Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning models for a variety of tasks under the control of a unified architecture for each proposed model.
YY Lazim, NAB Azizan, 2nd International Conference on Innovation and Entrepreneurship, 2014
Municipalities.
Abstract
The purpose of this research is to measure the impact of regulatory flexibility dimensions (formal and authoritarian procedures) to achieve response to the requirements of high performance dimensions (the effective recruitment, intensive training, motivate employees, participation of workers) in the general municipal Directorate as one of the directorates of the Ministry of Municipalities and Public Works. For the purpose of this measure it has been selected sample composed of 88 individuals from the research community represents the levels of assistant general manager of department heads and managers of people and some of the staff to answer the questionnaire prepared for the purpose Hama
... Show MoreDiarrhea is one of the most commonly encountered minor ailments in the community pharmacies. It is associated with significant morbidity and mortality. However, the majority of pharmacists in Iraq did not manage diarrheal cases in a proper way. Therefore, the current study aimed to evaluate the benefit of a new mobile application (diarrhea management step by step) to improve the pharmacist's role in the management of diarrhea. The study was conducted from 21th September to 21th October 2021 using a pre-post design via a simulated patient (SP) technique. A validated diarrhea scenario was presented to each pharmacist by the SP twice, once before and the other after giving the mobile application to the pharmacist. Furthermore, pharmaci
... Show MoreThis research dealt with the analysis of murder crime data in Iraq in its temporal and spatial dimensions, then it focused on building a new model with an algorithm that combines the characteristics associated with time and spatial series so that this model can predict more accurately than other models by comparing them with this model, which we called the Combined Regression model (CR), which consists of merging two models, the time series regression model with the spatial regression model, and making them one model that can analyze data in its temporal and spatial dimensions. Several models were used for comparison with the integrated model, namely Multiple Linear Regression (MLR), Decision Tree Regression (DTR), Random Forest Reg
... Show MoreAccurate 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
... Show MoreNowadays, people's expression on the Internet is no longer limited to text, especially with the rise of the short video boom, leading to the emergence of a large number of modal data such as text, pictures, audio, and video. Compared to single mode data ,the multi-modal data always contains massive information. The mining process of multi-modal information can help computers to better understand human emotional characteristics. However, because the multi-modal data show obvious dynamic time series features, it is necessary to solve the dynamic correlation problem within a single mode and between different modes in the same application scene during the fusion process. To solve this problem, in this paper, a feature extraction framework of
... Show MoreIn this work, satellite images for Razaza Lake and the surrounding area
district in Karbala province are classified for years 1990,1999 and
2014 using two software programming (MATLAB 7.12 and ERDAS
imagine 2014). Proposed unsupervised and supervised method of
classification using MATLAB software have been used; these are
mean value and Singular Value Decomposition respectively. While
unsupervised (K-Means) and supervised (Maximum likelihood
Classifier) method are utilized using ERDAS imagine, in order to get
most accurate results and then compare these results of each method
and calculate the changes that taken place in years 1999 and 2014;
comparing with 1990. The results from classification indicated that
In recent years, with the rapid development of the current classification system in digital content identification, automatic classification of images has become the most challenging task in the field of computer vision. As can be seen, vision is quite challenging for a system to automatically understand and analyze images, as compared to the vision of humans. Some research papers have been done to address the issue in the low-level current classification system, but the output was restricted only to basic image features. However, similarly, the approaches fail to accurately classify images. For the results expected in this field, such as computer vision, this study proposes a deep learning approach that utilizes a deep learning algorithm.
... Show MoreThe research aims to measure the economic efficiency and technological change and the total productivity of resources using the parameter and non-parameter methods, for agricultural companies registered in the Iraqi stock exchange, the number of 6 companies for the period from 2005 to 2017 based on the hypothesis that the agricultural companies do not achieve economic efficiency and does not control the management of its operations, and It may be technically efficient but the size of its operations is not optimal. From non-parametric methods, the data envelope analysis method was used. Using the DEAP program, the Middle East Company achieved the highest average technical and cost efficiency of 0.62 and 0.58, respectively. The Iraq
... Show MoreThis paper deals with the preparation of new monomers and polymers which including heterocyclic unit. The diacid chlorides compounds [1-3] were prepared from the reaction of glutaric acid, adipic acid, terephthalic acid with thionyl chloride. Succinic acid reacted with ethanol to produce compound [4]. Compound [4] reacted with hydrazine hydrate to obtain succinic hydrazide [5].Compound [5] reaction with CS2 and KOH in absolute ethanol to produce compound [6].The polymers [7-12] have been created by reacting diacid chlorides compounds [1-3] with compound[5] or [6] in dry pyridine with some drops of DMF. The topology of produced compounds has characterized through their spectral and analytical data as in FT-IR spectra, Thermal analysis [DSC,
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