• International Journal of Computer Science & Network Security
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• 제23권4호
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• pp.166-171
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• 2023

The Stock price analysis is an increasing concern in a financial time series. The purpose of the study is to analyze the price parameters of date, high, low, and news feed about the stock exchange price. Long short term memory (LSTM) is a cutting-edge technology used for predicting the data based on time series. LSTM performs well in executing large sequence of data. This paper presents the Long Short Term Memory Model has used to analyze the stock price ranges of 10 days and 20 days by exponential moving average. The proposed approach gives better performance using technical indicators of stock price with an accuracy of 82.6% and cross entropy of 71%.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2022년도 추계학술대회
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• pp.123-125
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• 2022

본 논문에서는 Yolo-pose를 이용하여 장단기 메모리(Long short-term Memory)에 적용하는 시스템을 소개한다. 영상데이터로부터 Yolo-pose를 이용하여 일상생활과 낙상으로 구분된 데이터를 추출하여 LSTM에 적용하여 학습시킨다. 학습은 오버피팅을 방지하기 위하여 8대2의 Validation을 진행하며 Confusion matrix로 나타낸다. Yolo-pose의 결과값은 sensitivity와 specificity 모두 100%를 기록하여 일상생활과 낙상을 잘 구분하는 것을 확인 하였다.

• 한국IT서비스학회지
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• 제16권1호
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• pp.73-82
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• 2017

Recently in-memory data stream processing has been actively applied to various subjects such as query processing, OLAP, data mining, i.e., frequent item sets, association rules, clustering. However, finding regular periodic patterns of events in an infinite data stream gets less attention. Most researches about finding periods use autocorrelation functions to find certain changes in periodic patterns, not period itself. And they usually find periodic patterns in time-series databases, not in data streams. Literally a period means the length or era of time that some phenomenon recur in a certain time interval. However in real applications a data set indeed evolves with tiny differences as time elapses. This kind of a period is called as a pseudo-period. This paper proposes a new scheme called FPMH (Finding Periods using Multiple Hash functions) algorithm to find such a set of pseudo-periods over a data stream based on multiple hash functions. According to the type of pseudo period, this paper categorizes FPMH into three, FPMH-E, FPMH-PC, FPMH-PP. To maximize the performance of the algorithm in the data stream environment and to keep most recent periodic patterns in memory, we applied decay mechanism to FPMH algorithms. FPMH algorithm minimizes the usage of memory as well as processing time with acceptable accuracy.

• 대한전자공학회논문지SD
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• 제45권2호
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• pp.69-81
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• 2008

메모리 기술이 발달함에 따라 메모리의 집적도가 증가하게 되었고, 이러한 변화는 구성요소들의 크기를 작아지게 만들고, 고장의 감응성이 증가하게 하였다. 그리고 고장은 더욱 복잡하게 되었다. 또한, 칩 하나에 포함되어있는 저장 요소가 늘어남에 따라 테스트 시간도 증가하게 되었다. 본 논문에서 제안하는 테스트 구조는 내장 테스트를 사용하여 외부 테스트 환경 없이 테스트가 가능하다. 제안하는 내장 테스트 구조는 여러 알고리즘을 적용 가능하므로 높은 효율성을 가진다. 또한 고장 난 메모리를 여분의 메모리로 재배치함으로써 메모리 수율 향상과 사용자에게 메모리를 투명하게 사용할 수 있도록 제공할 수 있다. 본 논문에서는 고장 난 메모리 부분을 여분의 행과 열 메모리로 효율적인 재배치가 가능한 복구 기술을 포함한다. 재배치 정보는 고장 난 메모리를 매번 테스트 해야만 얻을 수 있다. 매번 테스트를 통해 재배치 정보를 얻는 것은 시간적 문제가 발생한다. 이것을 막기 위해 한번 테스트해서 얻은 재배치 정보를 플래시 메모리에 저장해 해결할 수 있다. 본 논문에서는 플래시 메모리를 이용해 재배치 정보의 활용도를 높인다.

• 재활간호학회지
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• 제1권1호
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• pp.61-71
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• 1998

Defining prediction variables related to metamemory for the adults in aging process has worthwhile meaning from the perspective that the produced results can be helpful to reducing the difficulty of memorizing efforts and it can also enhance quality of life of aged. This study attempted to analysis relationship between perceived health status, depression, memory self-efficacy and meta memory for the subjects of middle age and old age adults. This study was designed by adopting descriptive correlational analysis method for the 468 middle and old age adults who are living in Seoul. Samples were selected by convenience sampling. Data collection was done over 1 month period in june 1998. The instruments used in this study were health status measuring scale including depression measuring scale, memory self efficacy measuring scale and metamemory measuring scale which were verified for reliability. Data collected were analized by using SPSS for frequency, Peason correlation, t-test and ANOVA according to the variables character and the study purposes. Results of the study were as follows. 1. Relationship between perceived health status, depression, memory self-efficacy and metamemory. Relational analyses between perceived health status, depression, memory self-efficacy and metamemory supported the hypotheses of 1st, 2nd and 3rd(p < .01). These results suggested that the aged perceived great health status then their memory self-efficacy, and metamemory showed the high scores. In the case of depression when its level became decreased metamemory was inclined to increased. Thus, it is identified that strong relationship exists between these variables. 2. Perceived health status, depression, memory self-efficacy by subject's general characteristics. Scores of perceived health status were high in the group of man compared to the group of women, and also highly educated group showed great perceived health status. Group of persons having occupation showed high score of perceived health status and low depression score. The score of memory self-efficacy and metamemory showed higher in the middle aged than the old aged. The high scores of memory self-efficacy and metamemory were found in the group of highly educated people and who have continuing education. The high scores of memory self-efficacy were found in the group of persons having their job and high metamemory scores found in the group of persons having religion. In summary, the greater perceived health status and memory self-efficacy, the more metamemory scores were likely increased and the more depression level was decreased, the more metamemory was likely increased. Also it was found that general characteristics like educational level, continuing education and religion influenced the metamemory of the aged. Therefore, prevention the aged from getting depression and activation of health promotion are needed to delay time of memory loss.

• 한국정보과학회논문지:시스템및이론
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• 제34권8호
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• pp.377-384
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• 2007

최근 VLSI 회로 직접도가 급속도로 증가함에 따라 하나의 시스템 칩에 고밀도와 고용량의 내장 메모리가 구현되고 있다. 고장난 메모리를 여분의 메모리로 재배치함으로써 메모리 수율 향상과 사용자에게 메모리를 투명하게 사용할 수 있도록 제공할 수 있다. 본 논문에서는 고장난 메모리 부분을 여분의 행과 열 메모리로 효율적인 재배치를 위해 재배치 알고리즘을 제안하고자 한다. 재배치 정보는 고장난 메모리를 매번 테스트해야만 얻을 수 있다. 매번 테스트를 통해 재배치 정보를 얻는 것은 시간적 문제가 발생한다. 이것을 막기 위해 한번 테스트해서 얻은 재배치 정보를 플래시 메모리에 저장해 해결할 수 있다. 본 논문에서는 플래시 메모리를 이용해 재배치 정보의 활용도를 높인다.

• 한국전자통신학회논문지
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• 제10권5호
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• pp.539-548
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• 2015

본 논문에서는 프로세서별 서로 다른 버스에 서로 다른 운영체제를 갖는 멀티코어 시스템에서 공유 메모리 기능을 구현하고, 임베디드 리눅스 시스템을 통하여 두 프로세서 사이에서 공유 메모리 기능을 실험하였다. 듀얼 버스 구조에서 공유 메모리 구현을 위해 메모리 컨트롤러를 이용하였으며, 리스트 자료구조를 통하여 공유 메모리 세그먼트를 관리한다. AMP 멀티 코어 실험을 위하여 2개의 프로세서 코어에 리눅스 운영체제를 탑재하도록 하였다. 그리고 공유 메모리 테스트를 위하여 구현된 커널 모듈을 이용하여 공유 메모리 생성 및 이용이 가능함을 확인 하였다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2020년도 추계학술발표대회
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• pp.20-23
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• 2020

This research is to design an effective prefetching method required for DRAM-PCM hybrid main memory systems especially used for big data applications and massive-scale computing environment. Conventional prefetchers perform well with regular memory access patterns. However, workloads such as graph processing show extremely irregular memory access characteristics and thus could not be prefetched accurately. Therefore, this research proposes an efficient dynamical prefetching algorithm based on the regression method. We have designed an intelligent prefetch engine that can identify the characteristics of the memory access sequences. It can perform regular, linear regression or polynomial regression predictive analysis based on the memory access sequences' characteristics, and dynamically determine the number of pages required for prefetching. Besides, we also present a DRAM-PCM hybrid memory structure, which can reduce the energy cost and solve the conventional DRAM memory system's thermal problem. Experiment result shows that the performance has increased by 40%, compared with the conventional DRAM memory structure.

• 전기전자학회논문지
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• 제10권1호
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• pp.22-29
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• 2006

본 논문에서는 마이크로프로세서와 주변블록 사이에서 SDRAM을 사용함에 있어서 DMA(Direct Memory Access)에 의한 효율적인 SDRAM 접근방식을 제시하고 있다. 여기에서 마이크로프로세서는 AMBA 버스를 통해서 SDRAM에 접근을 하고 DMA는 DMA 전용 버스를 통해서 SDRAM에 접근한다. 마이크로프로세서가 SDRAM에 접근하지 않고 다른 레지스터에 접근하거나, 아니면 마이크로프로세서 캐쉬에서 히트(hit)신호가 발생하여 SDRAM에 접근할 필요가 없을 때에 주변 블록에서는 DMA를 통해서 SDRAM에 접근하여 데이타를 읽거나 쓰기 동작을 통해서 SDRAM을 효율적으로 사용할 수 있다. 이 방법은 DMA가 마이크로프로세서의 SDRAM 억세스를 최소한의 방해로 SDRAM을 사용할 수 있다. 이와 같은 방법을 이용함으로써 전체적인 시스템 효율을 높여 약 16.8% 정도의 성능 향상 효과를 가져옴을 확인 할 수 있었다.

• 재활간호학회지
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• 제3권2호
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• pp.181-195
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• 2000

The purpose of this study is to find out the effects of personal characteristics, social support, depression, and metamemory on the older adults' memory performances. The subjects of the study consisted of 95 older adults over the age of 60 who are living in Busan. Some data were collected by means of the interview method, using questionnaires for metamemory (MIA questionnaire by Dixon, et al., 1988), and depression(GDS by Yesavage and Sheikl, 1986), social resoueces(Duke university, 1978), family support(Hyun-Sook Kang, 1985). The other data were collected by the testing method on the memory performance such as the immeadiate word recall task, the delayed word recall task, the word recognition task(Elderly Verbal Learning Test by Kyung Mi Choi, 1998), and the face recognition task(Face Recognition Task tool developed by Hye-Sook Min). The results of this study were as follows; 1. The level of metamemory is 3.4 points in the 5 point scale, the grades of the task and the achievement are relatively high and the grades of the change, the control, and the anxiety are relatively low in the sub-concepts. 2. Metamemory have significant relation with age(r=-.44), educational attainment(r=.46), depression(r=-.58), family support(r=.20), social resources(r=.20). 3. The significant variables to predict older adults' metamemory are educational attainment(22%), sex(11%), age (8.3%), depression(4.7%), and illness state(3%). 4. The strong variables to predict memory performances are metamemory, age, depression, social resources, educational attainment, illness state, and limitation of daily living activity related to illness. In conclusion, the enhancement strategies of metamemory and the social support and the prevention or reduction of depression are necessary to increase older adults' memory performances. Ultimately in this respect nurses' roles are very important in developing and performing some intervention programs for old adults' memory improvement, which have significant meanings in the field of nursing science.