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In this study, we propose a novel method for creating nutritious menus using vertex coloring, a fundamental concept in graph theory. Our team has combined the Welch-Powell algorithm with a mathematical combination technique to generate a range of menus that adhere to low-calorie nutritional guidelines while offering diversity. To showcase the practicality and efficacy of our approach, we have utilized dynamic simulation in Matlab, which generates three distinct diet combinations customized to meet specific nutritional needs. Our methodology can serve as a blueprint for developing balanced meal plans and underscores the flexibility of graph theory in real-world applications. Additionally, we have explored an alternative approach to arranging menus that employ vertex-disjoint paths in a graph, resulting in a streamlined process for creating diverse and nutritionally balanced menus. This study highlights the significance of innovative solutions for addressing the complexities of diet planning and provides valuable insights for future research. [ABSTRACT FROM AUTHOR]

Sustainable Development Goals (SDGs) are a set of 17 interrelated goals adopted by the United Nations (UN) for a better and sustainable future for all. One of the SDGs, SDG 2, relates to achieving food security, and improved nutrition and promoting sustainable agriculture. Millets are a group of small seeded grasses rich in different nutrients, micronutrients and minerals. Apart from many types, finger millet, pearl millet, foxtail millet, barnyard millet, proso millet, kodo millet, and sorghum are the most important ones grown worldwide. Millets can contribute to dietary diversity and promote sustainability. The objective of this research has been to identify an optimal combination of intake food items to satisfy the daily nutritional requirements by including millets. This research uses a modified form of the classic Diet problem. Using this mathematical model, an optimal combination of food items to be included in daily meal is found out. Apart from satisfying the nutritional need optimally, this research also takes into consideration to include the dietary preference of people. After solving for multiple scenarios, it has been concluded that that daily Recommended Dietary Allowance (RDA) cannot be fulfilled without including millets in the meal. Millets can have transforming impact on the nutritional intake of people and they can be highly beneficial in combating dietary nutrient deficiency. [ABSTRACT FROM AUTHOR]

Obesity is a global health issue which is growing rapidly. This results in an unhealthy diet containing high amounts of sugar, salt and fats in addition to an inactive lifestyle. The problems of chronic diseases like obesity and overweight are caused fundamentally because of the vitality of lopsidedness between calories ingested and calories burned. In this paper, an approach is proposed that incorporates the possible mitigation solutions to detect food images and suggest the calorie content using Faster RCNN and TensorFlow Lite for users. Faster RCNN model is first trained using multiple food images and then converted to TensorFlow Lite model which is compatible with Android devices and requires less computational and cloud resources for detecting objects. Real time food and calorie detection along with appropriate meal plan recommendations will definitely change the day-to-day performance of an individual. [ABSTRACT FROM AUTHOR]

Prospective nutritionists are required to have the ability to plan diet menus in providing nutritional care to patients. In order to facilitate the process, the existence of an instrument or supporting technology is a necessity. However, currently existing instruments, both conventional and technological, still have limitations. Starting from the ease of use, food sources, and calculation results. Menu Harianku is here as an alternative solution in the form of a website-based technology instrument. However, it is necessary to measure the performance of this instrument to justify its use. Therefore, this study aims to compare the effectiveness of using Menu Harianku with conventional instruments. Analytical-comparative design with a cross-sectional approach was used as an approach in this study. A total of 90 sixth-semester nutrition students at Nahdlatul Ulama University who were taken by probability sampling method were selected as respondents. The independent variable in this study is the diet menu planning method in the form of conventional methods and my daily menu website, and the dependent variable is the effectiveness of diet menu planning. Data were analyzed by Wilcoxon Signed Rank Test. The results showed that 76.6% of respondents felt that my daily menu website was very effective use in planning diet menus. While in the conventional method there are only 36.6%. The results of statistical tests showed that there was a significant difference in effectiveness between the conventional method and the Menu Harianku website in planning diet menus (p=0.000). In terms of the time required, the preparation of a diet menu plan using My Daily Menu takes 9 minutes 38 seconds. Meanwhile, using the conventional method, it takes 30 minutes 50 seconds. These results indicate that the overall use of the Menu Harianku website is more effective than conventional methods in planning diet menus. [ABSTRACT FROM AUTHOR]

According to a survey conducted by the Ministry of Education, Culture, Sports, Science and Technology, 99.1% of elementary schools in Japan provide school lunches. Nutrition teachers prepare school lunch menus at monthly meetings. Because nutrition teachers need to consider a large number and variety of constraints, it requires a lot of time and effort to prepare menus. Therefore, it is highly significant to introduce an automatic menu creation model for school lunches. In the school lunch standards, nutrition teachers are expected to expose students to various foods. From the viewpoint of dietary education, nutrition teachers are also required to expose students to a variety of ingredients and tastes. Therefore, it is necessary to consider the dishes diversity in terms of ingredients and seasonings. For automatic school lunch menu creation, the similarities between dishes are important to provide an appropriate combination of various foods. There were previous studies that calculated dishes similarity considering ingredients and food groups and grouped similar dishes considering the main seasoning. In our previous study of automatic school lunch menu creation, the inter-dish similarities were calculated based on the categories and the gram amounts of ingredients and seasonings in each dish. Based on the inter-dish similarities, similar dishes were classified into the same group, and constraints on the frequency of serving were created for each similar dish group to create an automatic menu creation model. The issue of the previous study was that the grouping of similar dishes was based solely on the same ingredients and seasonings in the end. In other words, the results were not sufficiently based on human senses. For example, the main ingredients of two dishes are different for beef and pork, respectively, but are the same meat food group. In addition, if their seasoning combinations are very similar, humans may judge these two dishes as similar. Considering the food groups of main ingredients, the grouping is expected to become close to the human senses. The purpose of this study is to propose a calculation method of inter-dish similarity that considers the dishes similarities based on the food group of the main ingredients and combination of seasonings. In this study, the main ingredient in each dish was determined based on the number of ingredients in each dish and their gram amounts. Specifically, ingredients with a gram amount of the ingredient larger than the threshold value were determined as the main ingredient. The threshold value was calculated by dividing the gram amounts of all the ingredients in a dish by the number of ingredients. The new inter-dish similarity was calculated by the cosine similarity using the food groups of the main ingredients and the combination of seasoning. As a result of the calculation using actual data from school lunch dishes, the proposed method calculated a large similarity value between the two dishes which are meat dishes seasoned with the combination of soy sauce and sugar. Since nutrition teachers evaluated these dishes as similar dishes, we succeeded in calculating the dishes similarities considering human senses. [ABSTRACT FROM AUTHOR]

Many companies in Japan operate cafeterias in universities, offices, factories, and other locations. Cafeterias offer a wide variety of menu items, including set menus, rice bowls, and noodles. Japanese cafeterias have a variety of styles to serve food. In particular, a la carte menu is preferred by many users. In the a la carte menu, dishes such as the staple meal, main dish and soup are sold as individual items, rather than as a set meal. The menu allows customers to freely select dishes according to their tastes, quantities, and economics. Therefore, customers can be very satisfied. In the a la carte menu, it is important to combine dishes of various tastes and prices and to use ingredients with different textures when preparing a menu for a day. If there are similar dishes and the number of choices is small, the number of visitors to the cafeteria may decrease, which will lead to a decrease in sales. In addition, when preparing a menu for several days, it is necessary to consider constraints such as frequency of service, cooking methods, and budget. It is very difficult to manually find combinations of dishes that satisfy many of these constraints. In addition, the menu contents vary depending on the menu planner, making it difficult to continue creating high-quality menus over a long period of time. Therefore, there is a need for an automatic menu planning model to improve operational efficiency.The purpose of this study is to propose a menu planning model that considers the characteristics of a la carte menu based on mathematical optimization. We regard menu planning as "finding the optimal combination of dishes that satisfies various constraints in the field for multiple periods from several sets of dishes". Then, we formulate a menu planning model for a la carte menu as a "combinatorial optimization problem" in mathematical optimization. In this study, we took into account constraints on dish categories, frequency of serving some ingredients, and cost. To demonstrate the usefulness of the proposed model, numerical experiments are conducted using actual data from a cafeteria that serves a la carte menu. The cafeteria serves approximately 25 dishes per day, including staples, main dishes, and side dishes. The menu creator manually prepares menu lists for multiple periods over a long period of time.Numerical experiments using the mathematical optimization solver Gurobi Optimizer produced a menu for one month. The menu consisted of six dishes that is composed of staple meals and main dishes. The results of the numerical experiments were evaluated by menu planners of the cafeterias. They regarded the menu created by the proposed model as a menu that can be served in the field. The time required to output a menu was less than one minute. Compared to manual menu creation, the time required was significantly reduced. [ABSTRACT FROM AUTHOR]

Japanese school lunches are said to be more nutritionally balanced than those of other countries. This is due to the fact that school lunch menus are prepared in consideration of various items such as food categories and coloring of dishes. As a specific example, Japanese school lunches include not only meat-based dishes, but also rice and side dishes as part of the daily menu. In Japan, there is a style of cooking called Washoku. It is an expression of the Japanese people's respect for nature, and has been selected as an intangible cultural heritage because it is a traditional social practice that has been passed down from generation to generation. In the field of school lunch, there is a need for a system to support nutrition teachers in menu planning. There are many restrictions to be considered in menu preparation, such as nutritional intake standards, ingredient costs, and cooking time, and it takes a lot of time and effort to complete a menu. In Japan, the intake of 13 nutrients is determined according to the School Meal Intake Standards established by the Ministry of Education, Culture, Sports, Science and Technology (MEXT). Therefore, when preparing menus, it is necessary to keep within the upper and lower limits of the standard's intake. Previous research has proposed a menu planning model using a mathematical optimization solver that takes into account about 70 different constraints. However, the model has two problems: First, it does not adequately take into account the frequency with which food items and dishes are served. Second, the solution time is too long (about 6,000 seconds). The second reason for this is the number of decision variables and constraints in a month, which are enormous: approximately 200,000 and 10,000, respectively. On the other hand, another previous studies using genetic algorithms (hereafter referred to as GAs) have produced menus in a relatively short time. However, the number of constraints considered is quite small (six), and the frequency of serving ingredients and dishes is not taken into account. In general, in GA, as the number of constraints increases, the solution generated by crossing becomes infeasible in many cases, and it is time-consuming to change to a feasible solution. In this study, we formulate an automatic menu creation model that takes into account the frequency of serving ingredients and dishes as a mathematical optimization problem. Using the tabu search method, we propose a heuristic solution method that can find a good solution in practical time when the number of constraints is large. The solution corresponds to a menu, which is a combination of dishes for a day. By exchanging dishes in the menu, a better solution is searched. In this study, a taboo list is provided to prevent the user from re-selecting a dish once it has been selected. Numerical experiments using real data of school lunch menus show that the proposed method reduces the solution time better than the conventional method. [ABSTRACT FROM AUTHOR]

The aim of present study is to explain the concept of menu, menu management process and mention the importance of the menu in terms of the establishments. It is also aimed to examine menu planning by explaining the subjects in menu management process and prove the importance of menu item selection. According to these aims, the stages of menu management process (planning, pricing, design and analysis) were examined and relationships of these stages with menu planning were explained. Also, the importance of menu item selection was emphasized. As a result of literature review, some recommendations were given both for the practitioners and the researchers. [ABSTRACT FROM AUTHOR]

Planning suitable menus for individuals who have health problems is a complex task since the solutions produced by professionals (dietitians) are usually very subjective and difficult to be systematically represented. This research focused on designing the knowledge base repository construction which consists of the existing cases to be used as the case-based for the retrieval process. The main aim of this research is, to design dietary knowledge representation base on set of rules, knowledge and experience adhered by human experts. Memory Organization Packet or MOP is proposed to be used along with the Similarity Measure for the matching process of pass cases from the case-based with the new cases. This research used actual data and cases which were obtained from Hospital Universiti Kebangsaan Malaysia (HUKM) and subsequently evaluated to determine its effectiveness. [ABSTRACT FROM PUBLISHER]

"Bento" is widely known as a part of Japanese food culture. There are many companies in Japan that manufacture thousands of bento every day and deliver them to customers working in offices and factories. The menus of bento manufacturing companies include daily bento, rice bowls, and noodles. The attraction of the Japanese daily bento is that one can enjoy a variety of flavors at once. A bento consists of rice as the staple food, a main dish, and a side dish. It contains dishes of different flavors. Another attraction of the Japanese daily bento is the variety of cooking styles. They include Japanese, Western, and Chinese styles. In menu planning for a daily bento, it is important to combine dishes with a variety of flavors and foods with different textures. If customers feel tired of eating, the number of customers buying bentos will decrease which leads to decrease in sales. In creating a multi-day menu, it is necessary to consider various constraints such as the frequency of serving food, cooking methods, and budget. However, it is very difficult to manually find a combination of dishes that satisfies these many constraints. In addition, the contents of menus vary depending on person to person in charge of creating menus, and it is difficult to continue preparing high-quality menus for a long period of time. The purpose of this study is to propose a menu planning model based on mathematical optimization. We consider menu planning as "finding optimal combinations of dishes for multiple periods from a set of dishes that satisfy various constraints in the field, taking into account similar dishes and ingredients". Then, we formulate a menu planning model for catered lunches as a "combinatorial optimization problem" in mathematical optimization. We took account of 37 constraints, including the constraint of similarly flavored dishes. The purpose of this study is to propose a menu planning model based on mathematical optimization. We consider menu planning as "finding optimal combinations of dishes for multiple periods from a set of dishes that satisfy various constraints in the field, taking into account similar dishes and ingredients". Then, we formulate a menu planning model for catered lunches as a "combinatorial optimization problem" in mathematical optimization. We took account of 37 constraints, including the constraint of similarly flavored dishes. As a result of numerical experiments using the mathematical optimization solver Gurobi Optimizer, the menu created by the proposed model was evaluated by experts who have been in charge of menu planning more than 10 years. They regarded the menu created by the proposed model as a menu that can be served on-site. In addition, the time required to prepare the menu was less than 10 minutes. The time required for menu preparation was significantly reduced compared to manual menu preparation. [ABSTRACT FROM AUTHOR]

We propose a system helping blind people to get character information in their surrounding environment, such as merchandise information (name, price, and best-before/use-by date) and restaurant menu (name and price). The system consists of a computer, a wireless camera/scanner and an earphone. It processes images captured/scanned by a user and extracts character regions in the image by using Support Vector Machine (SVM). Applying Optical Character Recognition (OCR) to the extracted regions, the system outputs the character information as synthesized speech. [ABSTRACT FROM AUTHOR]