Human-based quality control reduces the accuracy of this process. Also, the speed of decision making in some industries is very important. For removing these limitations in human-based quality control, in this paper, the design of an expert system for automatic and intelligent quality control is investigated. In fact, using an intelligent system, the accuracy in quality control is increased. It...

Using technology to assist both dementia patients and caregivers is of interest to caregivers, professionals, and treatment providers. This study looks to develop a system for detecting task performance of caregivers for dementia patients. In this interdisciplinary study, we create CAST (Caregiver Assessment using Smart Technology), a mobile application that personalizes a traditional word scra...

In the past few years, an evolution in the wireless communication has been emerged, along with the evolution a new type of large potential application of wireless network appears, which is the Mobile Ad-Hoc Network (MANET). Black hole attack considers one of the most affected kind on MANET. Therefore, the use of intrusion detection system (IDS) has a major importance in the MANET protection. In...

paper describes the design and implementation of an inference engine for the execution of Fuzzy Inference Systems (FIS), the architecture of the system is presented, and the object-oriented design of the main modules is also discussed. The engine is implemented as a component to be referenced by other applications locally or remotely as a web service. This engine is needed by our research group...

Edge detection is one of the most important low level steps in image processing. In this work we propose a fuzzy ensemble based method for edge detection including a fuzzy c-means (FCM) approach to define the input membership functions of the fuzzy inference system (FIS). We tested the performance of the method using a public database with ground truth. Also, we compared our proposal with class...

In this paper the development of a model for Mamdani type fuzzy rule-based systems using the new concept of granular computing (GrC) is presented. In this study a GrC algorithm is used to capture the required information in the form of data granules within a high dimensional complex database. The initial collection of information granules is used as a rule-base for a fuzzy inference system (FIS...

This work substantiates novel perspectives and tools for analysis and design of Fuzzy Inference Systems (FIS). It is shown rigorously that the cardinality of the set F of fuzzy numbers equals א1, hence a FIS can implement “in principle” א2 functions, where א2 = 2א1>א1 and א1 is the cardinality of the set R of real numbers; furthermore a FIS is endowed with a capacity for local generalization. A...

In the present study, the adaptive neuro-fuzzy inference system (ANFIS) is developed for the prediction of effective thermal conductivity (ETC) of different fillers filled in polymer matrixes. The ANFIS uses a hybrid learning algorithm. The ANFIS is a class of adaptive networks that is functionally equivalent to fuzzy inference systems (FIS). The ANFIS is based on neuro-fuzzy model, trained wit...

In this paper, a fuzzy inference system (FIS) that incorporated with an analogical reasoning schema based criterion-referenced assessment (CRA) is proposed. The aim of CRA is to report students’ achievement with reference to a set of objective reference points. Usually, scores were given to each task in order to eases the assessment as in common practice. A total-score is further obtained with ...

Most of the earlier studies in the inventory control and management make assumption that the manufacturing system is reliable and does not fail. However, in the real industrial applications, there is no completely reliable manufacturing system; Machine failure occur and the production does not resume before repair. In this paper we will study and analyze the optimal lot size in a real productio...