With the increasing integration of computers and smartphones into our daily lives, in addition to the numerous benefits it offers over traditional paper-based methods of conducting affairs, it has become necessary to incorporate one of the most essential facilities into this integration; namely: colleges. The traditional approach for conducting affairs in colleges is mostly paper-based, which only increases time and workload and is relatively decentralized. This project provides educational and management services for the university environment, targeting the staff, the student body, and the lecturers, on two of the most used platforms: smartphones and reliable web applications by cloud hosting. The services include project management, attendance marking, various notifications and alerts, files and resources, a grading system, and an assignment management system. This paper also aims to ultimately digitalize most of the information inside the college which is a great challenge. The proposed system defines five actors, namely: an admin; who is the person with the highest authority within the system, the head of the department, the department coordinator, the project coordinator, the lecturers, and the students. Each of those actors has its privileges and the interaction among participants via the cloud. The mobile platform targets the students exclusively and interacts with the web platform. Finally, this paper stresses the benefits of the proposed system and gives the avenues for future development.
The present investigation aims to determine the effects of aflatoxin B1 (AFB1) on biotransformation and antioxidant genes and the protective effects of curcumin, present in turmeric (Curcuma longa) powder (TMP). Specifically, the study included four groups of albino mice were fed for 30 days on diet Group I: Control, Group II: animals fed on the conventional basal diet supplemented with 0.5% food grade TMP that supplied 74 mg/kg total curcuminoids. Group III contained animals reared on conventional basal diet supplemented with 1.0 ppm AFB1 supplied by ground aflatoxin culture material (760 ppm AFB1). Finally, Group IV comprised of albino mice fed with basal diet supplemented with 1.0 ppm AFB1 and 0.5% TMP that supplied 74 mg/kg of the
... Show MoreThe aim of this research is to introduce agricultural insurance, to define financing in the form of salam and the role of agricultural insurance in the prevention of risks to agricultural finance operations in the form of salam by verifying the hypotheses through which to reach the results, including the imposition of risks for agricultural finance in the form of salam, The study of agricultural finance in the form of salm, the deductive approach to the development of the problem of research and hypotheses, and the inductive method to extrapolate the results through analysis and brother The researcher concluded that agricultural insurance works to bridge the risks facing agricultural finance in the form of the ladder in cases of
... Show MoreThe studying trying to determine the role of Strategic Intelligence on the Process of Green Manufacturing of Sample of Mineral water factories at Dahuk city. The study submit a theoretical frame of Strategic Intelligence and Green Manufacturing, a supposed sample, had been set to reverye the nature of the relations and effect in the study Varity, the study depend on group of the main and branch concurring with the relations and effect between the Strategic Intelligence and Green Manufacturing to answer the following questions about research to problems:
What are the relationships and effects between stra
... Show MorePermeability estimation is a vital step in reservoir engineering due to its effect on reservoir's characterization, planning for perforations, and economic efficiency of the reservoirs. The core and well-logging data are the main sources of permeability measuring and calculating respectively. There are multiple methods to predict permeability such as classic, empirical, and geostatistical methods. In this research, two statistical approaches have been applied and compared for permeability prediction: Multiple Linear Regression and Random Forest, given the (M) reservoir interval in the (BH) Oil Field in the northern part of Iraq. The dataset was separated into two subsets: Training and Testing in order to cross-validate the accuracy
... Show MoreIn the field of data security, the critical challenge of preserving sensitive information during its transmission through public channels takes centre stage. Steganography, a method employed to conceal data within various carrier objects such as text, can be proposed to address these security challenges. Text, owing to its extensive usage and constrained bandwidth, stands out as an optimal medium for this purpose. Despite the richness of the Arabic language in its linguistic features, only a small number of studies have explored Arabic text steganography. Arabic text, characterized by its distinctive script and linguistic features, has gained notable attention as a promising domain for steganographic ventures. Arabic text steganography harn
... Show MoreInvestigating gender differences based on emotional changes becomes essential to understand various human behaviors in our daily life. Ten students from the University of Vienna have been recruited by recording the electroencephalogram (EEG) dataset while watching four short emotional video clips (anger, happiness, sadness, and neutral) of audiovisual stimuli. In this study, conventional filter and wavelet (WT) denoising techniques were applied as a preprocessing stage and Hurst exponent
This work implements an Electroencephalogram (EEG) signal classifier. The implemented method uses Orthogonal Polynomials (OP) to convert the EEG signal samples to moments. A Sparse Filter (SF) reduces the number of converted moments to increase the classification accuracy. A Support Vector Machine (SVM) is used to classify the reduced moments between two classes. The proposed method’s performance is tested and compared with two methods by using two datasets. The datasets are divided into 80% for training and 20% for testing, with 5 -fold used for cross-validation. The results show that this method overcomes the accuracy of other methods. The proposed method’s best accuracy is 95.6% and 99.5%, respectively. Finally, from the results, it
... Show MoreDeep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to
... Show MoreThe fingerprints are the more utilized biometric feature for person identification and verification. The fingerprint is easy to understand compare to another existing biometric type such as voice, face. It is capable to create a very high recognition rate for human recognition. In this paper the geometric rotation transform is applied on fingerprint image to obtain a new level of features to represent the finger characteristics and to use for personal identification; the local features are used for their ability to reflect the statistical behavior of fingerprint variation at fingerprint image. The proposed fingerprint system contains three main stages, they are: (i) preprocessing, (ii) feature extraction, and (iii) matching. The preprocessi
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