The Influence of Cooperative Learning Model Type Team Assisted Individualized of Interactive Media Assistance to Students' Mathematical Communication Ability

Mathematics is a subject that must be mastered by every students because it relates to everyday life. However, many students consider mathematics to be a difficult and scary subject. Students only consider mathematics as a subject that includes numbers into the formula and the process of memorizing lessons. This results in low students' mathematical communication skills, especially in solving math tasks in the form of stories. This study aims to see the mathematical communication skills of students who are taught through the Team Assisted Individualized (TAI) type of cooperative learning model assisted by interactive media that is better than using scientific learning. The approach used in this research is quantitative. This research is a quasi experiment. The population of this study were all students of class VII and students of class VII 1 as the control class and class VII 3 as the experimental class. The samples were selected by purposive sampling. The research design used was the nonequivalent control group posttest-only design. Retrieval of data in the study using students' mathematical communication tests (posttest). Data collected from the results of the analysis test using SPSS 25 to find normality using the One-Sample Kolmogorov-Smirnov Test, and hypothesis testing using the Mann-Whitney U test. Regarding the research objectives, the results obtained from this study are students' mathematical communication skills. through cooperative learning type Team Assisted Individualized (TAI) assisted by interactive media gives an effect compared to students who get scientific learning. Based on the results of the Mann-Whitney U test, it is known that the Asymp value. Sig. (2-tailed), namely 0.001 <α 0.05.

A Convolutional Neural Network-Based Patent Image Retrieval Method for Design Ideation

The patent database is often used in searches of inspirational stimuli for innovative design opportunities because of its large size, extensive variety and rich design information in patent documents. However, most patent mining research only focuses on textual information and ignores visual information. Herein, we propose a convolutional neural network (CNN)-based patent image retrieval method. The core of this approach is a novel neural network architecture named Dual-VGG that is aimed to accomplish two tasks: visual material type prediction and international patent classification (IPC) class label prediction. In turn, the trained neural network provides the deep features in the image embedding vectors that can be utilized for patent image retrieval and visual mapping. The accuracy of both training tasks and patent image embedding space are evaluated to show the performance of our model. This approach is also illustrated in a case study of robot arm design retrieval. Compared to traditional keyword-based searching and Google image searching, the proposed method discovers more useful visual information for engineering design.

Retrieval of Similarity Measures of Code Component

<div><p><em>Modern programming languages, especially object oriented languages facilitate to create libraries of reusable components (e.g. class definition). The majority of software companies are designing the components and reusing those wherever applicable. Maintaining such components (i.e. class library) and accessing those at right time in right form is challenging because large no. of components in library. Object Oriented Programming supports the reusability of the code. The major challenge in programming is to improve the learning quality and productivity of the software developer, subject teachers and students. </em></p><p><em>To support programming in Java, researcher implemented a design retrieval algorithm which will make it possible to search through potentially reusable Java classes. </em><em>The proposed work, selects the appropriate descriptors of the inputted cases - .java files. It will separate the code components automatically and stores in the repository. The different levels of ambiguity in selection of cases are controlled through data preprocessing technique of data mining. The set of adjustments applied to get the similarity of the code components.</em></p></div>

Product Design Retrieval by Matching Bills of Materials

A new automatic design retrieval method that identifies the legacy product design most similar to a new one is proposed. Matching phylogenetic trees has been utilized in biological science for decades and is referred to as “tree reconciliation.” A new application of this approach in manufacturing is presented where legacy designs are retrieved based on reconciliation of trees representing products bill of materials (BOM). A product BOM is a structured tree, which represents its components and their hierarchal relationships; hence, it captures the contents and structure of assembled products. Making use of data associated with the retrieved designs also helps speed-up other downstream planning activities such as process planning, hence improving planning efficiency. A chemical processing centrifugal pump is used as a case study for illustration. The results obtained using the proposed method is compared with those recently published on BOM trees matching for further analysis and verification. This novel method is less computationally complex than available state-of-the-art algorithms.

Integrating corpus data in dynamic knowledge bases

Terminological information is a key element in the construction of a knowledge base. In order for a knowledge base to be useful to different users, terminological information should be extracted from corpora so as to reflect the different pragmatic nuances. Puertoterm is a knowledge base in the field of Coastal Engineering, which has made use of corpus information to develop terminological entries. It also includes contextual information in such a way that this information interacts with other elements of the knowledge base. We describe the methodology followed in the project regarding corpus design, retrieval of lexical information, conceptual organization of the domain of Coastal Engineering, and the elaboration of terminological entries.

Economic evaluations conducted by Canadian health technology assessment agencies: Where do we stand?

Objectives:To examine the production of Health Technology Assessments (HTAs) with economic evaluations (EEs) conducted by Canadian HTA agencies.Methods:This research used a three-step approach: (i) the Web sites of five Canadian organizations promoting HTA were searched to identify HTA reports with EEs; (ii) HTA agencies were surveyed to verify that our information was complete with respect to HTA activities and to describe the factors that influence the HTA process in Canada (i.e., selection of HTA topics, execution, dissemination of results and future trends); (iii) HTAs with EEs were appraised in terms of study design, retrieval of clinical and economic evidence, resource utilization and costing, effectiveness measures, treatment of uncertainty as well as presence of a budget impact analysis (BIA), and policy recommendations.Results:Two hundred forty-nine HTA reports were identified of which 19 percent included EEs (n= 48). Decision analytic techniques were used in approximately 75 percent of the forty-eight EEs and probabilistic sensitivity analyses were commonly used by all agencies to deal with parameter uncertainty. BIAs or policy recommendations were given in 50 percent of the evaluations. Differences between agencies were observed in terms of selection of topics, focus of assessment and production of HTA (e.g., in-house activities). Major barriers to the conduct of HTAs with EEs were capacity, a lack of interest by decision makers and a lack of robust clinical information.Conclusions:The results of this research point to the need for increased HTA training, collaboration, evidence synthesis, and use of pragmatic “real world” evaluations.