• Geomechanics and Engineering
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• v.34 no.3
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• pp.285-301
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• 2023

During the construction of E75 highway through Grdelica gorge in Serbia, a major failure occurred in the zone of reinforced rock slope. Excavation was performed in highly anisotropic Paleozoic schist rock formation. The reinforcement consisted of the two rows of micropile wall with pre-stressed anchors. Forces in anchors were monitored with load cells while benchmarks were installed for superficial displacement measurements. The aim of the study is to investigate possible causes of instability considering different probability distributions of the strength of discontinuities and anchor bond strength by applying different optimization techniques for finding the critical failure surface. Even though the deterministic safety factor value is close to unity, the probability of failure is governed by variability of shear strength of anisotropic planes and optimization method used for locating the critical sliding surface. The Cuckoo search technique produces higher failure probabilities compared to the others. Depending on the assigned statistical distribution of input parameters, various performance functions of the factor of safety are obtained. The probability of failure is insensitive to the variation of bond strength. Different sampling techniques should yield similar results considering that the sufficient number of safety factor evaluations is chosen to achieve converged solution.

• The Journal of Information Systems
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• v.32 no.3
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• pp.133-150
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• 2023

Purpose This study aims to develop classification models using a decision tree algorithm to identify core keywords and rules influencing online consumer review evaluations for the robot vacuum cleaner on Amazon.com. The difference from previous studies is that we analyze core keywords that affect the evaluation results by dividing the subjects that evaluate online consumer reviews into self-evaluation (star ratings) and peer evaluation (helpfulness votes). We investigate whether the core keywords influencing star ratings and helpfulness votes vary across different products and whether there is a similarity in the core keywords related to star ratings or helpfulness votes across all products. Design/methodology/approach We used random under-sampling to balance the dataset. We progressively removed independent variables based on decreasing importance through backwards elimination to evaluate the classification model's performance. As a result, we identified classification models that best predict star ratings and helpfulness votes for each product's online consumer reviews. Findings We have identified that the core keywords influencing self-evaluation and peer evaluation vary across different products, and even for the same model or features, the core keywords are not consistent. Therefore, companies' producers and marketing managers need to analyze the core keywords of each product to highlight the advantages and prepare customized strategies that compensate for the shortcomings.

• Journal of the Korean Society of Systems Engineering
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• v.19 no.2
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• pp.1-17
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• 2023

This study aimed to examine the characteristics of ESG activities among major domestic companies in the carbon-emitting industry compared to industries with lower emissions, as ESG has emerged as a significant agenda across various industries. Departing from the traditional focus on the "why" of ESG, which primarily centers around financial performance, this research sought to uncover the "how" of effective ESG management in domestic companies. The analysis involved studying the sustainability reports of 124 companies using the Global Reporting Initiative (GRI) indicators and comparing high-emitting and non-high-emitting industries. The findings revealed industry-specific patterns in companies' ESG activities, providing valuable insights for future ESG evaluations and assessments. Furthermore, the advancement of rating analysis methods holds implications for ESG rating agencies and financial authorities in terms of policy-making.

• Journal of Information Technology Applications and Management
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• v.31 no.3
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• pp.149-163
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• 2024

As conversational AI systems such as ChatGPT have become more advanced, researchers are exploring ways to use them in education. However, we need effective ways to evaluate these systems before allowing them to help teach students. This study proposes a detailed framework for testing conversational AI across three important criteria as follow. First, specialized benchmarks that measure skills include giving clear explanations, adapting to context during long dialogues, and maintaining a consistent teaching personality. Second, adaptive standards check whether the systems meet the ethical requirements of privacy, fairness, and transparency. These standards are regularly updated to match societal expectations. Lastly, evaluations were conducted from three perspectives: technical accuracy on test datasets, performance during simulations with groups of virtual students, and feedback from real students and teachers using the system. This framework provides a robust methodology for identifying strengths and weaknesses of conversational AI before its deployment in schools. It emphasizes assessments tailored to the critical qualities of dialogic intelligence, user-centric metrics capturing real-world impact, and ethical alignment through participatory design. Responsible innovation by AI assistants requires evidence that they can enhance accessible, engaging, and personalized education without disrupting teaching effectiveness or student agency.

• Fourth Industrial Review
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• v.4 no.1
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• pp.11-18
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• 2024

Purpose: The purpose of this study is to develop a geography class teaching and learning guide that enables learners to realistically explore the characteristics of the world's climate and geographical environment using digital tools. Research design, data and methodology: We review previous research on classes using goal-based scenario learning models, gamification, and digital tools, and explore tools that can be applied to world geography classes. Based on the exploration results, a goal-based scenario learning module is designed and a strategy for promoting educational gamification is established based on the ADDIE instructional design model. Results: The study comprises four sessions. Sessions 1-3 involve performance evaluations using a goal-based scenario learning module. Learners create game characters reflecting geographical characteristics, present results, and proceed with 3D modeling. In Session 4, a gamification class using Google Sites on the CoSpaces metaverse platform will be conducted. Conclusions: The study introduces a goal-based scenario learning model and a gamification class using digital tools to empower learners in exploring geographical diversity and its impact on lifestyles. Utilizing an accessible online platform, the study provides practical measures for integrating digital tools into geography education, addressing the current importance of digital technology in teaching.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.5
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• pp.3-9
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• 2015

The wireless communication system adopts an appropriate retransmission scheme on each system protocol layer to improve reliability of data transmission. In each system protocol layer, the retransmission scheme operates in independently other layers and operates based on the parameters without reference to end-to-end performance of wireless communication system. For this reason, it is difficult to design the optimal system parameters that satisfy the QoS requirements for each service class. Thus, the performance analysis of wireless communication system is needed to design the optimal system parameters according to the end-to-end QoS requirements for each service class. In this paper, we derive the mathematical model to formulate the end-to-end performance of wireless communication system. We also evaluate the performance at the MAC and transport layers in terms of average spectral efficiency and average transmission delay. Based on the results of performance evaluations, we design the optimal system parameters according to the QoS requirements of service classes. From the results, the HARQ combined with AMC is appropriate for the delay-sensitive service and the ARQ combined with AMC is appropriate for a service that is insensitive to transmission delay. Also, the TCP can be applied for the delay-insensitive service only.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.5
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• pp.48-61
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• 2017

An IaaS service of a cloud computing environment makes itself attractive for running large scale parallel application thanks to its innate characteristics that a user can utilize a desired number of high performance virtual machines without maintenance cost. The total execution time of a parallel application on a high performance computing environment depends on a task scheduling algorithm. Most studies on task scheduling algorithms on cloud computing environment try to reduce a user cost, and studies on task scheduling algorithms that try to reduce total execution time are rarely carried out. In this paper, we propose a task scheduling algorithm called an HAGD and a performance enhancement method called a group task duplication method of which the HAGD utilizes. The group task duplication method simplifies previous task duplication method, and the HAGD uses the group task duplication method or a task insertion method according to the characteristics of a computing environment and an application. We found that the proposed algorithm provides superior performance regardless of the characteristics in terms of normalized total execution time through performance evaluations.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.4
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• pp.595-604
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• 2013

Currently, registered number of imported vehicles is increasing rapidly over the years. Accordingly, environment improvements of vehicle maintenance company for maintenance of luxury vehicle such as imported vehicle are continuously being made. In this paper, we propose a key frame extraction method based on HSV color model for smart vehicle management system implementation to offer for customer reliability of maintenance vehicle. After automatically recognize the license plates of the vehicle using vehicle license plate recognition system when the vehicle come in the car center, we check the repair history and request of the vehicle based on it. We implement mobile services which provide extracted key frame images to the user after extract key frames from vehicle repair video. In addition, we verify the superiority of key frame extraction method by applying a smart vehicle management system. Finally, we convert the RGB color to HSV color to improve the performance of proposed key frame extraction scheme. As a result, we confirmed that our scheme is more excellence about 30% in terms of recall than RGB color model from the performance evaluations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.4
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• pp.701-712
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• 2012

The concept of $k$-shortest disjoint paths is considered important because the establishment of primary and backup forwarding paths exploiting shorter distance and faster propagation time is a dominant consideration for the design of a survivable backbone network. Therefore, we need to evaluate how well the concept of $k$-shortest disjoint paths is exploited for the design of a survivable ship backbone network considering the international standard related to ship backbone networks, the IEC61162-410 standard specifying how to manage redundant message transmissions among ship devices. Performance evaluations are conducted in terms of following objective goals: link capacity, hop and distance of primary and backup paths, even distribution of traffic flows, restoration time of backup forwarding paths, and physical network topology connectivity.

• Journal of KIISE:Software and Applications
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• v.31 no.8
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• pp.1101-1112
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• 2004

In this paper, we propose a Web page weighting scheme using the user preference in each sense of query word to improve the performance of Web search. Generally search engines assign weights to a web page by using relevancy only, which is obtained by comparing the query word and the words in a web page. In the information retrieval from huge data such as the Web, simple word comparison cannot distinguish important documents because there exist too many documents with similar relevancy In this paper we implement a WordNet-based user interface that helps to distinguish different senses of query word, and constructed a search engine in which the implicit evaluations by multiple users are reflected in ranking by accumulating the number of clicks. In accumulating click counts, they are stored separately according to senses, so that more accurate search is possible. The experimental results with several keywords show that the precision of proposed system is improved compared to conventional search engines.