• Journal of the Korean Institute of Telematics and Electronics D
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• v.34D no.12
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• pp.39-45
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• 1997

This study presents the first experimental data for the impact of hot-carrier degradtion on the performance of CMOS folded-cascode op-amps. A folded-cascode op-amp which has an NMOS input pair has been designed and fabricated using a 0.8.mu.m single-poly, double-metal CMOS process. After high voltage stress, the degradtion of perfomrance parameters such as open-metal CMOS process. After high voltage stress, the degradation of performance parameters such as open-loop voltage gain, unity-gain frequency and phase margin has been analized and physically explaniend in terms of hot carrier degradation.

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.590-595
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• 2000

On the contrary to the increasing needs of shape qualities, most of quality inspections are carried out by manual or operator's insight. To find the causes of shape inferiority, it is required to gather and analyze the shape measurement data. As a result the winding profile measurement system ($TELE-SCANNER^{(R)}$) is developed to analyze the coiling process and automate the manual measuring process for winding profile of hot-rolled coils. The winding profile measurement system measures and analyzes winding profile shapes of hot-rolled coils, and classifies them into several dominant patterns that are related to normal or abnormal mechanical conditions of down-coiler. The system also contains analysis software to quantify the winding profile shapes and patterns, and to produce statistics to help search the causes of profile shape inferiority.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.374-374
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• 2000

In this paper, we developed an ANFIS controller through ES algorithm for disturbances rejection in Hot Rolling. The looper of a Hot Rolling is installed between each pair of stands and plays key roles to enhance the product quality of the strip by controlling the tension and the width of the strip. At the same time, the AGC on top of the Mill produces a strip with the desired thickness through pressing its Mill. Between both, however, interactions are caused by coupling effects among strip tension, looper angle and strip thickness. In addition, in case disturbances, it is more difficult to keep strip quantities desirable. So we present an ANFIS controller through ES algorithm which is able to identify fuzzy rule with input/output data and update itself through output errors.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.15 no.11
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• pp.928-936
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• 2003

In the present study, feasibility investigation on the solar assisted hot water supply system for apartment houses was carried out by the review of service facility and heat load pattern. Also analysis and experiment of the small sized system model were performed. This hybrid system are consists of solar collector, heat storage tank, controller, and gas boiler using LPG as a secondary heat source. The analytical results showed a good agreement with experimental data. We found that this hybrid system could reduce the energy cost by 30% for hot water compared to typical boiler system in the apartment houses. Also we showed that this model could be used for the energy and economic analysis of the hybrid system.

• Journal of the Korea Society of Computer and Information
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• v.23 no.11
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• pp.1-7
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• 2018

In this paper, we propose soft dead pixels detection method by analysing different response at hot and cold images. Abnormal pixels are able to effect detecting a small target. It also makes confusing real target or not cause of changing target size. Almost exist abnormal pixels after image signal processing even if dead pixels are removed by dead pixel compensation are called soft dead pixels. They are showed defect in final image. So removing or compensating dead pixels are very important for detecting object. The key idea of this proposed method, detecting dead pixels, is that most of soft deads have different response characteristics between hot image and cold image. General infrared cameras do NUC to remove FPN. Working 2-reference NUC must be needed getting data, hot & cold images. The way which is proposed dead pixel detection is that we compare response, NUC gain, at each pixel about two different temperature images and find out dead pixels if the pixels exceed threshold about average gain of around pixels.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.187-204
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• 2016

Document classification based on emotional polarity has become a welcomed emerging task owing to the great explosion of data on the Web. In the big data age, there are too many information sources to refer to when making decisions. For example, when considering travel to a city, a person may search reviews from a search engine such as Google or social networking services (SNSs) such as blogs, Twitter, and Facebook. The emotional polarity of positive and negative reviews helps a user decide on whether or not to make a trip. Sentiment analysis of customer reviews has become an important research topic as datamining technology is widely accepted for text mining of the Web. Sentiment analysis has been used to classify documents through machine learning techniques, such as the decision tree, neural networks, and support vector machines (SVMs). is used to determine the attitude, position, and sensibility of people who write articles about various topics that are published on the Web. Regardless of the polarity of customer reviews, emotional reviews are very helpful materials for analyzing the opinions of customers through their reviews. Sentiment analysis helps with understanding what customers really want instantly through the help of automated text mining techniques. Sensitivity analysis utilizes text mining techniques on text on the Web to extract subjective information in the text for text analysis. Sensitivity analysis is utilized to determine the attitudes or positions of the person who wrote the article and presented their opinion about a particular topic. In this study, we developed a model that selects a hot topic from user posts at China's online stock forum by using the k-means algorithm and self-organizing map (SOM). In addition, we developed a detecting model to predict a hot topic by using machine learning techniques such as logit, the decision tree, and SVM. We employed sensitivity analysis to develop our model for the selection and detection of hot topics from China's online stock forum. The sensitivity analysis calculates a sentimental value from a document based on contrast and classification according to the polarity sentimental dictionary (positive or negative). The online stock forum was an attractive site because of its information about stock investment. Users post numerous texts about stock movement by analyzing the market according to government policy announcements, market reports, reports from research institutes on the economy, and even rumors. We divided the online forum's topics into 21 categories to utilize sentiment analysis. One hundred forty-four topics were selected among 21 categories at online forums about stock. The posts were crawled to build a positive and negative text database. We ultimately obtained 21,141 posts on 88 topics by preprocessing the text from March 2013 to February 2015. The interest index was defined to select the hot topics, and the k-means algorithm and SOM presented equivalent results with this data. We developed a decision tree model to detect hot topics with three algorithms: CHAID, CART, and C4.5. The results of CHAID were subpar compared to the others. We also employed SVM to detect the hot topics from negative data. The SVM models were trained with the radial basis function (RBF) kernel function by a grid search to detect the hot topics. The detection of hot topics by using sentiment analysis provides the latest trends and hot topics in the stock forum for investors so that they no longer need to search the vast amounts of information on the Web. Our proposed model is also helpful to rapidly determine customers' signals or attitudes towards government policy and firms' products and services.

• KIISE Transactions on Computing Practices
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• v.22 no.1
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• pp.44-49
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• 2016

Recently, data has been growing dramatically along with the growth of social media and digital devices. A distributed memory processing system has been used to efficiently process large amounts of data. However, if a load is concentrated in a certain node in distributed environments, a node performance significantly degrades. In this paper, we propose a load balancing scheme to distribute load in a distributed memory environment. The proposed scheme replicates hot data to multiple nodes for managing a node's load and migrates the data by considering the load of the nodes when nodes are added or removed. The client reduces the number of accesses to the central server by directly accessing the data node through the metadata information of the hot data. In order to show the superiority of the proposed scheme, we compare it with the existing load balancing scheme through performance evaluation.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.9
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• pp.118-124
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• 2002

The use of ceramic inserts in hot extrusion dies offers significant technical and economic advantages over other forms of manufacture. In this paper, process simulation and stress analysis are thus combined during the design, and a data exchange program has been developed that enables optimal design of the dies taking into account the elastic deflections generated in shrink fitting the die inserts and that caused by the stresses generated in the process. The shrink fit analysis has been performed that enables optimal design of the dies taking into account the elastic deflections which generated in shrink fitting the die inserts and that caused by the stresses generated in the process and by using DEFORM software for process analysis. This data can be processed as load input data for a finite element die-stress analysis. Process simulation and stress analysis are thus combined during the die design. The stress analysis of the dies is used to determine the stress conditions on the ceramic insert by considering contact and interference effects under both mechanical and thermal loads. The results are compared with the experimental ones for verification.

• JSTS:Journal of Semiconductor Technology and Science
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• v.5 no.4
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• pp.262-269
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• 2005

Semiconductor scientists and engineers ideally desire the faster but the cheaper non-volatile memory devices. In practice, no single device satisfies this desire because a faster device is expensive and a cheaper is slow. Therefore, in this paper, we use heterogeneous non-volatile memories and construct an efficient hierarchy for them. First, a small RAM device (e.g., MRAM, FRAM, and PRAM) is used as a write buffer of flash memory devices. Since the buffer is faster and does not have an erase operation, write can be done quickly in the buffer, making the write latency short. Also, if a write is requested to a data stored in the buffer, the write is directly processed in the buffer, reducing one write operation to flash storages. Second, we use many types of flash memories (e.g., SLC and MLC flash memories) in order to reduce the overall storage cost. Specifically, write requests are classified into two types, hot and cold, where hot data is vulnerable to be modified in the near future. Only hot data is stored in the faster SLC flash, while the cold is kept in slower MLC flash or NOR flash. The evaluation results show that the proposed hierarchy is effective at improving the access time of flash memory storages in a cost-effective manner thanks to the locality in memory accesses.

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.750-759
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• 2020

The wide application of various integrated location-based services (LBS social) and tourism application (app) has generated a large amount of trajectory space data. The trajectory data are used to identify popular tourist attractions with high density of tourists, and they are of great significance to smart service and emergency management of scenic spots. A hot spot analysis method is proposed, based on spatial clustering of trajectory stop points. The DBSCAN algorithm is studied with fast clustering speed, noise processing and clustering of arbitrary shapes in space. The shortage of parameters is manually selected, and an improved method is proposed to adaptively determine parameters based on statistical distribution characteristics of data. DBSCAN clustering analysis and contrast experiments are carried out for three different datasets of artificial synthetic two-dimensional dataset, four-dimensional Iris real dataset and scenic track retention point. The experiment results show that the method can automatically generate reasonable clustering division, and it is superior to traditional algorithms such as DBSCAN and k-means. Finally, based on the spatial clustering results of the trajectory stay points, the Getis-Ord Gi* hotspot analysis and mapping are conducted in ArcGIS software. The hot spots of different tourist attractions are classified according to the analysis results, and the distribution of popular scenic spots is determined with the actual heat of the scenic spots.