Mining of nutritional ingredients in food for disease analysis

Suitable nutritional diets have been widely recognized as important measures to prevent and control non-communicable diseases (NCDs). However, there is little research on nutritional ingredients in food now, which are beneficial to the rehabilitation of NCDs. In this paper, we profoundly analyzed the relationship between nutritional ingredients and diseases by using data mining methods. First, more than 7,000 diseases were obtained and we collected the recommended food and taboo food for each disease. Then, referring to the China Food Nutrition, we used noise-intensity and information entropy to find out which nutritional ingredients can exert positive effects on diseases. Finally, we proposed an improved algorithm named CVNDA_Red based on rough sets to select the corresponding core ingredients from the positive nutritional ingredients. To the best of our knowledge, this is the first study to discuss the relationship between nutritional ingredients in food and diseases through data mining based on rough set theory in China. The experiments on real-life data show that our method based on data mining improves the performance compared with the traditional statistical approach, with the precision of 1.682. Additionally, for some common diseases such as Diabetes, Hypertension and Heart disease, our work is able to identify correctly the first two or three nutritional ingredients in food that can benefit the rehabilitation of those diseases. These experimental results demonstrate the effectiveness of applying data mining in selecting of nutritional ingredients in food for disease analysis

Comparative Evaluation of Log-Based Process Performance Analysis Techniques

Käesolev magistritöö võrdleb erinevaid protsessikaeve uurimustöid ning liigitab neid järgnevate näitajate põhjal: aeg, kvaliteet ja ressursikasutus. Magistritöö põhjendab protsessikaeve meetodite kasutamist ja nende pakutavat lisandväärtust. Pakume ühiseid mõõtühikuid ja parameetreid, mida saab kasutada protsessi tulemuslikkuse analüüsimeetodite hindamiseks. Lisaks eelnevale kirjeldab lõputöö kirjanduses esinevaid tarkvaralahendusi ja algoritme.This paper gives a comparative overview of process mining performance studies and clusters them based on proposed metrics: time, quality and resources. This thesis provides an explanation of reasons for using process mining performance techniques and shows what value they can bring. We provide common metrics and unit of measurement that can be used to evaluate process performance analysis methods. Also, the paper describes tools and algorithms that have been implemented in the literature

Functional Expense Allocation Ratios to Predict Financial Condition at Public Higher Education Institutions

The higher education industry has faced increased competition in recent years from new institutions and learning platforms entering the marketplace. Public higher education institutions, in particular, have been forced to develop strategic plans due to limited state funding in recent years. These colleges and universities face the challenge of allocating their limited financial resources in a manner that will optimize financial strength and ensure long-term sustainability. Institutions classify their operating expenses into several different functional expense categories, including instruction, academic support, student services and operations and maintenance of plant. This paper analyzed the relationship between allocation ratios of functional expenses and an institution’s financial condition. Multiple regression analysis was performed to determine how fluctuations in financial allocation ratios impact an institution’s financial condition. The research could aide higher education institutions in strategically allocating resources to improve their financial position

State Appropriations and Allocation Ratios to Predict Financial Condition at Public Higher Education Institutions

The higher education industry has faced increased competition in recent years from new institutions and learning platforms entering the marketplace. Public higher education institutions, in particular, have been forced to develop strategic plans due to limited state funding in recent years. These colleges and universities face the challenge of allocating their limited financial resources in a manner that will optimize financial strength and ensure long-term sustainability. Institutions classify their operating expenses into several different functional expense categories, including instruction, academic support, student services and operations and maintenance of plant. This paper analyzed the relationship between changes in state appropriations, allocation ratios of functional expenses, and an institution’s financial condition. Bivariate and multiple regression analysis was performed to determine how fluctuations in state appropriations and financial allocation ratios impact an institution’s financial condition. The research could aide higher education institutions in strategically allocating resources to improve their financial position. God has called us all to live in community and flourish. Higher education institutions promote community among students, faculty, and staff as well as provide knowledge and skills for individuals to flourish upon graduation