Accurate emotion categorization is an important and challenging task in computer vision and image processing fields. Facial emotion recognition system implies three important stages: Prep-processing and face area allocation, feature extraction and classification. In this study a new system based on geometric features (distances and angles) set derived from the basic facial components such as eyes, eyebrows and mouth using analytical geometry calculations. For classification stage feed forward neural network classifier is used. For evaluation purpose the Standard database "JAFFE" have been used as test material; it holds face samples for seven basic emotions. The results of conducted tests indicate that the use of suggested distances, angles and others relative geometric features for recognition give accuracy about 95.73% when the seven emotion classes are tested and 97.23% when the 6 classes (except normal class) are only tested. These rates are considered high when compared with the results of other newly published works.
In this research various of 2,5-disubstituted 1,3,4-oxadiazole (Schiff base, oxo-thiazolidine , and other compounds) were synthesized from 2,5-di(4,4?- amino-1,3,4-oxadiazole ) which use quently synthesized from mixture of 4-amino benzoic acid and hydrazine in the presence of polyphosphorus acid. The synthesized compounds were characterized by using some Spectral data (UV, FT-IR, and 1H-NMR).
The development of information systems in recent years has contributed to various methods of gathering information to evaluate IS performance. The most common approach used to collect information is called the survey system. This method, however, suffers one major drawback. The decision makers consume considerable time to transform data from survey sheets to analytical programs. As such, this paper proposes a method called ‘survey algorithm based on R programming language’ or SABR, for data transformation from the survey sheets inside R environments by treating the arrangement of data as a relational format. R and Relational data format provide excellent opportunity to manage and analyse the accumulated data. Moreover, a survey syste
... Show MoreThe research seeks to identify the comprehensive electronic banking system and the role of the auditor in light of the customer's application of electronic systems that depend on the Internet in providing its services, as a proposed audit program has been prepared in accordance with international auditing controls and standards based on the study of the customer's environment and the analysis of external and internal risks in the light of financial and non-financial indicators, the research reached a set of conclusions, most notably, increasing the dependence of banks on the comprehensive banking system for its ability to provide new and diverse banking services, The researcher suggested several recommendations, the most important of whi
... Show MorePower-electronic converters are essential elements for the effective interconnection of renewable energy sources to the power grid, as well as to include energy storage units, vehicle charging stations, microgrids, etc. Converter models that provide an accurate representation of their wideband operation and interconnection with other active and passive grid components and systems are necessary for reliable steady state and transient analyses during normal or abnormal grid operating conditions. This paper introduces two Laplace domain-based approaches to model buck and boost DC-DC converters for electromagnetic transient studies. The first approach is an analytical one, where the converter is represented by a two-port admittance model via mo
... Show MoreSilica-based mesoporous materials are a class of porous materials with unique characteristics such as ordered pore structure, large surface area, and large pore volume. This review covers the different types of porous material (zeolite and mesoporous) and the physical properties of mesoporous materials that make them valuable in industry. Mesoporous materials can be divided into two groups: silica-based mesoporous materials and non-silica-based mesoporous materials. The most well-known family of silica-based mesoporous materials is the Mesoporous Molecular Sieves family, which attracts attention because of its beneficial properties. The family includes three members that are differentiated based on their pore arrangement. In this review,
... Show MoreFuture generations of wireless communications systems are expected to evolve toward allowing massive ubiquitous connectivity and achieving ultra-reliable and low-latency communications (URLLC) with extremely high data rates. Massive multiple-input multiple-output (m-MIMO) is a crucial transmission technique to fulfill the demands of high data rates in the upcoming wireless systems. However, obtaining a downlink (DL) training sequence (TS) that is feasible for fast channel estimation, i.e., meeting the low-latency communications required by future generations of wireless systems, in m-MIMO with frequency-division-duplex (FDD) when users have different channel correlations is very challenging. Therefore, a low-complexity solution for
... Show MoreRecently, there has been an increasing advancement in the communications technology, and due to the increment in using the cellphone applications in the diverse aspects of life, it became possible to automate home appliances, which is the desired goal from residences worldwide, since that provides lots of comfort by knowing that their appliances are working in their highest effi ciency whenever it is required without their knowledge, and it also allows them to control the devices when they are away from home, including turning them on or off whenever required. The design and implementation of this system is carried out by using the Global System of Mobile communications (GSM) technique to control the home appliances – In this work, an ele
... Show MoreIn this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de
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