazon Product Reviews dataset, which includes 60 000 customer reviews with 14 806 neutral reviews, 19 567 negative reviews, and 25 627 positive reviews. Further, the text data denoising is carried out using techniques such as stop word removal, stemming, segregation, lemmatization, and tokenization. Removing stop-words (duplicate and inconsistent text) and other denoising techniques improves the classification performance and decreases the training time of the model. Next, vectorization is accomplished utilizing the term frequency-inverse document frequency technique, which converts denoised text to numerical vectors for faster code execution. The obtained feature vectors are given to the modified convolutional neural network model for sentiment analysis on e-commerce platforms. The empirical result shows that the proposed model obtained a mean accuracy of 97.40% on the APR dataset.

Sustainable controlled low-strength material: Plastic properties and strength optimization

  • Mohd Azrizal, Fauzi;Mohd Fadzil, Arshad;Noorsuhada Md, Nor;Ezliana, Ghazali
    • Computers and Concrete
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    • v.30 no.6
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    • pp.393-407
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    • 2022
  • Due to the enormous cement content, pozzolanic materials, and the use of different aggregates, sustainable controlled low-strength material (CLSM) has a higher material cost than conventional concrete and sustainable construction issues. However, by selecting appropriate materials and formulations, as well as cement and aggregate content, whitethorn costs can be reduced while having a positive environmental impact. This research explores the desire to optimize plastic properties and 28-day unconfined compressive strength (UCS) of CLSM containing powder content from unprocessed-fly ash (u-FA) and recycled fine aggregate (RFA). The mixtures' input parameters consist of water-to-cementitious material ratio (W/CM), fly ash-to-cementitious materials (FA/CM), and paste volume percentage (PV%), while flowability, bleeding, segregation index, and 28-day UCS were the desired responses. The central composite design (CCD) notion was used to produce twenty CLSM mixes and was experimentally validated using MATLAB by an Artificial Neural Network (ANN). Variance analysis (ANOVA) was used for the determination of statistical models. Results revealed that the plastic properties of CLSM improve with the FA/CM rise when the strength declines for 28 days-with an increase in FA/CM, the diameter of the flowability and bleeding decreased. Meanwhile, the u-FA's rise strengthens the CLSM's segregation resistance and raises its strength over 28 days. Using calcareous powder as a substitute for cement has a detrimental effect on bleeding, and 28-day UCS increases segregation resistance. The response surface method (RSM) can establish high correlations between responses and the constituent materials of sustainable CLSM, and the optimal values of variables can be measured to achieve the desired response properties.

A Study on Optimum Reheating Process of Automotive Aluminum Piston using Neural Network and the Taguchi Method in Semi-Solid forming (반용융 성헝에서의 다구찌 방법과 신경망을 이용한 자동차 알루미늄 피스톤의 최적 재가열 과정에 대한 연구)

  • 윤재민;김영호;박준홍;최재찬
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2000.11a
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    • pp.902-905
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    • 2000
  • As the manufacturing processes of automotive engine piston, gravity die-casting, squeeze casting, hot forging and powder forging process are generally used for the various specifications. As the semi-solid forming(SSF) is compared with conventional casting such as gravity die-casting and squeeze casting for the characteristics of its process, the product without inner defects such as gas porosity and segregation can be obtained and its microstructure is globular grain. In SSF process, the materials are heated up to the temperature between the solvus and liquidus line at which the materials exists in the form of liquid-solid mixture. In this time, Discussion is given about reheating process of row material and results are presented regarding accurate temperature and process variables controlling for right solid fractions.

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Towards the Acceptance of Functional Requirements in M-Learning Application for KSA University Students

  • Badwelan, Alaa;Bahaddad, Adel A.
    • International Journal of Computer Science & Network Security
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    • v.21 no.4
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    • pp.145-166
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    • 2021
  • M-learning is one of the most important modern learning environments in developed countries, especially in the context of the COVID-19 pandemic. According to the Ministry of Education policies in Saudi Arabia, gender segregation in education reflects the country's religious values, which are a part of the national policy. Thus, it will help many in the target audience to accept online learning more easily in Saudi society. The literature review indicates the importance to use the UTAUT conceptual framework to study the level of acceptance through adding a new construct to the model which is Mobile Application Quality. The study focuses on the end user's requirements to use M-learning applications. It is conducted with a qualitative method to find out the students' and companies' opinions who working in the M-learning field to determine the requirements for the development of M-learning applications that are compatible with the aspirations of conservative societies.

Sorting for Plastic Bottles Recycling using Machine Vision Methods

  • SanaSadat Mirahsani;Sasan Ghasemipour;AmirAbbas Motamedi
    • International Journal of Computer Science & Network Security
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    • v.24 no.6
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    • pp.89-98
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    • 2024
  • Due to the increase in population and consequently the increase in the production of plastic waste, recovery of this part of the waste is an undeniable necessity. On the other hand, the recycling of plastic waste, if it is placed in a systematic process and controlled, can be effective in creating jobs and maintaining environmental health. Waste collection in many large cities has become a major problem due to lack of proper planning with increasing waste from population accumulation and changing consumption patterns. Today, waste management is no longer limited to waste collection, but waste collection is one of the important areas of its management, i.e. training, segregation, collection, recycling and processing. In this study, a systematic method based on machine vision for sorting plastic bottles in different colors for recycling purposes will be proposed. In this method, image classification and segmentation techniques were presented to improve the performance of plastic bottle classification. Evaluation of the proposed method and comparison with previous works showed the proper performance of this method.