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Facial Emotion Recognition from Videos Using Deep Convolutional Neural Networks
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Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.

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Publication Date
Wed Nov 12 2014
Journal Name
Wireless Personal Communications
A Multi-objective Disjoint Set Covers for Reliable Lifetime Maximization of Wireless Sensor Networks
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Publication Date
Wed Nov 16 2016
Journal Name
Eurasip Journal On Wireless Communications And Networking
Evaluation of efficient vehicular ad hoc networks based on a maximum distance routing algorithm
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Traffic management at road intersections is a complex requirement that has been an important topic of research and discussion. Solutions have been primarily focused on using vehicular ad hoc networks (VANETs). Key issues in VANETs are high mobility, restriction of road setup, frequent topology variations, failed network links, and timely communication of data, which make the routing of packets to a particular destination problematic. To address these issues, a new dependable routing algorithm is proposed, which utilizes a wireless communication system between vehicles in urban vehicular networks. This routing is position-based, known as the maximum distance on-demand routing algorithm (MDORA). It aims to find an optimal route on a hop-by-ho

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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Distributed Heuristic Algorithm for Migration and Replication of Self-organized Services in Future Networks
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Nowadays, the mobile communication networks have become a consistent part of our everyday life by transforming huge amount of data through communicating devices, that leads to new challenges. According to the Cisco Networking Index, more than 29.3 billion networked devices will be connected to the network during the year 2023. It is obvious that the existing infrastructures in current networks will not be able to support all the generated data due to the bandwidth limits, processing and transmission overhead. To cope with these issues, future mobile communication networks must achieve high requirements to reduce the amount of transferred data, decrease latency and computation costs. One of the essential challenging tasks in this subject

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Publication Date
Thu Oct 30 2025
Journal Name
Journal Of University Of Babylon For Engineering Sciences
Adaptive Beamforming and Ai-Driven Low-Power Signal Processing on ‎Fpga For 6G Networks
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As the demands of sixth-generation (6G) networks escalate towards achieving high speeds and improved energy efficiency, there is an increasing need for intelligent and real-time adaptive solutions within the physical processing layer. This study proposes an innovative engineering framework based on an encapsulated architecture utilising FBGA (micro-distributed spherical array) technology, integrated with an internal artificial intelligence module, to achieve adaptive beamforming with high efficiency in dense wireless environments. The primary objective of this research is to develop an intelligent communication architecture that determines the optimal transmission angles and regulates power consumption in real-time by integrating ar

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Publication Date
Mon Dec 14 2020
Journal Name
Baghdad Science Journal
Smart Flow Steering Agent for End-to-End Delay Improvement in Software-Defined Networks
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Publication Date
Thu Feb 09 2023
Journal Name
Artificial Intelligence Review
Community detection model for dynamic networks based on hidden Markov model and evolutionary algorithm
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Finding communities of connected individuals in complex networks is challenging, yet crucial for understanding different real-world societies and their interactions. Recently attention has turned to discover the dynamics of such communities. However, detecting accurate community structures that evolve over time adds additional challenges. Almost all the state-of-the-art algorithms are designed based on seemingly the same principle while treating the problem as a coupled optimization model to simultaneously identify community structures and their evolution over time. Unlike all these studies, the current work aims to individually consider this three measures, i.e. intra-community score, inter-community score, and evolution of community over

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Publication Date
Thu Oct 15 2026
Journal Name
Journal Of Baghdad College Of Dentistry
The relationship among bite force with facial dimensions and dental arches widths in a sample of Iraqi adults with Class I skeletal and dental relations
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Background: This study aimed to determine whether there is a relationship among the bite force with facial dimensions and dental arches in a sample of Iraqi adults with Class I skeletal and dental relations. Materials and methods: Forty dental students (20 males and 20 females) were selected under certain criteria. For those individuals, dental impressions, frontal facial photographs and maximum bite force at molar and incisor regions were taken. The dental arches widths and facial dimensions were measured using the AutoCAD program 2007, while the bite force was determined using special device. Descriptive statistics for the measured variables were performed and gender difference was determined using independent sample t-test, while the rel

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Publication Date
Sun Dec 15 2019
Journal Name
Journal Of Baghdad College Of Dentistry
Evaluation of effect of local exogenous application of Myrrh oil on healing of wound incisions of facial skin (Histochemical, Histological and Histomorphometrical study in rabbits)
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Aim of the study: Is to evaluate the effect of myrrh oil local application on the healing process of skin wounds histologically , histomorphometrically and , histochemically. Materials and methods:Twenty male white New Zealand rabbits were used in this study. An incisional wounds with full thickness depth and of 2 cm length were done on both sides of the cheek skin of each rabbit. The left sided incisions (the control group) were irrigated with distilled water (10µL). The right sided incisions (the experimental groups) were treated with myrrh oil (10µL). Each group was subdivided into 4 subgroups according to the healing interval into 1,3,7 and 14 days(5 rabbits for each group). Results: Histological findings of our current study s

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Publication Date
Wed Jan 21 2026
Journal Name
Advanced Materials Research
Sustainable Removal of Heavy Metals from Aqueous Solutions Using Untreated Cellulose from Office Paper Waste Based on the Circular Economy Approach
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This study explored the feasibility of removing nickel (Ni) and Pb (II) from water solutions using the adsorption technique by cellulose recovered from office paper waste. Metal removal is required to reduce the direct or indirect exposure of industrial waste to the environment, due to its potential for harm to human health and ecosystems. The release criterion is maintained to keep the efficient wastewater treatment of the metals of concern, which are toxic to both humans and other organisms. The cellulose was first prepared from office paper waste. The removal values can be rationalized as follows: Lead removal efficiencies of were obtained upto %95.0632, while the removals of nickel were obtained as 54.3866%. The adsorption proce

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Publication Date
Sun Mar 08 2015
Journal Name
All Days
Distribution of New Horizontal Wells by the Use of Artificial Neural Network Algorithm
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Abstract<p>It is an established fact that substantial amounts of oil usually remain in a reservoir after primary and secondary processes. Therefore; there is an ongoing effort to sweep that remaining oil. Field optimization includes many techniques. Horizontal wells are one of the most motivating factors for field optimization. The selection of new horizontal wells must be accompanied with the right selection of the well locations. However, modeling horizontal well locations by a trial and error method is a time consuming method. Therefore; a method of Artificial Neural Network (ANN) has been employed which helps to predict the optimum performance via proposed new wells locations by incorporatin</p> ... Show More
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