• Journal of Advanced Information Technology and Convergence
• /
• v.10 no.2
• /
• pp.33-48
• /
• 2020

By Digital Transformation, new technologies like ML (Machine Learning), Big Data, Cloud, VR/AR are being used to video streaming technology. We choose ML to provide optimal QoE (Quality of Experience) in various network conditions. In other words, ML helps DASH in providing non-stopping video streaming. In DASH, the source video is segmented into short duration chunks of 2-10 seconds, each of which is encoded at several different bitrate levels and resolutions. We built and compared the performances of five prototypes after applying five different machine learning algorithms to DASH. The prototype consists of a dash.js, a video processing server, web servers, data sets, and five machine learning models.

• International Journal of Computer Science & Network Security
• /
• v.22 no.9
• /
• pp.258-270
• /
• 2022

Cancer has become a common disease for the past two decades throughout the globe and there is significant increase of cancer among women. Breast cancer and ovarian cancers are more prevalent among women. Majority of the patients approach the physicians only during their final stage of the disease. Early diagnosis of cancer remains a great challenge for the researchers. Although several drugs are being synthesized very often, their multi-benefits are less investigated. With millions of drugs synthesized and their data are accessible through open repositories. Drug repurposing can be done using machine learning techniques. We propose a feature selection technique in this paper, which is novel that generates multiple populations for the grey wolf algorithm and classifies breast cancer drugs efficiently. Leukemia drug dataset is also investigated and Multilayer perceptron achieved 96% prediction accuracy. Three supervised machine learning algorithms namely Random Forest classifier, Multilayer Perceptron and Support Vector Machine models were applied and Multilayer perceptron had higher accuracy rate of 97.7% for breast cancer drug classification.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.21 no.8
• /
• pp.1348-1355
• /
• 1997

Machine element design is a very important course in the undergraduate program of mechanical engineering in that it presents traditional design concepts. While computer aided design(CAD) receives more attention, students tend to ignore the machine element design or traditional design concepts. However, design methodologies related to machine elements are utilized quite often in practical fields. Also, design methodologies provide good insight for the decision making process of modern design. Generally, CAD is used for simple drafting without the real design process in the undergraduate program. Design software has been developed for various machine elements. Through menu display, a user can select or furnish the design input such as design objects, dimensions, environmental forces and usages, and safety factors. Then the software carries out the design processes which are the same as those of textbooks. The result of the design is filtered to have the values in the standards. The designed machine element is drawn via commercial CAD software. The software has been developed with C language on a personal computer. The developed software is being utilized successfully in a design course, and the experiences are discussed in this paper. The software can be used in industries which require the repeated process of the machine element design.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2000.11a
• /
• pp.81-84
• /
• 2000

Rotating machine is used extensively and plays important roles in the industrial field. Therefore when rotating machine get out of order, it is necessary to know reasons then deal with the troubles immediately. So many studies far diagnosis of rotating machine are being done. However by this time most of study has an interest in gaining a high recognition But without considering error $rate^{(1)(2)(3)}$ , it is not desirable enough to apply h the actual application system. If the manager of system receives the result misjudging the condition of rotating machine and takes measures, we would lose heavily. So in order to play the creditable diagnosis, we must consider error rate. T h ~ t is. it must be able to reject the result of misjudgment. This study uses nearest neighbor classifier for diagnosis of rotating $machine^{(4)(8)}$ And the Smith's rejection $method^{(1)}$ used to recognize handwritten charter is done. Consequently creditable diagnosis of rotating machine is proposed.

• Women's Health Nursing
• /
• v.26 no.1
• /
• pp.5-9
• /
• 2020

Artificial intelligence (AI), which includes machine learning and deep learning has been introduced to nursing care in recent years. The present study reviews the following topics: the concepts of AI, machine learning, and deep learning; examples of AI-based nursing research; the necessity of education on AI in nursing schools; and the areas of nursing care where AI is useful. AI refers to an intelligent system consisting not of a human, but a machine. Machine learning refers to computers' ability to learn without being explicitly programmed. Deep learning is a subset of machine learning that uses artificial neural networks consisting of multiple hidden layers. It is suggested that the educational curriculum should include big data, the concept of AI, algorithms and models of machine learning, the model of deep learning, and coding practice. The standard curriculum should be organized by the nursing society. An example of an area of nursing care where AI is useful is prenatal nursing interventions based on pregnant women's nursing records and AI-based prediction of the risk of delivery according to pregnant women's age. Nurses should be able to cope with the rapidly developing environment of nursing care influenced by AI and should understand how to apply AI in their field. It is time for Korean nurses to take steps to become familiar with AI in their research, education, and practice.

• Journal of the Korea Safety Management & Science
• /
• v.14 no.2
• /
• pp.49-54
• /
• 2012

As all kind of industry has developed, metal structure and machine instrument use bolt, pin, rivet and welding for assembly and combination. For pin and hinge, dimension accuracy is crucial to keep the operation and safety of the structure and machine instrument. In case of complex machine, the hinge for cover open-loop system is one of the significant design elements. Most of the hinges are being imported and assembled sine they give high technology development cost for its unit cost position. The reason is that the localization of hinge is inadequate. As the demand increase and the necessity of localization grow, it is now more important than ever to develop low cost structure. By the low cost structure, a new technology could be obtained for electronic product and structural hinge since it would enable for complex machine hinge to be guaranteed, technologically. Open-loop hinge is the link type and designed for the structure to keep constant open-loop. And, the hinge is examined in design stability by finite element analysis method. In this paper, the operation result is presented when the hinge for complex machine open-loop is designed for link type structure.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.19 no.3
• /
• pp.121-126
• /
• 2019

Recently IoT named Internet of Things technology is widely used throughout the industry. In this paper, a smart vending machine system is proposed to solve inconvenience of vending machine which is commonly seen. This allows users to purchase goods without cash and saves management costs by allowing vending machine managers to stock and sell conveniently. For the production of this smart vending machine, Analysis example using UML which is object-oriented analysis method and flowchart and screen design applying it are presented. Also this presented method is shown to being applied usefully for a guideline of building smart vending machine commercialization system based on IoT.

• Journal of the Korean Society of Industry Convergence
• /
• v.24 no.4_2
• /
• pp.481-490
• /
• 2021

In the ultrasonic welding machine, when the load fluctuates, the L and C of the piezo element in the oscillation part change. As a result, the resonant frequency is changed, so it is necessary to match the operating frequency of the ultrasonic welding machine to the new resonant frequency. That is, in order to maximize the output of the oscillation unit of the ultrasonic welding machine, it is inevitable to follow the resonance frequency. Accordingly, many methods for following the resonant frequency are being actively studied. In addition, in order to check the effect of external inductance on the operation of the ultrasonic welding machine, The equivalent circuit of the piezo element was analyzed by including the external inductance for resonance in the equivalent circuit of the piezo element, and the method of selecting an appropriate inductance was described. In this paper, we propose a new system that allows the switching frequency of the inverter to tracking the resonance frequency even if the resonance frequency is changed due to the load of the ultrasonic welding machine.

• Computers and Concrete
• /
• v.32 no.3
• /
• pp.263-286
• /
• 2023

Experimenting with concrete to determine its compressive and tensile strengths is a laborious and time-consuming operation that requires a lot of attention to detail. Researchers from all around the world have spent the better part of the last several decades attempting to use machine learning algorithms to make accurate predictions about the technical qualities of various kinds of concrete. The research that is currently available on estimating the strength of concrete draws attention to the applicability and precision of the various machine learning techniques. This article provides a summary of the research that has previously been conducted on estimating the strength of concrete by making use of a variety of different machine learning methods. In this work, a classification of the existing body of research literature is presented, with the classification being based on the machine learning technique used by the researchers. The present review work will open the horizon for the researchers working on the machine learning based prediction of the compressive strength of concrete by providing the recommendations and benefits and drawbacks associated with each model as determining the compressive strength of concrete practically is a laborious and time-consuming task.

• The Journal of the Convergence on Culture Technology
• /
• v.8 no.1
• /
• pp.409-415
• /
• 2022

In computer vision, an image of a measurement target is acquired using a camera. And feature values, vectors, and regions are detected by applying algorithms and library functions. The detected data is calculated and analyzed in various forms depending on the purpose of use. Computer vision is being used in various places, especially in the field of automatically recognizing automobile parts or measuring the quality. Computer vision is being used as the term machine vision in the industrial field, and it is connected with artificial intelligence to judge product quality or predict results. In this study, a vision system for judging the quality of automobile parts was built, and the results were compared by applying five machine learning classification models to the produced data.