• Journal of The Korean Association For Science Education
• /
• v.38 no.4
• /
• pp.541-553
• /
• 2018

The purpose of this study is to explore the relationship between epistemic goals, epistemic considerations and complexity of reasoning of science high school students in an open inquiry and to explore the context on how open inquiry compares with the characteristics of an authentic scientific inquiry. Two teams were selected as focus groups and a case study was conducted. The findings are as follows: First, the contexts, such as 'sharing the value for the phenomenon understanding, reflection on the value of the research, task characteristics that require collaboration and consensus, and sufficient communication opportunities,' promote epistemic goals and considerations. On the other hand, contexts such as 'lack of opportunity for critical review of related literature and environmental constraints' lowered epistemic sides. Second, epistemic goals and considerations influenced the reasoning complexity. The goal of 'scientific sense making' led to reasoning that pose testable hypotheses based on students' own questions. The high justification considerations led to purposely focusing attention to the control designs and developing creative experimental know-how. The high audience considerations led to defending their findings through argumentation and suggesting future research. On the other hand, the goal of 'doing the lesson' and the low justification considerations led to reasoning that did not interpret the meaning of the data and did not control the limit of experiment. The low audience considerations led to reasoning that did not actively defend their findings and not suggest future research. The results of this study suggest that guidance should provide communication and critical review opportunities.

• Proceedings of the KSR Conference
• /
• 2004.10a
• /
• pp.982-987
• /
• 2004

Most design practices have not taken advantage of the advanced theories in the modern fracture mechanics and finite element analysis due to complexity of analysis as well as the large quantity of vaguely defined parameters in actual designs. This paper considers fatigue problems in bridge structures using effective analytical and design tools from the field of qualitative constraint reasoning. A set of software modules was developed for fatigue analysis ,and evaluation, which is easily applicable in engineering practices of bridge designers. The software modules integrate techniques in the field of knowledge representation and qualitative reasoning, into the conventional fatigue analysis. The techniques enable the use complex analysis formulations to tackle practical problems with uncertainties, and present the design outcome in two-dimensional design space. Appropriate engineering assumptions and judgments in carrying out these procedures, often the most difficult part for practicing engineers, can be partially produced by using qualitative reasoning to define the trends and ranges, interval constraint analysis to derive the controlling parameters, as well as design space to account for practical experience. This paper depicts a way of complex analysis to practical engineering designs with qualitative reasoning.

• Journal of Intelligence and Information Systems
• /
• v.6 no.2
• /
• pp.29-40
• /
• 2000

Process planning (selection and ordering of processes) and material selection for product manufacturing are two key things determined before taking full-scale manufacturing. Knowledge on product design. material characteristics, processes, time and cost all-together are mutually related and should be considered concurrently. Due to the complexity of problem, human experts have got only one of the feasilbe solutions with their field knowledge and experiences. We propose a hierarchical expert system framework of knowledge representation and reasoning in order to overcome the complexity. Manufacturing processes have inherently hierarchical relationships, from top level processes to bottom level operation processes. Process plan of one level is posted in process blackboard and used for lower level process planning. Process information on blackboard is also used to adjust the process plan in order to resolve the dead-end or inconsistency situation during reasoning. Decision variables for process, material, tool, time and cost are represented as object frames, and their relationships are represented as constraints and rules. Constraints are for relationship among variables such as compatibility, numerical inequality etc. Rules are for causal relationships among variables to reflect human expert\`s knowledge such as process precedence. CRSP(Constraint and Rule Satisfaction Problem) approach is adopted in order to obtain solution to satisfy both constraints and rules. The trade-off procedure gives user chances to see the impact of change of important variables such as material, cost, time and helps to determine the preferred solution. We developed the prototype system using visual C++ MFC, UNIK, and UNlK-CRSP on PC.

• Journal of Advanced Navigation Technology
• /
• v.12 no.1
• /
• pp.74-81
• /
• 2008

In this paper, adaptive watermarking algorithm which based on fuzzy reasoning and hybrid scheme is presented. To enforce the time and space complexity, hybrid scheme which utilize a color information as well as visual characteristics is also addressed. Proposed approach have double-aim: in first to use the visual characteristics so as to enforce the robustness of watermarking, and in second to select the optimal sub-band which is to be embedded a watermark. One of the principal advantage is that this approach involved the fuzzy inference module which is designed to select an optimal sub-band from the DWT coefficient blocks. In order to demonstrate the effectiveness of proposed algorithm, some numerical experiments of robustness and imperceptibility are evaluated with respect to such attacks as JPEG compression, noise and cropping.

• Proceedings of the Korean Society for Technology of Plasticity Conference
• /
• 2004.05a
• /
• pp.194-197
• /
• 2004

In the tube hydroforming process, a tube is placed into the die cavity and the ends of the tube are sealed by fixing the axial cylinder piston into the ends. Then the tube is pressurized with a hydraulic fluid and simultaneously the axial cylinders move to feed the material into the expansion zone. Therefore, the quantitative relationship between process parameters such as internal pressure and feeding amount and hydroformabillity, is hard to establish because of their high complexity and many unknown factors. In this study, the empirical and the quantitative relationship between process parameters and hydroformabillity are analyzed by fuzzy rules. Fuzzy expert system is an advanced expert system which uses fuzzy rule and approximate reasoning. Many process parameters are converted to the quantitative relationship by use of approximate reasoning of fuzzy expert system. The comparison between experimentally measured hydroformabillity from hydroforming experiments and the predicted values by fuzzy expert system shows a good agreement.

• Journal of KIISE:Software and Applications
• /
• v.34 no.8
• /
• pp.763-771
• /
• 2007

As software is widely used on various environments today, there is an increasing need for adaptive software. Adaptive software is robust and flexible software that modifies its own behavior in response to the changes in its environment. Due to time constraints, high complexity and so on, it is hard to acquire context information from environment. So, when implementing software, it is common to think easily acquired data to be the environments. This research proposes an adaptive software framework that assumes plane images to be environments. Plane images are easy to acquire and have enough complexity. From this, our framework is able to acquire context information, reasons with action rule, and acts on the result of reasoning. Stand on this framework, implements software that plays a simple game automatically.

• Journal of The Korean Association For Science Education
• /
• v.34 no.4
• /
• pp.335-347
• /
• 2014

Size/scale is a central idea in the science curriculum, providing explanations for various phenomena. However, few studies have been conducted to explore student understanding of this concept and to suggest instructional approaches in scientific contexts. In contrast, there have been more studies in mathematics, regarding the use of number lines to relate the nature of numbers to operation and representation of magnitude. In order to better understand variations in student conceptions of size/scale in scientific contexts and explain learning difficulties including alternative conceptions, this study suggests an approach that links mathematics with the analysis of student conceptions of size/scale, i.e. the analysis of mathematical structure and reasoning for a number line. In addition, data ranging from high school to college students facilitate the interpretation of conceptual complexity in terms of mathematical development of a number line. In this sense, findings from this study better explain the following by mathematical reasoning: (1) varied student conceptions, (2) key aspects of each conception, and (3) potential cognitive dimensions interpreting the size/scale concepts. Results of this study help us to understand the troublesomeness of learning size/scale and provide a direction for developing curriculum and instruction for better understanding.

• The Journal of Information Technology
• /
• v.7 no.3
• /
• pp.127-137
• /
• 2004

A Project planning is one of the most important processes that determines success and failure of a project. Scope management for a project planning is also essential job in system integration project. However project planning is very difficult because lots of factors and their relationships should be considered. Therefore project planning of system integration project has been done by project manager's own knowledge and experience. It is necessary to develop an algorithm of WBS(Work Breakdown Structure) identification & document selection along to project's specificity in project management system using AI technique. This study presents a methodology to cope with the limitations of the existing studies that have uniformly been customizing the methodology by only project complexity. We propose PPSM(Project planning support module) based on determination rules regarding route maps and document levels, and CBR(Case-Based Reasoning) for WBS identification.

• Journal of Communications and Networks
• /
• v.13 no.6
• /
• pp.567-582
• /
• 2011

The growing popularity of the Internet has caused the size and complexity of communications and computing systems to greatly increase in recent years. To alleviate this increased management complexity, novel autonomic management architectures have emerged, in which many automated components manage the network's resources in a distributed fashion. However, in order to achieve effective collaboration between these management components, they need to be able to efficiently exchange information in a timely fashion. In this article, we propose a context dissemination framework that addresses this problem. To achieve scalability, the management components are structured in a hierarchy. The framework facilitates the aggregation and translation of information as it is propagated through the hierarchy. Additionally, by way of semantics, context is filtered based on meaning and is disseminated intelligently according to dynamically changing context requirements. This significantly reduces the exchange of superfluous context and thus further increases scalability. The large size of modern federated cloud computing infrastructures, makes the presented context dissemination framework ideally suited to improve their management efficiency and scalability. The specific context requirements for the management of a cloud data center are identified, and our context dissemination approach is applied to it. Additionally, an extensive evaluation of the framework in a large-scale cloud data center scenario was performed in order to characterize the benefits of our approach, in terms of scalability and reasoning time.

• Journal of Korean Institute of Industrial Engineers
• /
• v.22 no.3
• /
• pp.399-412
• /
• 1996

With respect to the effects of types of knowledge on human diagnostic performance, the results of several experiments claimed that training with procedural knowledge is more effective than training with principle knowledge. However, more useful results would be attained by investigating when and how the principles of system dynamics is valuable for diagnosis. Accordingly, we conducted an experiment to reevaluate the value of principle knowledge in two problem situations. A simulator system, named DLD, to diagnose an electronic device was created. It is a context-free digital logic circuit which includes forty-one gates of three basic types. The experiment investigated the effects of principle knowledge over common procedural knowledge. The experimental results showed that the effects of principle knowledge is dependent on the complexity of diagnostic situations. This adds up on experimental evidence against the presumed ineffectiveness of principle knowledge and forward reasoning in fault diagnosis. The results also suggest the source of the usefulness of principle knowledge.