Yukiko Matsushima

An Online Fill-in-the-Blank Problem Function for Learning Reserved Words in Java Programming Education

The Java programming education to students has been held in a lot of universities and professional schools due to the reliability, portability, and easy learning. To assist this education, our group has developed a Java programming learning system based on the test-driven development method. However, this Web system targets students who have studied Java to some extent. In this paper, we propose a fill-in-the-blank problem function for this system to assist the learning of the Java reserved words by novice Java learners. Our function consists of a teacher service process and a student service process. By the former one, a teacher can generate a fill-in-the-blank problem easily by blanking the specified reserved words randomly from a sample Java code in the database. By the latter one, a student can repeatedly submit answers of a problem until all the questions are correctly solved for self-study. The function is implemented on an existing Web system and is applied to students who are currently learning Java. The questionnaire result confirms the effectiveness of our proposal.

A Proposal of a Menu Planning Algorithm for Two-phase Cooking by Busy Persons

For busy persons such as working people, students, and nurturing parents, it is very hard to spend a long time in cooking foods by themselves at home after working for long hours on weekdays. As one solution, the cooking process can be divided into two phases, where the preparation steps for foods that they will eat on the following weekdays are performed on a weekend, and the final steps for some foods are finished on the eating day in a short time. Then, the task of generating a menu planning with this two-phase cooking becomes a complex problem to satisfy the limited cooking time. In this paper, we formulate this time-constrained menu planning problem with the two-phase cooking, and prove the NP-completeness of its decision problem through the reduction from the NP-complete knapsack problem. Then, we present its heuristic algorithm based on a simple greedy method for the knapsack problem, where foods are sequentially selected into the menu in descending order of food priorities. We apply the algorithm to the generation of one week menu plan from 53 food candidates, where the result verifies the effectiveness of our approach.

An application of cooking-step scheduling algorithm for homemade cooking and its extensions

Homemade cooking can have a key role for a healthy and cost-efficient life. To help this activity for busy people such as workers, students, and child-rearing families, we have proposed a cooking-step scheduling algorithm to suggest an optimal sequence of the cooking-steps when multiple dishes are cooked within a limited time. In this algorithm, the cooking procedure for each dish is divided into a set of cooking-steps, and the execution sequence of all the cooking-steps for the dishes is optimized such that the total cooking time is minimized. In this paper, we first show our application result of this algorithm in cooking five dishes and the arisen problems through this experiment. Then, we present four extensions of this algorithm to solve them. Through simulations and cooking experiments, we verify the effectiveness of the algorithm extensions.

Extensions of cooking guidance function on Android tablet for homemade cooking assistance system

Previously, we proposed a cooking-step scheduling algorithm to find a schedule of applying the cooking steps in the recipes for efficiently cooking multiple dishes simultaneously, to help healthy and cost-efficient lives for busy person. Then, we implemented a cooking guidance function on an Android tablet to navigate the cooking schedule in a kitchen. Although we confirmed the effectiveness through cooking experiments, we found three problems: 1) a user may click a starting button even if the previous required steps are not completed, 2) a user may miss the proper timing to stop a cooking-step, and 3) the duration time for a cooking-step may be varied by a user skill or a dish nature. In this paper, we extend the cooking guidance function by adding three features of starting condition checking, time-up alarming, and cooking rescheduling to solve these problems. We verify the effectiveness of the extended guidance function through experimentally cooking four dishes.

A cooking guidance function on Android tablet for Homemade Cooking Assistance System

To assist busy people such as working persons, students, and nurturing families to have economical and healthy lives with homemade cooking, we have proposed a Web-based HOmemade Cooking Assistance System (HOCAS). Previously, we implemented the menu planning function and the cooking-step scheduling function at the server using JSP/Servlet, so that a user can plan a menu for the whole week and make a cooking-step schedule to efficiently cook multiple dishes at the same time. Unfortunately, a user needs to refer the next cooking-step on a paper during cooking process, which is actually not easy at critical timing in a kitchen, because the schedule is output as a PDF file. In this paper, we propose a cooking guidance function on an Android tablet as a Java application to navigate cooking-steps through touch panel operations. We confirmed the effectiveness by experimentally cooking four dishes using this function.

Practices of Cooking-Step Scheduling Algorithm for Homemade Cooking

Homemade cooking is essential not only for keeping healthy and cost-efficient dietary lives but also for constructing good family relationships and identities. Previously, we proposed the cooking-step scheduling algorithm to help homemade cooking by finding a schedule of applying the cooking-steps for multiple dishes with minimal cooking time. In this algorithm, the cooking procedure for each dish is divided into a sequence of six types of cooking-steps to consider the constraints in cooks and cooking utensils in a kitchen. In this paper, we conduct practices of the algorithm in actually cooking dishes by following the generated schedules to show the effectiveness.

An extension of menu planning algorithm for two-phase homemade cooking

Nowadays, many people keep busy lives due to working in companies, studying in schools, or taking care of children or senior parents. As a result, it has become very hard for them to cook foods for suppers by themselves at home after long-hour duties at daytime in weekdays. Previously, to assist homemade cooking of such busy people, we proposed a two-phase cooking such that the preparation phase of cooking foods that they will eat on the following weekdays is performed on a weekend, and the finishing phase for the foods for a supper is completed on the day in short time. Then, we presented a menu planning algorithm to assist generating one-week menus for this two-phase cooking. Unfortunately, we found that this algorithm has the following drawbacks in practical use: 1) the selection of food preference is not easy, 2) the use of preferred ingredients for cooking cannot be directly specified, and 3) the nutrition balance of foods in a menu is not considered. In this paper, we extend this algorithm to solve them by newly defining a preference index and the food balance guide by Japanese government. We verify the effectiveness of the extended algorithm through generating five-day menus from 241 food candidates.

Cooking-Step Scheduling Algorithm for Simultaneous Cooking of Multiple Dishes

Nowadays, cooking everyday is hard for busy persons such as workers, students, and child-rearing families, because the time is limited on weekdays. At the same time, it is important for a healthy diet not to rely on eating-out and instant foods heavily. One solution to this situation is to cook dishes for the whole week on the weekend and eat them on the following weekdays. Then, the way of cooking with a good cooking-step schedule for multiple dishes is very important to save the time. In this chapter, we first propose a cooking model to estimate the cooking time accurately under various conditions including the kitchen layout and the number of cooks. Then, using this model, we propose a cooking-step scheduling algorithm for simultaneous cooking of multiple dishes under the cooking time constraint. Through experiments, we verify the effectiveness of our model and algorithm, where the cooking time difference between the model and the real cooking is only 2 min.