• International Journal of Computer Science & Network Security
• /
• 제22권3호
• /
• pp.101-106
• /
• 2022

The Saudi Arabian Special Education Regulations define the role and requirements from teaching assistants within the educational process. Although all public special education programs are subject to such regulations, their implementation in practice sometimes appears contradictory. Therefore, special educators frequently encounter a range of problems when they fail to comply with such regulations. This article discusses how teaching assistants influence the teaching practices delivered to students with disabilities in special education settings. A qualitative case study approach was conducted using 22 semi-structured interviews. The results suggest a need to focus on the role of the teaching assistant in special education classes to ensure exposure to effective learning practices for students with disabilities. Based on these findings, a number of important implications for future practice, in terms adopting appropriate provisions are suggested.

• Human Ecology Research
• /
• 제61권4호
• /
• pp.505-520
• /
• 2023

This study aims to assess the effectiveness of the Marriage Checkup (MC) in community settings. Participants (N=57) were recruited from family centers and participated in the MC, which consisted of assessment and feedback visits. Participants completed marital satisfaction assessments before and after the MC. Overall, the participants reported significant improvements in terms of marital satisfaction with a large effect size (d=0.87). Specifically, 77.2% of participants demonstrated an increase in marriage satisfaction. Among them, 30.6% experienced a clinically significant change (from a clinical state to a non-clinical state). The reliable change index (RCI) identified 15.8% of participants as showing reliable improvement. Changes in marital satisfaction were larger for men and participants who experienced more positive changes during the MC in terms of intimacy and understanding of how to improve their marital relationships. This study supports the MC as an evidence-based approach for improving relationship health in community settings.

• 보건교육건강증진학회지
• /
• 제28권5호
• /
• pp.17-34
• /
• 2011

Objectives: The purposes of this study were to describe comprehensive health promotion policies for university students in Korea and to discuss the implications based on the socio-ecological approaches. Methods: A web-based search was performed to identify empirical programs and literature to develop health promotion policies and strategies in university settings. Results: Five domains for policy development are suggested for comprehensive health promotion policies in universities: evidence-based policy development; establishment of supportive policy through network and partnership; infrastructure of university; systems approach with education, environment, enforcement and policy tailored for universities; and sustainability for policy implementation. Conclusions: For healthy universities and students, government, community, health professionals, organizations and universities are all responsible as main agents for the five domains suggested in this study. Multi-level approaches with political, organizational and environmental changes should be sustained as an ongoing process.

• 대한산업공학회지
• /
• 제39권5호
• /
• pp.361-366
• /
• 2013

Prediction of process parameters is very important in parameter design. If predictions are fairly accurate, the quality improvement process will be useful to save time and reduce cost. The concept of dual response approach based on response surface methodology has widely been investigated. Dual response approach may take advantages of optimization modeling for finding optimum setting of input factor by separately modeling mean and variance responses. This study proposes an alternative dual response approach based on machine learning techniques instead of statistical analysis tools. A hybrid neural network-genetic algorithm has been proposed for the purpose of parameter design. A neural network is first constructed to model the relationship between responses and input factors. Mean and variance responses correspond to output nodes while input factors are used for input nodes. Using empirical process data, process parameters can be predicted without performing real experimentations. A genetic algorithm is then applied to find the optimum settings of input factors, where the neural network is used to evaluate the mean and variance response. A drug formulation example from pharmaceutical industry has been studied to demonstrate the procedures and applicability of the proposed approach.

• Genomics & Informatics
• /
• 제20권1호
• /
• pp.8.1-8.14
• /
• 2022

Despite the success of recent genome-wide association studies investigating longitudinal traits, a large fraction of overall heritability remains unexplained. This suggests that some of the missing heritability may be accounted for by gene-gene and gene-time/environment interactions. In this paper, we develop a Bayesian variable selection method for longitudinal genetic data based on mixed models. The method jointly models the main effects and interactions of all candidate genetic variants and non-genetic factors and has higher statistical power than previous approaches. To account for the within-subject dependence structure, we propose a grid-based approach that models only one fixed-dimensional covariance matrix, which is thus applicable to data where subjects have different numbers of time points. We provide the theoretical basis of our Bayesian method and then illustrate its performance using data from the 1000 Genome Project with various simulation settings. Several simulation studies show that our multivariate method increases the statistical power compared to the corresponding univariate method and can detect gene-time/ environment interactions well. We further evaluate our method with different numbers of individuals, variants, and causal variants, as well as different trait-heritability, and conclude that our method performs reasonably well with various simulation settings.

• 한국정보처리학회:학술대회논문집
• /
• 한국정보처리학회 2017년도 춘계학술발표대회
• /
• pp.373-375
• /
• 2017

Side-channel attacks and in particular differential power analysis (DPA) attacks pose a serious threat to cryptographic implementations. One approach to counteract such attacks is cryptographic schemes based on fresh re-keying. In settings of pre-shared secret keys, such schemes render DPA attacks infeasible by deriving session keys and by ensuring that the attacker cannot collect side-channel leakage on the session key during cryptographic operations with different inputs. This paper present a study on rekeying approach against side channel attacks with current secure schemes and their rekeying functions.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2002년도 하계학술대회 논문집 A
• /
• pp.196-198
• /
• 2002

This paper represents a new approach for the protective relay of power transmission lines using a Artificial Neural Network(ANN). A different fault on transmission lines need to be detected, classified and located accurately and cleared as fast as possible. However, The protection range of the distance relay is always designed on the basis of fixed settings, and unfortunately these approach do not have the ability to adapt dynamically to the system operating condition. ANN is suitable for the adaptive relaying and the detection of complex faults. The backpropagation algorithm based multi-layer perceptron is utilized for the learning process. It allows to make control to various protection functions. As expected, the simulation result demonstrate that this approach is useful and satisfactory.

• 경영과학
• /
• 제24권2호
• /
• pp.73-80
• /
• 2007

Robust Design(RD) is a cost-effective methodology to determine the optimal settings of control factors that make a product performance insensitive to the influence of noise factors. To better facilitate the robust design optimization, a dual response surface approach, which models both the process mean and standard deviation as separate response surfaces, has been successfully accepted by researchers and practitioners. However, the construction of response surface approximations has been limited to problems with only a few variables, mainly due to an excessive number of experimental runs necessary to fit sufficiently accurate models. In this regard, an innovative response surface approach has been proposed to investigate robust design optimization problems with larger number of variables. Response surfaces for process mean and standard deviation are partitioned and estimated based on the multi-level approximation method, which may reduce the number of experimental runs necessary for fitting response surface models to a great extent. The applicability and usefulness of proposed approach have been demonstrated through an illustrative example.

• Industrial Engineering and Management Systems
• /
• 제13권4호
• /
• pp.421-431
• /
• 2014

The market basket data in the form of a binary user-item matrix or a binary item-user matrix can be modelled as a binary classification problem. The binary logistic regression approach tackles the binary classification problem, where principal components are predictor variables. If users or items are sparse in the training data, the binary classification problem can be considered as a cold-start problem. The binary logistic regression approach may not function appropriately if the principal components are inefficient for the cold-start problem. Assuming that the market basket data can also be considered as a special regression problem whose response is either 0 or 1, we propose three supervised learning approaches: random forest regression, random forest classification, and elastic net to tackle the cold-start problem, comparing the performance in a variety of experimental settings. The experimental results show that the proposed supervised learning approaches outperform the conventional approaches.

• 대한자기공명의과학회:학술대회논문집
• /
• 대한자기공명의과학회 2001년도 제6차 학술대회 초록집
• /
• pp.152-152
• /
• 2001

Purpose： The most common instrumental approach to automatic shimming has been based on iterativ. optimization routine(e.g., simplex) to adjust shim settings to maximize the envelope of the FID. Disadvantage of iterative method, however, is very long to compute shim values. Thi paper supposes a non-iterative method that uses 2-D field map to adjust shim settin rapidly.