• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.9
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• pp.63-73
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• 2015

This work proposes a 2-channel time-interleaved (T-I) 10b 120MS/s pipeline SAR ADC minimizing offset mismatch between channels without any calibration scheme. The proposed ADC employs a 2-channel SAR and T-I topology based on a 2-step pipeline ADC with 4b and 7b in the first and second stage for high conversion rate and low power consumption. Analog circuits such as comparator and residue amplifier are shared between channels to minimize power consumption, chip area, and offset mismatch which limits the ADC linearity in the conventional T-I architecture, without any calibration scheme. The TSPC D flip-flop with a short propagation delay and a small number of transistors is used in the SAR logic instead of the conventional static D flip-flop to achieve high-speed SAR operation as well as low power consumption and chip area. Three separate reference voltage drivers for 4b SAR, 7b SAR circuits and a single residue amplifier prevent undesirable disturbance among the reference voltages due to each different switching operation and minimize gain mismatch between channels. High-frequency clocks with a controllable duty cycle are generated on chip to eliminate the need of external complicated high-frequency clocks for SAR operation. The prototype ADC in a 45nm CMOS technology demonstrates a measured DNL and INL within 0.69LSB and 0.77LSB, with a maximum SNDR and SFDR of 50.9dB and 59.7dB at 120MS/s, respectively. The proposed ADC occupies an active die area of 0.36mm2 and consumes 8.8mW at a 1.1V supply voltage.

• 대한공업교육학회지
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• v.34 no.2
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• pp.103-127
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• 2009

The purpose of this study is to offer the basic data regarding the problems of the employment training activities and their solutions by way of the research and analysis of the awareness of career development of university students and their preparation for employment opportunities. The results of the study are as follows. First, it is necessary that the students themselves make plans for future jobs and their preparation for them, from the start of their university work. This includes taking employment preparation courses as liberal arts requirements. It also needs to have a systematic association with some organizations such as employment preparation centers. Second, it is necessary that the career portfolios of university students be accepted as materials for objective evaluation so that the companies use them at the time of hiring new employees. If those materials are stored and managed in a database even after their graduation, they will be the strong foundation for the competitive power of the university.Third, it is necessary that university students establish the orientation of employment training in advance, according to their personal and disciplinary possibilities by diagnosing the level of basic employment ability they possess and that they find out the appropriate programs, both personal and disciplinary, to enforce the abilities they need to develop further. Accordingly, it is necessary to have an evaluation system in order to assess student's basic employment abilities, so as to increase the degree of their employment preparation and its support strategy based on the evaluation. Fourth, in the higher education level, university students' lower awareness (M=2.86) of their discipline satisfaction, their major selection, and the university's employment opportunity service shows that it is necessary that there be close connection between learning and work. For short-term purpose, the quantitative and qualitative evaluation must be preceded about the various employment training programs and self-development programs offered by the university. From the long-term perspective, it is urgently necessary that the university ensure the human resources development experts for the purpose of diagnosing employment services within the university.

• Korean Security Journal
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• no.12
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• pp.89-116
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• 2006

As the society changes, the Private Security has developed highly in a short time. However, it has brought about various problems. The best urgent problem of those problems is the wage problem. This study is examining into the difference with the wage satisfaction and devotion to organization, and analyzing influence that wage satisfaction has on devotion to organization. According to this research, the first, women appeared higher numerical value than men in satisfaction with a wage level, wage disparity, wage system and the welfare system and the highest age group is over 26 year-old. While the college graduates appeared high satisfaction with a wage level and wage disparity, the university graduates is high satisfaction with wage system and the welfare. This shows that as the scholarship is high, they think they must be getting wages higher and higher as their work result or produce. The second, in devotion to his(her) organization, the men is higher than the women. The third, the men show the high emotional devotion because the men devote to his work on his own initiative while the women show the high continuos service devotion because they are passively. The fourth, over the 26-year old group appeared high level in devotion to his(her) organization, the university graduate group appeared high level both the emotional devotion and the continuous service devotion. The long-term employed person showed the satisfaction with job position, pay grade, and career and also appeared high in devotion to his(her) organization. The fifth, as the scholarship is low, they were concerned about a wage level and wage disparity but, as the scholarship is high, they were concerned about the wage system and the welfare. The wage satisfaction has influence on the scholarship, job position and career therefore, the long-term employed persons showed high wage satisfaction and devotion to his(her) organization. In conclusion, for the development of Private Security and high devotion to organization, the wage level of private security guards must be systematize and the quality of the welfare must be improved. And the many factors about the wage and welfare must be studied and analyzed to occupy as one of the skill lists through the educational-industrial collaboration.

• Korean Journal of Construction Engineering and Management
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• v.5 no.5 s.21
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• pp.183-192
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• 2004

Even in Korea the number of steel structure buildings that allow internal space and easy change of their layouts in accordance with the purpose of buildings and box-type steel bridges constructed with thick plates with thickness in a rage just from a few $\beta$AE to \$100\beta$AE is increasing these days and therefore, domestic fabrication and processing technology of members for steel structures is being improved at a pace faster than in the past to meet the growing requirements of consumers for high reliability on quality control on the related steel structures. However, most domestic fabricators os steel structures who are turning out their steel products in accordance with the designs prepared by engineering companies in their respective works for the sake of cost cut more than anything else, hesitating to introduce any advanced new technology into themselves. In the case of the steel structure design application for small and mid-size buildings in particular, it is quite meaningful not only for those who are involved in steel structure business, but also for the people working at construction work fields to review the result of the study on the connections of steel structure members deigned to obtain superb quality of steel structures within short period for steel fabrication and erection at fields in economical ways, as there is a glowing tendency seeking standardization of connection of steel structure members as well as whole structure together with the development on design of construction system of buildings including their exterior and interior decoration materials, manufacture of the related members and fabrication technique structure. This paper has been prepared with the aim to review the peculiar characteristics of buildings constructed with the main frames of steel structures and actual cases of the change made ing the connections between steel structure columns and between columns and girder members in order to reduce the work period necessary for fabrication and erection of steel structures at the maximum as well as the some examples of steel structures fabricated through automatic welding by robots for box-type columns in addition to the description of the problems found in the course of fabricating those steel structures, suggesting possible counter-measures to solve them.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.141-154
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• 2019

Rapid growth of internet technology and social media is progressing. Data mining technology has evolved to enable unstructured document representations in a variety of applications. Sentiment analysis is an important technology that can distinguish poor or high-quality content through text data of products, and it has proliferated during text mining. Sentiment analysis mainly analyzes people's opinions in text data by assigning predefined data categories as positive and negative. This has been studied in various directions in terms of accuracy from simple rule-based to dictionary-based approaches using predefined labels. In fact, sentiment analysis is one of the most active researches in natural language processing and is widely studied in text mining. When real online reviews aren't available for others, it's not only easy to openly collect information, but it also affects your business. In marketing, real-world information from customers is gathered on websites, not surveys. Depending on whether the website's posts are positive or negative, the customer response is reflected in the sales and tries to identify the information. However, many reviews on a website are not always good, and difficult to identify. The earlier studies in this research area used the reviews data of the Amazon.com shopping mal, but the research data used in the recent studies uses the data for stock market trends, blogs, news articles, weather forecasts, IMDB, and facebook etc. However, the lack of accuracy is recognized because sentiment calculations are changed according to the subject, paragraph, sentiment lexicon direction, and sentence strength. This study aims to classify the polarity analysis of sentiment analysis into positive and negative categories and increase the prediction accuracy of the polarity analysis using the pretrained IMDB review data set. First, the text classification algorithm related to sentiment analysis adopts the popular machine learning algorithms such as NB (naive bayes), SVM (support vector machines), XGboost, RF (random forests), and Gradient Boost as comparative models. Second, deep learning has demonstrated discriminative features that can extract complex features of data. Representative algorithms are CNN (convolution neural networks), RNN (recurrent neural networks), LSTM (long-short term memory). CNN can be used similarly to BoW when processing a sentence in vector format, but does not consider sequential data attributes. RNN can handle well in order because it takes into account the time information of the data, but there is a long-term dependency on memory. To solve the problem of long-term dependence, LSTM is used. For the comparison, CNN and LSTM were chosen as simple deep learning models. In addition to classical machine learning algorithms, CNN, LSTM, and the integrated models were analyzed. Although there are many parameters for the algorithms, we examined the relationship between numerical value and precision to find the optimal combination. And, we tried to figure out how the models work well for sentiment analysis and how these models work. This study proposes integrated CNN and LSTM algorithms to extract the positive and negative features of text analysis. The reasons for mixing these two algorithms are as follows. CNN can extract features for the classification automatically by applying convolution layer and massively parallel processing. LSTM is not capable of highly parallel processing. Like faucets, the LSTM has input, output, and forget gates that can be moved and controlled at a desired time. These gates have the advantage of placing memory blocks on hidden nodes. The memory block of the LSTM may not store all the data, but it can solve the CNN's long-term dependency problem. Furthermore, when LSTM is used in CNN's pooling layer, it has an end-to-end structure, so that spatial and temporal features can be designed simultaneously. In combination with CNN-LSTM, 90.33% accuracy was measured. This is slower than CNN, but faster than LSTM. The presented model was more accurate than other models. In addition, each word embedding layer can be improved when training the kernel step by step. CNN-LSTM can improve the weakness of each model, and there is an advantage of improving the learning by layer using the end-to-end structure of LSTM. Based on these reasons, this study tries to enhance the classification accuracy of movie reviews using the integrated CNN-LSTM model.

• Archives of design research
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• v.20 no.3 s.71
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• pp.61-72
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• 2007

Having started with "Space War", the first game produced by MIT in the 1960's, the gaming industry expanded rapidly and grew to a large size over a short period of time: the brand new games being launched on the market are found to contain many different elements making up a single content in that it is often called the 'the most comprehensive ultimate fruits' of the design technologies. This also translates into a large increase in the number of things which need to be considered in developing games, complicating the plans on the financial budget, the work force, and the time to be committed. Therefore, an approach for analyzing the elements which make up a game, computing the importance of each of them, and assessing those games to be developed in the future, is the key to a successful development of games. Many decision-making activities are often required under such a planning process. The decision-making task involves many difficulties which are outlined as follows: the multi-factor problem; the uncertainty problem impeding the elements from being "quantified" the complex multi-purpose problem for which the outcome aims confusion among decision-makers and the problem with determining the priority order of multi-stages leading to the decision-making process. In this study we plan to suggest AHP (Analytic Hierarchy Process) so that these problems can be worked out comprehensively, and logical and rational alternative plan can be proposed through the quantification of the "uncertain" data. The analysis was conducted by taking FPS (First Person Shooting) which is currently dominating the gaming industry, as subjects for this study. The most important consideration in conducting AHP analysis is to accurately group the elements of the subjects to be analyzed objectively, and arrange them hierarchically, and to analyze the importance through pair-wise comparison between the elements. The study is composed of 2 parts of analyzing these elements and computing the importance between them, and choosing an alternative plan. Among these this paper is particularly focused on the Delphi technique-based objective element analyzing and hierarchy of the FPS games.

• Proceedings of the Materials Research Society of Korea Conference
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• 2011.05a
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• pp.5-5
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• 2011

The research and development of hybrid electric vehicle (HEV), plug-in hybrid electric vehicle (PHEV) and electric vehicle (EV) are intensified due to the energy crisis and environmental concerns. In order to meet the challenging requirements of powering HEV, PHEV and EV, the current lithium battery technology needs to be significantly improved in terms of the cost, safety, power and energy density, as well as the calendar and cycle life. One new technology being developed is the utilization of composite cathode by mixing two different types of insertion compounds [e.g., spinel $LiMn_2O_4$ and layered $LiMO_2$ (M=Ni, Co, and Mn)]. Recently, some studies on mixing two different types of cathode materials to make a composite cathode have been reported, which were aimed at reducing cost and improving self-discharge. Numata et al. reported that when stored in a sealed can together with electrolyte at $80^{\circ}C$ for 10 days, the concentrations of both HF and $Mn^{2+}$ were lower in the can containing $LiMn_2O_4$ blended with $LiNi_{0.8}Co_{0.2}O_2$ than that containing $LiMn_2O_4$ only. That reports clearly showed that this blending technique can prevent the decline in capacity caused by cycling or storage at elevated temperatures. However, not much work has been reported on the charge-discharge characteristics and related structural phase transitions for these composite cathodes. In this presentation, we will report our in situ x-ray diffraction studies on this mixed composite cathode material during charge-discharge cycling. The mixed cathodes were incorporated into in situ XRD cells with a Li foil anode, a Celgard separator, and a 1M $LiPF_6$ electrolyte in a 1 : 1 EC : DMC solvent (LP 30 from EM Industries, Inc.). For in situ XRD cell, Mylar windows were used as has been described in detail elsewhere. All of these in situ XRD spectra were collected on beam line X18A at National Synchrotron Light Source (NSLS) at Brookhaven National Laboratory using two different detectors. One is a conventional scintillation detector with data collection at 0.02 degree in two theta angle for each step. The other is a wide angle position sensitive detector (PSD). The wavelengths used were 1.1950 ${\AA}$ for the scintillation detector and 0.9999 A for the PSD. The newly installed PSD at beam line X18A of NSLS can collect XRD patterns as short as a few minutes covering $90^{\circ}$ of two theta angles simultaneously with good signal to noise ratio. It significantly reduced the data collection time for each scan, giving us a great advantage in studying the phase transition in real time. The two theta angles of all the XRD spectra presented in this paper have been recalculated and converted to corresponding angles for ${\lambda}=1.54\;{\AA}$, which is the wavelength of conventional x-ray tube source with Cu-$k{\alpha}$ radiation, for easy comparison with data in other literatures. The structural changes of the composite cathode made by mixing spinel $LiMn_2O_4$ and layered $Li-Ni_{1/3}Co_{1/3}Mn_{1/3}O_2$ in 1 : 1 wt% in both Li-half and Li-ion cells during charge/discharge are studied by in situ XRD. During the first charge up to ~5.2 V vs. $Li/Li^+$, the in situ XRD spectra for the composite cathode in the Li-half cell track the structural changes of each component. At the early stage of charge, the lithium extraction takes place in the $LiNi_{1/3}Co_{1/3}Mn_{1/3}O_2$ component only. When the cell voltage reaches at ~4.0 V vs. $Li/Li^+$, lithium extraction from the spinel $LiMn_2O_4$ component starts and becomes the major contributor for the cell capacity due to the higher rate capability of $LiMn_2O_4$. When the voltage passed 4.3 V, the major structural changes are from the $LiNi_{1/3}Co_{1/3}Mn_{1/3}O_2$ component, while the $LiMn_2O_4$ component is almost unchanged. In the Li-ion cell using a MCMB anode and a composite cathode cycled between 2.5 V and 4.2 V, the structural changes are dominated by the spinel $LiMn_2O_4$ component, with much less changes in the layered $LiNi_{1/3}Co_{1/3}Mn_{1/3}O_2$ component, comparing with the Li-half cell results. These results give us valuable information about the structural changes relating to the contributions of each individual component to the cell capacity at certain charge/discharge state, which are helpful in designing and optimizing the composite cathode using spinel- and layered-type materials for Li-ion battery research. More detailed discussion will be presented at the meeting.

• Journal of Korean Society of Forest Science
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• v.100 no.3
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• pp.423-431
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• 2011

The changes of forest degradation in North Korea have closely been related to political, economic and social conditions at all different times. The deforestation by local people for their livelihood has been accelerated when the recession has been worsened due to the 1990's collapse of socialism and the years of natural disasters, and the fall of the centralized and planned economy system. The serious recession in the 1990's has brought many changes in the North Korean society since the 2000's. Not only the underground economy, but also the market in which personal trades are occurred have been expanded as the distribution system of the planned economy system had fallen. In addition, even many state institutions have also increased timber harvest for export to acquire insufficient foreign currency. Eventually, North Korea felt the limits of utilization of forest resources under socialism then started to seek measures to restore devastated forest, while realizing the need of support from the international society. Therefore, some NGOs of South Korea started to give financial support on building tree nurseries in which seedlings for planting are produced to help the rehabilitation of the degraded forests in North Korea. Therefore, Planning of the basic directions for forest rehabilitation programs considering to economic and social conditions of North Korea are needed based on the successful rehabilitation experience of South Korea in the 1970's. First of all, relationships which was built after collapse of centrally planned economy between districts, businesses and workers must be consider to rehabilitate forests in North Korea. Secondly, due to the nature of forest rehabilitation projects this is very needs voluntary participation of resident for a long time, and then forest rehabilitation projects can create jobs for local resident, they can obtain continuous income on the forest rehabilitation projects field in order to promote resident's work in forest rehabilitation projects. Thirdly, the rate dependence on forests of the residents living must keep the level down by rural development projects going side by side with forest rehabilitation projects. Fourthly, use of exsisting forest management system in North Korea is also needed to ensure administrative power and labor for grand scale plantations in a short period of time. Meanwhile after the success of Forest Rehabilitation, it is very important to improve exsisting forest management system.

• Journal of Popular Narrative
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• v.26 no.4
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• pp.9-41
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• 2020

Park Jong-won's debut film "Guro Arirang," based on a short story of the same title by Lee Moon-yeol, is the first commercial film to deal with labor struggles from a worker's point of view in the wake of the 1987 democratic movement, and a pioneering work in terms of representing female workers the Korean cinema has traditionally turned away from. In this film Park Jong-won tried to win the sympathy of the middle class for labor movement in spite of the red scare which still stood firm in the Korean society at that time. To convey its progressive message in a form acceptable to the middle class public, the film portrays labor issues in the light of universal humanity and ethics, not in terms of class hostility or struggle. Park Jong-won calls this point of view "common sense of normal people" and emphasizes its universality and objectivity. This study critically examines the cinematic strategies to deal with labor issues in a form acceptable to the public in a conventional and commercial film and the ideological implications of the "common sense of normal people" reflected in such strategies. The first chapter of the study reveals that the film destroys the irony of the original story and reduces the complex constellation of the characters to the conflict between pure good and evil, creating a melodramatic composition in which the good falls victim to evil. The tragedies suffered by the workers in the film are of course intended to arouse the audience's strong sympathy and solidarity with them. The second chapter shows that the film's various scenes and episodes converge on the them of compassion and grief, and are mostly based on cultural and real experiences and events that caused great public sensations at that time. Especially in the last decisive scene of the movie, the memory of the June 1987 uprising is strongly recalled. So "Guro Arirang" can be seen as a patchwork of proven cases of compassion and grief. The third chapter examines the implications of the scene where the workers turn back demands for wages and put the issues of human treatment and trust to the forefront at the crucial moment of their struggle. It appeals to universal moral values and sentiments that everyone has to acknowledge and removes the political dimension from the workers' campaign. While the film tends to become a pure story of humanity marginalizing irreconcilable conflicts of class interest, the workers fall to the position of passive victims who can be deeply sympathetic on the one hand, and on the other, are idealized as leaders with noble attitude keeping themselves aloof from the hard reality. As a result, the movie loses its realistic ground and weakens its narrative probability. The scenes reminiscent of the 1987 uprising which evoke the solidarity between working and middle class fail to integrate harmoniously into the whole story of the film and remain only as fragmentary parts of the patchwork of compassion and grief.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.95-108
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• 2017

Recently, AlphaGo which is Bakuk (Go) artificial intelligence program by Google DeepMind, had a huge victory against Lee Sedol. Many people thought that machines would not be able to win a man in Go games because the number of paths to make a one move is more than the number of atoms in the universe unlike chess, but the result was the opposite to what people predicted. After the match, artificial intelligence technology was focused as a core technology of the fourth industrial revolution and attracted attentions from various application domains. Especially, deep learning technique have been attracted as a core artificial intelligence technology used in the AlphaGo algorithm. The deep learning technique is already being applied to many problems. Especially, it shows good performance in image recognition field. In addition, it shows good performance in high dimensional data area such as voice, image and natural language, which was difficult to get good performance using existing machine learning techniques. However, in contrast, it is difficult to find deep leaning researches on traditional business data and structured data analysis. In this study, we tried to find out whether the deep learning techniques have been studied so far can be used not only for the recognition of high dimensional data but also for the binary classification problem of traditional business data analysis such as customer churn analysis, marketing response prediction, and default prediction. And we compare the performance of the deep learning techniques with that of traditional artificial neural network models. The experimental data in the paper is the telemarketing response data of a bank in Portugal. It has input variables such as age, occupation, loan status, and the number of previous telemarketing and has a binary target variable that records whether the customer intends to open an account or not. In this study, to evaluate the possibility of utilization of deep learning algorithms and techniques in binary classification problem, we compared the performance of various models using CNN, LSTM algorithm and dropout, which are widely used algorithms and techniques in deep learning, with that of MLP models which is a traditional artificial neural network model. However, since all the network design alternatives can not be tested due to the nature of the artificial neural network, the experiment was conducted based on restricted settings on the number of hidden layers, the number of neurons in the hidden layer, the number of output data (filters), and the application conditions of the dropout technique. The F1 Score was used to evaluate the performance of models to show how well the models work to classify the interesting class instead of the overall accuracy. The detail methods for applying each deep learning technique in the experiment is as follows. The CNN algorithm is a method that reads adjacent values from a specific value and recognizes the features, but it does not matter how close the distance of each business data field is because each field is usually independent. In this experiment, we set the filter size of the CNN algorithm as the number of fields to learn the whole characteristics of the data at once, and added a hidden layer to make decision based on the additional features. For the model having two LSTM layers, the input direction of the second layer is put in reversed position with first layer in order to reduce the influence from the position of each field. In the case of the dropout technique, we set the neurons to disappear with a probability of 0.5 for each hidden layer. The experimental results show that the predicted model with the highest F1 score was the CNN model using the dropout technique, and the next best model was the MLP model with two hidden layers using the dropout technique. In this study, we were able to get some findings as the experiment had proceeded. First, models using dropout techniques have a slightly more conservative prediction than those without dropout techniques, and it generally shows better performance in classification. Second, CNN models show better classification performance than MLP models. This is interesting because it has shown good performance in binary classification problems which it rarely have been applied to, as well as in the fields where it's effectiveness has been proven. Third, the LSTM algorithm seems to be unsuitable for binary classification problems because the training time is too long compared to the performance improvement. From these results, we can confirm that some of the deep learning algorithms can be applied to solve business binary classification problems.