• International Journal of Knowledge Content Development & Technology
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• v.4 no.2
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• pp.49-65
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• 2014

This paper investigates how strategy formulation and implementation processes used by the University of Cape Coast (UCC) in building its digital collections compare with the Andrew's strategic formulation and implementation theoretical framework. Theory-testing case study methodology was used. The data collection instruments were the key informant interview technique and document reviews. During the formulation phase, two aspects (resources and aspirations of senior management) were emergent. During the implementation phase, five aspects (achieving results, processes and behaviour, standards, motivation, personal) were emergent. All other elements of building the UCC digital collections were planned during both the formulation and implementation phases. Although the emphasis on students and learning is laudable and apt, there seems to be lack of focus on research support beyond digital collection building, despite the fact that research excellence is one of the UCC's key priorities. Opportunities exist for improving feedback mechanisms between the users, digital library staff and the university management; and inclusion of social media tools in the digital library project. Since only the experience of a single institution of higher learning is considered, it cannot be definitively stated that strategy formulation and implementation will be similar in every institutional context. However, the results provide a basis for academic digital libraries to draw lessons from this case. In African public universities, there is little earlier research on strategy formulation and implementation in digital library management. Strategy formulation and implementation is a critical issue for higher education academic libraries especially in developing countries like Ghana, due to limited financial resources and the rapid change in the information environment during the last several decades.

• The Journal of Korea Robotics Society
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• v.4 no.3
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• pp.185-191
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• 2009

This paper presents a new shape-based algorithm using affine category shape model for object category recognition and model learning. Affine category shape model is a graph of interconnected nodes whose geometric interactions are modeled using pairwise potentials. In its learning phase, it can efficiently handle large pose variations of objects in training images by estimating 2-D homography transformation between the model and the training images. Since the pairwise potentials are defined on only relative geometric relationship betweenfeatures, the proposed matching algorithm is translation and in-plane rotation invariant and robust to affine transformation. We apply spectral matching algorithm to find feature correspondences, which are then used as initial correspondences for RANSAC algorithm. The 2-D homography transformation and the inlier correspondences which are consistent with this estimate can be efficiently estimated through RANSAC, and new correspondences also can be detected by using the estimated 2-D homography transformation. Experimental results on object category database show that the proposed algorithm is robust to pose variation of objects and provides good recognition performance.

• The KIPS Transactions:PartB
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• v.14B no.5
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• pp.383-390
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• 2007

Interactions between proteins and genes are often considered essential in the description of biomolecular phenomena and networks of interactions are considered as an entre for a Systems Biology approach. Recently, many works try to extract information by analyzing biomolecular text using natural language processing technology. Previous researches insist that linguistic information is useful to improve the performance in detecting gene interactions. However, previous systems do not show reasonable performance because of low recall. To improve recall without sacrificing precision, this paper proposes a new method for detection of gene interactions based on syntactic relations. Without biomolecular knowledge, our method shows reasonable performance using only small size of training data. Using the format of LLL05(ICML05 Workshop on Learning Language in Logic) data we detect the agent gene and its target gene that interact with each other. In the 1st phase, we detect encapsulation types for each agent and target candidate. In the 2nd phase, we construct verb lists that indicate the interaction information between two genes. In the last phase, to detect which of two genes is an agent or a target, we learn direction information. In the experimental results using LLL05 data, our proposed method showed F-measure of 88% for training data, and 70.4% for test data. This performance significantly outperformed previous methods. We also describe the contribution rate of each phase to the performance, and demonstrate that the first phase contributes to the improvement of recall and the second and last phases contribute to the improvement of precision.

• Journal of Ginseng Research
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• v.45 no.1
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• pp.108-118
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• 2021

Background: Korean ginseng (Panax ginseng Meyer) contains a variety of ginsenosides that can be metabolized to a biologically active substance, compound K. Previous research showed that compound K could be enriched in the red ginseng extract (RGE) after hydrolysis by pectinase. The current study investigated whether the enzymatically hydrolyzed red ginseng extract (HRGE) containing a notable level of compound K has cognitive improving and neuroprotective effects. Methods: A scopolamine-induced hypomnesic mouse model was subjected to behavioral tasks, such as the Y-maze, passive avoidance, and the Morris water maze tests. After sacrificing the mice, the brains were collected, histologically examined (hematoxylin and eosin staining), and the expressions of antioxidant proteins analyzed by western blot. Results: Behavioral assessment indicated that the oral administration of HRGE at a dosage of 300 mg/kg body weight reversed scopolamine-induced learning and memory deficits. Histological examination demonstrated that the hippocampal damage observed in scopolamine-treated mouse brains was reduced by HRGE administration. In addition, HRGE administration increased the expression of nuclear-factor-E2-related factor 2 and its downstream antioxidant enzymes NAD(P)H:quinone oxidoreductase and heme oxygenase-1 in hippocampal tissue homogenates. An in vitro assay using HT22 mouse hippocampal neuronal cells demonstrated that HRGE treatment attenuated glutamate-induced cytotoxicity by decreasing the intracellular levels of reactive oxygen species. Conclusion: These findings suggest that HRGE administration can effectively alleviate hippocampus-mediated cognitive impairment, possibly through cytoprotective mechanisms, preventing oxidative-stress-induced neuronal cell death via the upregulation of phase 2 antioxidant molecules.

• Communications of Mathematical Education
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• v.31 no.2
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• pp.167-185
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• 2017

The purpose of this study is to analyze the actual states of the elementary school and the middle school mathematics education as a curriculum quality-management. To this end, this study surveyed the input, process and output phase in the school curriculum to the teachers, students and parents. The results are like these: First, the achievement standards contents in the elementary school and the middle schools are relevant in the input phase. Second, the teachers in the elementary school have more concern on the teaching & learning methods than those in the middle school in the process phase. Third, students and parents' satisfaction on the cognitive and affective domain in the elementary school is higher than that in the middle school in the output phase. This study suggests that these result has to be affected to make ways to apply the new curriculum, and the curriculum revision system has to be established to revise the curriculum as an important method of quality management.

• Journal of The Korean Association of Information Education
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• v.18 no.1
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• pp.185-193
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• 2014

Software developing education teaches students computer programming, which allows them to actively use IT and talk to computers. In this study, we analyzed computer science curriculum in the United Kingdom, the United States, India, and Estonia. In order to teach 1st - 9th grade students computer programming, we suggested the learning objectives, instructional design, and evaluation methods in software developing education focusing on Information Science. The objectives were divided into four phases, which were determined by age and grade level. Then, we determined 2-3 outcomes for each phase.

• Journal of Multimedia Information System
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• v.3 no.2
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• pp.35-42
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• 2016

Electrocardiogram (ECG) signal gives a clear indication whether the heart is at a healthy status or not as the early notification of a cardiac problem in the heart could save the patient's life. Several methods were launched to clarify how to diagnose the abnormality over the ECG signal waves. However, some of them face the problem of lack of accuracy at diagnosis phase of their work. In this research, we present an accurate and successive method for the diagnosis of abnormality through Discrete Wavelet Transform (DWT), QRS complex detection and Support Vector Machines (SVM) classification with overall accuracy rate 95.26%. DWT Refers to sampling any kind of discrete wavelet transform, while SVM is known as a model with related learning algorithm, which is based on supervised learning that perform regression analysis and classification over the data sample. We have tested the ECG signals for 10 patients from different file formats collected from PhysioNet database to observe accuracy level for each patient who needs ECG data to be processed. The results will be presented, in terms of accuracy that ranged from 92.1% to 97.6% and diagnosis status that is classified as either normal or abnormal factors.

• The Journal of Korean Association of Computer Education
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• v.20 no.6
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• pp.1-15
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• 2017

The purpose of this study is to design a LMS(Learning Management System) dashboard for instructor feedback support based on learning analytics and to apply a LMS dashboard incorporating such taxonomy which allows an instructor to give a student personalized feedback according to the class content and a student's traits. In the dashboard design phase, usable instructional data were selected from LMS based on feedback taxonomy in terms of learning analytics. Two validity tests were conducted with 8 instructional technologists over 8 years of experience, and were revised accordingly. The final dashboard screen has three parts: A comprehensive analysis screen to provide appropriate feedback based on instructor feedback taxonomy analysis, a summary screen for learner analysis, and a recommended feedback guide screen. Detailed analysis information are provided through other dashboards that are displayed in eight screens: login analysis, learning information confirmation analysis, teaching materials learning analysis, assignment/tests, and posts analysis. All of these dashboards were represented by analysis information and data based on learner analytics through visualization methods including graphs and tables. The implications of educational utilization of the dashboard for instructor feedback support based on learning analytics and the future researches were suggested based on these results.

• Journal of The Korean Association of Information Education
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• v.19 no.2
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• pp.175-186
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• 2015

In this study, we developed the PATROL teaching and learning model by using digital textbooks in Smart Classrooms to correct the disadvantages of Flipped Classrooms. PATROL is an acronym for Planning, Action, Tracking, Recommending, Ordering, and Leading. In the Planning phase, teachers should make a lesson plan. Next, students take Action by watching online contents and completing assignments in their digital textbook. After that, Tracking is needed to analyze the students' activities and the results. Then, Recommending is used to provide suggested instructional activities to teachers based on that analysis. Next, Ordering requires that students request new materials for class activities. Finally, Leading allows teachers to provide materials at the appropriate level to their students based on the students' learning activities. Applying the PATROL model at two elementary schools resulted in an increase in student-directed speech as well as an increase in the number of group and individual activities. Teachers also had more time to walk around the classroom.

• Journal of Electrical Engineering and Technology
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• v.7 no.2
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• pp.245-254
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• 2012

In this study, we introduce a prototype-based classifier with feature selection that dwells upon the usage of a biologically inspired optimization technique of Particle Swarm Optimization (PSO). The design comprises two main phases. In the first phase, PSO selects P % of patterns to be treated as prototypes of c classes. During the second phase, the PSO is instrumental in the formation of a core set of features that constitute a collection of the most meaningful and highly discriminative coordinates of the original feature space. The proposed scheme of feature selection is developed in the wrapper mode with the performance evaluated with the aid of the nearest prototype classifier. The study offers a complete algorithmic framework and demonstrates the effectiveness (quality of solution) and efficiency (computing cost) of the approach when applied to a collection of selected data sets. We also include a comparative study which involves the usage of genetic algorithms (GAs). Numerical experiments show that a suitable selection of prototypes and a substantial reduction of the feature space could be accomplished and the classifier formed in this manner becomes characterized by low classification error. In addition, the advantage of the PSO is quantified in detail by running a number of experiments using Machine Learning datasets.