A study on the social and cultural context of toys for primary school children

In response to the post-epidemic relationship and other factors, the number of students who transfer from abroad is increasing daily. The timing and reasons such children return to their hometown to study nowadays are extremely diverse, often appearing in the floating population, emergencies, and individual cases. At present, more and more "international transfer students" appear in the education system of their hometown and home country, and they are facing great difficulties in academic and interpersonal relationships. Because of their lack of language skills, such children cannot successfully integrate into the education system after returning to their hometowns. In order to protect students' learning rights and avoid becoming "guests in the classroom," this study starts from the social and cultural context of toys among elementary school children; Analyzed and explored their cultural background through evaluation constructs, user journey maps, questionnaires, and applied grounded theory in qualitative research, as well as their emotional ups and downs during the game. Explore objects' meaning and relationships represented in the social culture of children to explore the emotional motivation of school children and the preferences of product modeling. It aims to understand the relationship between personal emotional fluctuations, environmental and behavior of use, hoping to create more possibilities for future curriculum development and toy design. This study adopts between-subjects design to investigate the acceptance level and psychological experience process of 120 elementary school children in the process of experiencing the interactive integration of toys into learning. Among them, 60 students are Eastern Asians and 60 are Western foreign students. Interview and record analysis. And from the popular toys on the e-commerce platform on the market, 20 items were screened out one by one for the classification of interactive toys and experience , integrated into the research and investigation of these 120 elementary school children, observed and recorded through questionnaires and interviews

Improving the Performance of Modular Production in the Apparel Assembly: A Mathematical Programming Approach

We construct the mathematical models to find the optimal allocation of the module’s capacity (module members) to different assembly operations in a module for given garment assembly tasks in a modular production system. The objectives of the models are minimizing the holding cost for work in process (WIP) inventories in the module and the total deviation of the WIP inventories from their corresponding target values in the module during a specific time interval. The solutions of the models can be used as reference to achieve better allocation of the module members to different operations in a module to fulfill the given garment assembly tasks

THE DISCRIMINATION OF BARBELL WEIGHT FOR WEIGHTLIFTERS

Ten college weightlifters were recruited in this study. The standard barbell weight (Ws) of each participant was set at 80% of personal best snatch record. The test barbell weights that include Ws, Ws+-1kg, Ws+-2kg, and Ws+-5kg were given randomly, then each lifter was asked to identify the difference between the test weight and standard weight. The discrimination was over 86% when the test weight was Ws+-5kg. For the test weight equal to the standard weight, the discrimination was significantly less than that of other test weights (p less than 01). Based on the results, the weightlifter seems to have good discrimination in the barbell mass at the difference of 5 kg. It seems that they could not be aware of the slight difference (ex: less than 2kg) of barbell mass by 80% of their best snatch record

Optimal Routing for Heterogeneous Fixed Fleets of Multicompartment Vehicles

We present a metaheuristic called the reactive guided tabu search (RGTS) to solve the heterogeneous fleet multicompartment vehicle routing problem (MCVRP), where a single vehicle is required for cotransporting multiple customer orders. MCVRP is commonly found in delivery of fashion apparel, petroleum distribution, food distribution, and waste collection. In searching the optimum solution of MCVRP, we need to handle a large amount of local optima in the solution spaces. To overcome this problem, we design three guiding mechanisms in which the search history is used to guide the search. The three mechanisms are experimentally demonstrated to be more efficient than the ones which only apply the known distance information. Armed with the guiding mechanisms and the well-known reactive mechanism, the RGTS can produce remarkable solutions in a reasonable computation time

The joint influence of quality assurance and postponement on a hybrid multi-item manufacturing-delivery decision-making

The present research explores the collective influence of quality assurance and postponement on a hybrid multiproduct replenishing-delivery decision-making. Assume the required multiproduct has a standard (common) component, and our replenishing-delivery model has incorporated a two-phase postponement strategy. The first phase makes all standard components and hires an external supplier to partially provide the required parts to cut short the needed uptime. In contrast, the second phase fabricates the finished multiproduct in sequence. To ensure the desired merchandise quality, we apply a quality-assurance action to the in-house processes to screen and remove scrap items and rework the repairable defects in both stages. Upon completing each merchandise, these products are transported to the customer in n fixed-quantity shipment in fixed-time intervals. We employ math modeling and formulating approaches to gain the overall supply-chain operating expenses comprising subcontracting, fabricating, stock holding, transportation, and customer holding costs. By minimizing system operating expenses, this research determines the optimal replenishing-delivery policy. Lastly, we give a numerical example to demonstrate our study’s applicability and usefulness/capability for facilitating managerial decision-making

Two-Echelon Inventory Optimization for Imperfect Production System under Quality Competition Environment

This paper develops two integrated optimization models of two-echelon inventory for imperfect production system under quality competition environment, in which the vendor’s production process is assumed to be imperfect, and JIT delivery policy is implemented to ship product from the vendor to the buyer. In the first model, product defect rate is fixed, and, in the second model, quality improvement investment is function of defect rate. The optimal policies of ordering quantity of buyer and shipment from vendor to buyer are obtained to minimize the expected annual total cost of vendor and buyer. Numerical examples are used to demonstrate the effectiveness and feasibility of the models. Sensitivity analysis is taken to analyze the impact of demand, production rate, and defect rate on the solution. Implications are highlighted in that both the vendor and the buyer can benefit from the vendor’s investing in quality improvement

Img2Logo:Generating Golden Ratio Logos from Images

Logos are one of the most important graphic design forms that use an abstracted shape to clearly represent the spirit of a community. Among various styles of abstraction, a particular golden-ratio design is frequently employed by designers to create a concise and regular logo. In this context, designers utilize a set of circular arcs with golden ratios (i.e., all arcs are taken from circles whose radii form a geometric series based on the golden ratio) as the design elements to manually approximate a target shape. This error-prone process requires a large amount of time and effort, posing a significant challenge for design space exploration. In this work, we present a novel computational framework that can automatically generate golden ratio logo abstractions from an input image. Our framework is based on a set of carefully identified design principles and a constrained optimization formulation respecting these principles. We also propose a progressive approach that can efficiently solve the optimization problem, resulting in a sequence of abstractions that approximate the input at decreasing levels of detail. We evaluate our work by testing on images with different formats including real photos, clip arts, and line drawings. We also extensively validate the key components and compare our results with manual results by designers to demonstrate the effectiveness of our framework. Moreover, our framework can largely benefit design space exploration via easy specification of design parameters such as abstraction levels, golden circle sizes, etc