Bilad Alrafidain Journal for Engineering Science and Technology (BAJEST)

The levels of development exhibit significant disparities across countries and even among different parts of the same governorates. The major focus of many planners and decision makers was to investigate and analyze the regional variation in development levels. The study aims to examine the regional disparities in investment within the industrial sector throughout the governorates of Iraq. This analysis is not just based on quantitative indicators, but also takes into account the specific investment requirements of each governorate. To overcome this issue, we do the following actions: A mathematical model is constructed to elucidate the regional differences in investment amongst governorates. This model use factor analysis to quantify the association between various variables studied. Utilize the Ridge Regression Model to assess the influence of the factors on the geographical distribution of investment. The study aimed to determine the allocation of investment in the industry sector among the Iraqi governorates. The priorities for distribution were as follows: \'\'Al-Muthanna\'\', \'\'Missan\'\', \'\'Wasit\'\', \'\'Salahuddinni\'\', \'\'Thi-Qar\'\', \'\'Diala\'\', \'\'Kerbala\'\', \'\'Kirkuk\'\', \'\'Al-Qadisiya\'\', \'\'Al-Anbar\'\', \'\'Al-Najaf\'\', \'\'Babil\'\', \'\'Nineueh\'\', \'\'Basrah\'\', and Baghdad. This allocation aimed to achieve a balanced regional development. The value of the challenge coefficient (R^2= 0.84 and the correlation coefficient) (R= 0.91), which indicates the strength of the effect of the economic variables on the investment sector. This value is the spatial distribution of industrial investments among the governorates, and this is confirmed by the decrease in the value of (MSE) as it reached 3319.41, which confirms the increase in the efficiency of the model at (k= 0.016).

With the tremendous progress in organizing data over networks, network security has become more important than ever in modern technologies. Hacking represents a serious security risk in the climate of data transmission and reception. Sometimes there are new types of intrusions that are constantly evolving and detection systems have a difficult problem in identifying them. In this research, we proposed Organization based Abnormality Discovery Framework (OADF) system based on training an algorithm VFDT to detect attacks detection (AD).Exploratory outcomes on the kdd cup'99 data mining list show that our system is profoundly material to arrange interruption acknowledgment. It has been shown that the proposed methodology performs better as far as acknowledgment rate, deceiving issue rate, and computational time contrasted with various techniques. To enhance the success of this work, we used other type of previously prepared test groups, it ssenet-2011 dataset, and we trained these two types separately for the purpose of reaching optimal training. The purpose of this work is to discover the largest number of attacks or penetrations that occur on the internet. Exceptionally very fast decision tree (VFDT) algorithm was utilized to build the classifier for attacks. Exceptionally VFDT algorithm is one of data mining algorithms that arrangement with high data streams in an extremely brief time frame. Trial results exhibited that the proposed Organization based Abnormality Discovery Framework (OADF) system is exceptionally effective in detecting known and obscure assaults by 93%.

India is among the most polluted nations with severe environmental implications of pollution increase in several bas cities. For the past few years’ Indian cities have witnessed an alarming drop in the Air Quality (AQ) which is a result of the rapid economic growth. The lives of billions of people are deeply affected by Air Pollution (AP) every year. The economic sectors that source poor urban AQ include transportation, agriculture, construction, forestry, and logging, emitting dangerous gases and particulates such as NO2, NH3, SO3, and Benzene. This research attempts to implement four different classifiers independently on the AQ dataset. The four classifiers that are being implemented are the Multiclass Decision Jungle (MDJ), Multiclass Logistic Regression (MLR), Multiclass Decision Forest (MDF), and Multiclass Neural Network (MNN). This project objective is to identify the most suitable among the four classification models in building the best model for AQ. The performance of a model is judged by accuracy, precision, and recall. Likewise, about other three modes MDF performs best, where it obtained 99.96% accuracies, 98.91% precision, and 99.76% recall.

Due to removing the mechanical brushes in BLDC motors, BLDC motors are widely used in many industrial applications. Therefore, they are maintenance-free and their control is easy to design, especially for high-speed applications. For example, eco-friendly vacuum cleaners prevent atopic dermatitis, allergic rhinitis, and asthma. Other applications are Micro Gas turbines or compressors with small impellers due to miniaturization, BLDC motors must rotate at very high speeds to maintain the compressor\'s compression ratio. Generally, airfoil bearings should be used instead of ball bearings because of the friction in high-speed motors. Unfortunately, the characteristics of airfoil bearings depend on rotational speed. In this work, a BLDC motor with an airfoil bearing is controlled by a PID controller, this work analyzed the BLDC SYSTEM to determine the PID coefficient using the feedback method. The proposed controller Fuzzy Logic is used for adaptive control. In addition, the controller of BLDC motors combines auto-tuning and self-tuning technology. The results demonstrate that the proposed method gives efficient control by reducing the settling time and maximum peek overshot. The designed controller for the airfoil-bearing BLDC motor has a good performance.

Human activities related to land use, such as the transformation of natural landscapes into urban areas and agricultural fields, as well as changes in land management practices, have caused substantial modifications to the Earth's surface. These alterations have had significant consequences for climate, soil, hydrology, biodiversity, and ecosystem processes. The research presented in this study provides a comprehensive summary of previous investigations in the field of landscape research. The main aim of this paper is to make a comprehensive review about the effect of the construction projects on the sustainable landscape , the results found that the projects effect adversely on the landscape and the free re should be increased.

Video captured during sand-dust weather conditions indicates significant degradation, diminished contrast, and pronounced color distortion. The reason behind this phenomenon is the impact of sand-dust particles, which result in the dispersion and assimilating of light. Consequently, resultant image seems blurred and lacks contrast. Additionally, the alteration in color is attributed to the swift reduction of blue light. Adverse weather circumstances, such as fog, sand, and dust storms, cause problems with vision for deploying self-driving automobiles. To guarantee secure and seamless operations during frequent adverse weather conditions, video enhancement plays a vital role in facilitating vehicular mobility and navigational in both road and air transportation. To improve the safety and efficiency of operation, it is imperative to employ video dehazing techniques, particularly in adverse weather conditions. The purpose of our overview is to offer interested researchers a thorough and methodical examination of image enhancement approaches, serving as an important point of reference for their work. The text explored different image enhancement methods, along with the challenges, constraints, advantages, and drawbacks associated with using these techniques throughout the past five years. Specifically, it focused on three aspects: supervised algorithms, unsupervised algorithms, and quality evaluation.

This paper exhibits an experimental study the effect of numbers of layers of reinforcement on the behavior of shallow footing under machine foundation. A reinforcement was inserted in to the sandy soil of relative density 50% during the raining techniques with 30*30cm at distance (0.5B, B,2B,3B) in a steel container with dimensions (50*50*55) cm. The test was performed under a machine foundation at frequency 10, 15 HZ. This research aims to find the optimal number of layers of reinforcement with geogrid under the square foundation under the machine foundation. For this purpose, laboratory experiments were conducted. The factors that were studied to find the optimal number of layers of reinforcement include the optimal number of layers of reinforcement, as well as displacement amplitude, velocity, acceleration, and settlement. The results showed at frequency 10 HZ, the optimal number of layers was one layer. The percentage of improvement in displacement, velocity, and settlement was (26%,39% and 75%), while acceleration increased when using one layer. At frequency 15 HZ, the optimal number of layers was four layers. The percentage of improvement in displacement, velocity, and settlement was (34%,44% and 66%). We conclude from this research that the type of reinforcement gave good results in reducing displacement amplitude, velocity, and settlement, but does not give good results in reducing acceleration.

A geographic information system is an integrated collection of computer applications and materials that it is employed to assess geographic relationships, model spatial processes, and analyze and arrange geographic data. The gathering, organizing, and analysis of geographic data are made easier with the use of a geographic information system (GIS). Information systems pertaining to geography Thus, it is employed in the gathering, examination, assessment, updating, and presentation of geographic data. This study dealt with Al-Khalis District, one of the five districts of Diyala Governorate. Al-Khalis District is in the western part of Diyala Governorate and the northern part of the capital, Baghdad, about 55 km north of the capital, Baghdad. 227 boreholes were collected for the entire governorate. The soil was classified, its properties were taken, and they were collected in an Excel sheet. After that, this data was entered into geographic information systems to produce clay shear strength maps. A very helpful soil map that can be used in all aspects through structural and engineering simulation is produced when GIS is used in conjunction with physical and strong geotechnical qualities. Building engineering facilities, roadways, and industrial structures may be made easier with the use of a GIS map. Additionally, it offers a strong tool for extrapolating developed regions. GIS soil maps are anticipated to positively influence the next geotechnical work. The results revealed a significant variance in shear resistance across the depths of the Khalis area, with the soil's strength ranging from weak to medium in the first layer and increasing downward with depth. So, we recommend not going for more than three multi-story buildings unless doing site investigation on the site and making sure it is suitable for that or using a pile foundation. This study aims to give geotechnical engineers and designers a first impression of the type of soil and help them quickly make decisions in terms of the type of foundations and the number of floors for multi-story buildings

The process of determining camera settings to deduce geometric attributes from recorded sequences is known as camera calibration. This process is essential in the fields of robotics and computer vision, encompassing both two-dimensional and three-dimensional applications. Traditional calibration methods, however, are time-consuming and require specific expertise. Recent endeavors have demonstrated that learning-based systems can replace the monotonous tasks associated with manual calibrations. Responses have been examined through a range of learning techniques, networks, geometric assumptions, and datasets. A thorough examination of camera calibration systems that rely on learning algorithms is offered in this paper, assessing their advantages and disadvantages. The primary categories of calibration presented are the regular pinhole camera model, distortion camera model, cross-sensor model, and cross-view model. These categories align with current research trends and have diverse applications. As there is no existing standard in this field, a large dataset of calibration has been created, which can be used as a public platform to assess the effectiveness of current methods. This collection consists of both artificially generated and genuine data, including images and videos obtained from various cameras in different locations. The difficulties faced will be analyzed, and alternative avenues for further research will be suggested in the next stage of this project. This survey represents the initial attempt to perform camera calibration using learning-based methods spanning a period of eight years. Our findings indicate that learning-based methods significantly reduce the time and expertise required for calibration while maintaining or improving accuracy compared to traditional methods. Specifically, our research demonstrates a calibration error reduction of up to 20% and speed improvements by a factor of three compared to traditional methods, as well as better adaptability to different camera types and environments.

A composite member is described as a structural steel shape that has been built up or rolled and filled with concrete, covered in reinforced concrete, or structurally attached to a slab of reinforced concrete. The shear connection between the steel beam and the concrete slab is the primary component of the composite beam. In risky situations, like building fires, the performance of a composite structures and steel structures are heavily dependent on the execution of connection. Numerous kinds of shear connectors exist and being utilized in the construction engineering rendering to their use. This paper reviews research conducted in the past years on the performance of shear connectors such as (ASTM A325 bolts, channel shear connector, T, T-mass and T-Proband shear connectors) exposed to raise heat degree. This research covers the experimental testing of push-out specimens, behavior of connectors in steel structures, various shapes of shear connectors under elevated temperatures, main failure modes, finite element modeling of shear connectors, design approaches offered by investigators, and various codes. Compared to the size of work available on shear connectors at room temperature, relatively slight research has been done on the conduct of shear connectors (studs) under high temperature. In addition, this report indicates several topics that need further investigations. Through this article, it was concluded that when temperatures raise, the strength of all shear connectors decreases proportionally regardless of its shape and type. A comparative study showed that the channel connectors are an economic and reliable option to standard shear connectors. Among the findings of some studies is that the effect of temperature on the shear resistance of head stud connector is significantly above 400℃, whether the test is done at temperature or post temperature conditions. Also, adding some materials to the concrete mix such as carbon nanotubes will be not effective on the ultimate shear at temperatures less than 400 ℃, but it reduces the spalling and cracking of the concrete. In general, the influence of elevated temperatures on the ultimate shear capacity of the headed stud connector is noticeably clearer when the test was conducted at exposed to certain temperature compared to post temperature conditions (the test is conducted after exposure the specimen to heat and cooling).

These days, the construction industry is increasingly producing buildings with extremely low damping values. Under structural vibrations caused by storms and earthquakes, structures can collapse easily. There are now several methods for reducing structural vibrations, and one of the methods currently employed is the Tuned Mass Damper (TMD). Research is being conducted to determine its performance and importance. The entire damper was tuned for various constructions. An eight-story model specifically designed for the structure was used in this study to observe the structure's response with and without TMD during shaking table experiments. Compared to passive control devices (PTMDs), Active Tuned Mass Dampers (ATMDs) are more efficient as they are active control devices powered externally. By maintaining the structure's frequency, damping, and stiffness constant, other variables such as the percentage reduction in structural capacity can effectively control structure vibrations. The findings and observations from TMD studies can be used to address challenges in earthquake structural control considering current technological limitations and energy demands. The results illustrate significant improvements with damping: the damped structure experienced a 21% increase in acceleration, a 17% increase in velocity, and a 79% reduction in displacement compared to the un damped structure. These findings underscore the effectiveness of damping in mitigating earthquake-induced vibrations.

In fact, pile usually carry static and dynamic load in same time, the case of simulations lateral and dynamic load is possible occurred. This case is not cover enough by previous researches especially by laboratory model. Therefore, the purpose of this study is to determine the extent to which altering the horizontal lateral loads impacts the behavior of individual piles during seismic events. An experimental test was devised using a physical model with an advanced shaking table that using El Centro earthquake. Sandy soil with 65% relative density used raining technique. Lateral loads were applied at levels of 0%, 50% and 100% from allowable lateral load capacity. It was observed that when lateral load increased from 0% to 50% and 100%, the lateral displacement response decreased by 32.10% and 49.59% respectively. While the vertical displacement increased by 49.96% and 76.95%. Finally, the acceleration decreased by 34.39% and 41.03%. This is possibly due to the load acts at an angle opposite to the earthquake as a restraining factor for the pile. led to a decrease in lateral displacement, vertical displacement, and peak ground acceleration.