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The authors analized statistically 635 cases of pathologically confirmed central nervous system tumors in the Chonnam and Chonbuk provinces from 1987 to 1989. The results were as follows : 1) Of the 635 cases, 327 cases(51.5%) were male and 308 cases(48.5%) were female. 2) Intracranial tumors were 518 cases(81.6%), spine and intraspinal tumors 94(14.8%), scalp and skull tumors 23(3.6%). 3) Average incidence rate of tumors was 3.5/year/100,000 population, 3.1 for Chonnam province, 4.4 for Chonbuk province. 4) Among the brain tumors, glial tumors were the most common(28.4%), and followed by meningiomas(18%), pituitary tumors(15.2%), metastatic tumors(8.9%), Among the intraspinal tumors, neurinomas and neurofibromas were found most frequently(41.5%), and rests were metastatic tumors(23.4%), meningiomas(9.5%) in order. 5) Sexual predilection of tumors was as follows : male preponderance was noted for oligodendrogliomas(9: 1), metastatic tumors(2.3:1), glioblastomas multiforme(GM)(1.8:1) cysticercoses(1.6:1), and female preponderance for meningiomas(1:3.2), pituitary tumors(1:2), paragonimiases(1:1.5). 6) The incidence rate of brain tumors in children below 15 years was 11.8% and that which occurred infratentorially was 47.5%. 7) The brain tumors were found mainly in cerebral hemispheres, in which area most of tumors were meningiomas, astrocytomas in order. In sellar, parasellar most of tumors were meningiomas, astrocytomas in order. In sellar, parasellar and suprasellar region, the majority of tumors were pituitary tumors and meningiomas. 8) Cysticercoses showed a predilection for the sixth and seventh decades, meningiomas, metastatic tumors, neurinomas for sixth decade, GM and supratentorial astrocytomas for fourth, fifth and sixth decades, oligodendroliomas for fifth decade, infratentorial astrocytomas, medulloblastomas and craniopharyngiomas for first and second decades. 9) In the spinal tumors, the favorable site was thoracic region and majority of them were located intradural extramedullarily and extradurally in similar incidence.
본논문에서는 LFM (Linear Frequency Modulated) 신호를 사용하는 능동소나에서 적은 연산량으로 표적반사신호의 시간지연과 도플러를 추정하는 기법을 제안하였다. 제안한 기법에서는 일반적인 추정기법들이 가지는 연산량의 문제를 해결하기 위해 LFM 신호의 상호모호함수 (cross ambiguity function)에서 시간지연과 도플러의 관계를 나타내는 대수적인 관계식을 이용하였다. FML (Fast Maximum Likelihood) 기법을 기반으로 하여 시간지연과 도플러의 대수적 관계식을 유도하였으며, 이를 이용하여 일반적인 2차원 탐색 대신 2번의 1차원 탐색으로 시간지연과 도플러를 추정하였다. 다양한 신호대 잡음비 (SNR)에서 제안한 알고리즘의 추정오차를 분석하였으며, 제안한 알고리즘이 우수한 추정 성능을 보임을 확인하였다. In this paper, a computationally efficient time delay and doppler estimation algorithm is proposed for active sonar with Linear Frequency Modulated (LFM) signal. To reduce the computational burden of the conventional estimation algorithm, an algebraic equation is used which represents the relationship between the time delay and doppler in cross-ambiguity function of the LFM signal. The algebraic equation is derived based on the Fast maximum Likelihood (FML) method. Using this algebraic relation, the time delay and doppler are estimated with two 1-D search instead of the conventional 2-D search. The estimation errors of the proposed algorithm are analyzed for various SNR's. The simulation result demonstrates the good performance of the proposed algorithm.
본 논문에서는 차량용 반도체가 제품 출하 후 사용 환경에 따라 발생되는 불량률을 데이터 마이닝 기법을 이용하여 분석하였다. 20세기 이후 가장 보편적인 이동 수단인 자동차는 전자 컨트롤 장치와 자동차용 반도체의 사용량이 급격히 증가하면서 매우 빠른 속도로 진화하고 있다. 자동차용 반도체는 차량용 전자 컨트롤 장치 중 핵심 부품으로 소비자들에게 안정성, 연료 사용의 효율성, 운전의 안정감을 제공하기 위해 사용되고 있다. 자동차용 반도체는 가솔린엔진, 디젤 엔진, 전기 모터를 컨트롤하는 기술, 헤드업 디스플레이, 차선 유지 시스템 등 많은 부분에 적용되고 있다. 이와 같이 반도체는 자동차를 구성하는 거의 모든 전자 컨트롤 장치에 적용되고 있으며 기계적인 장치를 단순히 조합한 이상의 효과를 만들어 내고 있다. 자동차용 반도체는 10년 이상의 자동차 사용 기간을 고려하여 높은 신뢰성, 내구성, 장기공급 등의 특성을 요구하고 있다. 자동차용 반도체의 신뢰성은 자동차의 안전성과 직접적으로 연결되기 때문이다. 반도체업계에서는 JEDEC과 AEC 등의 산업 표준 규격을 이용하여 자동차용 반도체의 신뢰성을 평가하고 있다. 또한 자동차 산업에서 표준으로 제시한 신뢰성 실험 방법과 그 결과를 이용하여 개발 초기 단계 및 제품 양산 초기 단계에서 제품의 수명을 예측 하고 있다. 하지만 고객의 다양한 사용 조건 및 사용 시간 등 여러 변수들에 의해 발생되는 불량률을 예측하는 데는 한계가 있다. 이러한 한계점을 극복하기 위하여 학계와 산업계에서 많은 연구가 있어왔다. 그 중 데이터 마이닝 기법을 이용한 연구가 다수의 반도체 분야에서 진행되고 있지만, 아직 자동 차용 반도체에 대한 적용 및 연구는 미비한 상태이다. 이러한 관점에서 본 연구는 데이터 마이닝 기법을 이용하여 반도체 조립(Assembly) 과 패키지 테스트(Package test) 공정 중 발생 된 데이터들간의 연관성을 규명하고, 고객 불량 데이터를 이용하여 잠재 불량률 예측에 적합한 데이터 마이닝 기법을 검증하였다. Since the 20th century, automobiles, which are the most common means of transportation, have been evolving as the use of electronic control devices and automotive semiconductors increases dramatically. Automotive semiconductors are a key component in automotive electronic control devices and are used to provide stability, efficiency of fuel use, and stability of operation to consumers . For example, automotive semiconductors include engines control, technologies for managing electric motors, transmission control units, hybrid vehicle control, start/stop systems, electronic motor control, automotive radar and LIDAR, smart head lamps, head-up displays, lane keeping systems. As such, semiconductors are being applied to almost all electronic control devices that make up an automobile, and they are creating more effects than simply combining mechanical devices. Since automotive semiconductors have a high data rate basically, a microprocessor unit is being used instead of a micro control unit. For example, semiconductors based on ARM processors are being used in telematics, audio/video multi-medias and navigation. Automotive semiconductors require characteristics such as high reliability, durability and long-term supply, considering the period of use of the automobile for more than 10 years. The reliability of automotive semiconductors is directly linked to the safety of automobiles. The semiconductor industry uses JEDEC and AEC standards to evaluate the reliability of automotive semiconductors. In addition, the life expectancy of the product is estimated at the early stage of development and at the early stage of mass production by using the reliability test method and results that are presented as standard in the automobile industry. However, there are limitations in predicting the failure rate caused by various parameters such as customer's various conditions of use and usage time. To overcome these limitations, much research has been done in academia and industry. Among them, researches using data mining techniques have been carried out in many semiconductor fields, but application and research on automotive semiconductors have not yet been studied. In this regard, this study investigates the relationship between data generated during semiconductor assembly and package test process by using data mining technique, and uses data mining technique suitable for predicting potential failure rate using customer bad data.
Korean grape-seed that is one of the agricultural wastes was used as a raw material to prepare activated carbon through roasting, carbonization and chemical activation processes. NaOH was used as activation reagent. It was examined the chracteristics of activated carbon through BET specific surface area, pore size distribution, average pore radius, pore volume and SEM photograph. The mixing of the ratio of the grape-seed and activation reagent was varied to 100 ~ 300 weight percent. The surface areas of the activated carbon manufactured from the grape-seed were 47.9- 121.3 ㎡/g. Adsorption of n-Hexane gas by our activated carbon under gas phase was carried out and structural change of pore surface was observed by SEM.
Activated carbon was produced from grape-seed, which is an agricultural by-product, by chemical activation with NaOH, KOH and ZnCl₂. It was examined the characteristics of activated carbon through BET specific surface area, N₂ adsorption isotherm, pore size distribution, average pore radius, pore volume and SEM photograph. Especially, most important factor of activated carbon produced by chemical activation was a ratio of chemical agent. The N₂-BET specific surface areas of activated grape-seed char prepared by chemical activation were measured as about 44.09 -121.33 ㎡/g with 100-300 wt% chemical ratio of NaOH, KOH and ZnCl₂, respectively. Removal of chromium in solution by activated carbon was carried out.
Activated carbon was widely used in industrial application such as purification of gas and water, catalyst, or catalyst support and separation process etc., owing to its highly adsorption capacity. In this paper, activated carbon was produced from water-melon seed, which is an agricultural by product, by chemical activation with ZnCl₂, NaOH and KOH. Preparation process involve the roasting of raw material and carbonization of roasted material followed by chemical activation. N₂-BET specific surface areas of activated water-melon char prepared by chemical activation were measured as 128-978 ㎡/g with 100-300 wt% chemical ratio of ZnCl₂, NaOH and KOH, respectively. Removal of phenol in solution by activated carbon was carried out and structure change of pore surface was observed by SEM.
This paper proposes a method of generating an array signal with directionality using Interpolation &Decimation Filtering process. We have selected triangular type sensor array model which is used to estimate the direction of the input signal and Polyphase Interpolation Filter is used for real time process. The input signal to the sensor has been modeled as a sum of a broadband component and discrete lines. Frequency-Domain Beamforming method is used to verify the directivity of array signal. Finally the validity of the proposed array signal model will be confirmed by computer simulation.
Specular structural colors generated by two-dimensional periodic binary gratings are investigated theoretically. An approximate mathematical model of the grating specular structural colors is described, based on scalar nonparaxial diffraction theory, and the functional relationships of specular structural color and structural parameters of gratings are analyzed. Through this, the optimal condition for maximizing the color-representation range in the standard CIE 1931 chromaticity diagram is derived.