scholarly journals An Architectural Framework for Generating Food Safety Key Performance Indicators

2020 ◽  
Vol 55 (5) ◽  
Author(s):  
Fatma Abogabal ◽  
Shimaa M. Ouf ◽  
Amira M. Idrees ◽  
Ayman E. Khedr
Keyword(s):  
Data Mining ◽  
Information Technology ◽  
Food Safety ◽  
Performance Indicators ◽  
Food Industry ◽  
Business Processes ◽  
Food Contamination ◽  
Data Mining Techniques ◽  
Threshold Conditions ◽  
Architectural Framework

Information Technology proved its effectiveness in all industry fields, taking the competition to unexpectedly high levels. Identifying the essential parameters is vital to success. In different fields, business processes monitoring is also essential. In the food industry, for example, food hazards may occur in any stage of generating food, from agriculture to serving. This research uses data mining techniques to propose an architectural framework that can be utilized as a guide for food contamination prevention. The proposed framework aims at detecting the current food status, determining the suitability of the current conditions compared with the required conditions, and alerting users of near-threshold conditions. The framework predicts the available parameters for maintaining the food’s acceptability and includes a plan to follow. The research provides a prototype with a benchmark dataset for proving the applicability of the proposed framework.

FUZZY LOGIC IN WEB DATA MINING FOR WEBSITE ASSESSMENT

2003 ◽  
Vol 03 (01) ◽  
pp. 119-133 ◽  
Author(s):  
XUE LI
Keyword(s):  
Data Mining ◽  
Information Technology ◽  
Fuzzy Logic ◽  
Web Data ◽  
Internet Commerce ◽  
Web Data Mining ◽  
Data Mining Techniques ◽  
Logic Problem

This paper proposes a novel application of fuzzy logic to web data mining for two basic problems of a website: popularity and satisfaction. Popularity means that people will visit the website while satisfaction refers to the usefulness of the site. We will illustrate that the popularity of a website is a fuzzy logic problem. It is an important characteristic of a website in order to survive in Internet commerce. The satisfaction of a website is also a fuzzy logic problem that represents the degree of success in the application of information technology to the business. We propose a framework of fuzzy logic for the representation of these two problems based on web data mining techniques to fuzzify the attributes of a website.

scholarly journals Critical Food Safety Issues Facing the Food Industry: A Delphi Analysis

2020 ◽  
Author(s):  
Kevan W Lamm ◽  
Nekeisha L. Randall ◽  
Francisco Diez-Gonzalez
Keyword(s):  
Environmental Policy ◽  
Food Safety ◽  
Research Methods ◽  
Comparative Research ◽  
Food Industry ◽  
Food Contamination ◽  
Safety Issues ◽  
Critical Issues ◽  
To Receive ◽  
Delphi Analysis

The topic of food safety continues to receive increased attention and has ramifications on various human, environmental, policy, and economic levels worldwide. By garnering feedback from 30 food industry experts, this study was undertaken to identify the most critical issues facing the food industry in relation to food safety. According to expert opinion and after three rounds of Delphi inquiry, food contamination detection, outbreaks, and prevention along with governmental oversight, education for and communication with consumers and employees, and globalization were identified as the main areas at the forefront of food safety. Delphi and constant comparative research methods are explained and suggestions on how to make meaning from the results to progress in this area are discussed.

Path Mining in Web Processes Using Profiles

2011 ◽  
pp. 896-901 ◽  
Author(s):  
Jorge Cardoso
Keyword(s):  
Data Mining ◽  
Quality Of Service ◽  
Business Process ◽  
Management System ◽  
Business Process Management ◽  
Process Management ◽  
Business Processes ◽  
Data Mining Techniques ◽  
Using Data

Business process management systems (BPMSs) (Smith & Fingar, 2003) provide a fundamental infrastructure to define and manage business processes, Web processes, and workflows. When Web processes and workflows are installed and executed, the management system generates data describing the activities being carried out and is stored in a log. This log of data can be used to discover and extract knowledge about the execution of processes. One piece of important and useful information that can be discovered is related to the prediction of the path that will be followed during the execution of a process. I call this type of discovery path mining. Path mining is vital to algorithms that estimate the quality of service of a process, because they require the prediction of paths. In this work, I present and describe how process path mining can be achieved by using data-mining techniques.

Importance of Neo-formed Contaminants (NFCs) in Chemical Food Safety

2017 ◽  
pp. 1-3
Keyword(s):  
Food Safety ◽  
Chronic Diseases ◽  
Food Industry ◽  
Food Contamination ◽  
Cross Contamination ◽  
Chemical Contamination ◽  
Safety Standards ◽  
Food And Drink ◽  
Food Safety Standards

Food safety is the number one priority of the food and drink industry worldwide. It is always the target for modern food industry to meet the highest food safety standards based on sound science. While there are many scenarios that might cause food contamination, most fall under one of four categories; biological, chemical, physical and cross-contamination. Specifically, chemical contamination occurs when food comes into contact with chemicals and can lead to chemical food toxicant. Chemicals can produce both acute and chronic diseases depending on the level of contaminants in the food.

scholarly journals The Application of Data Mining Techniques in Agricultural Science

2015 ◽  
Vol 37 ◽  
pp. 108 ◽  
Author(s):  
Hooman Fetanat ◽  
Leila Mortazavifar ◽  
Narsis Zarshenas
Keyword(s):  
Data Mining ◽  
Information Technology ◽  
Growth Factors ◽  
Data Base ◽  
Precision Agriculture ◽  
Positive Impact ◽  
Ornamental Plants ◽  
Large Data ◽  
Agricultural Science ◽  
Data Mining Techniques

Information Technology has a positive impact on other disciplines. Using today's technology, precision agriculture and InformationTechnology are mixed together. Use of Information Technology in agriculture will lead to improvements in productivity. For this purpose,the raw data is transformed into useful information through data mining. This research determined whether data mining techniques can alsobe used to improve pattern recognition and analysis of large growth factors of ornamental plants experimental datasets. Furthermore, theresearch aimed to establish data mining techniques can be used to assist in the classification and regression methods by determining whethermeaningful patterns exist various growth factors of ornamental plants characterized at various research sites across Kish Island. Differentdata mining techniques were used analyze a large data base of ornamental plants properties attributes. The data base has been collected fromdifferent plants of Kish Island in various areas in order to determine, classify and predict effective growth factors on blooming. In thisresearch, analyzed data with regression technique showed the effect of chlorophyll content on the number of flowers. The analysis of theseagricultural data base with different data mining methods may have some advantages in agriculture

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