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This paper has explored the technology beliefs of university students considering four parameters. We have proposed an automatic belief identification system for academic institutions. For this, we used two different clustering algorithms to segment the student group with different beliefs about the technology. In the Hierarchical Clustering (HC), the Agglomerative approach was followed. The beliefs…

Information on alternative technologies or new prototypes was analyzed to help improve the quality of business management services. The problem is the lack of application of new technologies that improve the quality of service and reduce disagreements in the management of organizations. The objective is to present a prototype for the management of engineering and…

This paper proposes a closed association rule generation technique to investigate the association patterns of diseases that are frequent co-occurrence. Diseases records of 5,000 patients are studied to find the association patterns of disease co-occurrence. The CHARM algorithm is adapted to find frequent diseases that can cover all-important patterns with a small number. Then the…

This paper deals with a multi closed-loop adaptive neuro-fuzzy inference system (ANFIS) design for the under-actuated quadrotor systems. First, the training data set for the fuzzy inference system is obtained using a proportional integral derivative controller. Then, an initial ANFIS controller is designed, where the integral control action is preserved in the multi-closed-cloop ANFIS for…

A distribution company in Mexico covers the travel expenses for 21 sales representatives. Currently, the routes they follow are not established clearly, which can lead to high costs in this subject. A reduction of such cost is sought after, by optimizing the routes for each one of them. The following research finds an improvement on…

Machine learning has been dramatically advanced over several decades, from theory context to a general business and technology implementation. Especially in healthcare research, it is obvious to perceive the scrutinizing implementation of machine learning to warranty the rewarded benefits in early disease detection and service recommendation. Many practitioners and researchers have eventually recognized no absolute…

Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis.…

In this article, we concentrate on the use of a metaheuristic technique based on an Evolutionary Algorithm (EA) for determining the optimal geometrical parameters of spiral inductors for RF circuits. For this purpose, we have opted for an optimization procedure through an enhanced Differential Evolution (DE) algorithm. The proposed tool allows the design of optimized…

The ability to verify the critical risk factors related to an effective diagnosis is very crucial for improving accuracy on coronary heart disease prediction. The objective of this research is to find the best predictive model for coronary heart disease diagnosis. Three approaches are set up to achieve the goals (1) investigating the classifier algorithms…

In this paper we design a large scale reconfigurable digital bio-inspired computing model. We consider the reconfigurable and event driven parameters in the developed field-programmable neuromorphic computing system. The various Intellectual Property (IP) cores are developed for the modules such as Block RAM, Differential Clock, Floating Point, and First In First Out (FIFO) for the…

With recent advancements in medical filed, the quantity of healthcare care data is increasing at a faster rate. Medical data classification is considered as a major research topic and numerous research works have been already existed in the literature. Presently, deep learning (DL) models offers an efficient method for developing a dedicated model to determine…

Analysis and classification of lung diseases using X-ray images is a primary step in the procedure of pneumonia diagnosis, especially in a critical period as pandemic of COVID-19 that is type of pneumonia. Therefore, an automatic method with high accuracy of classification is needed to perform classification of lung diseases due to the increasing number…

This paper focuses on a string encoding algorithm, which produces sparse distributed representations of text data. A characteristic feature of the algorithm described here, is that it works without tokenizing the text and can avoid other data preparation steps, such as stemming and lemmatization. The text can be of arbitrary size, whether it is a…

Global changes caused by the IV Industrial revolution and globalization processes resulted in a redistribution of roles of participants in innovative infrastructures of countries. Universities are leading both in terms of generating R&D products and in terms of developing business activities. Now there is a problem of insufficient methodological support of technological universities for pricing…

The difficulty of learning the underlying structure between processes is a common task found throughout the sciences, however not much work is dedicated towards this problem. In this paper, we attempt to use the language of structure learning to address learning the dynamic influence network between partially observable processes represented as dynamic Bayesian networks. The…

In modern deregulated power industry, private sector has invested a lot to supply for extended power demand using the preexisting power system framework. This resulted into increased loading of transmission lines which has to work now to hit their thermal limits. The overloading of transmission line resulted in congestion and hence increase in loss of…

This paper focuses on exploring efficient ways to find H2 optimal Structure-Preserving Model Order Reduction (SPMOR) of the second-order systems via interpolatory projection-based method Iterative Rational Krylov Algorithm (IRKA). To get the reduced models of the second- order systems, the classical IRKA deals with the equivalent first-order converted forms and estimates the first-order reduced models.…

Topic classification is a crucial task where knowledge categories exist within hierarchical information systems designed to facilitate knowledge search and discovery. An application of topic classification is article (e.g., journal/conference paper) classification which is very useful for online submission systems. In fact, numerous online journals/magazine submission systems usually receive thousands of article submissions or even…

A gas sensor array is used for gas analysis to aid in an inspection. The signals from the sensor array are fed into machine learning models for learning and classification. These signals are characterized by time series fluctuating according to the environment or drift. When an unseen pattern is entered, the classification may be incorrect,…

Road traffic accidents are primarily caused by drivers error. Safer roads infrastructure and facilities like traffic signs and signals are built to aid drivers on the road. But several factors affect the awareness of drivers to traffic signs including visual complexity, environmental condition, and poor drivers education. This led to the development of different ADAs…

Nowadays, Customer satisfaction is important for businesses and organizations. Manual methods exist, namely surveys and distributing questionnaires to customers. However, marketers and businesses are looking for quick ways to get effective and efficient feedback results for their potential customers. In this paper, we propose a new method for facial emotion detection to recognize customer’s satisfaction…

The integration of renewable energy distributed generation (REDG) into the energized distribution power grid has become more popular in recent years. This has been escalated by the general global energy shortages. The REDG has proven to be effective for energy sustainability and reliability. However, there are technical challenges which arise from integrating REDG into the…

The Hausdorff distance (HD) is defined as MAX-MIN distance between two geometric objects for measuring the dissimilarity between two objects. Because MAX-MIN distance is sensitive with the outliers, in face recognition field, average Hausdorff distance is used for measuring the dissimilarity between two sets of features. The computational complexity of HD, and also average HD,…

The classification of static or mobile objects, from a signal or an image containing information as to their structure or their form, constitutes a constant concern of specialists in the electronic field. The remarkable progress made in past years, particularly in the development of neural networks and artificial intelligence systems, has further accentuated this trend.…

The article considers the task of developing a fuzzy-logical PID-type controller for a nonlinear dynamic system. A feature of the structure is presented, which consists in simplifying its controller by decomposition. In the simplest version, three fuzzy controllers are used with one input and one output and separate rule bases. Parameters of fuzzy controllers are…