• ETRI Journal
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• v.41 no.3
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• pp.348-357
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• 2019

Fog radio access network (F-RAN) architectures provide markedly improved performance compared to conventional approaches. In this paper, an efficient genetic algorithm-based content distribution scheme is proposed that improves the throughput and reduces the transmission delay of a F-RAN. First, an F-RAN system model is presented that includes a certain number of randomly distributed fog access points (F-APs) that cache popular content from cloud and other sources. Second, the problem of efficient content distribution in F-RANs is described. Third, the details of the proposed optimal genetic algorithm-based content distribution scheme are presented. Finally, simulation results are presented that show the performance of the proposed algorithm rapidly approaches the optimal throughput. When compared with the performance of existing random and exhaustive algorithms, that of the proposed method is demonstrably superior.

• Communications for Statistical Applications and Methods
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• v.26 no.3
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• pp.273-293
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• 2019

We consider the problem of model selection in multiple linear regression with outliers and non-normal error distributions. In this article, the robust model selection criterion is proposed based on the robust estimation method with the least absolute deviation (LAD). The proposed criterion is shown to be consistent. We suggest proposed criterion based algorithms that are suitable for a large number of predictors in the model. These algorithms select only relevant predictor variables with probability one for large sample sizes. An exhaustive simulation study shows that the criterion performs well. However, the proposed criterion is applied to a real data set to examine its applicability. The simulation results show the proficiency of algorithms in the presence of outliers, non-normal distribution, and multicollinearity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.3219-3237
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• 2019

The Cloud Computing is growing rapidly in the current IT industry. Cloud computing has become a buzzword in relation to Grid & Utility computing. It provides on demand services to customers and customers will pay for what they get. Various "Cloud Service Provider" such as Microsoft Azure, Google Web Services etc. enables the users to access the cloud in cost effective manner. However, security, privacy and integrity of data is a major concern. In this paper various security challenges have been identified and the survey briefs the comprehensive overview of various security issues in cloud computing. The classification of security issues in cloud computing have been studied. In this paper we have discussed security challenges in cloud computing and also list recommended methods available for addressing them in the literature.

• Structural Engineering and Mechanics
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• v.70 no.3
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• pp.367-380
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• 2019

The paper concerns topology and geometry optimization of statically determinate beams with arbitrary number of supports. The optimization problem is treated as a bi-criteria one, with the objectives of minimizing the absolute maximum bending moment and the maximum deflection for a uniform gravity load. The problem is formulated and solved using the Pareto optimality concept and the lexicographic ordering of the objectives. The non-dominated sorting genetic algorithm NSGA-II and the local search method are used for the optimization in the Pareto sense, whereas the genetic algorithm and the exhaustive search method for the lexicographic optimization. Trade-offs between objectives are examined and sets of Pareto-optimal solutions are provided for different topologies. Lexicographically optimal beams are found assuming that the maximum moment is a more important criterion. Exact formulas for locations and values of the maximum deflection are given for all lexicographically optimal beams of any topology and any number of supports. Topologies with lexicographically optimal geometries are classified into equivalence classes, and specific features of these classes are discussed. A qualitative principle of the division of topologies equivalent in terms of the maximum moment into topologies better and worse in terms of the maximum deflection is found.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.176-179
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• 2022

In this paper, we consider a sectorized wireless powered sensor network (WPSN), wherein sensor nodes are clustered based on sectors and transmit data to the cluster head (CH) using energy harvested from a hybrid access point. We construct a system model for this sectorized WPSN and find optimal coordinates of CH that maximize the achievable transmission rate of sensing data. To obtain the optimal CH with low overhead, we perform an asymptotic geometric analysis (GA). Simulation results show that the proposed GA-based CH selection method is close to the optimal performance exhibited by exhaustive search with a low feedback overhead.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.1006-1027
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• 2022

In the crowdfunding market, various crowdfunding platforms can offer founders the possibilities to collect funding and launch someone's next campaign, project or events. Especially, healthcare crowdfunding is a field that is growing rapidly on health-related problems based on online platforms. One of the largest platforms, GoFundMe, has raised US$ 5 billion since 2010. Unfortunately, while providing crucial help to care for many people, it is also increasing risk of fraud. Using the largest platform of crowdfunding market, GoFundMe, we conduct an exhaustive search of detection on fraud from October 2016 to September 2019. Data sets are based on 6 main types of medical focused crowdfunding campaigns or events, such as cancer, in vitro fertilization (IVF), leukemia, health insurance, lymphoma and, surgery type. This study evaluated a detect of fraud process to identify fraud from non-fraud healthcare crowdfunding campaigns using various machine learning technics.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.1174-1192
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• 2021

With the assistance of non-orthogonal multiple access (NOMA), the spectrum efficiency and the number of users in cloud radio access network (CRAN) can be greatly improved. In this paper, the system performance of NOMA-assisted CRAN is investigated. Specially, the outage probability (OP) and ergodic sum rate (ESR), are derived for performance evaluation of the system, respectively. Based on this, by minimizing the OP of the system, a suboptimal power allocation (PA) scheme with closed-form PA coefficients is proposed. Numerical simulations validate the accuracy of the theoretical results, where the derived OP has more accuracy than the existing one. Moreover, the developed PA scheme has superior performance over the conventional fixed PA scheme but has smaller performance loss than the optimal PA scheme using the exhaustive search method.

• Earthquakes and Structures
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• v.23 no.2
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• pp.207-219
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• 2022

Seismic response control has always been a grave concern with the damage and collapse of many buildings during the past earthquakes. While there are several existing techniques like base isolation, viscous damper, moment-resisting beam-column connections, tuned mass damper, etc., many of these are succumbing to either of large displacement, near-fault, and long-period earthquakes. Keeping this viewpoint, extensive research on the application of smart materials for seismic response control of buildings was attempted during the last decade. Shape Memory Alloy (SMA) with its unique properties of superelasticity and shape memory effect is one of the smart materials used for seismic control of buildings. In this paper, an exhaustive review has been compiled on the seismic control applications of SMA in buildings. Unique properties of SMA are discussed in detail and different phases of SMA along with crystal characteristics are illustrated. Consequently, various seismic control applications of SMA are discussed in terms of performance and compared with prevalent base isolators, bracings, beam-column connections, and tuned mass damper systems.

• International Journal of Advanced Culture Technology
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• v.12 no.2
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• pp.90-97
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• 2024

Shoulder impingement syndrome (SIS) is a common musculoskeletal condition characterized by pain and functional limitation due to the impingement of subacromial structures. This comprehensive review elucidates the complex nature of SIS, covering its pathophysiology, diagnostic methodologies, treatment options, and preventive measures. Through an exhaustive examination of current literature and clinical practices, the review highlights the importance of a multifaceted approach to SIS management. Physical therapy plays a pivotal role, focusing on exercises to strengthen shoulder musculature, enhance scapular stability, and improve range of motion. The review also discusses the strategic use of medications such as NSAIDs and corticosteroid injections, emphasizing their effectiveness in pain and inflammation management. Additionally, it advocates for structured rehabilitation programs post-treatment to restore function and prevent recurrence, recommending preventive strategies like ergonomic adjustments, targeted exercises, and proper technique training. This paper underscores the need for personalized and evidence-based treatment strategies, integrating physical therapy and pharmacological management when necessary.

• Journal of Information Processing Systems
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• v.20 no.3
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• pp.307-316
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• 2024

In the realm of large-scale identification deployments, the EPCglobal Class-1 Generation-2 (Gen2) standard serves as a cornerstone, facilitating rapid processing of numerous passive RFID tags. The Q-Algorithm has garnered considerable attention for its potential to markedly enhance the efficiency of Gen2-based RFID systems with minimal adjustments. This paper introduces a groundbreaking iteration of the Q-Algorithm, termed Time-Efficient Q-Algorithm (SwiftQ), specifically designed to push the boundaries of time efficiency within Gen2-based RFID systems. Through exhaustive simulations, our study substantiates that SwiftQ outperforms existing algorithms by a significant margin, demonstrating exceptional expediency that positions it as a formidable contender in the landscape of large-scale identification environments. By prioritizing time efficiency, SwiftQ offers a promising solution to meet the escalating demands of contemporary Internet of Things applications, underscoring its potential to catalyze advancements in RFID technology for diverse industrial and logistical contexts.