Earticle

There are many signals around us. We are able to use the desired signals in the PLC environment through the data signal communication whenever we want. The natural signals are likely to have the continuous time form. To use them for signal communication, the sampling process of transforming them into discrete signals is needed. It is to transform the continuous signals into the discrete signals and to reconstruct them into the continuous signals in the desired place and at the desired time. The sampling interval is related to the reconstruction. This thesis will take a deep look at the sampling process for the effective signal reconstruction.

Bayesian Personalized Ranking (BPR) assigns ranks to a set of items to recommend them to users. This study proposes a novel approach to improve the performance of recommendation systems. The first proposed method for the enhanced recommendation system constructs positive preferences by utilizing only the items explicitly preferred by users rather than treating all interacted items (e.g., clicked, rated, or reviewed) as positive, as was traditionally done. The second method involves using explicitly non-preferred items as negative data, and the traditional approach of using only noninteracted items as negative. Message propagation is performed on subgraphs generated through meta-path design. The results of each subgraph are used to learn the representations of users and items through an attention mechanism and graph representation learning based on this data configuration. The system then predicts scores for user-item pairs. For evaluation, the performance of the recommendation system was assessed using not only traditional accuracy metrics but also by defining a pairwise ranking accuracy metric. Pairwise ranking accuracy assigns ranks to preferred and non-preferred items to determine if the model reflects user preferences. Experimental results showed improved performance in widely used evaluation metrics for recommendation systems, such as Hit Rate and Normalized Discounted Cumulative Gain, and higher performance in pairwise ranking accuracy.

최근 아일랜드 보건당국, 美송유관 등 全세계적으로 랜섬웨어 피해가 급증하고 있으며, 사회 모든 분야에 피 해를 입히고 있다. 특히, 랜섬웨어 탐지 및 대응에 기존의 탐지방법뿐 아니라 머신러닝 등을 이용한 연구가 늘어 나고 있다. 하지만, 전통적인 머신러닝은 모델이 데이터가 많은 쪽으로 예측하는 경향이 강해 정확한 예측값을 추 출하기 어려운 문제점이 있다. 이에 다수(Majority)의 Non-Ransomware(정상코드 또는 멀웨어)와 소수의(Minorit y) Ransomware로 구성된 불균형(Imbalance) 클래스에서 샘플링 기법을 통해 불균형을 해소하고 랜섬웨어탐지 성능을 향상시키는 기법을 제안하였다. 본 실험에서는 두가지 시나리오(Binary, Multi Classification)을 사용하여 샘플링 기법이 다수 클래스의 탐지 성능을 유지하면서 소수 클래스의 탐지 성능을 개선함을 확인하였다. 특히, 제 안된 혼합샘플링 기법(SMOTE+ENN)이 10% 이상의 성능(G-mean, F1-score) 향상을 도출했다.

Recently, ransomware damage has been increasing rapidly around the world, including Irish health authorities and U.S. oil pipelines, and is causing damage to all sectors of society. In particular, research using machine learning as well as existing detection methods is increasing for ransomware detection and response. However, traditional machine learning has a problem in that it is difficult to extract accurate predictions because the model tends to predict in the direction where there is a lot of data. Accordingly, in an imbalance class consisting of a large number of non-Ransomware (normal code or malware) and a small number of Ransomware, a technique for resolving the imbalance and improving ransomware detection performance is proposed. In this experiment, we use two scenarios (Binary, Multi Classification) to confirm that the sampling technique improves the detection performance of a small number of classes while maintaining the detection performance of a large number of classes. In particular, the proposed mixed sampling technique (SMOTE+ENN) resulted in a performance(G-mean, F1-score) improvement of more than 10%.

침입탐지 분야에서 딥러닝과 머신러닝을 이용한 탐지성능이 검증되면서 이를 활용한 사례가 나날이 증가하고 있다. 하지만, 학습에 필요한 데이터 수집이 어렵고, 수집된 데이터의 불균형으로 인해 머신러닝 성능이 현실에 적용되는데 어려움이 있다. 본 논문에서는 이에 대한 해결책으로 불균형 데이터 처리를 위해 t-SNE 시각화를 이용한 혼합샘플링 기법을 제안한다. 이를 위해 먼저, 페이로드를 포함한 침입탐지 이벤트에 대해서 특성에 맞게 필드를 분리한다. 분리된 필드에 대해 TF-IDF 기반의 피처를 추출한다. 추출된 피처를 기반으로 혼합샘플링 기법을 적용 후 t-SNE를 이용한 데이터 시각화를 통해 불균형 데이터가 처리된 침입탐지에최적화된데이터셋을얻게된다. 공개침입탐지데이터셋CSIC2012를통해9가지샘플링기법을적용하였으며, 제안 한 샘플링 기법이 F-score, G-mean 평가 지표를 통해 탐지성능이 향상됨을 검증하였다.

As the detection performance using deep learning and machine learning of the intrusion detection field has been verified, the cases of using it are increasing day by day. However, it is difficult to collect the data required for learning, and it is difficult to apply the machine learning performance to reality due to the imbalance of the collected data. Therefore, in this paper, A mixed sampling technique using t-SNE visualization for imbalanced data processing is proposed as a solution to this problem. To do this, separate fields according to characteristics for intrusion detection events, including payload. Extracts TF-IDF-based features for separated fields. After applying the mixed sampling technique based on the extracted features, a data set optimized for intrusion detection with imbalanced data is obtained through data visualization using t-SNE. Nine sampling techniques were applied through the open intrusion detection dataset CSIC2012, and it was verified that the proposed sampling technique improves detection performance through F-score and G-mean evaluation indicators.

This paper investigates the evaluation case of Korean translated texts of Jane Austen’s Pride and Prejudice which was conducted by Scholars for English Studies in Korea. The project group stated in the evaluation report published in 2005 that they couldn’t find either the best recommendable Korean translation or the second best one. This finding shows the following major challenges in the criticism : First, sampling-The quality of a few pages can't represent that of the whole text; Second, unconsidered translator's variety of expressions based on their idiolects or styles-The evaluators, exclusive of translators, overlooked a translator's unique way of conveying meaning; Third, failure to focus on literariness or poetics-Literature translation criticism needs to go beyond fidelity & readability evaluation applying to general informative texts.

본 연구는 Gibbs sampler와 MTDFREML 방법에 의해서 한우 도체형질의 유전력 및 유전(공)분산을 단형질 및 다형질 개체모형을 가지고 추정하고 비교 하였다. 배장근단면적(longissimus dorsi area), 등지방 두께(backfat thickness), 상강도(marbling score)의 유전 모수를 추정하였으며, 분석에 이용된 자료는 총 1,941두 이고, 혈연계수를 구하기 위한 혈통 자료는 23,058두를 이용하였다. 도체형질에 대한 유전력 추정 시 단형질과 다형질 개체모형에 의한 편차는 크게 나타나지 않았다. 단형질 개체모형에서 Gibbs sampler 방법을 이용한 추정에서는 LDA, BF 및 MS에서 각각 0.52, 0.59 및 0.42로서 고도의 유전력을 보였다. MTDFREML 방법을 통한 추정 시에는 LDA 0.41, BF 0.52로서 고도의 유전력을 보였으며, MS는 0.32로서 중도의 유전력을 보였다. 분석 방법에 의한 유전력 추정은 Gibbs sampler에 의한 방법이 MTDFREML에 의한 방법에 비해서 0.1정도 높게 추정되었다. MTDFREML 방법과 Gibbs Sampler 방법에 의한 도체 형질간의 유전상관은 LDA와 BF, MS 간에는 모두 부의 상관을 보였고, BF과 MS에서는 정의 상관을 보였다. MTDFREML과 Gibbs Sampler에서 이들의 분석 방법 간에 육종가 추정치에 대한 상관계수는 LDA와 BF에서는 0.989 이상의 높은 추정치를 보였으나, MS에 대해서는 이보다 다소 낮은 0.985를 나타내었다. 그리하여, 상강도(marbling score)와 같은 범주형 자료에 대한 유전분석은 기존의 선형의 정규분포를 가정한 REML방법에 의한 것 보다 범주형 모형을 설정하여 Gibbs sampling algorithm을 응용한 분석방법이 더 적합할 것으로 사료된다.

The objective of this study was to compare of genetic parameter estimates on carcass traits of Hanwoo(Korean Cattle) according to modeling with Gibbs sampler and MTDFREML. The data set consisted of 1,941 cattle records with 23,058 animals in pedigree files at Hanwoo Improvement Center. The variance and covariance among carcass traits were estimated via Gibbs sampler and MTDFREML algorithms. The carcass traits considered in this study were longissimus dorsi area, backfat thickness, and marbling score. Genetic parameter estimates using Gibbs sampler and MTDFREML from single-trait analysis were similar with those from multiple-trait analysis. The estimated heritabilities using Gibbs sampler were .52～.54, .54 ～.59, and .42～.44 for carcass traits. The estimated heritabilities using MTDFREML were .41, .52～.53, and .31～.32 for carcass traits. The estimated genetic correlation using Gibbs sampler and MTDFREML of LDA between BF and MS were negatively correlated as .34～.36, .23～.37. Otherwise, genetic correlation between BF and MS was positive genetic correlation as .36～.44. The correlations of breeding value for marbling score between via MTDFREML and via Gibbs sampler were 0.989, 0.996 and 0.985 for LDA, BF and MS respectively.

본 연구는 한우의 도체형질들에 대한 유전적 변이를 분석방법에 따라 어떠한 차이가 있는지를 알아보고자 한우 후대검정자료를 이용하여 분석하였다. 분석에 이용된 도체성적 관련 자료는 가축개량사업소와 한우개량단지에서 1996년부터 2001년까지 태어난 후대검정우 1526두로부터 조사었다. 한우에 있어서 주요 개량형질인 육량과 육질에 영향하는 도체중, 도체율, 배최장근단면적, 등지방두께, 근내지방도를 대상으로 유전력과 유전상관을 추정하였다. 유전모수 추정에 있어서 REML 분석법과 Bayesian추론방법으로써 Gibbs Sampling 분석법을 사용하였는데 각각의 모수들에 대한 Gibbs Sampler는 100,000회 실시하였고 초기 1,000회는 모수의 사후분포에 대한 부정확성으로 간주하여 모수의 사후분포특성 규명에서 제외하였다. 각각의 형질들에 대한 유전변이는 이러한 두 가지 분석방법을 상호 비교 함으로써 최적의 통계분석방법을 모색하였다.도체형질에 대한 유전력 추정은 REML 방법을 통한 추정에서는 근내지방도가 0.51로 고도의 유전력을 보였고, 도체율이 0.25로 중도의 유전력이 추정되었다. Gibbs Sampling 방법을 통한 추정에서도 근내지방도가 0.54로 고도의 유전력을 도체율에서 0.25로 중도의 유전력을 보였다. REML 분석방법과 Gibbs Sampling 분석방법에서의 유전력은 다소 큰 차이는 보이지 않았으나, 대체로 Gibbs Sampling 방법으로 분석한 유전력 추정치가 높게 추정되었다.그리고, 유전상관분석에서는 REML 방법을 통한 분석에서 도체중과 배최장근단면적에서 0.651로 높은 정의 유전상관을 나타내었고, 배최장근단면적과 등지방두께에서 -0.139로 부의 유전상관을 나타내었다. Gibbs Sampling 방법에서는 도체중과 도체율, 배최장근단면적에서 각각 0.814, 0.695으로 높은 정의 상관을 나타내었고, 배최장근단면적과 등지방두께에서 -0.126으로 부의상관을 나타내었다. Gibbs Sampling 방법을 통한 분석에서 특정 형질간 유전상관이 높게 나타났으며, 다소 큰 차이를 보이지 않았다.REML 분석방법과 Bayesian Inference를 바탕으로 한 Gibbs Sampling 분석에서 모수 추정은 큰 차이를 보이지 않았다. 따라서 방대한 현장정보를 활용하여 보다 정확한 모수 추정을 수행하기 위해서는 분석모형에 대한 계수행렬의 역행렬 계산을 통한 REML 방법의 한계성을 극복할 수 있는 방법으로써 Gibbs Sampling 분석 방법이 가능할 것으로 사료된다.

The aims of this study were to estimate genetic parameters for carcass traits on Hanwoo(Korean Native Cattle) and to compare two different statistical algorithms for estimating genetic parameters. Data obtained from 1526 steers at Hanwoo Improvement Center and Hanwoo Improvement Complex Area from 1996 to 2001 were used for the analyses. The carcass traits considered in these studies were carcass weight, dressing percent, eye muscle area, backfat thickness, and marbling score. Estimated genetic parameters using EM-REML algorithm were compared to those by Bayesian inference via Gibbs Sampling to find out statistical properties. The estimated heritabilities of carcass traits by REML method were 0.28, 0.25, 0.35, 0.39 and 0.51, respectively and those by Gibbs Sampling method were 0.29, 0.25, 0.40, 0.42 and 0.54, respectively. This estimates were not significantly different, even though the estimated heritabilities by Gibbs Sampling method were higher than ones by REML method.Since the estimated statistics by REML method and Gibbs Sampling method were not significantly different in this study, it is inferred that both mothods could be efficiently applied for the analysis of carcass traits of cattle. However, further studies are demanded to define an optimal statistical method for handling large scale performance data.

목적 : 본 연구는 work sampling 기법과 단면분석법을 이용하여 제조업 종사 근로자의 근골격계질환 노출 위험수준을 알아보고자 하였다. 연구방법 : 이를 위해 자동차부품 제조업 종사 근로자 29명의 근골격계질환 증상을 자기기입식 설문지로 조사하여, 그 정도를 기준1(KOSHA), 기준2(NIOSH), 기준3(인천노동과학연구소)으로 구분하였다. 그리고 개별 근로자의 작업과정을 고성능카메라로 촬영한 후 OWAS, RULA, REBA를 사용하여 work sampling 기법(1초당 1컷)과 단면분석법으로 근골격계질환 위험수준을 분석하였다. 결과 : 신체부위 중 1부위 이상 통증이 있다고 호소한 근로자는 기준1 24명(82.8%), 기준2 22명(75.9%), 그리고 기준3 19명(65.5%)이었다. 인간공학적 측정도구를 이용한 근골격계질환 노출위험수준은 OWAS는 단면분석-조치단계 4(근골격계에 매우 심한 해를 끼침), work sampling-조치단계 2(근골격계에 약간의 해를 끼침)인 근로자가 3명이었다. 또, RULA는 단면분석-조치단계 4(정밀조사와 즉각적인 개선필요), work sampling-조치단계 3(계속적 관찰과 빠른 작업개선 요함)인 근로자가 2명이었고, REBA에서는 단면분석-조치단계 3(위험 높음), work sampling-조치단계 2(위험 보통)인 근로자가 3명으로 분석되었다. 단면분석과 work sampling 기법에서 고위험군과 저위험군의 일치도는 OWAS Kappa=.4423, RULA Kappa=.4938, 그리고 REBA Kappa=.5193이었다. 결론 : Work sampling 기법을 이용하여 근로자의 근골격계질환 노출위험수준을 객관적으로 분석할 수 있었으며, 결과를 토대로 근로자 작업환경의 개선이 우선적으로 필요한 작업자를 선정하는데 신뢰할만한 방법임이 확인되었다.

Objective : Using a work sampling technique and cross-section analysis, this study was performed in order to analyze the risk level of musculoskeletal disorders for workers engaged in the manufacturing industry. Methods : Using a self-entering mode questionnaire, the study was conducted to survey the musculoskeletal disorders of 29 workers at an automative component factory. The extent of the musculoskeletal disorders of the workers was classified into basis 1(KOSHA), basis 2(NIOSH), and basis 3 (labor scientific research institute of Incheon university). And the risk levels of the musculoskeletal disorders were evaluated using OWAS, RULA, and REBA for each work posture, extracting 1 cut per 1 sec, based on the work sampling technique, after having photographed the work processes of the individual workers with a high performance camera. Results : The number of workers who complained of pain in one or more parts of their body were 24 persons (82.8%) in basis 1, 22 persons (75.9%) in basis 2, and 19 persons (65.5%) in basis 3. As a result of having analyzed the musculoskeletal disorders, OWAS was in risk level 4 in a cross-section analysis (inflicted with severe musculoskeletal disorders), and as for the work sampling technique, the workers in risk level 2 (inflicted with milder musculoskeletal disorders) were 3 persons. Also, the workers whose work sampling of risk level had been 3 (continuous observation and fast work improvement were required) while their cross-section analysis for RULA was at risk level 4 (precision survey and immediate improvement were required) were 2 persons, while in REBA, the workers whose work sampling risk level was 2 (risk was normal) while their cross-section analysis risk levels were 3 (risk was high) were analyzed as 3 persons. The consistencies of the work sampling and cross-section analysis in the high-risk group and the low-risk group are as follows; OWAS (Kappa=.4423), RULA (Kappa=.4938), and REBA (Kappa=.5193). Conclusion : The results showed that this study may be used to analyze the exposure risk level to the musculoskeletal disorders of workers using a work sampling technique, and it has been confirmed as a trusted method in selecting the workers who require a preferential improvement of their work environment.

In-band network telemetry (INT) is an emerging network monitoring framework based on a protocol-independent packet processor (P4). Network devices can be programmed with a domain-specific language to embed switch-internal states into data packets as they traverse through networks. However, the current P4-based INT does not support a sampling; thus, INT headers should be augmented for all incoming packets, which will incur high overhead in a large-scale network. In this paper, we propose a flexible sampling-based INT (FS-INT) scheme to address the aforementioned issues. Simulation results show that FS-INT can reduce the protocol overhead in a controlled manner while providing sufficiently high accuracy.

In-band network telemetry (INT) is one of the promising technologies for achieving fine-grained and real-time visibility into the network, however, it brings non-negligible traffic overhead due to the increased packet length. Several sampling methods have been introduced to reduce the INT overhead; although, the provision of satisfactory network visibility was not well investigated. In this paper, we introduce a utility-based INT sampling rate allocation scheme, namely uINT, that aims to reduce data redundancy while improving network visibility. We conducted experiments using the software switches and demonstrated that uINT reduces redundantly collected INT data by up to 15% compared to sINT.

Due to the existence of computer and development of its technology, anybody may make new music with the help of the synthesizer which is not expensive, and the problems about the digital sampling of sound recording have arisen in Korea. However, Korean courts have not decided any case because most issues about digital sampling have been settled before going to court. Therefore, this article introduces some U.S. cases and BGH cases to help Korean courts to decide in the future. Finally, this article argues the de minimis use test and fair use doctrine in U.S. courts should be applied to most digital sampling case to promote the progress of culture and Korean courts should not follow the BGH reasoning because, in most digital sampling cases, most people may not recognize the original music in the new music.

Purpose: To compare patient care multipliers estimated from subjective evaluation against work sampling (WS) techniques in genetic nursing activities. Methods: An observational WS technique was conducted from November to December 2019 with nine genetic nurses in a tertiary referral center in Malaysia. The WS activity instrument was devised, validated, and pilot tested. All care- and non-care-related activities were sampled at 10-minute intervals within 8 hours of working over 14 days, followed by a subjective evaluation of activities survey over the same period. Bonferroni correction was undertaken for multiple testing with a p value of 0.0025. Results: The two techniques produced significant differences in genetic nurses’ activities categorization. The WS showed that compared with subjective evaluation, direct care (19.3% vs. 45.0%; p < .001) was estimated to be significantly lower, and indirect care (40.4% vs. 25.6%; p < .001) and unit-related activity (28.5% vs. 16.9%; p < .001) were higher. Both techniques produced a similar proportion of time spent in other non-care activities (12.0%) but differed in genetic meetings and information-gathering activities. While the multipliers for patient face-to-face contact were significantly larger between WS (4.57) and the survey (1.94), the multipliers for patient care time were smaller between WS (1.47) and the survey (1.24), indicating that caution should be taken when multiplying for patient contact time compared to patient care activity to determine the cost of care provision. Conclusion: A considerable proportion of time spent away from the patient needs to be allocated to patient-related care time. Thus, estimating the paid cost solely based on direct time with patients considerably underestimates the cost per hour of nurses' care. It is recommended to employ ‘patientrelated activity’ instead of the ‘face-to-face contact’ multiplier because the former did not significantly differ from the one estimated using WS.

This study was performed to evaluate the microbial and temperature changes of boxed beef during transport and distribution under vacuum and modified atmosphere packaging (MAP), and to compare between excision and swab sampling for 15 days. The top round and striploin (quality grade 1) from Hanwoo steers at 2 days post-slaughter were obtained from a local meat processing plants and chilled at 4 ± 2°C in a cold room. The boxes were transported under refrigeration (4 ± 2°C) to the laboratory within half an hour. Vacuum and MAP packs were subsequently taken out from cool boxes, and microbiological examinations were carried out at 0, 6, 12, and 24 h of storage time. MAP was more effective than vacuum packaging for the inhibition of total aerobic, lactic acid bacteria and Pseudomonas (p < 0.05). Microbial loads of swab methods were slightly lower than those of excision ones (p < 0.05). The results of this study could be utilized by meat consumers in future studies as well as by manufacturers to determine the ideal storage conditions for cool boxed meat, thus ensuring reduced economic losses due to spoilage.

In this paper, we describe the design and evaluation of a second-generation front-end unit for wideband sampling radio receivers. The unit contains a surface acoustic wave (SAW) filter to protect the receiver from strong out-of-band signals, an RF limiter to protect both the filter and the receiver from physical damage due to strong signals, and a bias tee with a DC limiter to provide DC power to a masthead low-noise amplifier, if one is used. The unit allows receivers such as those of the universal software radio peripheral (USRP) N-series type to be effectively used in RF environments with weak signals and strong in-band and out-of-band interferences.

In this paper, we will consider the problem of multi-unmanned aerial vehicles (UAVs) deployment among users’ hotspots. UAVs carry reconfigurable intelligent surface (RIS) boards to strengthen millimeter wave (mmWave) coverage at these hotspots. UAVs should maximize hotspots’ sum data rates while minimizing their flights’ cost, i.e., hovering and flying energy consumptions. Moreover, collisions should be avoided among UAVs, i.e., one hotspot should be served by only one UAV at a time. In this paper, this problem is considered as a multi-player multi-armed bandit (MP-MAB) game with budget constraint and collision avoidance. In this context, budget constraint Thompson sampling (TS) with collision avoidance MAB algorithm (BTSCA-MAB) is proposed to efficiently implement the formulated MP-MAB game. Numerical analysis confirms the superior performance of the proposed BTSCA-MAB over other benchmarks.