Applied Mechanics and Materials Vols. 764-765

Abstract: This study aims to design a two-stage sliding function. First, plural function instructions are grouped into a functional classification, and a sliding operation is divided into anterior sliding and posterior sliding. Anterior sliding selects the functional classification, which contains the function instructions, while posterior sliding selects the function instruction to be executed. The operation and application of a sliding gesture to the smart phone and tablet PC can be greatly expanded by this design.

Abstract: The growing users’ awareness in practicing individual life style have led to diverse living products in business markets. Hence, how to effectively meet the emotional or kansei needs of target users become crucial issues for product designers. This article aims to propose a revised Kansei Form Composition (KFC) to more effectively analyze and develop product styling. The updated approach not only integrates kansei thinking and Morphological Analysis but also employs factor weights and flash cards. During the analyzing stages, the new KFC applies visual images as interfaces to induce latent demands of the target interviewers. Related kansei adjectives and form elements are selected as main design factors. Furthermore, weights of the factors are identified through the interviewees’ feedbacks. Core flash cards of design factors are submitted. The revised approach suggests the core flash cards as feasible inspiration tools to the designers in the idea development stages. By using the new KFC, timer form designs for LOHOS involvers are demonstrated. The authenticity and applicability is verified that the revised KFC can catch the preference of user needs more effectively.

Abstract: The permutation flow shop problem (PFSP) is an NP-hard permutation sequencing scheduling problem, many meta-heuristics based schemes have been proposed for finding near optimal solutions. A simple insertion simulated annealing (SISA) scheme consisting of two phases is proposed for solving PFSP. First, to reduce the complexity, a simple insertion local search is conducted for constructing the solution. Second, to ensure continuous exploration in the search space, two non-decreasing temperature control mechanisms named Heating SA and Steady SA are introduced in a simulated annealing (SA) procedure. The Heating SA increases the exploration search ability and the Steady SA enhances the exploitation search ability. The most important feature of SISA is its simple implementation and low computation time complexity. Experimental results are compared with other state-of-the-art algorithms and reveal that SISA is able to efficiently yield good permutation schedule.

Abstract: Research on gamification of learning has been very popular in the past years; especially, the learning effectiveness in applying games to the education of natural science in elementary and junior high schools has been proven. Aiming at the human blood circulation unit, which is rather difficult to comprehend, in the biology materials for junior high school students, Mobile Meaningful Blood Circulation Learning System, called MMBCLS game-based learning, is developed. The players could comprehend the functions of systemic circulation and pulmonary circulation through games. In the study, the instructional design is based on Meaningful Learning and follows the principles of digital game-based learning models to design the after-class multimedia materials, which allow learners enjoying learning with fun. The quasi-experimental design is utilized for the learning assessment, where the experimental group applies MMBCLS, while the control group uses general instruction for the teaching materials. The experimental results show significant difference of the experimental group in the learning effectiveness and better post-test results than the control group. The research outcomes could be the reference of material design for teachers and provide educators with the reference of mobile as meaningful media material design.

Abstract: This study was meant to construct an intelligent financial investment decision-making system capable of knowledge mining, performing assessments and evolving on its own based on event assessments by applying the classifier system in the artificial intelligence methodology. It is referred to as the Event Classifier System (ECS). In order to prove the feasibility and validity of the developed method and model, this study designed and developed the transaction model for event classifiers by creating the strategic modules for institutional investor’s holdings-related events and ex-right (dividend)-related events. Results of this empirical study show that the ECS established in this study had superior return on investment (ROI) performance than the Taiwan Weighted Stock Index for the same period of time.

Abstract: A multi-strategy based population optimization, referred to MSPO, is proposed in this paper. The algorithm is developed by hybridizing four different population-based algorithms, bare bone particle swarm optimization, quantum-behaved particle swarm optimization, differential evolution and opposition-based learning. It aims at enhancing the exploration and exploitation capability of population based algorithm for general optimization problem. These four options are randomly selected with equal probability during the search process. The proposed algorithm is validated against test functions and then compares its performance with those of particle swarm optimization and bare bone particle swarm optimization. Numerical results show that the performance is increased greatly both in solution quality and convergent speed.