Humans use deception daily since it can significantly affect their life and provide a getaway solution for any undesired situation. Deception is either related to low-stakes (e.g. innocuous) or high-stakes (e.g. with harmful situations). Deception investigation importance has increased, and it became a critical issue over the years with the increase of security levels around the globe. Technology has made remarkable achievements in many human life fields, including deception detection. Automated deception detection systems (DDSs) are widely used in different fields, especially for security purposes. The DDS is comprised of multiple stages, each of which should be built/trained to perform intelligently so that the whole system can give the right decision of whether the involved person is telling the truth or not. Thus, different artificial intelligent (AI) algorithms have been utilized by the researchers over the past years. In addition, there are different cues for DDS that have been considered for the previous works, which are either related to verbal or non-verbal cues. This paper presents a review on the basic methods and the used deception detection techniques for the recent 10 years, that were studied and performed in the field of DDS, with a comparison of the deception detection accuracy reached and the number of participants used for system training.
This research presents a new algorithm for classification the
shadow and water bodies for high-resolution satellite images (4-
meter) of Baghdad city, have been modulated the equations of the
color space components C1-C2-C3. Have been using the color space
component C3 (blue) for discriminating the shadow, and has been
used C1 (red) to detect the water bodies (river). The new technique
was successfully tested on many images of the Google earth and
Ikonos. Experimental results show that this algorithm effective to
detect all the types of the shadows with color, and also detects the
water bodies in another color. The benefit of this new technique to
discriminate between the shadows and water in fast Matlab pro
Automated medical diagnosis is an important topic, especially in detection and classification of diseases. Malaria is one of the most widespread diseases, with more than 200 million cases, according to the 2016 WHO report. Malaria is usually diagnosed using thin and thick blood smears under a microscope. However, proper diagnosis is difficult, especially in poor countries where the disease is most widespread. Therefore, automatic diagnostics helps in identifying the disease through images of red blood cells, with the use of machine learning techniques and digital image processing. This paper presents an accurate model using a Deep Convolutional Neural Network build from scratch. The paper also proposed three CNN
... Show MoreAn adaptive fuzzy weighted linear regression model in which the output is based
on the position and entropy of quadruple fuzzy numbers had dealt with. The solution
of the adaptive models is established in terms of the iterative fuzzy least squares by
introducing a new suitable metric which takes into account the types of the influence
of different imprecisions. Furthermore, the applicability of the model is made by
attempting to estimate the fuzzy infant mortality rate in Iraq using a selective set of
inputs.
This study aims to show, the strength of steel beam-concrete slab system without using shear connectors (known as a non-composite action), where the effect of the friction force between the concrete slab and the steel beam has been investigated, by using finite element simulation.
The proposed finite element model has been verified based on comparison with an experimental work. Then, the model was adopted to study the system strength with a different steel beam and concrete slab profile. ABAQUS has been adopted in the preparation of all numerical models for this study.
After validation of the numerical models, a parametric study was conducted, with linear and non-linear Regression analysis. An equation re
... Show MoreDue to its importance in physics and applied mathematics, the non-linear Sturm-Liouville problems
witnessed massive attention since 1960. A powerful Mathematical technique called the Newton-Kantorovich
method is applied in this work to one of the non-linear Sturm-Liouville problems. To the best of the authors’
knowledge, this technique of Newton-Kantorovich has never been applied before to solve the non-linear
Sturm-Liouville problems under consideration. Accordingly, the purpose of this work is to show that this
important specific kind of non-linear Sturm-Liouville differential equations problems can be solved by
applying the well-known Newton-Kantorovich method. Also, to show the efficiency of appl
Steady natural and mixed convection flow in a square vented enclosure filled with water-saturated aluminum metal foam is numerically investigated. The left vertical wall is kept at constant temperature and the remaining walls are thermally insulated. Forced convection is imposed by providing an inlet at cavity bottom surface, and a vent at the top surface. Natural convection takes place due to the temperature difference inside the enclosure. Darcy-Brinkman-Forchheimer model for fluid flow and the two-equation of the local thermal non-equilibrium model for heat flow was adopted to describe the flow characteristics within the porous cavity. Numerical results are obtained for a wide range of width of the inlet as a fraction
... Show MoreA modified Leslie-Gower predator-prey model with fear effect and nonlinear harvesting is developed and investigated in this study. The predator is supposed to feed on the prey using Holling type-II functional response. The goal is to see how fear of predation and presence of harvesting affect the model's dynamics. The system's positivity and boundlessness are demonstrated. All conceivable equilibria's existence and stability requirements are established. All sorts of local bifurcation occurrence conditions are presented. Extensive numerical simulations of the proposed model are shown in form of Phase portraits and direction fields. That is to guarantee the correctness of the theoretical results of the dynamic behavior of the system and t
... Show MoreThe electron correlation for inter-shells (1s 2p), (1s 3p) and (1s 3d) was described by the inter-particle radial distribution function f(r12). It was evaluated for Li-atom in the different excited states (1s2 2p), (1s2 3p) and (1s2 3d) using Hartree-Fock approximation (HF). The inter particle expectation values for these shells were also evaluated. The calculations were performed using Mathcad 14 program.
A study of non-diatom algal species composition in twelve sites from Greater Zab River path within
Erbil Province, was carried out from April 2021 to January 2022 with monthly sample collection in twelve studied sites. Among them site 4,5,6,7 and 9 are the first for algal study in this area. The 112 different species of algae belong to 33 genera, 25 families, 13 orders and 4 divisions have been identified. The predominant genera included Spirogyra and Cosmarium 17, 8 taxa respectively. 13 taxa were new recorded to Iraqi
Kurdistan algal flora and 9 of them were new recorded to Iraqi algal flora: Botryosphaerella sudetica, Muriella magna, Gloeotaenium loitlesbergianum, Apiocystis brauniana, Anabaena oscillarioides, C. distentum
In this research, Artificial Neural Networks (ANNs) technique was applied in an attempt to predict the water levels and some of the water quality parameters at Tigris River in Wasit Government for five different sites. These predictions are useful in the planning, management, evaluation of the water resources in the area. Spatial data along a river system or area at different locations in a catchment area usually have missing measurements, hence an accurate prediction. model to fill these missing values is essential.
The selected sites for water quality data prediction were Sewera, Numania , Kut u/s, Kut d/s, Garaf observation sites. In these five sites models were built for prediction of the water level and water quality parameters.