• Bioinformatics and Biosystems
• /
• 제1권1호
• /
• pp.51-60
• /
• 2006

The paradigm in biology is currently changing from that of conducting hypothesis-driven individual experiments to that of utilizing the results of a massive data analysis with appropriate computational tools. We present LayMap, an implemented visualization system that helps the user to deal with a high volume of the biomedical literature such as MEDLINE, through the layered maps that are constructed on the results of an information extraction system. LayMap also utilizes filtering and granularity for an enhanced view of the results. Since a biomedical information extraction system gives rise to a focused and effective way of slicing up the data space, the combined use of LayMap with such an information extraction system can help the user to navigate the data space in a speedy and guided manner. As a case study, we have applied the system to datasets of journal abstracts on 'MAPK pathway' and 'bufalin' from MEDLINE. With the proposed visualization, we have successfully rediscovered pathway maps of a reasonable quality for ERK, p38 and JNK. Furthermore, with respect to bufalin, we were able to identify the potentially interesting relation between the Chinese medicine Chan su and apoptosis with a high level of detail.

• International Journal of Computer Science & Network Security
• /
• 제22권12호
• /
• pp.229-238
• /
• 2022

Due to digitization, data has become a tsunami in almost every data-driven business sector. The information wave has been greatly boosted by man-to-machine (M2M) digital data management. An explosion in the use of ICT for farm management has pushed technical solutions into rural areas and benefited farmers and customers alike. This study discusses the benefits and possible pitfalls of using information and communication technology (ICT) in conventional farming. Information technology (IT), the Internet of Things (IoT), and robotics are discussed, along with the roles of Machine learning (ML), Artificial intelligence (AI), and sensors in farming. Drones are also being studied for crop surveillance and yield optimization management. Global and state-of-the-art Internet of Things (IoT) agricultural platforms are emphasized when relevant. This article analyse the most current publications pertaining to precision agriculture using ML and AI techniques. This study further details about current and future developments in AI and identify existing and prospective research concerns in AI for agriculture based on this thorough extensive literature evaluation.

• Wind and Structures
• /
• 제32권2호
• /
• pp.127-142
• /
• 2021

Wind load acting on a standalone structure is different from that acting on a similar structure which is surrounded by other structures in close proximity. The presence of other structures in the surrounding can change the wind flow regime around the principal structure and thus causing variation in wind loads compared to a standalone case. This variation on wind loads termed as interference effect depends on several factors like terrain category, geometry of the structure, orientation, wind incident angle, interfering distances etc., In the present study, a three building configuration is considered and the mean pressure coefficients on each face of principle building are determined in presence of two interfering buildings. Generally, wind loads on interfering buildings are determined from wind tunnel experiments. Computational fluid dynamic studies are being increasingly used to determine the wind loads recently. Whereas, wind tunnel tests are very expensive, the CFD simulation requires high computational cost and time. In this scenario, Artificial Neural Network (ANN) technique and Support Vector Regression (SVR) can be explored as alternative tools to study wind loads on structures. The present study uses these data-driven approaches to predict mean pressure coefficients on each face of principle building. Three typical arrangements of three building configuration viz. L shape, V shape and mirror of L shape arrangement are considered with varying interfering distances and wind incidence angles. Mean pressure coefficients (Cp mean) are predicted for 45 degrees wind incidence angle through ANN and SVR. Further, the critical faces of principal building, critical interfering distances and building arrangement which are more prone to wind loads are identified through this study. Among three types of building arrangements considered, a maximum of 3.9 times reduction in Cp mean values are noticed under Case B (V shape) building arrangement with 2.5B interfering distance. Effect of interfering distance and building arrangement on suction pressure on building faces has also been studied. Accordingly, Case C (mirror of L shape) building arrangement at a wind angle of 45º shows less suction pressure. Through this study, it was also observed that the increase of interfering distance may increase the suction pressure for all the cases of building configurations considered.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• 제16권2호
• /
• pp.88-93
• /
• 2017

Due to the requirement of the development of the precision manufacturing industry, the accuracy of machine tools has become a key issue in this field. A critical factor that affects the accuracy of machine tools is the feed system, which is generally driven by a ball screw. Basically, to improve the performance of the feed drive system, which will be thermally extended lengthwise by continuous usage, a thermal error compensation system that is highly dependent on the feedback temperature or positioning data is employed in the machine tool system. Due to the overdependence on measuring technology, the cost of the compensation system and low productivity level are inevitable problems in the machine tool industry. This paper presents a novel feed drive thermal error compensation system method that could compensate for thermal error without positioning or temperature feedback. Regarding this thermal error compensation system, the heat generation of components, principal of compensation, thermal model, mathematic model, and calculation method are discussed. As a result, the test data confirm the correctness of the developed feed drive thermal error compensation system very well.

• Journal of the Korean Society for Library and Information Science
• /
• 제57권3호
• /
• pp.279-301
• /
• 2023

The data-driven research environment is rapidly changing. Accordingly, domestic university libraries are also preparing to establish and operate research data management services to support university researchers. This study was designed to propose a research data management service to support researchers in science and technology specialized university libraries. In order to propose the service, 11 universities specializing in science and technology were selected from overseas and domestic universities and their research data management services were analyzed. Key categories were derived from analysis results, research data management, electronic research notebooks, and RDM training. In particular, the 'research data management' category included DMP, data collection, data management, data preservation, data sharing and publishing, data reuse, infrastructure and tools. And it consists of RDM guides and policies. The results of this study will be helpful in introducing and operating research data management services in science and technology specialized university libraries.

• Earthquakes and Structures
• /
• 제6권2호
• /
• pp.201-216
• /
• 2014

Many building codes use the empirical equation to determine fundamental period of vibration where in effect of length, width and the stiffness of the building is not explicitly accounted for. Also the equation, estimates the fundamental period of vibration with large safety margin beyond certain height of the building. An attempt is made to arrive at the simple empirical equations for fundamental period of vibration with adequate safety margin, using soft computing technique of Genetic Programming (GP). In the present study, GP models are developed in four categories, varying the number of input parameters in each category. Input parameters are chosen to represent mass, stiffness and geometry of the buildings directly or indirectly. Total numbers of 206 buildings are analyzed out of which, data set of 142 buildings is used to develop these models. It is observed that GP models developed under B and C category yield the same equation for fundamental period of vibration along X direction as well as along Y direction whereas the equation of fundamental period of vibration along X direction and along Y direction is of the same form for category D. The equations obtained as an output of GP models clearly indicate the influence of mass, geometry and stiffness of the building over fundamental period of vibration. These equations are then compared with the equation recommended by other researcher.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1999년도 제14차 학술회의논문집
• /
• pp.177-180
• /
• 1999

Nowadays, one of the major technical issues in manufacturing is to create an environment to promote collaboration among diverse engineering activities. Collaborative engineering is an innovative approach integrating widely distributed engineering activities through promoting information sharing and actual collaboration. It requires close interactions among developers, suppliers and customers, and consideration of entire product life cycle from concept to disposal. A carefully-designed operating system is crucial for successful collaboration of many different activities in a Networked Virtual Manufacturing System(NVMS). High extensibility, flexibility and efficiency ale the key characteristics requested of an operating system to handle the complexity of the NVMSs. In this paper, we propose a model of the operating system for collaborative engineering using concurrent quasi-procedural method(QPM). QPM is a goal-driven data management technique for distributed and parallel computing environments. It is to be applied to the evaluation of activities to be executed, validities of input data, execution path of activities for a needed output, and expected to greatly improve the productivity of operations by preventing redundant evaluations. Collaboration among many different engineering activities in NVMSs is to be performed by the network of agents that encapsulate the capabilities of both users and their tools.

• Nuclear Engineering and Technology
• /
• 제50권1호
• /
• pp.151-158
• /
• 2018

The neutron powder diffractometer (NPD) is used to study a variety of technologically important and scientifically driven materials such as superconductors, multiferroics, catalysts, alloys, ceramics, cements, colossal magnetoresistance perovskites, magnets, thermoelectrics, zeolites, pharmaceuticals, etc. Monte Carlo-based codes are powerful tools to evaluate the neutronic behavior of the NPD. In the present study, MCNPX 2.6.0 and Vitess 3.3a codes were applied to simulate NPD facilities, which could be equipped with different optic devices such as pyrolytic graphite or neutron chopper. So, the Monte Carlo-based codes were used to simulate the NPD facility of the 5 MW Tehran Research Reactor. The simulation results were compared to the experimental data. The theoretical results showed good conformity to experimental data, which indicates acceptable performance of the Vitess 3.3a code in the neutron optic section of calculations. Another extracted result of this work shows that application of neutron chopper instead of monochromator could be efficient to keep neutron flux intensity higher than $10^6n/s/cm^2$ at sample position.

• Computers and Concrete
• /
• 제13권6호
• /
• pp.765-780
• /
• 2014

Many building codes use the empirical equation to determine fundamental period of vibration where in effect of length, width and the stiffness of the building is not explicitly accounted for. In the present study, ANN models are developed in three categories, varying the number of input parameters in each category. Input parameters are chosen to represent mass, stiffness and geometry of the buildings indirectly. Total numbers of 206 buildings are analyzed out of which, data set of 142 buildings is used to develop these models. It is demonstrated through developed ANN models that geometry of the building and the sizes of the columns are significant parameters in the dynamic analysis of building frames. The testing dataset of these three models is used to obtain the empirical relationship between the height of the building and fundamental period of vibration and compared with the similar equations proposed by other researchers. Experiments are conducted on Mild Steel frames using uniaxial shake table. It is seen that the values obtained through the ANN models are close to the experimental values. The validity of ANN technique is verified by experimental values.

• Journal of The Korean Association For Science Education
• /
• 제40권6호
• /
• pp.657-670
• /
• 2020

The knowledge-information-processing competency is the most essential competency in a knowledge-information-based society and is the most fundamental competency in the new problem-solving ability. Data-driven science inquiry, which emphasizes how to find and solve problems using vast amounts of data and information, is a way to cultivate the problem-solving ability in a knowledge-information-based society. Therefore, this study aims to develop a teaching-learning model and strategy for data-driven science inquiry and to verify the validity of the model in terms of knowledge information processing competency. This study is developmental research. Based on literature, the initial model and strategy were developed, and the final model and teaching strategy were completed by securing external validity through on-site application and internal validity through expert advice. The development principle of the inquiry model is the literature study on science inquiry, data science, and a statistical problem-solving model based on resource-based learning theory, which is known to be effective for the knowledge-information-processing competency and critical thinking. This model is titled "Exploratory Scientific Data Analysis" The model consisted of selecting tools, collecting and analyzing data, finding problems and exploring problems. The teaching strategy is composed of seven principles necessary for each stage of the model, and is divided into instructional strategies and guidelines for environment composition. The development of the ESDA inquiry model and teaching strategy is not easy to generalize to the whole school level because the sample was not large, and research was qualitative. While this study has a limitation that a quantitative study over large number of students could not be carried out, it has significance that practical model and strategy was developed by approaching the knowledge-information-processing competency with respect of science inquiry.