• 한국공작기계학회논문집
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• 제15권6호
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• pp.44-49
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• 2006

The use of snap-fit features is highly recommended to reduce overall product cost and manufacturing time by reducing the number of parts and eliminating assembly with conventional fasteners. Application to particular product for integral attachment using snap-fit features is needed. Alternative attachment concept for specific application has been introduced. In this study, the optimal attachment design based on the given design objectives is identified using newly developed alternative attachment concept for the specific application to LCD monitor case assembly. Integral attachment using snap-fit features applies the systematic procedure and the intensity analysis.

• Journal of Information Processing Systems
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• 제18권5호
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• pp.650-664
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• 2022

Mobile applications can be easily downloaded and installed via markets. However, malware and malicious applications containing unwanted advertisements exist in these application markets. Therefore, smartphone users install applications with reference to the application review to avoid such malicious applications. An application review typically comprises contents for evaluation; however, a false review with a specific purpose can be included. Such false reviews are known as fake reviews, and they can be generated using artificial intelligence (AI)-based text-generating models. Recently, AI-based text-generating models have been developed rapidly and demonstrate high-quality generated texts. Herein, we analyze the features of fake reviews generated from Generative Pre-Training-2 (GPT-2), an AI-based text-generating model and create a model to detect those fake reviews. First, we collect a real human-written application review from Kaggle. Subsequently, we identify features of the fake review using natural language processing and statistical analysis. Next, we generate fake review detection models using five types of machine-learning models trained using identified features. In terms of the performances of the fake review detection models, we achieved average F1-scores of 0.738, 0.723, and 0.730 for the fake review, real review, and overall classifications, respectively.

• JSTS:Journal of Semiconductor Technology and Science
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• 제16권2호
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• pp.236-250
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• 2016

Electrical Designs for Application Specific Integrated Circuits (ASIC) has undergone a change recently with the advent of the sub-wavelength lithography. The optical projection with 193 nm wavelength has been further extended with the use of immersion and other techniques. The competing trends for printing smaller design features have been discussed in this paper with the discussion of the electrical layout analysis to find unfriendly design features. The early knowledge of the unfriendly design features allows remedial actions in time for better yield on the wafer. There are existing standard design qualification criteria being used in the design and fabrication community, but they seem to be insufficient to guarantee defect free designs. This paper proposes an integrated approach for screening the layout with multiple aspects: layout geometry based, graphical analysis and process model based verification. The results have been discussed with few example design features from the 28nm design layout.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 춘계학술대회 논문집
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• pp.455-459
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• 1997

A methodology which supports the feature used from design to manufacturing for sculptured pocket is newly devlored and present. The information contents in a feature can be easily conveyed from one application to another in the manufacturing domain. However, the feature generated in one application may not be directly suitable for another whitout being modified with more information. Theobjective of the paper is to parsent the methodology of decomposing a bulky feature of sculptured pocket to be removed into compact features to be efficiently machined. In particular, the paper focuses on the two task: 1) to segment horizontally a bulky feature into intermediate features by determining the adequate depth of cut and cutter size and to generate the temporal precedence graph of the intermediate features and 2)to further decompose each intermediate feature vertical into smaller manufacturing features and to apply the variable feed rate to each small feature. The proposed method will provid better efficiency in machining time and cost than the classical method which uses a long string of NC codes necessary to remove a bulky fecture.

• 한국멀티미디어학회논문지
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• 제20권8호
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• pp.1395-1405
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• 2017

In this paper, we analyses heart beat data to identify subjects stress state (binary) using heart rate variability (HRV) features extracted from heart beat data of the subjects and implement supervised machine learning techniques to create the mental stress classifier. There are four steps need to be done: data acquisition, data processing (HRV analysis), features selection, and machine learning, before doing performance measurement. There are 56 features generated from the HRV Analysis module with several of them are selected (using own algorithm) after computing the Pearson Correlation Matrix (p-values). The results of the list of selected features compared with all features data are compared by its model error after training using several machine learning techniques: support vector machine, decision tree, and discriminant analysis. SVM model and decision tree model with using selected features shows close results compared to using all recording by only 1% difference. Meanwhile, the discriminant analysis differs about 5%. All the machine learning method used in this works have 90% maximum average accuracy.

• 한국과학교육학회지
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• 제13권2호
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• pp.152-162
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• 1993

The high school students' problem solving patterns and their features in scientific inquiry, especially on controlling variables and stating hypothesis have been investigated. The 8 problems on controlling variables and stating hypothesis were selected out of the scientific inquiry area in the experimental tryout of Aptitude Assessment for College Education, and had been used to find the patterns and their features. The results of findings are as follows: There were seven patterns in the process of solving problems. Five of seven patterns were found in right answers and four patterns in wrong answers. Two patterns were found in both right and wrong answers. Some students could solve the problems even though they did not understand the elements of the scientific inquiry, controlling variables and stating hypothesis. The false application of physics concepts, misunderstanding about the elements of the scientific inquiry and using unrelated experience and conjectures were the features of students' wrong answers. On the other hand, the right application of physics concepts, understanding and applying the elements right, infering answers from the tables and figures on statements of suggested problems were the features of right answers. The further studies on this kind may helpful to find the higher mental abilities related to scientific inquiry and to develop tools for testing students' scientific inquiry thinking skills.

• 한국전기전자재료학회논문지
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• 제25권1호
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• pp.76-83
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• 2012

In a real-time indoor place recognition system using image features detection, specific markers included in input image should be detected exactly and quickly. However because the same markers in image are shown up differently depending to movement, direction and angle of camera, it is required a method to solve such problems. This paper proposes a technique to extract the features of object without regard to change of the object scale. To support real-time operation, it adopts SURF(Speeded up Robust Features) which enables fast feature detection. Another feature of this system is the user mark designation which makes possible for user to designate marks from input image for location detection in advance. Unlike to use hardware marks, the feature above has an advantage that the designated marks can be used without any manipulation to recognize location in input image.

• 수산해양교육연구
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• 제23권4호
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• pp.568-581
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• 2011

This thesis is the study about application development for management obesity and personal health matters systematically based on Android smart phone system. Growing obesity problem for students organized by the lack of a device or program to manage at home has been favored as a serious problem. Currently developed smart phones has come into wide use by portable features and many applications. And to support populations of these features smart phones will be available for obesity management in your home without any equipment using. Accordingly, this paper is the study about application development for management obesity for growing students at home based on the latest smart phone platform Android.

• 제어로봇시스템학회논문지
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• 제17권1호
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• pp.17-21
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• 2011

This paper presents a real- time detection of on-road succeeding vehicles based on low level edge features and a boosted cascade of Haar-like features. At first, the candidate vehicle location in an image is found by low level horizontal edge and symmetry characteristic of vehicle. Then a boosted cascade of the Haar-like features is applied to the initial hypothesized vehicle location to extract the refined vehicle location. The initial hypothesis generation using simple edge features speeds up the whole detection process and the application of a trained cascade on the hypothesized location increases the accuracy of the detection process. Experimental results on real world road scenario with processing speed of up to 27 frames per second for $720{\times}480$ pixel images are presented.

• 대한전기학회논문지:시스템및제어부문D
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• 제52권1호
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• pp.45-50
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• 2003

Texture analysis has been efficiently utilized in the area of terrain classification. In this application features have been obtained in the 2D image domain. This paper suggests 3D co-occurrence texture features by extending the concept of co-occurrence to 3D world. The suggested 3D features are described using co-occurrence histogram of digital elevations at two contiguous position as co-occurrence matrix. The practical construction of co-occurrence matrix limits the number of levels of digital elevation. If the digital elevation is quantized into the number of levels over the whole DEM(Digital Elevation Map), the distinctive features can not be obtained. To resolve the quantization problem, we employ local quantization technique which preserves the variation of elevations. Experiments has been carried out to verify the proposed 3D co-occurrence features, and the addition of the suggested features significantly improves the classification accuracy.