bluuebunny/crossref_metadata_2025_split huggingface dataset:
Compressive Strength Development of Slag-Based Geopolymer Paste Reinforced with Fibers Cured at Ambient Condition
Authors: Sachet Wrood H. , Salman Wissam D. 
Published: November 2020

AbstractGeopolymer mixtures (such as concrete, mortar, and paste) were used as sustainable alternatives to Portland cement, and enhancement the mechanical properties by addition fibers, due to their great potential in reducing environmental pollution and reducing consumption of raw materials. In this paper, verified the effect of different fibers added to slag based geopolymer paste, on compressive strength development. Ten mixes were preparing and curing at ambient condition. The variables included; type of fibers added (i.e. micro steel fiber, carbon fiber,orpolypropylene fiber), and volumetric ratio of fibers included, (1%, 2%, or 3%) of micro steel fiber, and (0.2%, 0.4%, or 0.6%) of carbon fiber and polypropylene fiber. The alkaline solution was combination of sodium silicate (Na2SiO3), and sodium hydroxide (NaOH) with concentrically 10 molar. The results were found that the addition of fibers led to improving significant of the compressive strength. Generally, the development of compression was estimate by about (30% and 23%) at ages (7 and 28) days, respectively. Finally, the slag based geopolymer paste is more suitable to use in construction sites as alternative sustainable of Portland cement.
The influence of dust physical specifications photovoltaic modules performance
Authors: Mahdy Aedah M J , Ibrahim S I , Al-Zubidi Dina S M , Ali A J , Chaichan Miqdam T , Kazem Hussein A 
Published: November 2020

Abstract
In this article, an experimental analysis was performed to assess the effect of dust accumulation on PV modules resulting energy losses. The dust used in the experiments was collected from three specific sites in the Republic of Iraq. Samples of pollen and common dust were collected from three sites for a period of three months in order to assess their physical properties.
The results showed that 64% of all dust particles are 2 to 62 μm in diameter. The effect of dust deposition on the PV modules has mixed results from one location to another. The surface mass of the precipitated dust is concentrated on the PV unit only (up to 5 g/m2/day), and the decrease in the energy results was evident. The daily maximum decrease in efficacy was 0.05% for the samples examined, and when compared to neighboring countries its value is clear and effective. The results showed that the exposure of the photovoltaic cells to external conditions for a period longer than two months caused a decrease in the productivity of the photovoltaic unit by 35-40%. Therefore, it is recommended that there be periods of cleaning the cells up to two months. The study concluded that the use of PV systems in the studied sites is a practical and economical option.
Study the effect of cold working on the mechanical properties of aluminum alloy 2024 T4
Authors: Saud Haneen M. , Abdulrazzaq Mohammed A. 
Published: November 2020

Abstract
This paper studied the effect of cold working process on (AA2024-T4). shot peening and burnishing processes were utilized in this work. different times of peening (2, 4, 6,8,16 and 24 min) and two parameter of burnishing process (feed rate, spindle speed) were used to analysis the effect of these processes on the mechanical characteristic of aluminum alloy 2024 T4. Fatigue strength, surface hardness and surface roughness were studied. It was observed the shot peening and burnishing process leads to improve fatigue strength of AA2020 T4. The best value of fatigue strength (219 MPa) was obtained in burnishing process at spindle speed (720rpm) and constant feed rate (0.1). This improvement in fatigue life due to compressive residual stresses introducing on alloy’s surface. The highest vales of surface hardness and roughness were(394HVN)) and (8.1 μm) that obtained at (24min) times of shot peening process.
Numerical study of nanofluid natural convection in a partially heated tall enclosure
Authors: Al-Farhany Khaled , Al-Dawody Mohamed F. , Hamzah Dhafer A. , Hamza Naseer H. 
Published: November 2020

Abstract
Numerical study of natural convective heat transfer of partially heated tall rectangular cavity filled with (Al2O3-water) nanofluid. Two opposing horizontal walls are adiabatic, while the right vertical wall is kept at fixed cold temperature, and the left wall of the cavity heated partially. The effect of Rayleigh number (Ra), Aspect ratio (A), and the volume fractions of nanoparticles (ϕ) on the isotherms, streamline, and the average Nusselt number (Nu) have been investigated. The dimensionless governing equations with the Boussinesq approximation have been solved numerically, by using the finite element approach. The results presented for a wide range of parameters including; (103≤Ra≤105, 5≤A≤10, and 0.02≤ϕ≤0.06). The result shows that; the Nu increase when the effect of Rayleigh number (Ra), and the volume fractions of nanoparticles (ϕ) increasing, and also it increase when the Aspect ratio (A) increasing.
Optimization of glass powder content in self-compacting concrete as partial replacement of cement
Authors: Khudair Athraa younis , Mohammed Mahmoud Khashaa , Hama Sheelan Mahmoud. 
Published: November 2020

AbstractThe main aim of the present work is to investigate the fresh and hardened properties of self-compacting concrete by utilization recycled glass powder as partial replacement material for cement and to specify the optimum percent from performance and sustainability point of views. In this study, five mixes were designed with different percentage of grinded glass powder used as cement replacement at 0%, 10%, 20%, 30%, and 40% by weight. Slump flow diameter, time needed to achieve a flow diameter of 500 mm, sieve segregation resistance and L-box height ratio were utilized to examine the rheological properties of the produced self-compacting concrete. For the main mechanical properties, compressive strength at 7, 28, 56 days, splitting tensile, and flexural strengths test at 28 day were conducted. The test results illustrate that the increase in the partial replacement of cement by glass powder led to keep flow ability and caused small decrease in T500 mmtime. However, there was slight decrease in the passing ability and better performance in segregation resistance compared to the mix without glass powder. The mechanical properties of the produced mixes increased up to the replacement level of 30%. However, the optimization results using Minitab 18 statistical software deduced that the optimum percent is 24% to achieve optimum performance in terms tested properties and evaluated sustainability aspects.
Magnetic–type Climbing Wheeled Mobile Robot for Engineering Education
Authors: Mahmood Saif K. , Bakhy Sadeq H. , Tawfik Mouwafak A. 
Published: November 2020

Abstract
The tendency of developing wheeled mobile robots in different applications is growing every day. During the past decades, the need for robots capable for climbing vertical wall has been increased. As a result of that, this paper presents a light and low cost wall climbing robot WCR of wheeled locomotion and adopted neodymium magnets to provide adhesion force. This climbing system is intended to be used for educational and research purposes. The mechanical and electrical constructions are presented. The proposed design has the ability to achieve ground-wall transitioning. In order to provide sufficient information about robot mass properties, novel mechanisms to determine the coordinates of the center of mass COM and moment of inertia MOI of the proposed climbing robot have been introduced. In addition, the vision system was suggested to provide feedback signal of robot pose (position and orienting). Finally, to evaluate the performance of the robot design, a prototype was built and tested in the laboratory environment.
EFFECT OF THE ELECTRODEPOSITION CONDITIONS ON THE EROSION CORROSION OF AUSTENITIC STAINLESS STEEL 316L USING RESPONSE SURFACE METHODOLOGY (RSM)
Authors: Naje Bashar Saed , Al–juboori Haydar A.H. , Al-Saffar Nabil L. 
Published: November 2020

Abstract
This study represents an attempt to improve the erosion corrosion resistance for industrial pumping station used to produce sulfuric acid through electrodeposition coating samples of Austenitic stainless steel 316L. Minitab 19 program was used to precipitate a composite coating layer (Cr-WC) because it is used in many industrial applications that require corrosion resistance, As well as high hardness. The samples were coated using different variables as inputs: temperature(T), WC concentration(WC wt% ), stirring velocity (r.p.m) and deposition time (t) for four levels using central composite design for design laboratory experiments. The factors of coating thickness (C.T), surface roughness (Ra) and micro- hardness (HV) were adopted as outputs response and a complete analysis of variances (ANOVA) at constants significances levels of %5, was done to fully identify the most significant parameters.
The surface response methodology (RSM) was used to provide an optimized model with the best optimum properties such as micro-hardness, surface roughness, coating corrosion rate and oxidation corrosion rate to improve the corrosion resistance of Austenitic 316L stainless steel samples.
The results showed respectively that the wc wt.% was the most effective on all the outputs response then deposition time (min), temperature(T) and stirring velocity (r.p.m).
Structural Response of Post-Fire Exposed Reinforced Concrete Column with Pre-Load
Authors: Jawad Samah Adnan , Ali Ammar Yasir 
Published: November 2020

Abstract
This paper presents the results of experimental and numerical studies of the fundamental response of normal concrete (NSC) columns under fire exposure with pre concentric load. The present study aims to investigate experimentally the behavior of reinforced concrete columns exposed to fire flame with concentric axial load, post-fire behavior under the effect of axial eccentric load. Also, it aims to give a comprehensive account of the fire effects on the ductility and stiffness of these columns. The test results indicated that columns lost about (47.60-51.4) % of bearing capacity after exposure to fire at 500 °C with one hour. Moreover, increased decrease in residual bearing capacity significantly with increasing load level applied during fire exposure. Also, Non-linear finite element (FE) analyses of postfire exposed RC columns with axially load using the ABAQUS computer program is discussed in this paper.
Design and Optimization of Coupled and Self-Adaptive of An Underactuated Robotic Hand Using Particle Swarm Optimization
Authors: Salman Hasan Dawood , Bakhy Sadeq Hussein , Hamzah Mohsin Noori 
Published: November 2020

Abstract

A large work has been devoted to create and design the novel underactuated robotic hand that mimic human hand in terms of motion and grasps. The objective of this paper is to design and development of four-finger underactuated robotic hand mechanisms with 2-DOF for each finger that is highly underactuated which controlled by single actuator that can be used with wide applications. The principle of this hand mechanism is to use the linkage seesaw differentials and the design of robotic finger integrates segments by pin joints and a tendon, that allowing it easily of grasping and adaptable different objects. Furthermore, the robotic finger was designed with combines advantages of the concept of rigid coupled and selfadaptive into one unit to achieve better performance with simple design. To plan the trajectory of the robotic finger and force-isotropic that resembled the human finger in motion and grasping operation, Underactuated finger mechanism was preliminary analysis to predict the relationship between the joint angles of robotic finger related to mechanical parameters as well as contact forces then, modified by optimized set of parameters using particle swarm optimization (PSO). Where, the parameter design constraints were formulated for a multi objective optimization problem using the evaluation criteria for human finger in motion and grasping. Experiments were conducted in order to validate the theoretical analysis by addition of angles sensors on each segment of fingers and the results show that the proposed hand is able to mimic human hand in terms of motion and adaptive grasps.
PRICE PREDICTION OF DIFFERENT CRYPTOCURRENCIES USING TECHNICAL TRADE INDICATORS AND MACHINE LEARNING
Authors: khalid salman Mohammed , Abdu Ibrahim Abdullahi 
Published: November 2020

Abstract
From the past two years with increasing geopolitical and economic issues, global currency values have been falling and stock markets have been having a poor run & investors losing wealth. This has led to a renewal of interest in digital currencies. Cryptocurrency one of the most prominent digital currency has found itself in spotlight with investors wanting a piece of it and business establishments accepting it as a source of payment due to its stable performance in the last few years. This research has been done on predicting cryptocurrency prices using machine learning based neural network which has a lowest the model loss over 100 epochs during training and Technical Trade Indicators (TTI) graphs depicts a real BTC value 5 to 10 times in 300-days of current fiscal year has further supported this increasing trader confidence and a shift in global cryptocurrency graph by predicted BTC values. On the same lines, we are analyzing bitcoin prices using Machine Learning and Sentiment Analysis. We also study stock market trends in order to better predict bitcoin prices quantitively. In this work we analyze the impact of global currencies like US Dollar, foreign exchanges on Bitcoin prices and whether Bitcoin has the stability to dethrone global currencies and become the single medium of transaction. This work is adequate enough to aid in predicting price and with results obtained from predicting Bitcoin prices using machine learning based neural network achieving an accuracy of 94.89% under all circumstances of technical trade indication thereby bringing down its price prediction by over 13.7% in April 2020 itself during evaluation.
Face Recognition Using The Basic Components Analysis Algorithm
Authors: Kamil Hussein Marwah , J.Jalil Alyaa , Alhijaj Asaad 
Published: November 2020

Abstract
Since all the things surrounding us have characteristics, therefore, of course, there are several characteristics and features of the human face that distinguish it and know it from others, making it a distinct organism with certain features that can be classified and identified on its basis. Since the detection and cutting of faces from the image is a critical problem that has gained importance in recent times, they play a major role in facial recognition systems. In this research, we present a new method for identifying faces using the Principal Component Analysis PCA algorithm, through the passage of the image in several stages, starting with the stage of obtaining the image (taking it); then, the face detection phase of the original image, and aligning the image (i.e. adjusting the face angle to the camera angle). After that, we enter the image with the stage of extracting the important basic features of the image; then, we match the required image with the available image store. The proposed algorithm was tested with several images and faces and faces without faces were successfully recognized. The proposed algorithm is characterized by a high efficiency in the detected faces. The accuracy of this algorithm is more than 95% in the detection faces. The proposed algorithm is a prerequisite for any system that uses the face as the main feature.
The review of NAO robotics in Educational 2014-2020 in COVID-19 Virus (Pandemic Era): technologies, type of application, advantage, disadvantage and motivation
Authors: A.Younis Hussain , Jamaludin R. , Wahab M.N.A. , Mohamed A.S.A 
Published: November 2020

Abstract
The use of robotics in education is a very important issue for disposal and galaxies in this era of the pandemic (COVID-19). Where this study examines the topic of robotics in education (RIE) by using modern and specific query methods extracted from different research sites and based on judicious scholar’s standards. These sites are Web of Science, Taylor and Francis and Science Direct. After careful investigation and deep research, the following titles should be taken which are (a)Educational robots, (b)education in robots, (c) human-robot interaction, (d) Higher Education, (e) academic, (f) smart pedagogy, (j)student, and (h) tutors. The retrieved articles were filtered according to the Use of robotics in Education. A total of 98 articles were selected and examined. Finally, we examined the taxonomy of these articles of robotics in Education base on faith and guidance, according to specific criteria, into six groups, which include Faith and Guidance, Concepts, Device, Application, Manufacturing, Studies Analysis and educational. Therefore, this work will be the platform and the guide for student, researcher, educators, anyone how interest in this field. The current focus in this area is on employing papers containing NAO robots and that 17 articles.
A New Medical Images Encryption algorithm Based on Gold Code: Futures Trends Towards Telemedicine
Authors: Ellewe Mohammad H. , Sagheer Ali M. , Shawkat Abdulbaqi Azmi 
Published: November 2020

Abstract
The rising necessity for telemedicine has made the healthcare sector an urgent and unlimited necessity to secure important data sent between medical centers for treatment purposes. The medical image encryption is a significant technique to attain a medical images security (MIS). There are numerous researchers utilized advanced encryption standard (AES) to guarantee of MIS. The direct application of AES encryption technology on medical images led to a long-time of processing; also it leads to a clear background regions, which are considered defects. This article includes the application of information theory (IT) to detect regions of the medical image that include, ROI (regions of interest) and ROB (regions of background). To reduce processing time and protect the medical image by utilizing AES with a higher degree of protection, a hybrid encryption is applied to ROI, and a method of coding such as gold code (GC) is applied to ROB after creation. The proposed method involves less time processing for the entire medical image of the AES application and has the best possible security as described in the entropy and link calculations.
PAM Clustering Aided Android Malicious Apps Detection
Authors: Talib Mohammed Nibras , Hasan Hussein Mohsin , Jabber Rashid Abbas 
Published: November 2020

Abstract
The exponential growth of android contrivances has attracted cybercriminals strongly and dramatically. The applications existed in the android market represented an attack surface owing to the lack of security mechanisms applied by the Google play store. Additionally, downloading apps from unofficial sources lead to a further security threat. Any mobile application requests several permissions to access users’ data to run the app. Thus, attackers exploited this feature in compromising users’ sensitive data. This motivated several researchers to investigate security mechanisms to detect Android malware based on this feature utilizing machine learning techniques, particularly classification techniques. However, This research proposes a permission-based android malware detection framework using a clustering algorithm. Further motivation for this research is that large datasets labeling is a tough mission. Therefore, Our work will contribute to android malware detection as well as android apps datasets labeling. PAM (Partitioning Around Medoid) clustering has been exploited for this purpose since its less affected by outliers or other extreme values. The most significant features have been selected as an input to the clustering algorithm to enhance its results. The results depicted that our clustering algorithm was able from grouping our dataset into two categories malevolent and genuine apps. Moreover, our result has been validated by evaluation standard F-Measure, which is counting for 0.86 for 40 attributes subset, while it is 0.88 for 30 features subset. This reveals a good performance level of permission-based android malware detection and android applications datasets labeling into malware and good ware.
Deep Learning with network of Wearable sensors for preventing the Risk of Falls for Older People
Authors: Mishkhal Israa , AL_ Kareem Sarah Abd , Hadi Saleh Hassan , Alqayyar Ammar 
Published: November 2020

Abstract
Activity recognition (AR) systems for older adults are common in residential health care including hospitals or nursing homes; therefore, numerous solutions and studies presented to improve the performance of the AR systems. Yet, delivering sufficiently robust AR systems from sensor data recorded is a challenging task. AR in a smart environment utilizes large amounts of sensor data to derive effective features from the data to track the activity daily living. This paper maximizes the performance of AR system from using the convolutional neural network (CNN). Here, it analyzes signals from the network sensors distributed in different places in two clinical rooms at the Elizabeth hospital, such as W2ISP and RFID sensors. The proposed approach recognized the daily activities that consider a key to falling cases for older adults at a hospital or a nursing health house. A deep activity CNNets is used to train the effective features of daily activities sensors data then used for recognizing the highest falling risk activities in testing data. This approach used existing data of fourteen healthy older volunteers (ten females and four males) and then compared to other proposed approaches that used the same dataset. The experimental results show that this approach is superior to others. It achieved (96.37±3.63%) in the first clinic room and (98.37±1.63%) in the second clinic room. As the result, this experiment concludes that deep learning methodology is effectively assessing fall risk based on wearable sensors.
Hybrid Algorithm to Solve Timetabling Problem
Authors: Algasm Wesam Ali 
Published: November 2020

Abstract
The university course timetabling problem is a well-known highly-constrained difficult optimization problem. The problem seeks the best allocation of courses to time slots and rooms while ensuring all related constraints are satisfied. Due to the limited resources (rooms and time slots), finding an optimal, or even a high quality, timetable is a challenging task that every university encounters every semester. Many metaheuristic algorithms have been proposed for university course timetabling problem. Genetic algorithm is a class of metaheuristic and has shown very good results for many real-world problems. However, for university course timetabling problems, a traditional genetic algorithm is not usually considered as an efficient solver because it is very hard to maintain the solution feasibility. In this research, we propose a new hybrid algorithm that combines genetic algorithm with simulated annealing to find good solutions for university course timetabling problems. The proposed hybrid algorithm uses simulated annealing in adaptive manner to rectify solutions and to improve the quality of the generated solution by genetic algorithm. The proposed algorithm is tested over Socha dataset from the scientific literature and compared with the state of the art methods.