Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep learning model was utilized to resize images and feature extraction. Finally, different ML classifiers have been tested for recognition based on the extracted features. The effectiveness of each classifier was assessed using various performance metrics. The results show that the proposed system works well, and all the methods achieved good results; however, the best results obtained were for the Support Vector Machine (SVM) with a linear kernel.
Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing flower pollination algorithm in the environmental field to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement. We estimate the regression function of the semi-parametric model by estimating the parametric model and estimating the non-parametric model, the parametric model is estimated by using an instrumental variables method (Wald method, Bartlett’s method, and Durbin
... Show MoreFlexible job-shop scheduling problem (FJSP) is one of the instances in flexible manufacturing systems. It is considered as a very complex to control. Hence generating a control system for this problem domain is difficult. FJSP inherits the job-shop scheduling problem characteristics. It has an additional decision level to the sequencing one which allows the operations to be processed on any machine among a set of available machines at a facility. In this article, we present Artificial Fish Swarm Algorithm with Harmony Search for solving the flexible job shop scheduling problem. It is based on the new harmony improvised from results obtained by artificial fish swarm algorithm. This improvised solution is sent to comparison to an overall best
... Show MoreThe study aims to predict Total Dissolved Solids (TDS) as a water quality indicator parameter at spatial and temporal distribution of the Tigris River, Iraq by using Artificial Neural Network (ANN) model. This study was conducted on this river between Mosul and Amarah in Iraq on five positions stretching along the river for the period from 2001to 2011. In the ANNs model calibration, a computer program of multiple linear regressions is used to obtain a set of coefficient for a linear model. The input parameters of the ANNs model were the discharge of the Tigris River, the year, the month and the distance of the sampling stations from upstream of the river. The sensitivity analysis indicated that the distance and discharge
... Show MoreThe compound 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), an environmental contaminant, is a potent ligand for aryl hydrocarbon receptor (AhR). In the current study, we made an exciting observation that naive C57BL/6 mice that were exposed i.p. to TCDD showed massive mobilization of myeloid-derived suppressor cells (MDSCs) in the peritoneal cavity. These MDSCs were highly immunosuppressive and attenuated Con A–induced hepatitis upon adoptive transfer. TCDD administration in naive mice also led to induction of several chemokines and cytokines in the peritoneal cavity and serum (CCL2, CCL3, CCL4, CCL11, CXCL1, CXCL2, CXCL5, CXCL9, G-CSF, GM-CSF, VEGF, and M-CSF) and chemokine receptors
Ultrasound has been used as a diagnostic modality for many intraocular diseases, due its safety, low cost, real time and wide availability. Unfortunately, ultrasound images suffer from speckle artifact that are tissue dependent. In this work, we will offer a method to reduce speckle noise and improve ultrasound image to raise the human diagnostic performance. This method combined undecimated wavelet transform with a wavelet coefficient mapping function: where UDWT used to eliminate the noise and a wavelet coefficient mapping function used to enhance the contrast of denoised images obtained from the first component. This methods can be used not only as a means for improving visual quality of medical images but also as a preprocessing
... Show MoreStudying the spatially distribution pattern of fuel station in province of Baghdad
was done by utilizing GIS techniques which they are the most powerful tools for
design, display and analysis for the spatial data. Nearest Neighbor Analysis method
was applied for analyzing the spatial distributions of the fuel stations. Baghdad was
considered to be divided in to two main parts (outskirts of Baghdad and center of
Baghdad). The nearest neighbour for all parts of Baghdad indicates for the
distribution pattern is random and differs from place to another in randomly rate.
The core objective of this paper was to diagnosis and detect the expected rotor faults in small wind turbine SWT utilize signal processing technique. This aim was achieved by acquired and analyzed the current signal of SWT motor and employed the motor current signature analysis MCSA to detect the sudden changes can have occurred during SWT operation. LabVIEW program as a virtual instrument and (NI USB 6259) DAQ were take advantage of current measurement and data processing.
Face recognition system is the most widely used application in the field of security and especially in border control. This system may be exposed to direct or indirect attacks through the use of face morphing attacks (FMAs). Face morphing attacks is the process of producing a passport photo resulting from a mixture of two images, one of which is for an ordinary person and the other is a judicially required. In this case, a face recognition system may allow travel of persons not permitted to travel through face morphing image in a Machine-Readable Electronic Travel Document (eMRTD) or electronic passport at Automatic Border Control (ABC) gates. In creating an electronic passport, most countries rely on applicant to submit ima
... Show MoreDigital tampering identification, which detects picture modification, is a significant area of image analysis studies. This area has grown with time with exceptional precision employing machine learning and deep learning-based strategies during the last five years. Synthesis and reinforcement-based learning techniques must now evolve to keep with the research. However, before doing any experimentation, a scientist must first comprehend the current state of the art in that domain. Diverse paths, associated outcomes, and analysis lay the groundwork for successful experimentation and superior results. Before starting with experiments, universal image forensics approaches must be thoroughly researched. As a result, this review of variou
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