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Research on Emotion Classification Based on Multi-modal Fusion
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Nowadays, 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 the three-dimensional dynamic expansion is established based on the common multi-modal data, for example video , sound ,text.Based on the framework, a multi-modal fusion-matched framework based on spatial and temporal feature enhancement, respectively to solve the dynamic correlation within and between modes, and then model the short and long term dynamic correlation information between different modes based on the proposed framework. Multiple group experiments performed on MOSI datasets show that the emotion recognition model constructed based on the framework proposed here in this paper can better utilize the more complex complementary information between different modal data. Compared with other multi-modal data fusion models, the spatial-temporal attention-based multimodal data fusion framework proposed in this paper significantly improves the emotion recognition rate and accuracy when applied to multi-modal emotion analysis, so it is more feasible and effective.

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Publication Date
Wed Sep 16 2020
Journal Name
Al-kindy College Medical Journal
The importance of anatomical zonal classification in the early management of penetrating neck injuries
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Background: Penetrating neck injuries are common problem in our country due to increasing violence, terrorist bombing and military operations.
These injuries are potentially life threating and need great attention and proper management.
Objective: The aim of this study is to focus on the importance of anatomical zonal classification of the neck in the management of penetrating injuries of the visceral compartment of the Neck.
Methods :70 patients with various injuries who were managed at causality unit and Otolaryngology department in Al-Kindy Teaching Hospital during aperiod from January 1st 2015 to October 31st 2015.
The study carried on those patient depending on proper clinical examination and their urgent management.

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Publication Date
Wed Sep 23 2020
Journal Name
Artificial Intelligence Research
Hybrid approaches to feature subset selection for data classification in high-dimensional feature space
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This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe

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Publication Date
Mon Apr 03 2023
Journal Name
International Journal Of Online And Biomedical Engineering (ijoe)
An Integrated Grasshopper Optimization Algorithm with Artificial Neural Network for Trusted Nodes Classification Problem
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Wireless Body Area Network (WBAN) is a tool that improves real-time patient health observation in hospitals, asylums, especially at home. WBAN has grown popularity in recent years due to its critical role and vast range of medical applications. Due to the sensitive nature of the patient information being transmitted through the WBAN network, security is of paramount importance. To guarantee the safe movement of data between sensor nodes and various WBAN networks, a high level of security is required in a WBAN network. This research introduces a novel technique named Integrated Grasshopper Optimization Algorithm with Artificial Neural Network (IGO-ANN) for distinguishing between trusted nodes in WBAN networks by means of a classifica

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Future Scenario of Global Climate Map change according to the Köppen -Geiger Climate Classification
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Earth’s climate changes rapidly due to the increases in human demands and rapid economic growth. These changes will affect the entire biosphere, mostly in negative ways. Predicting future changes will put us in a better position to minimize their catastrophic effects and to understand how humans can cope with the new changes beforehand. In this research, previous global climate data set observations from 1961-1990 have been used to predict the future climate change scenario for 2010-2039. The data were processed with Idrisi Andes software and the final Köppen-Geiger map was created with ArcGIS software. Based on Köppen climate classification, it was found that areas of Equator, Arid Steppes, and Snow will decrease by 3.9 %, 2.96%, an

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Publication Date
Sat Feb 01 2025
Journal Name
Saudi Medical Journal
Spectrum and classification of ATP7B variants with clinical correlation in children with Wilson disease
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Publication Date
Mon Apr 01 2024
Journal Name
Telkomnika (telecommunication Computing Electronics And Control)
Classification of grapevine leaves images using VGG-16 and VGG-19 deep learning nets
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The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi

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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Basement Kind Effects on Air Temperature of a Solar Chimney in Baghdad - Iraq Weather
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A solar updraft tower power plant (solar tower) is a solar thermal power plant that utilizes a combination of solar

air collector and central updraft tube to generate an induced convective flow which drives pressure staged turbines to generate electricity.

 

 This paper presents practical results of a prototype of a solar chimney with thermal mass, where the glass surface is replaced by transparence plastic cover. The study focused on chimney's basements kind effect on collected air temperatures. Three basements were used: concrete, black concrete and black pebbles basements. The study was conducted in Baghdad from August to November 2009.

The results show that the best chimney efficiency attaine

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Publication Date
Mon Dec 18 2017
Journal Name
Al-khwarizmi Engineering Journal
The Effect of Magnetic Field with Nanofluid on Heat Transfer in a Horizontal Pipe
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This work presents an experimental study of heat transfer and flow of distilled water and metal oxide nanofluid Fe3O4-distilled water at concentrations of (φ = 0.3, 0.6, 0.9 %) by volume in a horizontal pipe with constant magnetic field. All the tests are carried out with Reynolds number range (2900-9820) and uniform heat flux (11262-19562 W/m2). The results show that, the nanofluid concentration and magnetic intensity increase, the Nusselt number increases. The maximum enhancement in Nusselt number with magnetic nanofluid is (5.4 %, 26.4 %, 42.7 %) for volume concentration (0.3, 0.6, 0.9 %) respectively. The enhancement is maximized with magnetic intensity (0.1, 0.2, 0.3 tesla) respectively to (43.9, 44

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Publication Date
Sun Sep 01 2019
Journal Name
Al-khwarizmi Engineering Journal
The Effect of Wind Velocity on the Suppression of Composite Wing Airfoil NACA 0012
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The first studies on shocks and vibrations were carried out at the beginning of the 1930s to improve the behavior of buildings during earthquakes. Vibration tests on aircraft were developed from 1940 to verify the resistance of parts and equipments prior to their first use. Flutter is a well-known example of dynamic aero elasticity, where when oscillation of structure interacted with unsteady aerodynamic forces the flutter will occur. Vibration on any structure without damping means that self-harmonic oscillation will occur, and in most cases the oscillation may start to increase until structural failure. This behavior is very similar to resonance phenomena if only the oscillation is being studied as a vibration case. In vibration suppre

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Publication Date
Fri Aug 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Preventive measures for banking supervision on money laundering (Search in the Gulf Commercial Bank)
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The research aims to study and assess the effectiveness of preventive measures banking for the reduction of money laundering based on the checklist (Check list), which have been prepared based on the paragraphs of some of the principles and recommendations of international and Money Laundering Act No. 93 of 2004 and the instructions thereto, to examine and assess the application of these measures by Gulf Commercial Bank, which was chosen to perform the search.

I've been a statement the concept of money laundering in terms of the definition and characteristics, stages and effects of political, economic and social as well as the nature of banking supervision in terms of the definition and the most important

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