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In this paper, a new efficient cryptographic system will be designed based on constructing a hybrid cryptosystem which is consisting of stream and block cryptosystems in order to increase the security of the images. Many tests are made to check the efficiency of the proposed cryptosystem, like, General Complexity (Key Space), Key Sensitivity, Mean Squared Error, Correlation Tests, ... etc. were applied. The performance and the security of the new hybrid cryptography system was high which proved by the results of the applied tests. [ABSTRACT FROM AUTHOR]

The purpose of this study is to find the resourceful links to use as monitoring resources (detectors/sensors) to collect traffic data in order to estimate an accurate Network Fundamental Diagram (NFD). The NFD which depicts the relationship between average flow and average occupancy is an established tool utilized for observing and reducing traffic congestion in major cities. The ultimate goal is to critically select resourceful link(sensors) using a systematic technique assisted by principal component analysis (PCA). This allows the construction of reduced NFDs with less number of sensors while retaining the most informative link(sensors). The performance of the proposed method is tested and compared with four other link selection methods, evaluated with real loop-detector data from an urban network. The suggested method enables the selection of the appropriate sensor for traffic monitoring by correlating the primary component to the relevant resourceful variable (link). The evaluation results indicate good estimation accuracy and effective. These findings highlight the effectiveness of the suggested PCA-based method in identifying an ideal sensor placement on networks. It is expected that the proposed strategy will play a significant role in achieving smart yet economical sensor installation whilst improving the estimation of NFD. [ABSTRACT FROM AUTHOR]

Continuous advancements in medical diagnostics and therapies drive progress within the field. Individuals recovering from upper limb injuries due to stroke benefit from rehabilitation exercises to restore function and regain daily activities. Addressing this need, there's an urgent demand for a cooperative robot-assisted prototype tailored for upper limb rehabilitation, capable of devising safe training programs. This study delved into Electromyography (EMG) signal patterns of the right deltoids in nine healthy subjects. Tasks included horizontal abductions, adductions, elbow flexions, and extensions, each performed for 30 seconds, both freely and with robotic assistance. Results revealed EMG signals during robotic assistance closely resembled those without, suggesting the effectiveness of these movement sequences in stroke rehabilitation. Further refinement through patient trials promises even more precise outcomes. [ABSTRACT FROM AUTHOR]

Microgrid (MG), which combines renewable energy sources, energy storage devices, and loads, has lately gained attention as a sustainable energy alternative for mitigating climate change. MG may operate in grid-connected or islanded modes based on upstream grid circumstances. The energy management and control of the MG are important to increase the power quality of the MG. This study provides a MG system consisting of a 60 kWp Si-mono photovoltaic (PV) system made of 160 modules, and a Li-ion battery energy storage system (BESS). Moreover, each unit was linked to the DC bus throughout the DC/DC converters and DC/AC central inverter. The suggested system control relied on harnessing renewable energy to provide loads effectively and monitor battery charge. Simulation findings using MATLAB Simulink show the performance of the suggested microgrid stability solutions. The PV system was controlled by maximum power point tracking-based fuzzy logic (FL-P&O). In addition, the BESS with its battery management system (BMS) using the PI controller was used to stabilize the bus voltage within reference value at variations of irradiance. The MG was connected to the DC side by a voltage source converter (VSC) which is controlled by the hysteresis current control technique. Finally, the DC bus voltage was kept constant at 700 V to preserve the microgrid's balance under different environmental conditions with a minimum value of THD 3.7% in the injection current. [ABSTRACT FROM AUTHOR]

The essential radiant heating system component is a water heater so this study presents an experimental and numerical work of a water heater with an AC heating element powered by photovoltaic panels. The experimental work included a study of the thermal performance of a water tank under a constant ambient temperature and different supplied water temperatures. The impact of ambient temperatures of (290,292, and 294) K on the tank water temperature distribution under a constant supplied water temperature of 280K had been studied. Also, the stratification of water temperature is analyzed with the height of the tank. Numerical work studied the tank water temperature distribution with time for different supplied water temperatures of (280,285 and,290) K. Experimental work results have been utilized for developing and validating the numerical work results The comparison between experimental and numerical results appears good matching and the error does not exceed 3%. [ABSTRACT FROM AUTHOR]

In the wipe bending process, after the bending load or pressure is removed, the elastic strains remaining in the bend region cause a slight reduction in the bend angle. The term "spring back" refers to this reduction in bend angle, and it depends on many parameters like tool design, process conditions, and material parameters. In this work, simulations by Deform 2D software and experimental work were conducted to determine the effect of die radius, sheet thickness, and Silicone rubber pad thickness on spring back angle while bending Titanium Grade2 sheets. The results showed that die radius is the most important factor affecting the spring back angle in the wipe bending process. When the die radius increases, the spring back angle is also increased by (36%) and the second factor, when Silicon rubber pad thickness increases to (15) mm, decreases the spring back angle by (20.6%). The third factor is the Titanium thickness. When it increases (1) mm, the spring back is decreased by (12.4%). Also, surface roughness was improved when adding a Silicon Rubber pad in the range of (58.5% and 61%) for sheet thicknesses of 0.5 and 1mm, respectively. The results validate the same behavior for Titanium in a numerical and experimental model. [ABSTRACT FROM AUTHOR]

The purpose of this research is to investigate experimentally the effects of extrusion speed on the die strength and product properties. Three factors related to the die strength are studied, indicated as extrusion load, temperature, and wear rate. A direct cold extrusion process is employed to transfer the circular section bar into a square section with an extrusion ratio of 1.67 using two types of materials; Lead and Aluminum. Three speeds (10, 50, and 150 mm/min) are implemented in the extrusion process. Results show that for the low extrusion speed, the load increased at the beginning with time, then went settled till it became constant during the extrusion process for both two materials. The extrusion load increases significantly by increasing the extrusion speed. The increase in the extrusion speed leads to a change in the behavior of the load–time curve. The temperature and wear rate increased with increasing the extrusion speed depending on the type of billet material. Moreover, the product hardness increases with increasing the speed for all materials. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the effect of additives and forward extrusion die profiles on the improvement of mechanical properties of foam aluminum alloy. The sintering and dissolution method was used to produce the foam aluminum alloy, which contains 30% NaCl only, and another alloy with the additive of 1.5% (Mg+Sn). Two forward extrusion dies were designed and manufactured according to concepts of cosine and Bezier curve with a reduced area of 55% and die length of 20 mm. The results show that the additives improved the compressive stress and hardness of the alloy by 10.6% and 10.5%, while these ratios increased to 30.3% and 41.1%, respectively, after extrusion with the Bezier curve profile of the die. Also, the additives improved the energy absorption during the compression test of the alloy by 35%. [ABSTRACT FROM AUTHOR]

In this study, the influence of pulses on the durability of weldments produced by resistance spot welding was investigated. Four variables were used: welding current (9000 - 10500 - 12000) Ampere, squeezing time (1.2 - 1.6 - 1.8 seconds), welding time (0.6 - 0.8 - 1) seconds, and pulses (1 - 2 - 3 pulses). Additionally, 25 * 100 mm by 1 mm thick strips of aluminum metal (AA1050-O) were employed, and nine welding settings were set up in accordance with the previous factors. The durability of the welds that were welded in the overlapping position was examined using the shear tensile test. It was discovered that the weldment that was welded using a welding current of 9000 A with a squeezed time of 1.6 seconds, welding time of 0.8 seconds, and two pulses produced the best shear force. [ABSTRACT FROM AUTHOR]

Cases of breast cancer are on the rise. In accordance with the American Cancer Society, 297, 790 women and 2, 800 men in the United States will be diagnosed with invasive breast cancer in 2023. However, mortality in breast cancer can be reduced through early detection. This can be accomplished by developing a dependable algorithm capable of detecting breast cancer in near-real time. As in the previous studies it is evident that the Inception V3 deep learning model performs well for the image classification tasks therefore this study implements Inception V3 model to detect breast cancer. In this research, the classifier was trained on 1200 images that were split into two categories; these were patients without breast cancer and patients having breast cancer. To determine the effectiveness of this algorithm, it was compared with VGG 16 model. The VGG 16 model is an additional deep learning model that has been demonstrated to be effective for image classification tasks. On the purpose of breast cancer detection, the Inception V3 model outperformed the VGG 16 model, achieving an accuracy of 99% compared to 53% for the VGG 16 model. The algorithm gained this accuracy after 23 epochs, which was recommended number according to (records), as opposed to the standard learning rate of 0.001. The Inception V3 model is a promising approach for the early diagnosis of breast cancer, based on these results. To validate the classifier on a larger dataset and evaluate its clinical utility, additional research is recommended. [ABSTRACT FROM AUTHOR]

In order to enhance the efficiency of the photovoltaic module, a sun concentration and cooling technique is being used in this research. Standard polycrystalline photovoltaic module, photovoltaic module with active cooling system as well as concentrated photovoltaic (C-PV module) and a cooling C-PV system were used in the experiments. On the 5th and 6th of November, the experiments were carried out in Baghdad, Iraq. The photovoltaic panel's frontal water flow serves as the cooling system using evaporative cooling. When compared to a standard PV module, the average power output and maximum power output from the C-PV system is increased by 23.6% and 28.3%. Furthermore, the C-PV system and the C-PV system with cooling technique have an average increase in electrical efficiency of 7 percent and 9 percent, respectively. In comparison to the other three configurations, the C-PV with the cooling system produced significantly more energy. [ABSTRACT FROM AUTHOR]

This paper discusses the comparison between the treatment process using the conventional wire-EDM and the unconventional CNC milling machine in terms of surface finish and dimensional accuracy of the product. The design process was simulated using SolidWorks software for two mechanical parts (Cam and Spinner). These are considered important parts in manufacturing, used to convert rotational motion into linear motion, which depends on the high-quality surface and dimensional accuracy and finishing. Scientific parameters of WEDM were improved through initialization experiments and analysis by surface finish ratio and dimensional accuracy. These parameters for both machines were adopted on experimental work carried out during this research to choose the best inputs for this process to obtain high surface quality. Selected two samples were tested for surface quality and dimensional accuracy, which were used as criteria to evaluate the process. The results show that the surface finish of the products processed by the CNC milling machine is better than the product on WEDM. A WEDM is more accurate than a CNC milling machine in terms of dimensional accuracy. [ABSTRACT FROM AUTHOR]

The nonlinear system of a photovoltaic (PV) module was studied in this article. For PV panel temperature prediction, three types of Artificial Neural Network (ANN) time series are used: Nonlinear Autoregressive with External Input (NARX), Nonlinear Autoregressive (NAR), and Nonlinear Input-Output modeling. The model's input data parameters were (ambient temperature, humidity, wind speed, and irradiance), while the model's output data parameter was the temperature of the photovoltaic panel. All modeling techniques are evaluated using Mean Square Error (MSE), and their results are compared to determine which technique is the best. The results indicated that the MSE for the NARX method was 0.1196, while the MSE for the NAR and nonlinear input-output methods were 0.1385 and 0.2806, respectively. [ABSTRACT FROM AUTHOR]

Building Information Modelling (BIM) is a process established to enhance the construction project efficiency. It has been used in Malaysia and globally especially in the construction sectors. There has been a gradual acceptance of Malaysia construction industry stakeholders especially in the Peninsular in the uptake of BIM implementation. However, in Sarawak itself, this point turns out to be much more burdensome as the development projects in the state turns out to be more branched out and complex. Research shows on BIM uptake in Sarawak and Sabah lagging at a low 6% as compared to Peninsular of 78% in the central region only. Thus, this research objectives are to investigate the challenges faced by industry stakeholders in implementing BIM and also to explore on the drivers that increases the usage of BIM Sarawak construction industry. The virtual semi-structured interview sessions target the policy makers such as Public Works Department (JKR) and contractors from G6 to G7 in Kuching, Sarawak. The data obtained will be analysed using a qualitative content analysis technique supported by matrix table method. The challenges to BIM implementation are lack of readiness in BIM implementation, lack of manpower and special equipment's for BIM and lastly, BIM training, courses and software are costly. The driving factors of the BIM implementations are to improve organizations collaboration, to boost and enhance company capability in technology and mandatory rule imposed by the government to implement BIM. This research is significant to spearhead initiatives by tackling the challenges and generate better driving factors for BIM implementations especially in Sarawak construction industry. [ABSTRACT FROM AUTHOR]

Among the blessings of God (Glory be to Him) upon humans is that people see the details of things in their surroundings in different colors. Unfortunately, some people have problems with correct vision, and the most important and common problem in this regard is "Color Blindness". It is a disease that makes people unable to distinguish some colors, that is, seeing colors is not enough. So, the contribution to solving the problem of Color Blindness is important, because the hassle of Color Blindness leads to the non-discrimination of information seen via the infected person. Data visualization is one of the proposals that contributed to fixing the trouble of colour blindness. In this paper, we are going to explain the nature of this disease and its types, then we proposed a new approach by using data visualization technique and principal component analysis (PCA) that might contribute to easy data recognition and color blindness problem-solving. We are based on the famous "ISHIHARA" data set, which is used to measure Color Blindness. The efficiency of the results used to be mathematically tested the usage of equations and images by means of a website to simulate colour blindness, it is correct and information is clear and understandable for patient color-blindness. [ABSTRACT FROM AUTHOR]

The process of overheating in the engine system, particularly in the #10-cylinder shank section, is the only factor considered in the investigation of this damage or failure. As a piece of scientific literature, the goal of this study is to ascertain the primary reason for the connecting rod's failure. Analyzing the results of the thermal simulation produced by the finite element approach is the way for identifying the primary source of the damage. The finite element approach was used to do a thermal simulation of radiation heat transfer in steady-state circumstances based on the findings of the analysis (FEM). According to the average temperature coming out of the exhaust valve, the temperature in the cylinder liner is 442°C, and the heat in the piston rod is 90°C, which is in line with the typical operating temperature of the 3516 B Series diesel engine. According to a finite element simulation, the discoloration in the piston rod is mostly caused by radiation, namely the transmission of heat from the liner wall to the piston rod as a result of the combustion gases being trapped in cylinder #10. The connecting rod parts that changed color are still usable according to the finite element approach and the feasibility test. [ABSTRACT FROM AUTHOR]

Facial palsy (FP) is an inflammation or disorder of the seventh nerve that leads to sagging of the facial muscles on the affected side and loss of control over movements and expressions. All ages and genders are susceptible to this disease. The medical diagnosis of this disease is prone to errors because it is based on the doctor's visual observation. Deep learning based technologies are the perfect solution for real-time FP detection. This study used a set of pre-trained deep learning based models including ResNet, AlexNet, DenseNet, GoogleNet and VGG16, to detect in real time FP, age and gender using a Raspberry Pi equipped with a digital camera. The accuracy obtained in the proposed system reaches 98% by using a wide variety of data consisting of 20,600 images, which includes 19,000 normal images and 1,600 images of persons with FP with different side of the injury. Thus, the proposed detection system can be considered as an effective and high accurate diagnostic system for FP, age and gender detection. [ABSTRACT FROM AUTHOR]

Dysphagia is regarded as one of the most typical adverse effects of head and neck cancer or as a result of cancer therapy. The majority of HNC patients have trouble swallowing, particularly those receiving radiation or chemotherapy. Additionally, 38% to 46% of individuals with HNC may have long-term dysphagia. The purpose of the current study is to ascertain the prevalence of dysphagia in patients diagnosed with HNC. A descriptive, cross-sectional design was used to accomplish the goals of the current study, a non-probability (heterogeneous-purposeful sampling) method is used to pick 91 patients with head and neck cancer. Three components make up the study tool: demographic and clinical information on the participants; the Gugging Swallowing Screen (GUSS), which measures difficulties swallowing for patients with HNC. According to the study's findings, dysphagia affects 84.7% of patients, and there is a substantial correlation among dysphagia and the patient's clinical and demographic information. The current study came to the conclusion that (HNC) can result in dysphagia, which can be impacted by the location, prognosis, and therapy of the malignancy. [ABSTRACT FROM AUTHOR]

The glycoprotein Osteopontin (OSP) has been detected in various cell types in both human and animal organisms, including skeletal, immune, smooth muscle, epithelial, and endothelial cells. Moreover, Osteopontin has been acknowledged in the renal system, particularly in the dense ascending limbs of the Henle loop and distal nephrons, as well as in urine. Protein plays a crucial role in both bone mineralization and bone resorption processes. Osteopontin also plays a role in regulating processes outside of its primary function, including immunity and inflammation, angiogenesis, and apoptosis. Plasma Osteopontin levels were correlated with Diabetic Nephropathy Progression in this study. Ninety patients with type 2 diabetic nephropathy served as the study's sample, and a control group of thirty people served as a comparison. Participants were sought out and enrolled in the study from the Iraqi cities of Baghdad and Maysan. Participants' urine was collected for analysis of protein concentration in the urine. Serum creatinine (s-Cr), fasting plasma glucose (FPG), glycated haemoglobin A1c (Hba1c), and serum osteopontin were also measured from the collected blood and serum samples. Stage 2 (microalbuminuric) patients had significantly lower Osteopontin levels compared to controls (P<0.001), and stage 3 (macroalbuminuric) patients had significantly higher Osteopontin levels compared to controls (P<0.001). Moreover, there was a statistically significant difference in Osteopontin levels between those with stages 2 and 3 of diabetic nephropathy (p=0.032). These results show that the levels of Osteopontin in the blood rose steadily throughout the progression of diabetic kidney disease, reaching a peak in the macroalbuminuric group. An increase in plasma Osteopontin levels was associated with the development of diabetic nephropathy, according to the study results, it seems likely that measuring Osteopontin plasma concentration can be a useful diagnostic biomarker for estimating the severity of diabetic nephropathy and its long-term prognosis. [ABSTRACT FROM AUTHOR]

In this work, frictional servo actuator systems are discussed, along with the application of an adaptive sliding mode control in such systems. There are a number of benefits to using adaptive sliding mode control rather than the more common sliding mode approach: primarily, the control effort is scaled back to an acceptable amount determined by the constraints on the sliding mode, though it also makes it unnecessary to know beforehand how high the limits of uncertainty are. The adaptive sliding mode control technique thus works well; however, to verify the efficacy of the proposed robust adaptive sliding mode control strategy, a numerical simulation was conducted in MATLAB for a servo actuator system with friction. When the results were compared to the results produced using traditional sliding mode control, it was clear that the control efforts were lowered and the chattering intensity was attenuated, while the major positive features of the traditional sliding mode control were retained. [ABSTRACT FROM AUTHOR]

Some children have problems concentrating and difficulty in using their hands for basic daily activities due to a condition known as ataxia, which has many causes. The impact of this thus varies from case to case. The idea underlying the current work is to design and manufacture a technological device inspired by traditional occupational therapy that can function in a toy-like manner while allowing users to improve their hand-eye coordination and focus, thus enabling affected children to be able to take better care of themselves and become more active members of society in time. The proposed device consists of a small lap desk, an electronic unit, thirteen LED buttons in four different colours, and a glove with five LEDs on each fingertip. The LED lights on the lap desk are turned on randomly, and the matching LED on one of the fingertips should then be turned on by the user. This product trains the brain, seeking to improve hand-eye coordination by repeated selection and activation of the appropriate button on the lap desk to match the colour on the glove, and pressing the button. A software program was therefore designed to create random runs of colour groups to ensure the brain is trained to respond quickly rather than memorising colour sequences. The device has shown effective initial results in terms of accelerating the learning and rehabilitation process, and, due to the current lack of technology use in occupational therapy in the treatment of ataxia, the response speed of standard sessions is relatively slow. The utility of the proposed device lies in its ability to develop and accelerate cognitive assistance to help mitigate the impact of this condition, leading those with ataxia to a stage where they can become self-reliant in less time than traditional methods of occupational therapy. [ABSTRACT FROM AUTHOR]

In this article, A new method to achieve the exact solution of a special type of linear partial differential equations (LPDEs) will be introduce which involving mixed partial derivatives. This method is called the Laplace substitution method (LSM), This method is used to solve Poisson equation and the results are compared with other methods. Three examples are presented to explain the simplicity and reliability of this method. [ABSTRACT FROM AUTHOR]

Research activities are becoming increasingly challenging for educators in Higher Education Institutions (HEIs). Obtaining a research grant is increasingly competitive. Proposal constructions need to be robust and researchable. One of the significant criteria in a research proposal is budget allocation. This study highlights the importance and usefulness of a dynamic budget template known as KKPLive Budget in assisting researchers in preparing a dynamic budget. A mixed-method approach was used to evaluate the usability, practicality, and stability of the KKPLive Budget. While quantitative research was used to examine evaluators' assessments of the KKPLive Budget, qualitative research was used to gauge evaluators' views about the KKPLive Budget. Data were collected from 12 second-year university students enrolled in the Bachelor of Accounting (Information Systems) programme who served as evaluators. The findings suggest that the KKPLive Budget is highly reliable in usability, practicality, and stability. [ABSTRACT FROM AUTHOR]

Nowadays, the IoT (Internet of Things) plays a crucial role in many requirements of daily life, where healthcare, safety, security, and energy management are considered some of the most significant applications that rely on IoT in their operation. One of these requirements is to perform a smart home that can be controlled by a smartphone, to operate and switch off the electrical or electronic devices and sensors. This can be executed depending on the IoT capabilities to simulate and operate a smart home. This paper focused on practical home automation that involves several devices like a webcam, humidifier, ceiling fan, air conditioner, etc. By using some sensors and devices, the designed smart home is controlled and monitored. The findings revealed that smart devices and sensors can be easily added to the home gateway; additionally, this system will make real-life easier and more comfortable. [ABSTRACT FROM AUTHOR]

Lately, tremendous industrial wastes such as glass waste, clay-ceramic waste, fly ash, sludge and metallurgical steel slag, particularly electric arc furnace (EAF) slag have been progressively recycled as partial replacement of raw materials in sustainable clay-based ceramics such as brick, ceramic tile and roofing tile. Among these waste, metallurgical steel slag could be an excellent sustainable choice due to its similar chemical composition as raw materials for the ceramics. From literature surveys, the first attempt of recycling the slag into ceramics was proposed by Badiee [1] and they have successfully utilized the slag generated by one of the steel making plants in Iran. This idea was further succeeded by Sarkar [2] by reusing the slag waste generated in India. To the best of author's knowledge, this current research work [3,4] is the third attempt and the research is focussing on utilization of Malaysia's metallurgical steel slag into clay-based ceramics, i.e. ceramic tile. Therefore, this article will be briefly reviewing the previous and current progresses as well as achievements on efforts of recycling the worldwide metallurgical steel slag as partial replacement of raw materials in sustainable clay-based ceramics. The brief review will focus on body formulation, firing temperature, properties of the ceramics, as well as sintering mechanism involved during the firing process. [ABSTRACT FROM AUTHOR]

The process of the power conversion increases harmonics and losses and reduces the stability of the power. New technology of multilevel inverter can be used to overcome disadvantages of traditional inverters. Multilevel inverter technologies have recently gained popularity as a cost-effective alternative for a variety of industrial applications. This topology has a few noteworthy properties, including lower component, lower switching losses, and better output voltage/current waveform. The reduction of harmonic components in the inverter output voltage/current is the most important requirement in multilevel inverters. The system suggested in this study is made up of four separate renewable energy sources. Three PV solar systems with voltages of (1:3:4)E values and wind-turbine of 2E value are recommended. The total dc sources were combined are (1:2:3:4)E to produce a 21-level output voltage. Also the system is designed to produce 17-level in the case of absence wind. The system is designed using MATLAB program. [ABSTRACT FROM AUTHOR]

There is an urgent need to preserve the environment in sustainable ways and to pay attention to the quality of life that leads to preserving the quality of human life because it represents a kind of natural wealth that is important for the continuation of life in any city. Sustainable infrastructure services are among the most important services that help provide a healthy and safe environment and enhance Economic and social development and increase happiness in the city. Therefore, it is an important need for the development of urban areas, and it is an important element for developing cities and achieving their urban sustainability. This research deals with the issue of sustainable infrastructure services in cities and deals with sustainable transportation as one of the most important infrastructure elements that are directly linked to the sustainability and prosperity of cities. Transport affects many aspects of daily life and the quality of life for mobile communities. Hence, the importance of sustainable transportation and its impact on the quality of life emerges. Therefore, the research aims to demonstrate the importance of sustainable transportation services in providing effective, safe, and healthy means of transportation for individuals and goods, while achieving sustainability in economic activity and its integration with the natural environment. This research took the interview approach as a method of application and measurement of the elected sample. As for the approach followed, it is a qualitative exploratory approach, where the research problem is represented in the research on how to apply sustainable services represented by sustainable transport in cities, where the research concluded that sustainable transport services are one of the most important services for the growth of any city and upgrading it to be of high quality and its environmental and economic prosperity. [ABSTRACT FROM AUTHOR]

The study aimed to demonstrate the role of the chartered accountant in studying the laws relating to the phenomenon of money laundering and its application in Iraqi government banks, which is reflected in financial sustainability. With a review of the Iraqi laws enacted to combat money laundering and the mechanism for their application through the existence of sound and good accounting and control systems, especially after the expansion of this phenomenon globally in the context of globalization, the escalation of the information revolution, telecommunications technology, the lack of transparency in commercial transactions and the weakness of laws and regulations established by the State to reduce them. The research proceeded from a problem of knowing the role of the chartered accountant in studying the laws relating to the phenomenon of money laundering and the extent of their application in Iraqi government banks to achieve financial sustainability in (Rafidain Bank Right Side 217) Sample Search, Based Search to Basic Hypothesis, The chartered accountant has a role in studying the laws on the phenomenon of money laundering and its application in Iraqi banks to achieve financial sustainability. The research has reached a number of conclusions, the most important of which are, although many regulators are involved in the fight against money laundering, the accountant and the legal auditor have a role to play in studying laws and legislation relating to the fight against money laundering, because in the list of those who discover the anomalies in the movement of money and that is the nature of their profession and their good qualification to achieve financial sustainability in banks. There are no legislation and laws that preserve the rights of banks that report suspicious money-laundering that relates to the confidentiality of data and information they send to those entities even if the data are preserved, because the suspicion of money-laundering is not established. The research recommended the need to seek a mechanism binding on all banks and financial institutions. by establishing specialized anti-money laundering teams, following up on the sale and purchase of securities and introducing employees into banking institutions in international courses to identify modern methods used by perpetrators when committing money-laundering, as well as to develop banking secrecy laws, To establish an effective and robust oversight mechanism to monitor banking companies deployed in Iraq for the purpose of regulating their operations and removing them from money-laundering operations. Monitoring the movement of liquidity and researchers used a tool for this study a questionnaire form (questionnaire) designed on the basis of a quinquennial Licert scale and analyzed by the statistical program (SPSS). [ABSTRACT FROM AUTHOR]

The objectives of this study are to inspect structural member of bridge to identify any damage in these members, to analyze the internal forces in designed and service stage by adopting static analysis, to determine bending moment, vertical shear force, axial force, tensile stress, compression stress, and vertical deflection under effect of dead load, prestressed load, moving load, temperature load, and combination of these loads, to evaluate the structural performance of bridge structure. Bata bridge was selected as case study in this study which was located in Babylon province near center of Hilla city. Ver. 24 is used in the analysis of bridge structure model for static. The inspection process of structural damages for bridge structure show that there are many damages in the old bridge especially in the concrete deck, expansion joints, and abutments structure. The results of analysis showed that the span No. 1 of bridge structure suffers from higher values of positive bending moment, tensile stress, and downward vertical deflection than others spans, and lower values of compression stress and negative bending moment. After improvement of prestressed tendons, the values of vertical deflection of bridge structure were decreased by more than 50% according to values before improvement. In general, the structural performance of old bridge structure need to improve by using some methods of repairing and strengthening to decrease the tensile stress and downward vertical deflection. External prestressing tendons is suitable method in the state of old bridge. [ABSTRACT FROM AUTHOR]

Managing IoT networks is complicated due to the increasing number of devices in the network. Furthermore, several challenges are raised regarding communication, traffic patterns, and characteristics. The network scalability should be evaluated by modelling the behaviour of IoT devices, particularly traffic patterns. However, as IoT is relatively new, it is challenging to model thoroughly. Many models are proposed, but no standard modelling paradigm is available for real-world complex IoT-based scenarios addressing all the requirements. This research provides an overview of network analysis and modelling, focusing on the central issues to introduce specific knowledge that helps to understand the traffic and guide the new research directions in network traffic modelling and analysis. [ABSTRACT FROM AUTHOR]

This study identified the genetic polymorphisms of seven plant isolates (S2 to S8) and assessed their ribosomal sequence phylogenetic distribution. This study amplified one genetic locus covering part of the internal transcribed spacers (ITS1–ITS2) rRNA sequences. The amplified genetic locus PCR amplicons were sequenced directly. A comprehensive phylogenetic tree was then constructed in the observed variants for these plant sequences to show accurate phylogenetic distances and other relative sequences. Our sequencing reactions identified seven plant species: Silybum marianum, Raphanus raphanistrum, Melilotus indicus, Lolium rigidium, Lolium temulentum, Phragmites australis, and Avena fatua. G302A was the only ribosomal variation found in Lolium rigidum. The current comprehensive tree placed the investigated samples in seven phylogenetic clades. The phylogenetic tree showed that this ribosomal variation was minor within the identified clade, which included our S5 sample. Ribosomal sequences showed that Lolium rigidum and Lolium temulentum had close phylogenetic distances and high homology. Phragmites australis had the most diverse phylogenetic distribution of all samples. In the current tree, Silybum marianum, Raphanus raphanistrum, Melilotus indicus, Phragmites australis, and Avena fatua had diverse phylogenetic clades. In conclusion, the current tree served as an all-inclusive tool that ensured the correct identification of the tested samples of the researched plant. Therefore, the use of the PCR-sequencing approach in the samples that were analysed has produced evidence that corroborated the samples' identities and shown the pattern of their phylogenetic distribution. This kind of diversity that was seen for these plant species may imply that it is possible to use the existing ITS1-ITS2 rRNA sequences in the precise identification and discrimination of a broad range of additional plant sequences. [ABSTRACT FROM AUTHOR]

The study deals with factors that affect the making of the architectural decision and the great impact it has on the process of architectural design. it has shed the light on a group of academic scientific studies, which was represent through the proposed problem of the study that is (the lack of clarity of the concept of effecting factors on the making of the architectural design on the process of architectural design). The study aims at (reveling the affecting factors on the making of the architectural decision and providing a thinking methodology that better reflects the architectural field). The study then moved to creating a theoretical framework of the concept and developing a survey that analyzed a group of samples from local and international projects, it contained a number of questions that were aimed at architects. finally, the study discussed the results and proposed the conclusions. [ABSTRACT FROM AUTHOR]

After different consecutive waves, the pandemic phase of COVID-19, which started in Wuhan, China, seems to have no imminent end worldwide transmission of the SARS coronavirus has prompted the World Health Organization to proclaim a worldwide pandemic (known as COVID-19). Its effects on regular life and health have been devastating. In order to stop the spread of the disease and provide immediate care for infected patients, Rapid identification of positive cases is essential. The demand for diagnostic aids has grown. Recent advances in medical imaging show that these pictures reveal important information about the COVID-19 virus. The current shortage of specialists can be alleviated in part through the use of cutting-edge user artificial intelligence technologies and medical imagery in making correct diagnoses of this condition. The small size of the virus cells makes it difficult to distinguish them visually with the naked eye. Therefore, the transmission electron microscope with different magnifications was used to detect and image the virus cells. In recent years, medical diagnoses have significantly benefited from the widespread use of machine learning-based image processing technologies and have proven to be an effective method for helping diagnostic professionals to identify subtle lesions in images accurately. This work presents a customized computer-assisted automatic detection system specifically focused on quantifying and counting viral cells detected in blood samples from patients using electron microscopy images to detect infected blood cells. The average accuracy of the proposed custom model is 86.5% mAP, which makes it suitable for the upcoming COVID-19 surveillance system. [ABSTRACT FROM AUTHOR]

The importance of biomaterials is increased steadily with the augmentation of population and aging. In this paper, guailfensin used as an inhibitor for corrosion of stainless steel 316L in simulated body fluid by electrochemical polarization technique. The results showed that guailfensin reduce the corrosion current density and serve as an anodic inhibitor type. The inhibition efficiency is increased by increasing the concentration of guaifensin. The maximum inhibition efficiency of guaifensin has been obtained at 0.01 ppm, and the alloy examined by atomic force microscope. [ABSTRACT FROM AUTHOR]

Silver nanoparticle (AgNPs) extract was recently explored in many studies and it was used in the manufacture of many medical and non-medical industries. Regarding medical uses, it was used as an anti-fungal and anti-bacterial, and hence, we attempted in this study to investigate anti-cancer activity in vitro. The cytotoxic effect of AgNPs Conocarpous erectus leaves aqueous extract was tested against breast cancer cell lines MDA-MB231, MCF7, and REF (normal cell line) by MTT assay after co-culture with escalating doses of extract for 48 hours. Viability results indicated sensitivity in breast cancer cells and MDA-MB231 (GI50 =79 µg/ml) was more sensitive than MCF7. In addition, REF cells was resistant (GI50>100 µg/ml). In conclusion, AgNPs extract showed sensitivity in breast cancer cells and no cytotoxic effect was observed in normal cells [ABSTRACT FROM AUTHOR]

This paper provides an overview of current cybersecurity solutions for industrial control systems (ICS) that rely on machine learning. Especially in the field of anomaly detection in the Distribution Network Protocol (DNP3). Attacks on power grid systems are a common target for cybercriminals. The energy equivalent of an entire country can be saved through these systems. Therefore, it is necessary to protect these facilities from any security breaches, as they are vital for people. For this, the paper outlines a proposal for an intrusion detection system. It introduces a classification system that uses different machine learning methods to find the most effective model for detecting flaws related to this network protocol. standard IDS datasets for (DNP3) was used to create each model (7326 observations) containing nine network attack scenarios. In terms of performance, the Random Forest algorithm outperformed the competition, SVM and KNN. Thus, it is possible to obtain a predictive accuracy of about 99%. A categorization system is thus the result of the employed method. [ABSTRACT FROM AUTHOR]

The spread of multimedia material, such as text, images, audio, and videos, has revolutionized the way we generate, exchange, and use data in the modern digital age. However; the surge in multimedia has also led to an increase in worries about protected distribution, data security, copyright safety, and validity of information. In contrast, Blockchain, which was first created as the foundational technology for cryptocurrencies offers a not centralized, tamper-resistant ledger, which makes it a perfect choice for improving multimedia content security and efficiency. Every piece of content that is stored on blockchain creates an unchangeable, stable record that reduces the risks associated with unauthorized access, data handling, and content theft. This article reviews the relationship between blockchain technology and multimedia content and explains how this combination improves security, transparency, and trustworthiness in the digital media space. By contrasting numerous publications on multimedia that employ the blockchain technology and discuss its benefits and drawbacks for each one. The result show that most of the proposed technique used the permissioned (private) blockchain more than public and hybrid blockchain, furthermore; Most of these approaches use digital fingerprinting to provide copyright multimedia content protection, finally, Hyperledger fabric platform mostly used more than other blockchain platforms. [ABSTRACT FROM AUTHOR]

The pervasive integration of technology into our daily lives is a commonplace occurrence, extending its influence to operators of industrial systems who are increasingly harnessing the potential of new technologies. Adapting the use of cyber-physical systems (CPS) beyond their original scope is often necessary to support evolving applications. However, this heightened interconnectivity and exposure to the Internet make these systems more vulnerable to attacks, given the expanded attack surface. Timely detection of security issues in Cyber-Physical Systems (CPS) is critical due to their integration with the real environment, as delayed detection could lead to significant harm. Anomaly and intrusion detection play a pivotal role in identifying potential threats, serving as a prerequisite for initiating a prompt incident response. To address the industrial sector's specific needs, we illustrate the process of transferring and adapting existing detection systems. However, the restricted availability of data in industrial applications can pose challenges to the utilization of current detection systems, despite their indispensable nature. Consequently, we delve into valuable data exploration and introduce two Cyber-Physical Systems (CPS)-specific approaches to obtain essential information for existing intrusion detection algorithms. To optimize the efficient gathering of real-world data, we suggest employing a streamlined and effective compression technique tailored specifically for industrial network data. Recognizing the constraints of direct capture in specific scenarios, we illustrate the generation of suitable datasets through the simulation of underlying processes. In the domain of anomaly detection, we present an innovative approach crafted to address the unique conditions prevalent in Cyber-Physical Systems (CPSs). Harnessing the power of deep learning, we formulate a method for efficient feature learning and anomaly detection that can be applied to various industrial field bus protocols. Not requiring knowledge of data encoding in the protocols, this approach achieves detection rates as high as 99% for specific attack types. Building upon these foundational components, we investigate the behavior of distributed detection methods in Cyber-Physical Systems (CPS). Leveraging simulations of complex CPS networks allows for the evaluation and optimization of specific configurations. Through this process, optimal configurations can be derived, minimizing the time before detection or maximizing detection rates while considering resource limitations. In conclusion, this study provides crucial insights into the deployment of anomaly and intrusion detection systems within the industrial sector. The application of these measures in practical scenarios empowers operators to detect security issues at an earlier stage, thereby mitigating potential severe damages through prompt incident response. [ABSTRACT FROM AUTHOR]

Substitution boxes are discovered to be significant components of data security in both contemporary and historical ciphers of public-key cryptography. Every online application must be secure. There are two types of S-boxes in the block cipher algorithms: Static S-box: In this type, the same S-box is used in every round of the block cipher. It remains constant throughout the encryption process. Dynamic S-box: Unlike the static S-box, the dynamic S-box employs different S-boxes in each round. The choice of S-box varies based on how it is generated. The dynamic S-box approach enhances security by introducing variability during encryption. The paper you mentioned focuses on dynamic block cipher encryption techniques. It surveys various methods for creating dynamic S-boxes and frames them together as a comprehensive literature review. These techniques play a crucial role in ensuring robust security for data encryption. In modern cryptography, S-box generation and cryptanalysis are crucial. The phases of producing S-Boxes are covered in this article, including bioinformatics technologies, AI techniques, and chaotic systems. The model of a typical S-Box generation system is shown, along with the system's output. The current work will compare the effectiveness of several approaches to S-box generation for security considerations. The results showed that Bioinformatics gives better results when used in generating the S-Box, and thus Bioinformatics showed higher efficiency in the process of generating and analyzing the S-Box than those other methods. [ABSTRACT FROM AUTHOR]

During the era of web 4.0, social media has become a popular trend among internet users. People use social media platforms to share their thoughts and emotions, seeking support from their peers. However, this also exposes them to privacy threats from certain individuals. Cyberbullying is a significant issue in this context, referring to attacks that occur on social media platforms through comments or tweets. The consequences of cyberbullying can be severe, leading to depression, anxiety, and other forms of self-harm. To gain a deeper understanding of this problem, a comprehensive survey was conducted, focusing on the contributions of various authors. This survey primarily examined different machine learning techniques and pre-processing techniques, utilizing data from popular sources between 2015 and 2023. The findings of this survey indicate that the most commonly employed methods in cyberbullying research are tokenization processing and support vector machines. [ABSTRACT FROM AUTHOR]

The proposed two-stages vehicle detection and classification model presents an approach combines a Haar cascade detector for initial vehicle detection and a Convolutional Neural Network (CNN) for subsequent classification. This model was rigorously evaluated using RGB images of size 110×110 pixels from the Thai-Vehicle-Classification-Dataset (TR1), demonstrating an impressive validation accuracy of 98.10 %. This accuracy surpassed other existing methods, showcasing the model's superiority in terms of dependability, computing complexity, and layer count. Additionally, the proposed model exhibited notable improvements in performance parameters, including recall, area under the curve, and precision. These results highlight the efficacy of the model in tackling the challenges associated with vehicle detection and classification tasks. Furthermore, the potential real-world applications of the proposed model are significant, with promising prospects in areas such as traffic surveillance, autonomous driving, and smart transportation systems. [ABSTRACT FROM AUTHOR]

Hand, foot, and mouth disease (HFMD) is amongst communicable diseases which often occurs in outbreaks and up to now, there is no effective vaccine yet to be found. Finding ways to stop the transmission of HFMD has received a lot of interest due to its widespread nature and the morbidity and mortality it causes. Infected children who are not been isolated or quarantine can transmit the disease, as children are known to be physically active and impractical in complying to any intervention. In this study, Susceptible-Exposed-Infected-Quarantine-Recovered (SEIQR) model for HFMD based on Malaysia data are examined. Number of cases in epidemic week are used to estimate parameter values for SEIQR model for the year 2014 to 2017. The results indicated that, quarantine rate is important to display the behaviour in halting the disease, where the value of quarantine rate is 0.522, highest in 2017, while for other years the value is found to be below 0.5. Even though the fraction of infectious individual being quarantine is quite high, about 0.8 for all those years, they do not indicate in higher quarantine rates and seems that the cases are still high. This condition may be due to parents not willing to quarantine their children due to work constraint. Most parents hesitate and act late to quarantine their children as they may have lack in knowledge and experience. Therefore, there is a possibility that the infected individual who was not being quarantine has contaminated the spaces and spread the HFMD. [ABSTRACT FROM AUTHOR]

There are numerous studies on the coprime graph of a group which produced several fascinating results that made researchers' study more on the generalization of the graph and their properties for some finite groups. A continuation of the coprime graph has been carried out by past researchers, where another new graph namely the relative coprime graph has been introduced. The relative coprime graph of a group has vertices that are the elements of a group, and two distinct vertices are adjacent if and only if their orders are coprime and any of them is in the subgroups of the group. In this research, the generalization of the relative coprime graph of cyclic subgroups for some dihedral groups are discussed along with the properties of the graph such as the types of graphs, clique number, diameter, dominating number, chromatic number, independence number, and number of edges. [ABSTRACT FROM AUTHOR]

A proper graph coloring assigns different colors to vertices in a way that no two connected vertices share the same color. The cyclic-intersection graph of subgroups, represented as Γ ∩ C (퐺), consists of all nontrivial subgroups of a group 퐺 as vertices. In this graph, two vertices, subgroups 퐻 and 퐾, are connected by an edge if their intersection results in a non-trivial cyclic subgroup. In this paper, the graph's general presentations on generalized quaternion groups are given. Additionally, the vertex chromatic number and edge chromatic number of the cyclic-intersection graph of subgroups of generalized quaternion groups are established in terms of its maximum degree and clique number. The resulting analysis shows that the vertex chromatic number of the graph is the same as the size of its maximum clique, and the edge chromatic number is the same as the maximum degree of the graph. [ABSTRACT FROM AUTHOR]

In this study, hybrid approaches are proposed to deal with the complex features of nonstationary and nonlinear behaviour. The proposed model takes into account some features, such as the seasonal component and the trend as an input data. However, to the best of the authors' knowledge, statistical patterns, including trend, seasonality and nonlinear behaviour, have rarely been studied simultaneously in bitcoin data. Therefore, a hybrid of structural time series (STS) and nonlinear autoregressive with exogenous input (NARX) is developed to predict bitcoin closing price. The results reveal that the optimal model is the hybrid STS, combining Local Level with Drift Deterministic Seasonal and NARX, featuring two inputs, one output, two delay values, and ten neurons in a hidden layer. This model demonstrates superior performance with the lowest values across all three measurement errors when compared to a single linear STS in bitcoin price prediction. [ABSTRACT FROM AUTHOR]

The main purpose of this paper is to establish an improved Newton iteration method for solving large-scale nonlinear constrained optimization problems. The proposed method simplifies the calculation of the Newton iteration direction in the form of a large-scale Hessian matrix to treat the nonlinear constrained optimization problems into the corresponding unconstrained optimization problems via the Lagrangian multiplier method. Due to the advantage of the block iteration method, the formulation of the proposed method combines the Newton iteration and the four-point Explicit Group Gauss-Seidel (4EGGS) iterative method namely as Newton-4EGGS iteration for solving the generated linear system during the implementation of inner iteration process. To illustrate the efficient calculation of the proposed method, the formulation and implementation of Newton-Gauss-Seidel (Newton-GS) and two-point Newton-Explicit Group Gauss-Seidel (Newton-2EGGS) iterative methods are also presented. Finally, numerical experiments have revealed its superiority with lesser iteration and faster time taken as compared with other two iterative methods. [ABSTRACT FROM AUTHOR]

Research is concerned with using a photoacoustic imaging system based on a diode laser and a condenser microphone to image white cement phantoms and polyvinyl chloride phantoms. The white cement phantom represents hard tissue, while the polyvinyl chloride phantom represents soft tissue. The white cement phantom was varied in density to represent the osteoporosis phenomenon. The optimal laser modulation frequency system is 19 kHz, and the optimal duty cycle is 60%. The white cement phantom and polyvinyl chloride phantom can be distinguished even though the contrast is not very good. The two phantoms' distribution of acoustic intensity levels is not much different. The acoustic intensity level of the white cement phantom is 16 to 21 a.u., while the phantom PVC-DOTP is 17 to 25 a.u. The average acoustic intensity level of the white cement phantom tends to be higher when the density is also high. The average acoustic intensity levels obtained were (18±1), (19±1), and (20±1) a.u. [ABSTRACT FROM AUTHOR]

Solar cells are the most potential energy source for the future because they are a renewable and pollution-free energy source. Currently, solar power plants are increasingly being used to meet the electricity needs of consumers. Fixed-mounted solar panel construction makes the panel position the sun does not always face the sun, so the absorbed energy becomes not maximal and the electrical energy produced is not optimal. Therefore, solar panels equipped with a solar tracker system that can absorb energy more sunlight and produce greater electrical energy are described in this paper. This paper aims to investigate the solutions which were thought to maximize the absorbed solar energy. The performance of this system has been tested and compared between fixed-mounted, single-axis solar trackers, and dual-axis solar trackers. As a result, the dual-axis solar tracking system generates more power, voltage, and current. [ABSTRACT FROM AUTHOR]

To enhance the precision of bankruptcy prediction by implementing Logistic Regression, as opposed to Linear Regression, with a particular focus on efficiency. The study involves a classification approach where Logistic Regression is applied to a sample of 20 cases, while a separate sample of 20 cases is used for Linear Regression. The study configured a Logistic Regression model with specific parameters (alpha, g-power, beta) and aimed to assess its performance with a 95% confidence interval (likely to ensure the results are statistically significant). They compared this to a Linear Regression model. The Logistic Regression achieved a higher accuracy (95.1%) compared to Linear Regression (88.8%) for this task. The mean accuracy detection stands at 0.660 (±2SD), with a significance value of 0.00 (p<0.05). Thus, it is evident that a statistically significant distinction exists between the two groups. The assertion is correct, and it has been conducted through an Independent Sample T-test. The investigation into bankruptcy, the Logistic Regression had greater accuracy (95.3%) while in comparison with the Linear Regression (LR). This research proposes a novel Logistic Regression approach that addresses the limitations of previous studies and achieves higher accuracy. This method empowers users to make more accurate predictions. [ABSTRACT FROM AUTHOR]

The primary goal of Exploratory Data Analysis (EDA) is exploring and understanding data in order to gain insights and guide for further analysis. It allows for data cleaning which involves removing redundancies, handling missing values, correcting errors and transforming data if necessary as it is an important part of overall data preparation process. The aim of this study is to conduct a preliminary study before applying the survival method of analysis to censored lung cancer observations. The Kaplan-Meier survival curve, proportional hazard assumption, time varying covariate assumption via Scaled Schoenfeld residuals, Cox-Snell residuals for overall goodness of fit of the model assumption, and normality assumption via quantile-quantile (Q-Q) plot were all used in this study. The study discovered that the lung cancer censored observations were not violated with the parametric assumption among semi-parametric, and non-parametric assumptions. Thus, future work is recommended to include a comparison of the parametric method of survivals using the lung cancer data. The application of survival analysis would be ambiguous and mislead the researcher if the fundamental part of survival being left out. As a result, this study may aid in identifying appropriate assumptions for prior application on the survival analysis of censored observations. [ABSTRACT FROM AUTHOR]