• Nuclear Engineering and Technology
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• 제54권9호
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• pp.3299-3309
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• 2022

Nuclear energy has the potential to play an influential role in energy transition efforts than is now anticipated by many countries. Realizing sustainable human development and reducing global climate crises will become more difficult without significantly increasing nuclear power. This paper aims to probe the role of nuclear energy, external debt, and financial globalization in sustaining human development and environmental conditions simultaneously in BRICS (Brazil, Russia, India, China, and South Africa) countries. This study applied a battery of second-generation estimation approaches over the period from 1990 to 2019. These methods are useful and robust to cross-countries dependencies, slope heterogeneity, parameters endogeneity, and serial correlation that are ignored in conventional approaches to generate more comprehensive and reliable estimates. The empirical findings indicate that nuclear energy and financial globalization contribute to human development, whereas external debt inhibits it. Similarly, financial globalization accelerates ecological deterioration, but nuclear energy and external debt promote environmental sustainability. Moreover, the study reveals bidirectional feedback causalities between human development, carbon emissions and nuclear energy consumption. The study offers useful policy guidance on accomplishing sustainable and inclusive development in BRICS countries.

• International Journal of Computer Science & Network Security
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• 제21권7호
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• pp.331-340
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• 2021

The Internet of Things (IoT) is a rapidly growing physical network that depends on objects, vehicles, sensors, and smart devices. IoT has recently become an important research topic as it autonomously acquires, integrates, communicates, and shares data directly across each other. The centralized architecture of IoT makes it complex to concurrently access control them and presents a new set of technological limitations when trying to manage them globally. This paper proposes a new decentralized access control architecture to manage IoT devices using blockchain, that proposes a solution to concurrency management problems and enhances resource locking to reduce the transaction conflict and avoids deadlock problems. In addition, the proposed algorithm improves performance using a fully distributed access control system for IoT based on blockchain technology. Finally, a performance comparison is provided between the proposed solution and the existing access management solutions in IoT. Deadlock detection is evaluated with the latency of requesting in order to examine various configurations of our solution for increasing scalability. The main goal of the proposed solution is concurrency problem avoidance in decentralized access control management for IoT devices.

• The Journal of Asian Finance, Economics and Business
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• 제8권9호
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• pp.11-22
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• 2021

This study investigates the long-run relationship between the de jure economic, political, and social globalization and foreign direct investments in the Gulf Cooperation Council (GCC) to establish whether policies that foster trade and investment relations among geographical entities can help revive the GCC countries from the prevailing economic debacles of the COVID-19 pandemic. This study is driven by the GCC's quest to fully overcome the economic challenges occasioned by the outbreak of the global pandemic and position itself as the most potent regional economic bloc in the Middle East and North Africa (MENA) region. The study employs the panel data of the six GCC countries of Bahrain, United Arab Emirates, Kuwait, Qatar, Oman, and Saudi Arabia from 1971 to 2017. The findings of the panel fully modified ordinary least square regression estimation show that the de jure economic and social globalization have a significant positive impact on the region's foreign direct investment inflows. The impact of the de jure political globalization on foreign direct investment is statistically significant but negatively signed. Based on the preceding findings, we offer some holistic policy recommendations to the GCC region as recipes for timely recovery from the economic impact of COVID-19 and beyond.

• International Journal of Computer Science & Network Security
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• 제22권3호
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• pp.61-66
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• 2022

Object classification is one of the main fields in neural networks and has attracted the interest of many researchers. Although there have been vast advancements in this area, still there are many challenges that are faced even in the current era due to its inefficiency in handling large data, linguistic and dimensional complexities. Powerful hardware and software approaches in Neural Networks such as Deep Neural Networks present efficient mechanisms and contribute a lot to the field of object recognition as well as to handle time series classification. Due to the high rate of accuracy in terms of prediction rate, a neural network is often preferred in applications that require identification, segmentation, and detection based on features. Neural networks self-learning ability has revolutionized computing power and has its application in numerous fields such as powering unmanned self-driving vehicles, speech recognition, etc. In this paper, the experiment is conducted to implement a neural approach to identify numbers in different formats without human intervention. Measures are taken to improve the efficiency of the machines to classify and identify numbers. Experimental results show the importance of having training sets to achieve better recognition accuracy.

• ETRI Journal
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• 제44권6호
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• pp.991-1003
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• 2022

Industrial control systems (ICSs) used to be operated in closed networks, that is, separated physically from the Internet and corporate networks, and independent protocols were used for each manufacturer. Thus, their operation was relatively safe from cyberattacks. However, with advances in recent technologies, such as big data and internet of things, companies have been trying to use data generated from the ICS environment to improve production yield and minimize process downtime. Thus, ICSs are being connected to the internet or corporate networks. These changes have increased the frequency of attacks on ICSs. Despite this increased cybersecurity risk, research on ICS security remains insufficient. In this paper, we analyze threats in detail using STRIDE threat analysis modeling and DREAD evaluation for distributed control systems, a type of ICSs, based on our work experience as cybersecurity specialists at a refinery. Furthermore, we verify the validity of threats identified using STRIDE through case studies of major ICS cybersecurity incidents: Stuxnet, BlackEnergy 3, and Triton. Finally, we present countermeasures and strategies to improve risk assessment of identified threats.

• 셀메드
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• 제12권1호
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• pp.5.1-5.8
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• 2022

Ābzan(sitz bath or hydration therapy) is one of the important and widely practised methods of regimenal therapy used for local evacuation or diversion of morbid humours described for various diseases in Unani system of medicine. Itis a type of bath in which hips and buttocks are immersed in water, either plain or medicated for therapeutic effects. Thus, it serves as an important and effective external mode of treatment. It has been successfully practised by Greeko-Arab physicians in the management of almost all types of gynaecological disorders like genital prolapse, leucorrhoea, pruritus vulvae, menstrual disorders, infertility, pelvic inflammatory diseases etc, but its efficacy has been proved in very few gynaecological diseases only. Hence, there is a need for systemic review to investigate the effectiveness of sitz bath in gynaecological disorders to generate scientific based evidence for the clinician as well as for common public. Based on the available literature, this review article suggests that the sitz bath has a scientific evidence-based effect in treating gynaecological diseases.

• Computers and Concrete
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• 제29권 5호
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• pp.347-360
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• 2022

Fiber-reinforced cementitious composites (FRCC) have emerged as a response to the calls for strong, ductile and sustainable concrete mixes. FRCC has shown outstanding mechanical properties and ductility where special fibres are used in the mixes to give it the strength and the ability to exhibit strain hardening. With the possibility of designing the FRCC mixes to include sustainable constituents and by-products materials such as fly ash, FRCC started to emerge as a green alternative as well. To be able to design mixes that achieve these conflicting properties in concrete, there is a need to understand the composition effect on FRCC and optimize these compositions. Therefore, this paper aims to investigate the influence of FRCC compositions on the properties of fresh and hardened of FRCC and then to optimize these mix compositions using factorial design approach. Three factors, water-to-binder ratio (w/b), mineral admixtures (total of fly ash and metakaolin by cement content (MAR)), and metakaolin content (MK), were investigated to determine their effects on the properties of fresh and hardened FRCC. The results show the importance of combining both FA and MK in obtaining a satisfactory fresh and mechanical properties of FRCC. Models were suggested to elucidate the role of the studied factors and a method for optimization was proposed.

• 국제학술발표논문집
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• The 8th International Conference on Construction Engineering and Project Management
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• pp.50-59
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• 2020

The 21st century is witnessing a rapid growth of tall buildings in urban centers globally to create more urban space for an anticipated urban population. Tall buildings, however suffer from incessant delays and sometimes total abandonment. Consequently, this study investigated and ranked the causes of delay in tall building projects, while focusing on the Gulf Cooperation Council (GCC) countries. Initially, 36 common delay causes investigated globally were categorized into 9 groups, and then further ranked utilizing the Relative Importance Index (RII) through a questionnaire survey. Tall building professionals in the GCC countries (Saudi Arabia, United Arab Emirates, Bahrain, Kuwait, Oman and Qatar) were contacted. The respondents' categories include Consultants, Contractors, and Clients' Representatives/Facility Managers. The results reveal that the top three causes include "client's cash flow problems/delays in contractor's payment", "contractor's financial difficulties", and "poor site organization and coordination between various parties". The findings from this study could help construction professionals develop guidelines and controls for delay mitigation, as well as support them in risk-based decision making in the planning of tall building projects.

• 한국수소및신에너지학회논문집
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• 제35권1호
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• pp.1-13
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• 2024

Hydrogen is emerging as an essential material for carbon neutrality. In particular, Korea needs 22.9 million tons of imported clean hydrogen by 2050 to achieve carbon neutrality. However, a large amount of carbon is emitted during the import process, and market regulations are being discussed. This research estimates the carbon emissions of importing green hydrogen from Vietnam, Australia, and the United Arab Emirates to Korea, and calculates imported green hydrogen prices under carbon emission market regulations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권1호
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• pp.105-125
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• 2024

Gliomas are the most common malignant brain tumor and cause the most deaths. Manual brain tumor segmentation is expensive, time-consuming, error-prone, and dependent on the radiologist's expertise and experience. Manual brain tumor segmentation outcomes by different radiologists for the same patient may differ. Thus, more robust, and dependable methods are needed. Medical imaging researchers produced numerous semi-automatic and fully automatic brain tumor segmentation algorithms using ML pipelines and accurate (handcrafted feature-based, etc.) or data-driven strategies. Current methods use CNN or handmade features such symmetry analysis, alignment-based features analysis, or textural qualities. CNN approaches provide unsupervised features, while manual features model domain knowledge. Cascaded algorithms may outperform feature-based or data-driven like CNN methods. A revolutionary cascaded strategy is presented that intelligently supplies CNN with past information from handmade feature-based ML algorithms. Each patient receives manual ground truth and four MRI modalities (T1, T1c, T2, and FLAIR). Handcrafted characteristics and deep learning are used to segment brain tumors in a Global Convolutional Neural Network (GCNN). The proposed GCNN architecture with two parallel CNNs, CSPathways CNN (CSPCNN) and MRI Pathways CNN (MRIPCNN), segmented BraTS brain tumors with high accuracy. The proposed model achieved a Dice score of 87% higher than the state of the art. This research could improve brain tumor segmentation, helping clinicians diagnose and treat patients.