한국원자력연구원 부지 내에 위치한 지하처분연구시설(KAERI Underground Research Tunnel, KURT) 에서는 선진핵주기 고준위폐기물처분시스템(A-KRS)을 기반으로 고준위방사성폐기물을 처분하였을때, 예상되는 공학적방벽(Engineered Barrier System, EBS)과 자연방벽(Natural Barrier System, NBS)에서의 열-수리-역학적 복합거동(Thermo-Hydro-Mechanical coupled behavior)의 특성을 규명하고자 현장시험(In-situ Demonstration of Engineered Barrier System, In-DEBS)을 2012년부터 계획 및 설계를 시작하여, 2016년 5월부터 지하처분연구시설 3번 연구 갤러리(Research gallery 3)에서 진행하고 있다. 현장시험의 데이터를 분석하고 열-수리-역학적 복합거동 특성을 명확히 규명하기 위해서는 경주 벤토나이트와 KURT 암석 및 암반의 열적, 수리적, 그리고 역학적 물성 특성을 반드시 파악하고 있어야만 한다. 이에 본 연구에서는 지금까지 수행된 KURT 부지 특성과 KURT 화강암 및 경주 벤토나이트의 열적, 수리적, 그리고 역학적 특성을 정리하고, 열적, 수리적, 그리고 역학적 모델을 제시하였다. 특히, 온도에 따른 암석의 열팽창계수 변화, 응력에 따른 암석의 투수계수 변화, 포화도에 따른 벤토나이트 및 암석의 열전도도 변화, 포화도에 따른 벤토나이트의 비열 및 흡입력 변화와 같은 열-수리-역학적 복합물성에 대한 다양한 모델을 도출함으로써, In-DEBS 현장시험 결과 분석과 열-수리-역학적 복합거동 특성 평가를 위해 수행 될 수치시험에 필요한 벤토나이트와 암석 및 암반의 입력자료를 제시하고자 하였다.

People write reviews of numerous products or services on the Internet, in their blogs or community bulletin boards. These unstructured data contain important emotions and opinions about the author's product or service, which can provide important information for future product design or marketing. However, this text-based information cannot be evaluated quantitatively, and thus they are difficult to apply to mathematical models or optimization problems for product design and improvement. Therefore, this study proposes a method to quantitatively extract user’s opinion or preference about a specific product or service by utilizing a lot of text-based information existing on the Internet or online. The extracted unstructured text information is decomposed into basic unit words, and positive rate is evaluated by using existing emotional dictionaries and additional lists proposed in this study. This can be a way to effectively utilize unstructured text data, which is being generated and stored in vast quantities, in product or service design. Finally, to verify the effectiveness of the proposed method, a case study was conducted using movie review data retrieved from a portal website. By comparing the positive rates calculated by the proposed framework with user ratings for movies, a guideline on text mining based evaluation of unstructured data is provided.

Speech and language are uniquely human-specific traits that have contributed to humans becoming the predominant species on earth from an evolutionary perspective. Disruptions in human speech and language function may result in diverse disorders, including stuttering, aphasia, articulation disorder, spasmodic dysphonia, verbal dyspraxia, dyslexia, and specific language impairment (SLI). These disorders often cluster within a family, and this clustering strongly supports the hypothesis that genes are involved in human speech and language functions. For several decades, multiple genetic studies, including linkage analysis and genome-wide association studies, were performed in an effort to link a causative gene to each of these disorders, and several genetic studies revealed associations between mutations in specific genes and disorders such as stuttering, verbal dyspraxia, and SLI. One notable genetic discovery came from studies on stuttering in consanguineous Pakistani families; these studies suggested that mutations in lysosomal enzyme-targeting pathway genes (GNPTAB, GNPTG, and NAPGA) are associated with non-syndromic persistent stuttering. Another successful study identified FOXP2 in a Caucasian family affected by verbal dyspraxia. Furthermore, an abnormal ultrasonic vocalization pattern (USV) was observed in knock-in (KI) and humanized mouse models carrying mutations in the FOXP2 gene. Although studies have increased our understanding of the genetic causes of speech and language disorders, these genes can only explain a small fraction of all disorders in patients. In this paper, we summarize recent advances and future challenges in an effort to reveal the genetic causes of speech and language disorders in animal models.

As power consumption increases, more power utilities are required to satisfy the demand and consequently results in tremendous cost to build the utilities. Another issue in construction of power utilities to meet the peak demand is an inefficiency caused by surplus power during non-peak time. Therefore, most power company considers power demand management with time-based electricity rate policy which applies different rate over time. This paper considers an optimal machine operation problem under the time-based electricity rates. In TOC (Theory of Constraints), the production capacities of all machines are limited to one of the bottleneck machine to minimize the WIP (work in process). In the situation, other machines except the bottleneck are able to stop their operations without any throughput loss of the whole manufacturing line for saving power utility cost. To consider this problem three integer programming models are introduced. The three models include (1) line shutdown, (2) block shutdown, and (3) individual machine shutdown. We demonstrate the effectiveness of the proposed IP models through diverse experiments, by comparing with a TOC-based machine operation planning considered as a current model.

Uncovering enzyme (UCE), encoded by the human NAGPA, is a trans-Golgi enzyme that adds the mannose-6- phosphate recognition tag on lysosomal enzymes destined for the lysosome. Mutations in NAGPA are known to cause stuttering, a common speech disorder with unknown etiology. The human NAGPA gene is transcribed into two different forms, probably due to alternative splicing. One of them, known as a brain isoform, is lacking exon 8 (102-bp). We performed quantitative real-time PCR for the NAGPA brain and non-brain isoforms in a cDNA panel originating from 16 human tissues and 24 sub-brain regions. According to our findings, the relative quantity of the NAGPA brain isoform in the brain was 4.7 times more than that in the control cDNA, a pooled mixture of equal amounts of cDNAs from the 16 different tissues. Further analysis using the cDNA panel originating from 24 different sub-brain regions revealed that the cerebral cortex contained the largest amount of NAGPA brain isoform. Relative quantity in the cerebral cortex was 8.6 times more than that in the control cDNA (P=0.00004). The lowest quantity of this isoform was detected in cDNA from the pituitary gland. In conclusion, findings of the current study suggest that the cerebral cortex, expressing the highest quantity of the NAGPA brain isoform, might be the region associated with speech function.

The advanced planning and scheduling(APS) is an well known enterprise information system that provides optimal production schedules and supports to complete production on time by solving the complex scheduling problems including capacity and due dates. In