This study employs evolutionary optimization and Artificial Intelligence algorithms to determine an individual’s age using a single-faced image as the basis for the identification process. Additionally, we used the WIKI dataset, widely considered the most comprehensive collection of facial images to date, including descriptions of age and gender attributes. However, estimating age from facial images is a recent topic of study, even though much research has been undertaken on establishing chronological age from facial photographs. Retrained artificial neural networks are used for classification after applying reprocessing and optimization techniques to achieve this goal. It is possible that the difficulty of determining age could be reduced by using an algorithm that calculates the predicted value. The utilization of machine learning models that have been trained on massive datasets, the implementation of strategies for correct face alignment, and the utilization of expected value regression formulations have all been significantly incorporated into the suggested approach. The model’s performance is optimized and improved in this study by utilizing several distinct classifiers, increasing the effectiveness of explicit expectations. We aimed to optimize the selection of classifiers to minimize energy consumption while achieving a mean absolute error of 2.08 (average) and a power usage of 2700 W.
A model using the artificial neural networks and genetic algorithm technique is developed for obtaining optimum dimensions of the foundation length and protections of small hydraulic structures. The procedure involves optimizing an objective function comprising a weighted summation of the state variables. The decision variables considered in the optimization are the upstream and downstream cutoffs lengths and their angles of inclination, the foundation length, and the length of the downstream soil protection. These were obtained for a given maximum difference in head, depth of impervious layer and degree of anisotropy. The optimization carried out is subjected to constraints that ensure a safe structure aga
... Show MoreDetermining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on
... Show MoreOffline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu
... Show MoreArtificial fish swarm algorithm (AFSA) is one of the critical swarm intelligent algorithms. In this
paper, the authors decide to enhance AFSA via diversity operators (AFSA-DO). The diversity operators will
be producing more diverse solutions for AFSA to obtain reasonable resolutions. AFSA-DO has been used to
solve flexible job shop scheduling problems (FJSSP). However, the FJSSP is a significant problem in the
domain of optimization and operation research. Several research papers dealt with methods of solving this
issue, including forms of intelligence of the swarms. In this paper, a set of FJSSP target samples are tested
employing the improved algorithm to confirm its effectiveness and evaluate its ex
This research was carried out to determine the impact of heat shock, electric shock and seeds in soaking nitrous acid mutagen solution on three cultivars of faba beans plant (Zaina, Aguadulce and Local) at the year 2012-2013. Factorial experiment was arranged in randomized complete block design (RCBD) with three replicates were used. The results showed that heat shock lead to early plants of 50% in flowering and an increase in the number of branches/plant and the number of seeds/pod compared to other treatments, whereas the seeds soaked in nitrous acid mutagen solution gave the highest plant height, leaf area index, number of pods/plant, seed weight, seed yield kg/ha, and did not differ significantly with treatment of electric shock in the
... Show MoreDocument clustering is the process of organizing a particular electronic corpus of documents into subgroups of similar text features. Formerly, a number of conventional algorithms had been applied to perform document clustering. There are current endeavors to enhance clustering performance by employing evolutionary algorithms. Thus, such endeavors became an emerging topic gaining more attention in recent years. The aim of this paper is to present an up-to-date and self-contained review fully devoted to document clustering via evolutionary algorithms. It firstly provides a comprehensive inspection to the document clustering model revealing its various components with its related concepts. Then it shows and analyzes the principle research wor
... Show MoreBackground: obesity is nowadays a pandemic condition. Obese subjects are commonly characterized by musculoskeletal disorders and particularly by non-specific low back pain (LBP). However, the relationship between obesity and LBP remain to date unsupported by an objective measurement of the mechanical behavior of spine and it is morphology in obese subjects. . Objectives: To identify the relationship between obesity and LBP regarding (height, weight, sleeping, chronic diseases, smoking, and steroid). Method: A cross-sectional study was conducted from the first of January 2016 to January 2018 in obe
... Show MoreDust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system
... Show MoreThe study aims to identify the relationship between forgiveness and social intelligence among elementary school students. The study employed a descriptive analytical approach, whereby a total of (500) elementary school student were selected randomly regarding the variable of gender and economical status. Two scales were prepared: one to measure the forgiveness depending on Albort’s theory that consist of (20) item, and the other to measure the social intelligence according to Tony’s theory which composed of (20) item as well. The result revealed that 6th grade students have interested level of the forgiveness and social intelligence, the girl showed significant differences according to the forgiveness variable, the sample
... Show MoreBased on the theoretical review of researches and studies concerned with virtual teams in organizations, it was found that the role of virtual teams varies from case to another, and it may be positive or opposite. The purpose of the current research is to examine the role of virtual teams in the impact of cultural intelligence on the strategic excellence of Zain worldwide Group. An electronic questionnaire was designed through the (Google) and (Microsoft) forms, and distributed then on a sample of (146) participants with a high organizational level of the HRM departments within the group. The results showed that there was a positive moderator role of virtual teams in the relationship of cultural intelligence and strategic excellence
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