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Emotion Recognition Based on Mining Sub-Graphs of Facial Components
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Facial emotion recognition finds many real applications in the daily life like human robot interaction, eLearning, healthcare, customer services etc. The task of facial emotion recognition is not easy due to the difficulty in determining the effective feature set that can recognize the emotion conveyed within the facial expression accurately. Graph mining techniques are exploited in this paper to solve facial emotion recognition problem. After determining positions of facial landmarks in face region, twelve different graphs are constructed using four facial components to serve as a source for sub-graphs mining stage using gSpan algorithm. In each group, the discriminative set of sub-graphs are selected and fed to Deep Belief Network (DBN) for classification purpose. The results obtained from the different groups are then fused using Naïve Bayes classifier to make the final decision regards the emotion class. Different tests were performed using Surrey Audio-Visual Expressed Emotion (SAVEE) database and the achieved results showed that the system gives the desired accuracy (100%) when fusion decisions of the facial groups. The achieved result outperforms state-of-the-art results on the same database.

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Publication Date
Wed Mar 01 2023
Journal Name
Baghdad Science Journal
A Study on Co – odd (even) Sum Degree Edge Domination Number in Graphs
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 An edge dominating set    of a graph  is said to be an odd (even) sum degree edge dominating set (osded (esded) - set) of G if the sum of the degree of all edges in X is an odd (even) number. The odd (even) sum degree edge domination number  is the minimum cardinality taken over all odd (even) sum degree edge dominating sets of G and is defined as zero if no such odd (even) sum degree edge dominating set exists in G. In this paper, the odd (even) sum degree domination concept is extended on the co-dominating set E-T of a graph G, where T is an edge dominating set of G.  The corresponding parameters co-odd (even) sum degree edge dominating set, co-odd (even) sum degree edge domination number and co-odd (even) sum degree edge domin

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
Metal Complexes of Multidentate N<sub>2</sub>S<sub>2</sub> Heterocyclic Schiff-base Ligands;Formation, Structural Characterisation and Biological Activity
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Abstract<p>The synthesis of ligands with N<sub>2</sub>S<sub>2</sub> donor sets that include imine, an amide, thioether, thiolate moieties and their metal complexes were achieved. The new Schiff-base ligands; N-(2-((2,4-diphenyl-3-azabicyclo[3.3.1]nonan-9-ylidene)amino)ethyl)-2-((2-mercaptoethyl)thio)-acetamide (H<sub>2</sub>L<sup>1</sup>) and N-(2-((2,4-di-p-tolyl-3-azabicyclo[3.3.1]nonan-9-ylidene)amino)ethyl)-2-((2-mercaptoethyl)thio) acetamide (H2L<sup>2</sup>) were obtained from the reaction of amine precursors with 1,4-dithian-2-one in the presence of triethylamine as a base in the CHCl3 medium. Complexes of the general formula K<sub>2<</sub></p> ... Show More
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Publication Date
Mon Jan 01 2018
Journal Name
International Journal Of Data Mining, Modelling And Management
Association rules mining using cuckoo search algorithm
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Association rules mining (ARM) is a fundamental and widely used data mining technique to achieve useful information about data. The traditional ARM algorithms are degrading computation efficiency by mining too many association rules which are not appropriate for a given user. Recent research in (ARM) is investigating the use of metaheuristic algorithms which are looking for only a subset of high-quality rules. In this paper, a modified discrete cuckoo search algorithm for association rules mining DCS-ARM is proposed for this purpose. The effectiveness of our algorithm is tested against a set of well-known transactional databases. Results indicate that the proposed algorithm outperforms the existing metaheuristic methods.

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Publication Date
Tue Jun 01 2021
Journal Name
Baghdad Science Journal
The Dominant Metric Dimension of Corona Product Graphs
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The metric dimension and dominating set are the concept of graph theory that can be developed in terms of the concept and its application in graph operations. One of some concepts in graph theory that combine these two concepts is resolving dominating number. In this paper, the definition of resolving dominating number is presented again as the term dominant metric dimension. The aims of this paper are to find the dominant metric dimension of some special graphs and corona product graphs of the connected graphs  and , for some special graphs  . The dominant metric dimension of  is denoted by  and the dominant metric dimension of corona product graph G and H is denoted by .

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
Fractional Local Metric Dimension of Comb Product Graphs
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The local resolving neighborhood  of a pair of vertices  for  and  is if there is a vertex  in a connected graph  where the distance from  to  is not equal to the distance from  to , or defined by . A local resolving function  of  is a real valued function   such that  for  and . The local fractional metric dimension of graph  denoted by , defined by  In this research, the author discusses about the local fractional metric dimension of comb product are two graphs, namely graph  and graph , where graph  is a connected graphs and graph  is a complate graph &

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Publication Date
Sun Mar 07 2010
Journal Name
Baghdad Science Journal
Proposed methods of image recognition depend on the PCA
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This paper suggest two method of recognition, these methods depend on the extraction of the feature of the principle component analysis when applied on the wavelet domain(multi-wavelet). First method, an idea of increasing the space of recognition, through calculating the eigenstructure of the diagonal sub-image details at five depths of wavelet transform is introduced. The effective eigen range selected here represent the base for image recognition. In second method, an idea of obtaining invariant wavelet space at all projections is presented. A new recursive from that represents invariant space of representing any image resolutions obtained from wavelet transform is adopted. In this way, all the major problems that effect the image and

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Publication Date
Sat Jan 01 2011
Journal Name
Journal Of Computer Sciences
Connectedness in Graphs and Gm-Closure Spaces
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This paper is devoted to the discussion the relationships of connectedness between some types of graphs (resp. digraph) and Gm-closure spaces by using graph closure operators.

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Publication Date
Sat Jul 12 2025
Journal Name
Journal Of Baghdad College Of Dentistry
Management of facial fistulas and sinuses
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Background: A major difference between the treatment of the skin lesions and the odontogenic and non-odontogenic sinuses. We aimed to analyze a substantial number of consecutive causes in order to clinical suspicion in the differential diagnoses may be correctly weighted. Materials and methods: The material of this research consisted of 40 patients. A complete history is collected from the patients with the duration and the site of the sinus present, the patient was examined for factors of the fistulas and sinuses and its associations, and patient having any concomitant lesions, a medical consultation done for opinion and management. Clinical examination with facial fistulas and sinuses was mandatory to avoid any mistakes that may occur. A

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Intelligent Systems
A study on predicting crime rates through machine learning and data mining using text
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Abstract<p>Crime is a threat to any nation’s security administration and jurisdiction. Therefore, crime analysis becomes increasingly important because it assigns the time and place based on the collected spatial and temporal data. However, old techniques, such as paperwork, investigative judges, and statistical analysis, are not efficient enough to predict the accurate time and location where the crime had taken place. But when machine learning and data mining methods were deployed in crime analysis, crime analysis and predication accuracy increased dramatically. In this study, various types of criminal analysis and prediction using several machine learning and data mining techniques, based o</p> ... Show More
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Publication Date
Mon Dec 30 2019
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Adsorption Behavior of Light Naphtha Components on Zeolite (5A) and Activated Carbon
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Light naphtha one of the products from distillation column in oil refineries used as feedstock for gasoline production. The major constituents of light naphtha are (Normal Paraffin, Isoparaffin, Naphthene, and Aromatic). In this paper, we used zeolite (5A) with uniform pores size (5Aº) to separate normal paraffin from light naphtha, due to suitable pore size for this process and compare the behavior of adsorption with activated carbon which has a wide range of pores size (micropores and mesopores) and high surface area. The process is done in a continuous system - Fixed bed reactor- at the vapor phase with the constant conditions of flow rate 5 ml/min, temperature 180oC, pressure 1.6 bar and 100-gram weight o

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