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Diabetes mellitus (DM) represents a heterogeneous and multifactorial metabolic disorder, leading to diverse economic challenges and health complications, significantly affecting individuals’ lives. Type 2 diabetes (T2DM) stands as the predominant form of diabetes, with its onset influenced by a range of genetic and environmental factors. Currently, conventional diabetic medications are employed in clinical practice, but they may entail certain side effects. Fortunately, diverse natural polysaccharides extracted from plants exhibit antidiabetic properties, which have been demonstrated to effectively mitigate hyperglycemia, reverse insulin resistance, and forestall complications associated with diabetes. Consequently, exploring the utilization of these polysaccharides as adjuncts to conventional therapies has emerged as a novel research direction in recent years. Thus, this review centers on the extraction, purification, and characterization of plant polysaccharides, providing an overview of the advancements in the antidiabetic effects and mechanisms of natural polysaccharides. This perspective offers fresh insights to explore potential research domains and enhances understanding for the development of diabetic drugs derived from polysaccharides.

End-stage renal disease (ESRD) is a serious disease that requires hemodialysis as the main regimen for supporting patients. The pathophysiology of the disease is still an interesting field of study. In the present study, matrix metalloproteinase-3 (MMP3), a tissue inhibitor of metalloproteinase-1 (TIMP1), and vitamin D (VitD) were studied in ESRD. MMP3, TIMP1, VitD, and other related biomarkers were measured in 53 ESRD patients and compared with 33 healthy controls. The results showed a significant increase in serum MMP3 and TIMP1 and a significant decrease in serum VitD in ESRD patients compared with the control group. The multivariate GLM results revealed no significant effects of the covariates (sex, age, smoking and BMI) on the levels of MMP3, TIMP1 and VitD. ESRD was found to be the major factor affecting the measured parameters, with a huge effect size (Partial η2) of 0.824. According to our data, eGFR, Creatinine, Urea, phosphate, uric acid and VitD (as estimated glomerular filtration rate) are the top 6 factors highly affected by the presence of the disease. MMP3 and TIMP1 are important parameters in ESRD and may act as drug targets. As the patients also suffered from hypovitaminosis D and hypocalcemia, these factors also need intervention.

We theoretically investigate the frequency shift of a free-running semiconductor laser when optically injected by an optical frequency comb. By numerical integration of the laser rate equations, we have identified two types of frequency shifts, frequency pulling, and frequency pushing. The free-running slave laser seems to switch between pulling and pushing in a regular manner. We have systematically determined the dependence of these shifts on comb parameters, including comb spacing and number of lines. We have found that the occurring frequency pushing seems to be almost independent of comb signals and comb spacing, while in contrast, the frequency pulling shows weak dependence on comb signals but largely affected by comb spacing. We have also shown that carrier density dynamic is the origine of these phenomena.

A study was conducted in the summer season of 2022 in the village of Aday in Baquba District - Diyala Governorate on the mung plant Vigna radaita L. (a local green variety) in clay soil ,in order to study the effect of bio-fertilization with Azotobacter chroococcum and the Mycorhiza fungi (Glomus mosseae ) and organic fertilization using humic acid on the vegetative characteristics of the mung bean (V. radaita L.). The Experiment were carried out according to the randomized complete block design (R.C.B.D) with three replications using two fertilization, the first was biological fertilization, which included four treatments, namely (without addition, the addition of Azotobacter, the addition of Mycorrhizae, and the addition of Azotobacter + Mycorrhizae) and the second was organic fertilization, which included four concentrations of humic acid 0, 3, 6 and 9 gm.l-1 the result findings were:The treatment of biofertilization by adding Azotobacter and Mycorrhizae in all the studied characteristics of plant height, root length, number of branches, leaf area of the vegetative total reached76.87 cm , 43.01 cm,15 branch.plants-1 , 660.77 cm2 . The treatment of organic fertilization with humic acid at a concentration of 9 gm.l-1 was superior giving it the highest mean of plant height, root length, number of branches, leaf area of the vegetative total.77.6cm, 16cm, 15.39branch.plant- 1 , 660.83 cm2 .

The field experiment was carried out in one of the agricultural fields of Al-Khalis District / Diyala Governorate, Iraq, which is located 14 km north of Baquba District, during the autumn season of 2022, in soil with clay loam textured to study the effect of organic fertilization with humic and fulvic acid and the interaction between them on the growth and yield of the sunflower plants ( Helianthus annuus L.). A two-factor experiment was carried out using three replications of the (RCBD) randomized complete block design. The first factor was sprayed with humic acid at a concentration of 6gm.L.-1 And the second agent was sprayed with fulvic acid at a concentration of 6 gm.L -1The results showed that there was a significant superiority when adding humic acid + fulvic acid at a concentration of 6gm.L.-1 In the average characteristic of plant height, stem diameter, chlorophyll index, plant leaf area, number of leaves per plant,the weight of 1000 seeds, total yield, percentage of oil in seeds, and percentage of protein in seeds.

Several application programs, including Global Mapper, Surfer and GIS, which deal with spatial analysis and extract spatial data and information for land features, were used to extract geometric elements of the proposed Derlock Dam reservoir based on the digital elevation model (DEM) with a discriminating ability of 10 m. It started at a level of 740 m at the site of the dam and reached a height of 900 m above sea level with an interval of 10 m. The relationship of the level with the negative volumetric and negative spatial elements showed that there is a large difference in the values of Negative Volume (NV), Negative Planar Area (NPA), and negative surface area (NSA) at the level of the reservoir (900 m), which is a positive factor in choosing the topograph Negative Surface Area depression, as it shows a significant decrease in the surface area (evaporation area) and the wet area (the area of penetration). This corresponds to a significant increase in the volume of the reservoirs, and indicates that the depression is deep and small in area, as well as the final economic feasibility of the project. It consists of two reservoirs, which will allow a strategy to maneuver the amount of water storage, as well as reduce the risks of flood waves and sediments that will be deposited behind the dam gate. The reservoir volume reached 900 m, 3611048537 billion m3, distributed among reservoirs near the dam with volumes of 445189305 million/m3 and 3166195232 billion/m3 for the reservoir far from the dam site, because the Upper Zab River does not have dams, so it will be able to build important reservoirs and control the river water during floods.‎

Titanium-based dental prostheses are essential for prosthodontics and can now be 3D printed using powder bed fusion (PBF) technology with different densities by controlling the process parameters. This study aimed to assess the surface topography and bonding strength of dental resins made of 3D-printed titanium alloys with varying densities and growth directions. Three groups of titanium alloy (Ti6Al4V) specimens differentiated by density (low, medium, and high) were produced using laser-melting 3D printing technology (N = 8). Each group included specimen surfaces with vertical and horizontal growths. Vickers microhardness, surface profilometry, wettability, and shear bond strength (SBS) of the titanium samples were measured for all groups. Scanning electron microscopy (SEM) was performed. Statistical analyses were conducted using a two-way ANOVA and Fisher’s multiple test. Higher-density specimens exhibited greater microhardness (p < 0.05), and those with horizontal growth directions were harder (p < 0.05) than their vertical counterparts within the same density category. Additionally, low-density specimens in both growth directions had the highest surface roughness values (p < 0.05) compared to the other groups. The wettability values were similar (p > 0.05) among the groups in the vertical direction, but not in the horizontal direction (p < 0.05). However, the density type did not significantly (p > 0.05) influence the bonding strength of 3D-printed titanium. This study revealed significant variations in surface roughness, contact angle, and microhardness based on density and growth direction.

To ensure that a software/hardware product is of sufficient quality and functionality, it is essential to conduct thorough testing and evaluations of the numerous individual software components that make up the application. Many different approaches exist for testing software, including combinatorial testing and covering arrays. Because of the difficulty of dealing with difficulties like a two-way combinatorial explosion, this brings up yet another problem: time. Using client-server architectures, this research introduces a parallel implementation of the TWGH algorithm. Many studies have been conducted to demonstrate the efficiency of this technique. The findings of this experiment were used to determine the increase in speed and compare it to the results obtained from the various methodologies. TWGH was shown to be a demonstration of scalability in studies involving speedups. When the recommended method was implemented, the rate of acceleration increased by eight.

In this paper, studied the types of (k, r)-arcs were constructed by action of groups on the three-dimensional projective space over the Galois field of order eight. Also, determined if they form complete arcs or not.

This laboratory study aimed to evaluate the effect of different surface patterns using femtosecond laser treatment on the enclosed mold shear bond strength (EM-SBS) of resin composite to zirconia (ZrO2) surfaces and to contrast it with the widely used tribochemical silica coating (TBC) surface conditioning method. A set of fifteen rectangular ZrO2 blocks were randomly divided into five groups according to surface pretreatment: Control G0—no treatment; G1—TBC with silane application; G2—femtosecond laser irradiation with horizontal lines 30 µm apart; G3—femtosecond laser irradiation with horizontal lines 15 µm apart; and G4—femtosecond laser irradiation with cross lines 30 µm apart. The pretreated surfaces were characterized by a surface profilometer, tensiometer and scanning electron microscope. The EM-SBS of resin composite stubs to ZrO2 was measured followed by fractographic analysis. The surface roughness and water contact angle were observed to be statistically higher among the femtosecond laser groups compared to the TBC and control groups. The G4 group exhibited the highest EM-SBS among all the groups, irrespective of the ageing conditions used. At the end of 5000 thermocycles, G4 exhibited EM-SBS of 14.05 ± 4.21 MPa compared to 13.80 ± 3.01 MPa in G1 and 5.47 ± 0.97 MPa in G0. The two-way ANOVA revealed a significant effect of both study groups and ageing conditions on the EM-SBS (p < 0.001). Utilization of femtosecond laser technology holds promise as a potential and alternative mechanical retention approach for enhancing the bonding strength of the resin composite to ZrO2.

هدفت الدراسة الى بيان أثر ممارسات القيادة الاستراتيجية في الحساسية الاستراتيجية لمجموعة من القيادات الأمنية في مديرية شرطة صلاح الدين والمنشآت، كما تهدف الدراسة الى تعريف عينة الدراسة بموضوعات (ممارسات القيادة الاستراتيجية، الحساسية الاستراتيجية). ولتحقيق هدف الدراسة قام الباحث باختبار عينة من القيادات في المديرية عينة البحث من خلال الاعتماد على استمارة الاستبانة كأداة أساسية لجمع البيانات من الميدان المبحوث، وتم بناء الاستبانة بناء على الدراسات السابقة ذات العلاقة بالدراسة، واعتماد المنهج الوصفي التحليلي، لهذا اعتمد الباحث في الدراسة أسلوب الحصر الشامل في تحديد حجم العينة، فقد تطلب ذلك دراسة اراء القيادات الأمنية من رتبة (العقيد، العميد، اللواء) في المستويات الإدارية العليا في مديرية شرطة صلاح الدين والمنشآت، وعليه ومن اجل إمكانية تعميم نتائج الدراسة قام الباحث بتوزيع (85) استمارة، استرجع منها (79) صالحة للتحليل. وتوصلت الدراسة الى مجموعة من الاستنتاجات كان أهمها: أوضحت نتائج الدراسة الحالية وجود علاقة ارتباط معنوية بين متغير ممارسات القيادة الاستراتيجية بأبعادها ومتغير الحساسية الاستراتيجية. وقدمت الدراسة مجموعة من المقترحات كان أهمها ينبغي أن تقوم القيادات في مديرية شرطة صلاح الدين والمنشآت بعقد دورات وبرامج تدريبية مستمرة لتطوير الملاك البشري فيما يتعلق بالفكر الاستراتيجي.

يأخذ تخطيط المنتج الأولوية عندما يتم تسويق المنتج في أسواق خارجية، حيث أن المستهلك هنا بتسميته مستهلك أجنبي لديه سلوك مختلف عن المستهلك المحلي، لذلك أخذت عملية تخطيط المنتج أولوية في ذلك لكي تتمكن المنظمة من غزو الأسواق الخارجية ونشر منتجاتها فيها وتلبية احتياجات المستهلكين فيها. وتناول البحث مفهوم تخطيط المنتجات، وعلاقته بدورة حياة المنتج, ومكونات تخطيط المنتج بالإضافة الى مفهوم سلوك المستهلك الأجنبي وتأثير تخطيط المنتجات السورية على السلوك الشرائي للمستهلك الأجنبي، واعتمد البحث على المنهج الوصفي التحليلي، بغية وصف متغيرات الدراسة وصياغة الفرضيات من أجل معرفة العلاقة بين المتغيرات المستقلة والمتغير التابع، وتم الاعتماد على أداة الاستبيان، وتوزيعها على عينة من المستهلكين في أسواق الإمارات، واستخدم برنامج SPSS في تحليل البيانات ودراسة الفرضيات باستخدام التحليلات الإحصائية المناسبة. وتوصلت الدراسة الى مجموعة من النتائج من أهمها: وجود علاقة قوية بين المتغير المستقل (مزيج المنتج) والمتغير التابع (سلوك المستهلك الأجنبي) وجود علاقة قوية بين المتغير المستقل (جودة المنتج) والمتغير التابع (سلوك المستهلك الأجنبي) وجود علاقة قوية بين المتغير المستقل (جودة الأداء) والمتغير التابع (سلوك المستهلك الأجنبي) وجود علاقة قوية بين المتغير المستقل (جودة المطابقة) والمتغير التابع (سلوك المستهلك الأجنبي) وجود علاقة قوية بين المتغير المستقل (تصميم وسمات المنتج) والمتغير التابع (سلوك المستهلك الأجنبي) وجود علاقة قوية بين المتغير المستقل (التعبئة والتغليف) والمتغير التابع (سلوك المستهلك الأجنبي) وجود علاقة قوية بين المتغير المستقل (التبيين) والمتغير التابع (سلوك المستهلك الأجنبي) وجود علاقة قوية بين المتغير المستقل (الاسم والعلامة التجارية) والمتغير التابع (سلوك المستهلك الأجنبي)

This paper presents an automatic visual inspection of exterior surface defects of oil tanks using unmanned aerial vehicles (UAVs) and image processing with two cascading fuzzy logic algorithms. Corrosion is one of the defects that has a serious effect on the safety of the surface of oil and gas tanks. At present, human inspection, and climbing robots inspection are the dominant approach for rust detection in oil and gas tanks. However, there are many shortcomings to this approach, such as taking longer, high cost, and covering less surface area inspection of the tank. The purpose of this research is to detect the rust in oil tanks by localizing visual inspection technology using UAVs, as well as to develop algorithms to distinguish between defects and noise. The study focuses on two basic aspects of oil tank inspection through the images captured by the UAV, namely, the detection of defects and the distinction between defects and noise. For the former, an image processing algorithm was developed to improve or remove noise, adjust the brightness of the captured image, and extract features to identify defects in oil tanks. Meanwhile, for the latter aspect, a cascading fuzzy logic algorithm and threshold algorithm were developed to distinguish between defects and noise levels and reduce their impact through three stages of processing: The first stage of fuzzy logic aims to distinguish between defects and low noise generated by the appearance of objects on the surface of the tank, such as trees or stairs, and reduce their impact. The second stage aims to distinguish between defects and medium noise generated by shadows or the presence of small objects on the surface of the tank and reduce their impact. The third stage of the thresholding algorithm aims to distinguish between defects and high noise generated by sedimentation on the surface of the tank and reduce its impact. The samples were classified based on the output of the third stage of the threshold process into defective or non-defective samples. The proposed algorithms were tested on 180 samples and the results show its superiority in the inspection and detection of defects with an accuracy of 83%.

The study focuses on the feasibility of connecting urban green spaces at an urban scale through a network because of the population growth and land use changes at the expense of green areas, which has led to the fragmentation and destabilization of the ecosystem in the Hilla city center in Babylon province /Iraq. The methodology will be according to two stages: first, the current state assessment was used to determine the encroachment of the areas. Secondly, it uses the gravity model and the least-cost path model in GIS to determine the level of interaction between nodes. Therefore, the research hypothesis was that connecting strong nodes to a comprehensive and integrated network increases the strength of the interaction. According to the results, there is no clear hierarchy in the distribution of urban green spaces within Hilla city, with only two levels: locality and urban on the urban level, there is no possibility of establishing a network between green spaces because of three factors: encroached uses mainly the residential, distance between patches and the node weight.

This study seeks to provide a broad and thorough review of the literature on the big five traits (BFT) and its major developments through a long history of conceptual and applied studies in many areas that have been conducted on large samples of individuals, groups and countries. The BFT is the most widely accepted and most prominent model to describe the structure of personality traits, so this study sought to identify them in order to achieve a better understanding as well as for consideration by researchers in their future studies. This review focused on the eight key observations related to the BFT. These observations are as follows: meaning of the traits; the history of the BFT model; unity or hierarchy of traits; number of the traits; three perspectives on BFT; BFT questionnaires; BFT and performance; and the need for a sixth trait. The results of the study clearly confirmed that there are problems with universal models that tend to generalize a limited number of dimensions in order to interpret personality across borders and cultures. This generalization of the models is accompanied by the numerous observations and problems mentioned in the above eight points.

Intelligent reflecting surfaces (IRS) and power-domain non-orthogonal multiple access (PD-NOMA) have recently gained significant attention for enhancing the performance of next-generation wireless communications networks. More specifically, IRS can smartly reconfigure the incident signal of the source towards the destination node, extending the wireless coverage and improving the channel capacity without consuming additional energy. On the other side, PD-NOMA can enhance the number of devices in the network without using extra spectrum resources. This paper proposes a new optimization framework for IRS-enhanced NOMA communications where multiple drones transmit data to the ground Internet of Things (IoT) devices under successive interference cancellation errors. In particular, the power budget of each drone, PD-NOMA power allocation of IoT devices, and the phase shift matrix of IRS are simultaneously optimized to enhance the total spectral efficiency of the system. Given the system model and optimization setup, the formulated problem is coupled with three variables, making it very complex and non-convex. Thus, this work first transforms and decouples the problem into subproblems and then obtains the efficient solution in two steps. In the first step, the closed-form solutions for the power budget and PD-NOMA power allocation subproblem at each drone are obtained through Karush–Kuhn–Tucker (KKT) conditions. In the second step, the subproblem of efficient phase shift design for each IRS is solved using successive convex approximation and DC programming. Numerical results demonstrate the performance of the proposed optimization scheme in comparison to the benchmark schemes.

Accurate and timely traffic flow prediction not just allows traffic controllers to evade traffic congestion and guarantee standard traffic functioning, it even assists travelers to take advantage of planning ahead of schedule and modifying travel routes promptly. Therefore, short-term traffic flow prediction utilizing artificial intelligence (AI) techniques has received significant attention in smart cities. This manuscript introduces an autonomous short-term traffic flow prediction using optimal hybrid deep belief network (AST2FP-OHDBN) model. The presented AST2FP-OHDBN model majorly focuses on high-precision traffic prediction in the process of making near future prediction of smart city environments. The presented AST2FP-OHDBN model initially normalizes the traffic data using min–max normalization. In addition, the HDBN model is employed for forecasting the traffic flow in the near future, and makes use of DBN with an adaptive learning step approach to enhance the convergence rate. To enhance the predictive accuracy of the DBN model, the pelican optimization algorithm (POA) is exploited as a hyperparameter optimizer, which in turn enhances the overall efficiency of the traffic flow prediction process. For assuring the enhanced predictive outcomes of the AST2FP-OHDBN algorithm, a wide-ranging experimental analysis can be executed. The experimental values reported the promising performance of the AST2FP-OHDBN method over recent state-of-the-art DL models with minimal average mean-square error of 17.19132 and root-mean-square error of 22.6634.

There are many studies that have focused on the Albrecht model of organizational intelligence (OI) and its seven dimensions (strategic vision, shared fate, appetite for change, heart, alignment and congruence, knowledge deployment, and performance pressure), but the current study presents a new attempt to study OI using the Yolles model in its three dimensions (self-reference, self-regulation, and self-organization) (2005). This study sought to determine the effect of organizational intelligence on market expansion (new markets and new product) in the Jordanian pharmaceutical industry, and it examined the effect of transformational leadership as a mediating variable on the relationship between organizational intelligence and market expansion. The study sample consisted of 231 respondents taken from six pharmaceutical companies divided into three categories according to their size as small, medium and large companies. The results confirmed that there is a significant positive effect of the two dimensions (self-regulation and self-organization) on new markets, while three dimensions of OI have a significant effect on new products in the pharmaceutical companies.

The main aims of this research are to find the stabilizer groups of cubic curves over a finite field of order 7 and studying the properties of their groups and then constructing the arcs of degree 2 which are embedding in cubic curves of even size which are considering as the arcs of degree 3. Also drawing all these arcs.

The main aim of this research is to introduce the relationship between the topic of coding theory and the projective plane of order four. The maximum value of size code M over the finite field of order four and an incidence matrix with the parameters, n (length of code), d (minimum distance of code) and e (error-correcting of code) have been constructed. Some examples and theorems have been given.

Unmanned Aerial Vehicles (UAVs), or drones, provided with camera sensors enable improved situational awareness of several emergency responses and disaster management applications, as they can function from remote and complex accessing regions. The UAVs can be utilized for several application areas which can hold sensitive data, which necessitates secure processing using image encryption approaches. At the same time, UAVs can be embedded in the latest technologies and deep learning (DL) models for disaster monitoring areas such as floods, collapsed buildings, or fires for faster mitigation of its impacts on the environment and human population. This study develops an Artificial Intelligence-based Secure Communication and Classification for Drone-Enabled Emergency Monitoring Systems (AISCC-DE2MS). The proposed AISCC-DE2MS technique majorly employs encryption and classification models for emergency disaster monitoring situations. The AISCC-DE2MS model follows a two-stage process: encryption and image classification. At the initial stage, the AISCC-DE2MS model employs an artificial gorilla troops optimizer (AGTO) algorithm with an ECC-Based ElGamal Encryption technique to accomplish security. For emergency situation classification, the AISCC-DE2MS model encompasses a densely connected network (DenseNet) feature extraction, penguin search optimization (PESO) based hyperparameter tuning, and long short-term memory (LSTM)-based classification. The design of the AGTO-based optimal key generation and PESO-based hyperparameter tuning demonstrate the novelty of our work. The simulation analysis of the AISCC-DE2MS model is tested using the AIDER dataset and the results demonstrate the improved performance of the AISCC-DE2MS model in terms of different measures.

Water is the basis of the existence of all kinds of life, so obtaining it with good quality represents a challenge to human existence and development especially in the desert and remote cities because these areas contain small populations and water purification requires great materials and huge amounts of fossil fuels resulting pollution of the environment. Cheap and environmentally friendly desalination methods have been done by using solar distillations. Passive solar stills have low yields, so in this research, the problem is overcome by connecting four heat pipes which are installed on the parabolic concentrator reflector with passive solar still to increase the temperature of hot water to more than 90°C, as a result, the yield increases. An extensive theory is studied to manufacture two systems: the first consists of passive solar still has dimensions are 1000 mm × 500 mm and the glass cover tilted at the angle 33°. It is approximately equal to the latitude of the city of Baghdad [(Latitude: (33.34° N) Longitude: (44.4° E)]. This gives 5.04 kg/m2.day, the second solar still which is associated with 4 heat pipes gives a water yield of about 7. 2 kg/m2.day. This means that the improvement in the daily production of distilled water is 50 % over the productivity of the passive solar still All results above are calculated when the depth of water is 1. 5 cm. In addition, heat balance for each part of the system is achieved and calculations of the performance of the solar still are done by using the program in the language of Matlab. All these results are compared with the experimental ones of different depths of water (1.5 cm, 2 cm, 3 cm, and 4 cm) which are taken from the experimental part to ensure the system reliability at different weather conditions in Baghdad throughout the year and to give a good approach. The system associated with heat pipes gives promising results and can be widely used for its abundant productivity and durability of its components. (TDS) and (pH) value are carried out in the laboratory and it is found that water is safe and pure for drinking.

The aim of the paper is to classify certain geometric structures, called arcs. The main computing tool is the mathematical programming language GAP. In the plane PG(2,16),the important arcs are called complete and are those that cannot be increased to a larger arc. So far, all arcs up to size eighteen have been classified. Each of these arcs gives rise to an error-correcting code that corrects the maximum possible number of errors for its length.

Pneumatosis intestinalis (PI) is a radiographic finding which refers to the presence of gas within the wall of any part of the gastrointestinal tract. While in some cases it is an incidental finding which usually represent its benign nonischemic etiology, it may indicate a catastrophic intra-abdominal condition and distinctly characteristic of ischemic enterocolitis. Herein, we discuss the clinical signs and symptoms, the radiological features, the surgical management and outcome of an extremely rare concurrent triad of PI, gastric outlet obstruction, and the sigmoid volvulus based on a case of a patient who underwent surgery in our hospital, which, we think, can emphasize the mysterious concept of PI’s mechanical etiology.

The software cost prediction is a crucial element for a project’s success because it helps the project managers to efficiently estimate the needed effort for any project. There exist in literature many machine learning methods like decision trees, artificial neural networks (ANN), and support vector regressors (SVR), etc. However, many studies confirm that accurate estimations greatly depend on hyperparameters optimization, and on the proper input feature selection that impacts highly the accuracy of software cost prediction models (SCPM). In this paper, we propose an enhanced model using SVR and the Optainet algorithm. The Optainet is used at the same time for 1-selecting the best set of features and 2-for tuning the parameters of the SVR model. The experimental evaluation was conducted using a 30% holdout over seven datasets. The performance of the suggested model is then compared to the tuned SVR model using Optainet without feature selection. The results were also compared to the Boruta and random forest features selection methods. The experiments show that for overall datasets, the Optainet-based method improves significantly the accuracy of the SVR model and it outperforms the random forest and Boruta feature selection methods.

Today moderation of Islam faces severe challenges. Through this paper presented diagnosis of this social disease and it cure, by suggesting the correct understanding of two terms; extremism, and flattery, so it does not cause negative effects for individuals and groups. The important goals of this research be alert contemporary muslim generation from extremism, fanaticism and hypocrisy.