Fuzzy Clustering Algorithm Based on Improved Global Best-Guided Artificial Bee Colony with New Search Probability Model for Image Segmentation.

Clustering using fuzzy C-means (FCM) is a soft segmentation method that has been extensively investigated and successfully implemented in image segmentation. FCM is useful in various aspects, such as the segmentation of grayscale images. However, FCM has some limitations in terms of its selection of the initial cluster center. It can be easily trapped into local optima and is sensitive to noise, which is considered the most challenging issue in the FCM clustering algorithm. This paper proposes an approach to solve FCM problems in two phases. Firstly, to improve the balance between the exploration and exploitation of improved global best-guided artificial bee colony algorithm (IABC). This is achieved using a new search probability model called PIABC that improves the exploration process by choosing the best source of food which directly affects the exploitation process in IABC. Secondly, the fuzzy clustering algorithm based on PIABC, abbreviated as PIABC-FCM, uses the balancing of PIABC to avoid getting stuck into local optima while searching for the best solution having a set of cluster center locations of FCM. The proposed method was evaluated using grayscale images. The performance of the proposed approach shows promising outcomes when compared with other related works.

Knowledge, Attitude and Practice Tools for Health Education Among Diabetic Patients.

Health education is an integral part of self-management programs and an important element for the control and effective management of any chronic disease including diabetes. Patient Knowledge, Awareness, and Practices (KAP) are considered to be the most important factors for assessing the results of health education in patients with diabetes. In order to develop such health education models, it is important to have a validated and reliable tools which asses a diabetic patient's knowledge, attitude and practice. The aim of this study is to systematically review the literature on KAP assessment tools regarding health education among diabetic patients. The researchers conducted a systematic literature review using MEDLINE database from 1980 up to 2016. A developed search strategy was conducted by the researchers for MEDLINE and EBESCO. Of the 94 articles identified only 16 articles fully met the inclusion criteria. This review identifies useful assessment tools of KAP regarding health education for diabetic patients which will help to improve strategies in regards to assessing KAP for diabetic patients worldwide. The KAP assessment tools should be: carefully developed, user friendly, evidence-based, valid and reliable.