• Asian Journal of Innovation and Policy
• /
• v.8 no.1
• /
• pp.73-96
• /
• 2019

This study suggests a new approach for identifying core robot tech-nologies based on technological cross-impact. Specifically, the approach applies data mining techniques and multi-criteria decision-making methods to the co-classification information of registered patents on the robots. First, a cross-impact matrix is constructed with the confidence values by applying association rule mining (ARM) to the co-classification information of patents. Analytic network process (ANP) is applied to the co-classification frequency matrix for deriving weights of each robot technology. Then, a technique for order performance by similarity to ideal solution (TOPSIS) is employed to the derived cross-impact matrix and weights for identifying core robot technologies from the overall cross-impact perspective. It is expected that the proposed approach could help robot technology managers to formulate strategy and policy for technology planning of robot area.

• International journal of advanced smart convergence
• /
• v.10 no.3
• /
• pp.149-156
• /
• 2021

Today, 3D softwares have become an essential tool in all areas of Video, including Movies, Animations, CFs, Motion Graphics and Games. One of the most commonly used fields is the 3D character video part. However, these 3D character animations and motion graphics softwares are difficult to learn and too much to learn, making it difficult to learn them all in a university education with a limited time of four years. In this paper, many Inverse kinematics tools, which are essential in the 3D character animations and motion graphics field, compare and analyze the strengths and weaknesses of each tool, focusing on Bone, Character Studio, and Character Animation Toolkit, which are most commonly used in work fields. And use Delphi techniques for 3D experts to secure objectivity. Therefore, for universities that require large amounts of teaching in a limited time, I propose an analysis of which of the above three Inverse Kinetics tools is advantageous for students to select and focus on for efficient education.

• International Journal of Computer Science & Network Security
• /
• v.21 no.4
• /
• pp.209-213
• /
• 2021

Data mining is the application of specific algorithms for extracting patterns from data and KDD is the automated or convenient extraction of patterns representing knowledge implicitly stored or captured in large databases, data warehouses, the Web, other massive information repositories or data streams. Data mining can be used for decision making in educational system. But educational institution does not use any knowledge discovery process approach on these data; this knowledge can be used to increase the quality of education. The problem was happening in the educational management system, but to make education system more flexible and discover knowledge from it huge data, we will use data mining techniques to solve problem.

• International Journal of Computer Science & Network Security
• /
• v.21 no.4
• /
• pp.214-222
• /
• 2021

Recently, the growth of e-commerce in Saudi Arabia has been exponential, bringing new remarkable challenges. A naive approach for product matching and categorization is needed to help consumers choose the right store to purchase a product. This paper presents a machine learning approach for product matching that combines deep learning techniques with standard artificial neural networks (ANNs). Existing methods focused on product matching, whereas our model compares products based on unstructured descriptions. We evaluated our electronics dataset model from three business-to-consumer (B2C) online stores by putting the match products collectively in one dataset. The performance evaluation based on k-mean classifier prediction from three real-world online stores demonstrates that the proposed algorithm outperforms the benchmarked approach by 80% on average F1-measure.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.4
• /
• pp.1146-1165
• /
• 2022

A huge amount of data in the form of videos and images is being produced owning to advancements in sensor technology. Use of low performance commodity hardware coupled with resource heavy image processing and analyzing approaches to infer and extract actionable insights from this data poses a bottleneck for timely decision making. Current approach of GPU assisted and cloud-based architecture video analysis techniques give significant performance gain, but its usage is constrained by financial considerations and extremely complex architecture level details. In this paper we propose a data pipeline system that uses open-source tools such as Apache Spark, Kafka and OpenCV running over commodity hardware for video stream processing and image processing in a distributed environment. Experimental results show that our proposed approach eliminates the need of GPU based hardware and cloud computing infrastructure to achieve efficient video steam processing for face detection with increased throughput, scalability and better performance.

• Corrosion Science and Technology
• /
• v.22 no.1
• /
• pp.36-43
• /
• 2023

Single-crystal Ni-rich NCM is a material that has drawn attention in the field of lithium-ion batteries due to its high energy density and long cycle life. In this study, we investigated the properties of single-crystal NCM 811 and its potential for use in lithium-ion batteries. High-quality single crystals of NCM 811 were successfully synthesized by crystal growth via a flux method. The single-crystal nature of the samples was confirmed through detailed characterization techniques, such as scanning electron microscopy and x-ray diffraction with Rietveld refinement. The crystal structure and electrochemical performances of the single-crystal NCM 811 were analyzed and compared to its poly-crystal counterpart. The results indicated that single-crystal NCM 811 had electrochemical performance and thermal stability superior to poly-crystalline NCM 811, making it a suitable candidate for high-performance batteries. The findings of this study contribute to a better understanding of the characteristics and potential of single-crystal NCM 811 for lithium-ion batteries.

• International conference on construction engineering and project management
• /
• 2009.05a
• /
• pp.970-977
• /
• 2009

Organizational personnel must have well-developed interpersonal skills to deal with the different stakeholders and departments, to work at different levels in the hierarchy, and to meet varying performance requirements. Many leadership development and mentoring programs are designed to expose students as well as construction professionals to contemporary leadership techniques and skills. Leadership skills generally separate into three decision-making styles with varying degrees: 1) Autocratic, 2) Participate, and 3) Free-rein. This paper describes the study of leadership styles among 174 construction professionals and addresses the most appropriate leadership style for a project executive and a project manager in relation to compare with the characteristic leadership style and job functions. The study supports the growing importance of leadership skills as a component of managerial functions and provides a benchmark to identify a dominant leadership skill for a specific managerial position.

• International conference on construction engineering and project management
• /
• 2005.10a
• /
• pp.503-508
• /
• 2005

In the modern, distributed and dynamic construction environment it is important to exchange information from different sources and in different data formats in order to improve the processes supported by these systems. Previous research has demonstrated that (i) a significant percentage of construction data is stored in semi-structured or unstructured data formats (ii) locating and identifying such data that are needed for the important decision making processes is a very hard and time-consuming task. In this paper, an automated methodology for the classification and retrieval of construction images in AEC/FM model based systems will be presented. Specifically, a combination of techniques from the areas of image processing, computer vision, and content-based image retrieval have been deployed to develop a method that can retrieve related construction site image data from components of a project model.

• Journal of Korean Library and Information Science Society
• /
• v.30 no.4
• /
• pp.87-106
• /
• 1999

The purpose of this paper is to find out the present status of public library management. The assumptions on which this research is based are that there are differences between th theories taught at the educational institutions for librarians and the practices actually managed at libraries, and that the differences are greater in Korea than those in the United States of America as the former has a shorter library history and is a more bureaucratic society. The data were collected were collected through the questionnaires sent to fifty-five public library managers in Taegu and Kyungpook province. Forty-two respondents replied, making the returned rate of 76.4%. The results show that there exist some differences between theories and practices, but they are not so great as expected. It was found out that there is a difference between what the theorists state and what the practicing managers accept. It was also found out that the library managers agree that the new management theories and techniques can be adopted to their libraries. The hindering factors are found out, and based on the findings, a few suggestions are provided.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.5
• /
• pp.1356-1376
• /
• 2023

Software effort estimation is one of the most difficult tasks in software development whereas predictability is also of equal importance for strategic management. Accurate prediction of the actual cost that will be incurred in software development can be very beneficial for the strategic management. This study discusses the latest trends in software estimation focusing on analogy-based techniques to show how they have improved the accuracy for software effort estimation. It applies the standard deviation technique to the expected value of analogy-based estimates to improve accuracy. In more than 60 percent cases the applied technique of this study helped in improving the accuracy of software estimation by reducing the Magnitude of Relative Error (MRE). The technique is simple and it calculates the expected value of cost or time and then uses different confidence levels which help in making more accurate commitments to the customers.