• International conference on construction engineering and project management
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• 2015.10a
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• pp.425-428
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• 2015

New technologies using a CNC machine are being developed to reduce the production cost of free-form buildings. For production of free-form members using such technologies, vast free-form buildings should be first split into multiple panels that are productible. Taking into consideration of the curved surface of free-form members, the segmented free-form panels may vary in shape and size, which may cause a lot of errors. In addition, it is time-consuming for the work. However, the current panelizing work is completed with the trials and errors of engineers and architectural designers even in large-scale projects, which results in increased construction duration and cost. Thus, it is necessary to develop a technology for panelizing free-form panels so as to maximize the economic feasibility of production technologies for free-form concrete members. The study intends to develeop automatic panelizing algorithms of free-form buildings considering the curved surface and size of free-form panels and the production conditions. The developed algorithms will be useful in applying the production technologies of free-form buildings using CNC machine and reducing the cost.

• Tuberculosis and Respiratory Diseases
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• v.86 no.4
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• pp.251-263
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• 2023

The stethoscope has long been used for the examination of patients, but the importance of auscultation has declined due to its several limitations and the development of other diagnostic tools. However, auscultation is still recognized as a primary diagnostic device because it is non-invasive and provides valuable information in real-time. To supplement the limitations of existing stethoscopes, digital stethoscopes with machine learning (ML) algorithms have been developed. Thus, now we can record and share respiratory sounds and artificial intelligence (AI)-assisted auscultation using ML algorithms distinguishes the type of sounds. Recently, the demands for remote care and non-face-to-face treatment diseases requiring isolation such as coronavirus disease 2019 (COVID-19) infection increased. To address these problems, wireless and wearable stethoscopes are being developed with the advances in battery technology and integrated sensors. This review provides the history of the stethoscope and classification of respiratory sounds, describes ML algorithms, and introduces new auscultation methods based on AI-assisted analysis and wireless or wearable stethoscopes.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.190-194
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• 2023

By looking the importance of communication, data delivery and access in various sectors including governmental, business and individual for any kind of data, it becomes mandatory to identify faults and flaws during cyber communication. To protect personal, governmental and business data from being misused from numerous advanced attacks, there is the need of cyber security. The information security provides massive protection to both the host machine as well as network. The learning methods are used for analyzing as well as preventing various attacks. Machine learning is one of the branch of Artificial Intelligence that plays a potential learning techniques to detect the cyber-attacks. In the proposed methodology, the Decision Tree (DT) which is also a kind of supervised learning model, is combined with the different cross-validation method to determine the accuracy and the execution time to identify the cyber-attacks from a very recent dataset of different network attack activities of network traffic in the UNSW-NB15 dataset. It is a hybrid method in which different types of attributes including Gini Index and Entropy of DT model has been implemented separately to identify the most accurate procedure to detect intrusion with respect to the execution time. The different DT methodologies including DT using Gini Index, DT using train-split method and DT using information entropy along with their respective subdivision such as using K-Fold validation, using Stratified K-Fold validation are implemented.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.179-191
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• 2024

With the advancement of modern technology, cyber-attacks are always rising. Specialized defense systems are needed to protect organizations against these threats. Malicious behavior in the network is discovered using security tools like intrusion detection systems (IDS), firewall, antimalware systems, security information and event management (SIEM). It aids in defending businesses from attacks. Delivering advance threat feeds for precise attack detection in intrusion detection systems is the role of cyber-threat intelligence (CTI) in the study is being presented. In this proposed work CTI feeds are utilized in the detection of assaults accurately in intrusion detection system. The ultimate objective is to identify the attacker behind the attack. Several data sets had been analyzed for attack detection. With the proposed study the ability to identify network attacks has improved by using machine learning algorithms. The proposed model provides 98% accuracy, 97% precision, and 96% recall respectively.

• Journal of Medicine and Life Science
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• v.20 no.4
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• pp.141-157
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• 2023

Stroke is a leading cause of disability and death. The condition requires prompt diagnosis and treatment. The quality of care provided to patients with stroke can vary depending on the availability of medical resources, which in turn, can affect prognosis. Recently, there has been growing interest in using machine learning (ML) to support stroke diagnosis and treatment decisions based on large medical data sets. Current ML applications in stroke care can be divided into two categories: analysis of neuroimaging data and clinical information-based predictive models. Using ML to analyze neuroimaging data can increase the efficiency and accuracy of diagnoses. Commercial software that uses ML algorithms is already being used in the medical field. Additionally, the accuracy of predictive ML models is improving with the integration of radiomics and clinical data. is expected to be important for improving the quality of care for patients with stroke.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.29-34
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• 2024

Since the outbreak of COVID-19, there has been a surge in sports conducted through online platforms due to the increase in remote and non-contact activities. Billiards, being suitable for online platforms, has received much attention, leading to research on detecting the position and trajectory of balls. In this paper, we propose a new method utilizing machine vision to detect the position of the balls accurately. The proposed method detects the outline of the ball using the Canny edge detection and then employs simple correlation to determine its position. This correlation-based approach offers satisfactory system performance and is easily applicable in practical systems due to its low implementation complexity and robustness to noise.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.5B no.2
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• pp.111-117
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• 2005

Several of the conventional hydraulic systems in an automobile are now being replaced by more reliable and energy efficient electromechanical systems. Developments in the brushless permanent magnet machine and in the power and control electronics are the key factors responsible for this transformation. These applications brought out some performance challenges associated with the brushless machines. This paper will focus on these challenges to be able to use these machines in such applications. In terms of replacing hydraulic systems with electromechanical systems, steering system is leading the way in automobiles. Currently, steering systems using Electro-hydraulically assisted systems and Electrically assisted (Electromechanical) systems are in the market. Though the Electrically assisted power steering has several advantages over other systems, certain performance and cost challenges delayed the penetration of such systems in to the market.

• Steel and Composite Structures
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• v.29 no.3
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• pp.309-318
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• 2018

Steel girders are the structural members often used for passing long spans. Mostly being subjected to patch loading, or concentrated loading, steel girders are likely to face sudden deformation or damage e.g., web breathing. Horizontal or vertical stiffeners are employed to overcome this phenomenon. This study aims at assessing the feasibility of a machine learning method, namely the support vector machines (SVM) in predicting the patch loading resistance of longitudinally stiffened webs. A database consisting of 162 test data is utilized to develop SVM models and the model with best performance is selected for further inspection. Existing formulations proposed by other researchers are also investigated for comparison. BS5400 and other existing models (model I, model II and model III) appear to yield underestimated predictions with a large scatter; i.e., mean experimental-to-predicted ratios of 1.517, 1.092, 1.155 and 1.256, respectively; whereas the selected SVM model has high prediction accuracy with significantly less scatter. Robust nature and accurate predictions of SVM confirms its feasibility of potential use in solving complex engineering problems.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.30 no.4
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• pp.69-78
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• 1998

Papers loaded with 10-40% $TiO_2$ by dry weight were calendered under the various combinations of calendering conditions such as calender type, linear pressure, and roll temperature. After being calendered, light scattering coefficient, surface roughness, density, and tensile strength of the papers were measured and the results were summerized as follows: 1. To increase the light scattering coefficient of $TiO_2$-highly-loaded paper further by calendering, the calender roll pressure and temperature should be kept low. Under these conditions, the physical strength of the paper was not significantly affected. 2. At low roll temperature, soft nip calender and machine calender type showed the same relationship between paper density and its roughness. At high roll temperature, soft nip calender type gave much lower roughness than machine calender type at the same density. 3. At high roll temperature of both calenders, the density as well as the tensile strength of the TiO$_2$-loaded paper was increased significantly.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.4
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• pp.555-566
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• 2012

This paper presents a thermal analysis of an interior PM synchronous machine with concentrated winding for electric vehicle. The conventional thermal equivalent network model has been used for a long time for calculation of the temperature rises in electrical machines. In spite of being popular, this method can not be applied correctly for elements with complicated cooling structure like liquid cooled housing. To overcome this drawbacks, in this paper, a hybrid thermal model using the result of CFD analysis partly. Using this method, to improve a thermal performance of PMSM with concentrated winding, the effects of two design parameters are analysed. Finally, the accuracy of this model has been verified by experiments for the developed 21kW motor.