• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.3
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• pp.46-55
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• 2016

This work proposes a 13b 100MS/s 45nm CMOS ADC with a high dynamic performance for IF-domain high-speed signal processing systems based on a four-step pipeline architecture to optimize operating specifications. The SHA employs a wideband high-speed sampling network properly to process high-frequency input signals exceeding a sampling frequency. The SHA and MDACs adopt a two-stage amplifier with a gain-boosting technique to obtain the required high DC gain and the wide signal-swing range, while the amplifier and bias circuits use the same unit-size devices repeatedly to minimize device mismatch. Furthermore, a separate analog power supply voltage for on-chip current and voltage references minimizes performance degradation caused by the undesired noise and interference from adjacent functional blocks during high-speed operation. The proposed ADC occupies an active die area of $0.70mm^2$, based on various process-insensitive layout techniques to minimize the physical process imperfection effects. The prototype ADC in a 45nm CMOS demonstrates a measured DNL and INL within 0.77LSB and 1.57LSB, with a maximum SNDR and SFDR of 64.2dB and 78.4dB at 100MS/s, respectively. The ADC is implemented with long-channel devices rather than minimum channel-length devices available in this CMOS technology to process a wide input range of $2.0V_{PP}$ for the required system and to obtain a high dynamic performance at IF-domain input signal bands. The ADC consumes 425.0mW with a single analog voltage of 2.5V and two digital voltages of 2.5V and 1.1V.

• The Korean Journal of Air & Space Law and Policy
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• v.30 no.2
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• pp.201-248
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• 2015

In Korea the number of unlawful interference act on board aircrafts has been increased continuously according to the growth of aviation demand, and there were 55 incidents in 2000, followed by 354 incidents in 2014, and an average of 211 incidents a year over the past five years. In 1963, a number of states adopted the Convention on Offences and Certain Other Acts Committed on Board Aircraft (the Tokyo Convention 1963) as the first worldwide international legal instrument on aviation security. The Tokyo Convention took effect in 1969 and, shortly afterward, in 1970 the Convention for the Suppression of Unlawful Seizure of Aircraft(the Hague Convention 1970) was adopted, and the Convention for the Suppression of Unlawful Acts Against the Safety of Civil Aviation(the Montreal Convention 1971) was adopted in 1971. After 9/11 incidents in 2001, to amend and supplement the Montreal Convention 1971, the Convention on the Suppression of Unlawful Acts Relating to International Civil Aviation(the Beijing Convention 2010) was adopted in 2010, and to supplement the Hague Convention 1970, the Protocol Supplementary to the Convention for the Suppression of Unlawful Seizure of Aircraft(the Beijing Protocol 2010) was adopted in 2010. Since then, in response to increased cases of unruly behavior on board aircrafts which escalated in both severity and frequency,, the Montreal Protocol which is seen as an amendment to the Convention on Offences and Certain Other Acts Committed on Board Aircraft(the Tokyo Convention 1963) was adopted in 2014. Korea ratified the Tokyo Convention 1963, the Hague Convention 1970, the Montreal Convention 1971, the Montreal Supplementary Protocol 1988, and the Convention on the Marking of Plastic Explosive 1991 which have proven to be effective. Under the Tokyo Convention ratified in 1970, Korea further enacted the Aircraft Navigation Safety Act in 1974, as well as the Aviation Safety and Security Act that replaced the Aircraft Navigation Safety Act in August 2002. Meanwhile, the title of the Aviation Safety and Security Act was changed to the Aviation Security Act in April 2014. The Aviation Security Act is essentially an implementing legislation of the Tokyo Convention and Hague Convention. Also the language of the Aviation Security Act is generally broader than the unruly and disruptive behavior in Sections 1-3 of the model legislation in ICAO Circular 288. The Aviation Security Act has reflected the considerable parts of the implementation of national legislation under the Beijing Convention and Beijing Protocol 2010, and the Montreal Protocol 2014 that are the modernized international conventions relating to aviation security. However, in future, when these international conventions would come into effect and Korea would ratify them, the national legislation that should be amended or provided newly in the Aviation Security Act are as followings : The jurisdiction, the definition of 'in flight', the immunity from the actions against the aircraft commander, etc., the compulsory delivery of the offender by the aircraft commander, etc., the strengthening of penalty on the person breaking the law, the enlargement of application to the accomplice, and the observance of international convention. Among them, particularly the Korean legislation is silent on the scope of the jurisdiction. Therefore, in order for jurisdiction to be extended to the extra-territorial cases of unruly and disruptive offences, it is desirable that either the Aviation Security Act or the general Crime Codes should be revised. In conclusion, in order to meet the intelligent and diverse aviation threats, the Korean government should review closely the contents of international conventions relating to aviation security and the current ratification status of international conventions by each state, and make effort to improve the legislation relating to aviation security and the aviation security system for the ratification of international conventions and the implementation of national legislation under international conventions.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.25-38
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• 2019

Selecting high-quality information that meets the interests and needs of users among the overflowing contents is becoming more important as the generation continues. In the flood of information, efforts to reflect the intention of the user in the search result better are being tried, rather than recognizing the information request as a simple string. Also, large IT companies such as Google and Microsoft focus on developing knowledge-based technologies including search engines which provide users with satisfaction and convenience. Especially, the finance is one of the fields expected to have the usefulness and potential of text data analysis because it's constantly generating new information, and the earlier the information is, the more valuable it is. Automatic knowledge extraction can be effective in areas where information flow is vast, such as financial sector, and new information continues to emerge. However, there are several practical difficulties faced by automatic knowledge extraction. First, there are difficulties in making corpus from different fields with same algorithm, and it is difficult to extract good quality triple. Second, it becomes more difficult to produce labeled text data by people if the extent and scope of knowledge increases and patterns are constantly updated. Third, performance evaluation is difficult due to the characteristics of unsupervised learning. Finally, problem definition for automatic knowledge extraction is not easy because of ambiguous conceptual characteristics of knowledge. So, in order to overcome limits described above and improve the semantic performance of stock-related information searching, this study attempts to extract the knowledge entity by using neural tensor network and evaluate the performance of them. Different from other references, the purpose of this study is to extract knowledge entity which is related to individual stock items. Various but relatively simple data processing methods are applied in the presented model to solve the problems of previous researches and to enhance the effectiveness of the model. From these processes, this study has the following three significances. First, A practical and simple automatic knowledge extraction method that can be applied. Second, the possibility of performance evaluation is presented through simple problem definition. Finally, the expressiveness of the knowledge increased by generating input data on a sentence basis without complex morphological analysis. The results of the empirical analysis and objective performance evaluation method are also presented. The empirical study to confirm the usefulness of the presented model, experts' reports about individual 30 stocks which are top 30 items based on frequency of publication from May 30, 2017 to May 21, 2018 are used. the total number of reports are 5,600, and 3,074 reports, which accounts about 55% of the total, is designated as a training set, and other 45% of reports are designated as a testing set. Before constructing the model, all reports of a training set are classified by stocks, and their entities are extracted using named entity recognition tool which is the KKMA. for each stocks, top 100 entities based on appearance frequency are selected, and become vectorized using one-hot encoding. After that, by using neural tensor network, the same number of score functions as stocks are trained. Thus, if a new entity from a testing set appears, we can try to calculate the score by putting it into every single score function, and the stock of the function with the highest score is predicted as the related item with the entity. To evaluate presented models, we confirm prediction power and determining whether the score functions are well constructed by calculating hit ratio for all reports of testing set. As a result of the empirical study, the presented model shows 69.3% hit accuracy for testing set which consists of 2,526 reports. this hit ratio is meaningfully high despite of some constraints for conducting research. Looking at the prediction performance of the model for each stocks, only 3 stocks, which are LG ELECTRONICS, KiaMtr, and Mando, show extremely low performance than average. this result maybe due to the interference effect with other similar items and generation of new knowledge. In this paper, we propose a methodology to find out key entities or their combinations which are necessary to search related information in accordance with the user's investment intention. Graph data is generated by using only the named entity recognition tool and applied to the neural tensor network without learning corpus or word vectors for the field. From the empirical test, we confirm the effectiveness of the presented model as described above. However, there also exist some limits and things to complement. Representatively, the phenomenon that the model performance is especially bad for only some stocks shows the need for further researches. Finally, through the empirical study, we confirmed that the learning method presented in this study can be used for the purpose of matching the new text information semantically with the related stocks.

• Journal of the Korean Chemical Society
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• v.44 no.5
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• pp.422-428
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• 2000

Optimum analytical conditions of the aluminium ion were established by flow injection analysis. Eriochrome Cyanine R(ECR) dye reacts with the aluminium ion at pH 6.0 to form a complex that exhibits maximum absorption at 535 nm. Reaction conditions including the mixing and the reaction coil length, the concentration and the pH of the buffer solutio, temperature, and injection loop volume were optimized to intro-duce this reaction into flow injection analysis. The results were as follows. A mixing coil length of 0.5 m and a reaction coil length of 4.0 m, the pH 6.0 and 1M of acetate buffer solution, the ECR concentration of 0.56 mM, the reaction temperature of 40$^{\circ}C$, the injection loop volume of 300${\mu}L$ were chosen as optimum conditions. Under these conditions the detection limit of the aluminiumion was less than 0.05 mg/L and the repeatability was better than 1%. A sampling frequency of 24 times for an hour was achieved. Interfering ions such as $F^-$, HP$O_4^{2-}$, $Fe^{2+}$, $Fe^{3+}$, $Mn^{2+}$, and other anions were tested, interference did not occur up to 1,000mg/L of ion concentration and up to 2,CO0mg/L of sulfate ion con-centration. This method was applied for the determination of aluminium ion in tap water and ground water of Jeonju and the Gochang area. The results showed that the aluminium residual in tap water of the Jeonju area was at a mean of 0.478mg/L and that in tap water of the Gochang area was at a mean of 0.278mg/L. Aluminium ion residual of the tap waters in the Jeonju area was higher level than that in the Gochang area. Aluminium residual in the ground water of the Jeonju area was 0.386 mg/L and was lower compared to 0.564 mg/L for the Gochang area.

• Korean Journal of Psychosomatic Medicine
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• v.27 no.1
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• pp.50-59
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• 2019

Objectives : Many of the patients with type 2 diabetes are associated with sleep problems, and the rate of insomnia is known to be higher in the general population. The aims of this study were to know the frequency and clnical characteristics of insomnia, and related variables to insomnia in patients diagnosed with type 2 diabetes. Methods : For 99 patients from 18 to 80 years of age (65 males and 34 females) with type 2 diabetes, interviews were performed. Total sleep time and sleep latency was evaluated. Insomnia was evaluated using the Korean Version of the Insomnia Severity Index (ISI-K). Severity of depressive symptoms were evaluted using the Korean version of the Hamilton Depression Scale (K-HDRM). According to the cutoff score of 15.5 on the ISI-K, subjects were divided into the group of type 2 diabetics with insomnia (N=34) and those without insomnia (N=65) at first, and then statistically analyzed. Results : TInsomnia could be found in 34.34% of type 2 diabetics. Type 2 diabetics with insomnia had significantly more single or divorced (respectively 11.8%, p<0.05), higher total scores of the K-HDRS ($11.76{\pm}5.52$, p<0.001), shorter total sleep time ($5.35{\pm}2.00hours$, p<0.001), and longer sleep latency ($50.29{\pm}33.80minutes$, p<0.001). The all item scores of the ISI-K in type 2 diabetics with insomnia were significantly higher than those in type 2 diabetics without insomnia, that is, total ($18.38{\pm}2.69$), A1 (Initial insomnia) ($2.97{\pm}0.76$), A2 (Middle insomnia) ($3.06{\pm}0.69$), A3 (Terminal insomnia) ($2.76{\pm}0.61$), B (Satisfaction) ($3.18{\pm}0.72$), C (Interference) ($2.09{\pm}0.97$), D (Noticeability) ($2.12{\pm}1.09$) and E (Distress) ($2.21{\pm}0.81$) (respectively p<0.001). Variables associated with insomnia in type 2 diabetics were as following. Age had significant negative correlation with A3 items of the ISI-K (${\beta}=-0.241$, p<0.05). Total scores of the K-HDRS had significant positive correlation, while total sleep time had significant negative correlation with all items of the ISI-K (respectively p<0.05). Sleep latency had significant positive correlation with total,, A1, B and E item scores of the ISI-K (respectively p<0.05). Conclusions : Insomnia was found in about 1/3 of type 2 diabetics. According to the presence of insomnia, clinical characteristics including sleep quality as well as quantity seemed to be different. Because depression seemed to be correlated with insomnia, clinicians should pay attention to early detection and intervention of depression among type 2 diabetics.