Semantics-Based Calorie Calculator

In recent years, people are considering healthy diet habits and many of them are trying to track and maintain their daily diet and consumption. To assist them, there are many applications available online and those applications are capable of recording calories for the ingredients consumed, but users must check individual calories and calculate total calories manually. In this paper, we propose a new technique to calculate calories for a given recipe in multiple formats. The new technique uses tokenization, hashing techniques and fuzzy matching for entity extraction and finally does the unit conversion to calculate calories. We compared the results of the proposed technique with the outcomes of the existing applications. These results proved that the new technique has the capacity to produce similar results compared to that of the existing applications and able to calculate calories for recipes in the different formats available on the internet

The Use or Non-Use of Calculators Affects on Student\u27s Ability to Perform Basic Mathematics Problems

The purpose of this study was to determine if the use or non-use of calculators in eighth grade mathematics classes affects a student\u27s ability to solve basic mathematics equations in the Teen living (family and Consumer Science) class when working with simplistic life skill problems

Case-Based Menu Planner: Web-Based System

Case-Based Menu Planner is a web based system and will apply Case-Based Reasoning (CBR) teclmique. This system is developed in order to help user to know the amount of calories needed in one day and also to give advice to the user about the food they take in one day. Given a user query, the system first retrieves similar cases from the case base in which past successful food menu are stored. Then it formalizes desirability criteria of menu accordance with the user query by using the similar cases. Then the system will gives the solution to the user based on similarity and prompt it as an output. CBR is a problem-solving paradigm that allows us to utilize the specific knowledge of previous problem situation (cases) to solve a new problem situation. New problem solved by finding the most similar past cases and then adapt and reuse them in the new problem situation. The most important concept of CBR is that the ability of continuous learning from experience, since a new problem is retained each time a problem have been solved, making it immediately available for the future problem. The development of this system will focus on entering information or data as a new request and also to retrieve saved case as a result for the problems. The methodology that selected for the system development is Rapid Application Development (RAD). The expected output from the project will be the implementation of real system that can be used by the healthy user which is to know the amount of calories needed by them in their daily life. Besides, the users also can know the amount of calories that contains in their meal and can help the users to plan their intake of calories for each day

Financial education for 7 to 19-year-olds in Wales : guidance for schools and colleges

Replaces Guidance document No: 043/201

Temporal case-based reasoning for insulin decision support

Type 1 diabetes mellitus is an autoimmune disease resulting in insucient insulin to regulate blood glucose levels. The condition can be successfully managed through eective blood glucose control, one aspect of which is the administration of bolus insulin. Formulas exist to estimate the required bolus, and have been adopted by existing mobile expert systems. These formulas are shown to be eective but are unable to automatically adapt to an individual. This research resolves the limitations of existing formula based calculators by using case-based reasoning to automatically improve bolus advice. Case-based reasoning is a method of articial intelligence that has successfully been adopted in the diabetes domain previously, but has primarily been limited to assisting doctors with therapy adjustments. Here case-based reasoning is instead used to directly assist the patient. The case-based reasoning process is enhanced for bolus advice through a temporal retrieval algorithm coupled with domain specic automated adjustment and revision. This temporal retrieval algorithm includes factors from previous events to improve the prediction of a bolus dose. The automated adjustment then renes the predicted bolus dose, and automated revision improves the prediction for future advice through the evaluation of the resulting blood glucose level. Analysis of the temporal retrieval algorithm found that it is capable of predicting bolus advice comparable to closed-loop simulation and existing formulas, with adapted advice resulting in improvements to simulated blood glucose control. The learning potential of the model is made evident through further improvements in blood glucose control when using revised advice. The system is implemented on a mobile device with a focus on safety using formal methods to help ensure actions performed do not violate the system constraints. Performance analysis demonstrated acceptable response times, providing evidence that this approach is viable. The research demonstrates how formula based mobile bolus calculators can be replaced by an articially intelligent alternative which continuously learns to improve advice

Financial education for 7 to 19-year-olds in Wales: guidance for schools and colleges

"This document provides guidance on the provision of financial education for 7 to 19-year-olds in schools and colleges in Wales. It identifies the opportunities for the provision of financial education and provides guidance on learning and teaching strategies. It also includes advice on teaching resources and working with partners in developing and delivering a planned approach to the provision of financial education." - Page 2

Simulating What?

Any attempt to simulate science has first to say what science is. This involves asking three questions: 1) The Scope Question: What bit of science is the target? It is immensely confusing (as the history of these debates shows), if one simulates some little aspect of science, as in the case of BACON, and then claims that one has built a machine that can 'do science'. 2) The Micro-World Question: Is the criterion of success the reproduction of human science – with all the same findings turning up – or the simulation of something that is believed to be a scientific process with results that pertain only to the world of the simulation which do not correspond to the outcome of human science as we know it? If the latter it will be important to be sure that one is not merely developing a 'micro-world' – a world so tidied up for the purposes of simulation that it does not bear on human science. 3) The Chess Question: Even if the idea to reach the same results as has been reached by human science, does it have to be by 'the same' means in order to count as a simulation of human science? I call it the 'chess question' because Deep Blue does not play in the same way as human grand masters but is still better at winning.Science, Language, Demarcation, Micro-World, BACON, Chess