درخت حوزه‌های تخصصی

The Web has become the most important information source for most of us. Unfortunately, there is no guarantee for the correctness of information on the Web. Moreover, different websites often provide conflicting information on a subject. Several truth discovery methods have been proposed for various scenarios, and they have been successfully applied in diverse application domains. In this paper, we have attempted to answer the question whether the truth is relevant. We conducted an experimental study in which we analyzed and compared the results of two different truth discovery methods: Relevance-based sources ranking and Majority vote. We have found that the truth is not always held by the most relevant sources on the web. Sometimes the truth is given by the majority vote of the crowd. In addition, we have proposed a method of presenting the results of truth discovery with gradual degrees of belief. A method that allows to configure and target the desired level of trust.

Internet users all over the world are increasing day by day and showing great interest for online shopping. The main reason for the high usage of the internet is the affordable price of mobile gadgets and low internet tariff plans. Consumer behavior is influenced by various factors such as culture, social class, reference groups relationship, family, income level and income independency, age, gender, etc. The purpose of this study was to find out the differences in buying behaviors among the university students. The study was carried out using google survey with a sample size of 236 students randomly selected from the university of India and Saudi Arabia. The study shows that University students of both countries have more online shopping experience because they use the internet more frequently and they have larger internet usage. Nowadays Students are more computer professionals and those who use the internet for their study work and assignments work are more active in online shopping. As per student’s opinion, they said few things remember in our mind when coming to payment options credit card is the safest option or using online services like pay pal and google wallet services also a good way but finally, cash on delivery is the best way of shopping online. The result of this study would contribute marketers who want to penetrate the market in India and in Kingdom of Saudi Arab, who are already present in the market and desire to take care of the loyalty and satisfaction of their customers.

The evolution of today's application technologies requires a certain level of robustness, reliability and ease of integration. We choose the Fields Programmable Gate Array (FPGA) hardware description language to implement the facial recognition algorithm based on "Eigen faces" using Principal Component Analysis. In this paper, we first present an overview of the PCA used for facial recognition, then use a VHSIC Hardware Description Language (VHDL) simulation and design platform, which is the ISE. We describe the operation of each block and implement, thereafter, the computation of the global centered images. This corresponds to the first step of the PCA algorithm to assess its performance. The comparison of the results of this implementation with that of MATLAB confirmed the operability and effectiveness of this method for centralizing images. We also implemented the last part of this algorithm which is the computation of the Manhattan distance. The tests have given very satisfactory results.

The great development witnessed by our current age has led to the emergence of many diverse modern technologies, one of these advanced technologies is Hologram technology and Augmented reality technology, These two technologies are somewhat similar to somewhat, as it can be said that they perform almost the same purpose, and at the same time, Hologram technology differs from augmented reality in several aspects, as the way in which the three-dimensional images are created and the properties of that images itself. This paper aims to compare and study the similarities and differences between Hologram technology and Augmented reality technology. It is a standard comparison as the comparison takes place according to a number of different aspects of both technologies. Comparing the characteristics of the two technologies showed that there is no one of them excels over the other, but according to different systems and situations, it is maybe better and more appropriate to use one of them than using the other one.

To bridge the gap between invention and innovation, prenovation has to be focused. One of the elements of prenovation is emphasizing and creating policies for institutions. This research paper highlights the importance of having an intrapreneurial culture in higher education institutions. The purpose of this paper is to review literature related to intrapreneurial culture and find out the positive aspects of having intrapreneurial culture through think tanks in higher education institutes.

The study is aimed at assessing the strategic importance of a business processes for achieving sustainable competitive advantage, therefore, in this article the theoretical approach for measuring the strategic contribution of a business process to an enterprise’s business system is presented.  For evaluating of a business process strategic importance the study proposes the system of economic and managerial indicators, which includes the process’ contribution to the added value, its compliance to critical success factors, and its organizational involvement. Сombining these three indicators into one integral allows it to be used in different types of matrix analysis to make decisions on improving of a company’s business system.

K nearest neighbor algorithm is one of the most frequently used techniques in data mining for its integrity and performance. Though the KNN algorithm is highly effective in many cases, it has some essential deficiencies, which affects the classification accuracy of the algorithm. First, the effectiveness of the algorithm is affected by redundant and irrelevant features. Furthermore, this algorithm does not consider the differences between samples, which led the algorithm to have inaccurate predictions. In this paper, we proposed a novel scheme for improving the accuracy of the KNN classification algorithm based on the new weighting technique and stepwise feature selection. First, we used a stepwise feature selection method to eliminate irrelevant features and select highly correlated features with the class category. Then a new weighting method was proposed to give authority value to each sample in train dataset based on neighbor categories and Euclidean distances. This weighting approach gives a higher preference to samples that have neighbors with close Euclidean distance while they are in the same category, which can effectively increase the classification accuracy of the algorithm. We evaluated the accuracy rate of the proposed method and analyzed it with the traditional KNN algorithm and some similar works with the use of five real-world UCI datasets. The experiment results determined that the proposed scheme (denoted by WAD-KNN) performed better than the traditional KNN algorithm and considered approaches with the improvement of approximately 10% accuracy.

Environmental pollution and rapid depletion are among the chief concerns about fossil fuels such as oil, gas, and coal. Renewable energy sources do not suffer from such limitations and are considered the best choice to replace fossil fuels. The present study develops a mathematical model for optimal allocation of regional renewable energy to meet a country-wide demand and its other essential aspects. The ultimate purpose is to minimize the total cost by planning, including power plant construction and maintenance costs and transmission costs. Minimum-cost flow equations are embedded in the model to determine how regions can supply energy to other regions or rely on them to fulfill annual demand. In order to verify the applicability of the model, it is applied to a real-world case study of Iran to determine the optimal renewable energy generation-transmission decisions for the next decade. Results indicate that the hydroelectric and solar power plants should generate the majority of the generated renewable electricity within the country, according to the optimal solution. Moreover, regarding the significant population growth and waste generation in the country’s large cities, biomass power plants can have the opportunity to satisfy a remarkable portion of electricity demand.

The special issue aims to cover the latest research topics in designing and deploying visual information analytics and management techniques using deep learning. It is intended to serve as a platform to researchers who want to present research in deep learning. The special issue focuses explicitly on deep learning and its application in visual computing and signal processing. It emphasizes on the extent to which Deep Learning can help specialists in understanding and analyzing complex images and signals. The field of Visual Information Analytics and Management is considered in its broadest sense and covers both digital and analog aspects. This involves development of techniques for image analysis, understanding and restoration. Deep learning techniques are effective for visual analytics. Deep learning is a fast growing area and is gaining impetus for application in various fields. Therefore, in this special issue, the objective is to publish articles related to deep learning in various problems of visual information analytics and management.

Flash floods are considered to be one the worst kind of hazard. They are characterized by their suddenness, rarity, small scale, heavy rain and peak discharge, unpredictable, fast and violent movement. It has severe effects on human society in the form life losses, damages to property, roads, communication and on natural settings. Advances in hydrology, meteorology, engineering, using of GIS and remote sensing still not able to increase real time forecast. Researchers from developed countries have stressed to more focus to improve very short time an effective early warning system with collaboration of local communities for flash flood risk supervision. The data were combined with the Geographical Information System to analyze the temporal and spatial distribution of flood events in Salah Al-Din Governorate and Ramadan Valley. The analysis of the spatial distribution of the floods proves that most of the occurrences are recorded in the southern part of the study area. Most of the flooded areas in the study area are mainly pre-classified areas within the areas threatened by the flood due to the low level of its surface and its proximity to the course of the main valley (Wadi Jarnav), which flows into the Tigris River. The proposed method estimates the localization of sites prone to flood, and it may be used for flood hazard assessment mapping and for flood risk management. It was therefore, suggested that government agencies and policy makers should adopt this powerful technique for reliable and well synthesized information which is a vital component of flood risk assessment and planning.

The study aimed to determine the impact between rational governance and financial performance on a sample of pharmaceutical companies listed in the Amman Stock Exchange. The questionnaire was used to collect data, where (200) inquiries were received (170) valid for statistical analysis were excluded (10) where used in Analysis process (160) of the total questionnaires distributed and to achieve the objectives of the study the study reached the most relevant results, the presence of a statistically significant impact of disclosure and transparency on financial performance The study made the most critical recommendations: The establishment of institutions to design an effective and sound control system in order to fulfil the role for which it was found, And also work on Control continuously updated system.