bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimum Design of Reinforced Concrete One-Way Ribbed Slabs Using Genetic Algorithm
Authors: Galeb Alaa C. , Saeed Noor K. 
Published: November 2020

Abstract
This paper deals with the problem of optimum design of reinforced concrete one-way ribbed using genetic algorithms. ACI-Coefficient method is used for the structural analysis and design of slabs. The cost function represents the cost of concrete, steel, and formwork for the slab. The design variables are taken as slab thickness, spacing between ribs, lower width of ribbed, upper width of ribbed, depth of rib, depth of beam, shear reinforcement spacing of ribs, bar diameter and spacing of top slab, depth of the neutral axis from bottom fiber, beam width, and areas of flexural reinforcement at moment critical section along ribs and beams. The constraints include the constraints of the joist construction constraints stated by ACI-code, constraints on the top slab thickness to satisfy fire resistance, constraints on the areas of steel reinforcement to satisfy the flexural and the minimum area requirements, the constraints on the total slab thickness to satisfy deflection, and flexural behavior. The parameters were taken in this study included: the span length(4-12)m, the compressive of concrete(25-60) MPa, the strength of steel (345-600)MPa, the live load (2-7)KN/m2, unit cost ratio(cost of concrete/cost of steel)(0.1-0.35), aspect ratio (1-2), the formwork cost(10,000-22,000)I.D. The results show that, when discussed the span length, the ratio of (total slab depth/span length) should be (1/18-1/4) using G.A, to get the optimum slab design. It is also concluded that the optimum ratio of (depth of rib/lower rib width) is to be ranged within (1.243-2.917) using G.A. The optimum (rib spacing/span length) ratio is found to be ranged from (1/40- 1/5) using G.A, the results also showed that the range of the optimum (slab thickness/spacing of rib) ratio is found to be ranged as (1/4-1/2) using G.A, in order to find the optimum solution.
A computer program is written using MATLAB for the implementation of structural analysis and the design of one-way ribbed slabs by the ACI coefficient method. The optimization process is performed using the built-in genetic algorithm toolbox of MATLAB.
Experimental study of steel-concrete composite beams with slab opening
Authors: Hassan Ali Dheyaa Mohammed , Nimnim Hayder Talib 
Published: November 2020

Abstract
This study investigates experimentally the effect of openings in the concrete slab of the composite beams. Composite beams consisted of concrete slab connected with steel I-beams by steel headed stud connectors is used in the study with eleven specimens. The test specimens are designed to test and failed in flexure. The test specimens are classified depending on the variable parameters into the following groups: control sample; opening ratio; ratio the short to the long dimension of opening; thickness of the concrete slab; grade of compressive strength; strengthen of opening by steel plate. The results of the study indicate that the general trend in the ultimate load is to increase with increasing thickness of the concrete slab and increasing the compressive strength of concrete. While the ultimate load decreased when increasing the opening ratio because decreasing the effective width of the concrete slab and the cracks develop when the opening was near to the applied loads. Also, the distribution of shear connectors in place of opening on both sides and present the diagonal reinforcing rebars about the opening minimize from the significant decrease for the ultimate load.
Improving the performance of air conditioning system experimentally by a new type of heat pipe heat exchanger
Authors: Al-fahham Mohamed , Eidan Adel A. , Ahmed Ahmed Qasim , AlSahlani Assaad 
Published: November 2020

Abstract
The air conditioning system efficiency is measured by it is coefficient of performance (COP). Higher COP means better system. However, the improving of COP is not an easy work since it linked the heat rejected by the system to power consumed by mechanical part in system, especially the compressor. In this study, a smart employing of heat pipe heat exchanger (HPHE) is used to reduce the power consumed by compressor through super heating the refrigerant vapor pre-enter the compressor and improve the cooling capacity. The results show that using (HPHE) improves the COP of the system by 10% compared to other conventional system.
Biodiesel production from spirulina microalgae oil
Authors: Murad Mariam Emad , Al-Dawody Mohamed F. 
Published: November 2020

Abstract
The present study, experimentally aimed to extract oil form spirulina microalgae then convert it to biodiesel via transesterification process. Different samples are collected from various locations. The samples are cleaned, dried and prepared for the process of oil extraction by soxhlet apparatus. The transesterification process is used to produce biodiesel fuel derived from spirulina microalgae oil, which is then used as an alternative fuel in diesel engine. The methanol along with sodium hydroxide as base catalyst used to minimize the raw oil’s FFA content. The transesterification reaction is carried out at (1:6) oil to methanol molar ratio. Then the mixture is kept inside the separating funnel for 12 hours to separate the glycerine from mixture. The produced biodiesel algae methyl ester (AME) is subjected to gas chromatograph analysis as well as FTIR analysis. All the physical properties are measured and compared with ASTM standard.
Boiling Heat Transfer in a Micro- Channel Complex Geometry
Authors: Shakir R. 
Published: November 2020

Abstract

"This prediction demonstrates an inclusive investigation on" single-phase and two- phase pressure drop properties and flows boiling" instabilities in micro-channels to resume the concepts in the boiling heat transfer tests". The predictions of "single-phase and two- phase heat transfers" in the aluminum micro-channel heat sink have been investigated". "Different heat fluxes and different mass fluxes have been applied "(each mass flow rate under numerous heats fluxes) in an aluminum parallel channel test piece is tested". "It was built up from a piece of aluminum," twenty-five mm wide by twenty-five mm long and ten mm high"."R113 working fluid temperature was constant (25°C) for all prediction tests; "Therefore the heat applies have been applied "in the ranges of (40-600 Watts) "The processes and iteration loops have reached for the prediction heat transfer properties "for three mass flow rates are (0.0125;0.015 and 0.0175 kg/s) "respectively;" and another heat transfer properties. "The aluminum micro-channels heat sink" with 0.5 mm channel height and 0.5 mm channel width "is heated via a wire electrical heater device". "The single-phase and two-phase flows are important parameters" for geometrical configuration of the aluminum micro-channels under variations heat applied". The purpose of this investigation is to explore the relationship between "prediction heat transfer coefficients and mini-scale heat sink geometrical configuration". Heat-transfer coefficients and pressure drops are investigated"." For sub-cooled and saturated boiling data acquired with Single-phase and boiling flows," The single-phase consequences are seen to be location-following, regular with a fully developed laminar flow. All the prediction boiling heat transfer coefficients are seen to have reasonably relied on as mass fraction and mass flux"."" Nevertheless, some are seen to have relied on heat flux whereas others are not. The convective boiling consisting is seen to have a boiling heat-transfer coefficient that is moderately relied on mass flow rate, gas mass fraction, and heat applied"." The prediction work presented here provides one of the first investigations into how to get single-phase" and two-phase properties" data via computer programming. In the end, "the single-phase and two-phase" heat transfer coefficients are reported" for square aluminum micro-channels heat sink under" boiling tests".
Improve Efficiency Solar Cells Using PID Controller
Authors: Najd Ahmed Harb , Gorel Goksu , Hammood Husam Faisal 
Published: November 2020

Abstract
The photovoltaic cell (PV) converts the solar radiation into electric energy and the current coming out of the photovoltaic cell is of the direct current type. The external power of the PV system depends on solar radiation (G) and cell temperature (T). The method of using photovoltaic cells (PV) is efficiently known by the method of tracking the maximum power points (MPPT) using the PID console. This paper introduces MPPT controllers and is a traditional Relative Integration derivative (PID). The work to simulation and modeling to PV cell by MATLAB program. The results show the relationship of curve IV and V-P of the PV panel, as is the case with changes in cell parameters and environmental parameters (radiation and temperature). Optimize PV results for maximum power and maximum voltage using the PID controller used. According to the results, observe the best PID control if compared with other MPPT algorithms.
Optimum Groundwater use Management Models by Genetic Algorithms in Karbala Desert, Iraq
Authors: Hassan Waqed H. , Khalaf Rasul M. 
Published: November 2020

Abstract
Shortage in resources of water in semi-arid region as in Iraq have become an increasing extent dangerous problem. This research objective to improve a new management simulation model for resources of groundwater by linked simulation-optimization (S/O) model. The numerical responses of the 3-D numerical model were Integrated with Genetic Algorithm (GA) optimization model in order to obtain the optimal use of groundwater resources in study area of Karbala desert area in Iraq. The three-dimensional numerical simulation program is used to simulate the system of groundwater flow for Al-Dammam confined aquifer under different conditions. The development management simulation model was adopted by operating the model with considered calibrated variables for current and future periods. Results of analysis the management (S/O) models indicate that the maximum value of pumping rate is reach to (450 E05) m3/year). Also, the pumping rates of the wells within study area could be increased to three times the present water required, with a maximum fall reach to 7.21m in the static heads of groundwater of aquifer.
Design a Suitable Optimized Low Pass FIR Filter for Ultrasonic Signal
Authors: Therib Mohammed Azher , Al-Kharsan Ibrahim H. , Al-Baghdadi Ahmed Fahem 
Published: November 2020

Abstract
Sensors play a vital role in the human life, so it is very important to improve their output signals. One of the most known sensors is ultrasonic sensor. The mentioned sensor uses simple principle to measure a distance between it and nearest obstacle. The output of this sensor improved in this work using FIR filter. The FIR filter parameters are calculated based on Genetic Algorithm (GA). The simulated results using MATLAB show that the optimized filtered data is more suitable and effective to use in many applications.
Using Box-Behnken experimental design for optimization of gas oil desulfurization by electrochemical oxidation technique
Authors: Mohammed Israa , Alwan Hameed Hussein , Ghanim A. N. 
Published: November 2020

Abstract
Iraqi gas oil with sulfur content 9400 ppm was desulfurized electrochemically at constant current (300 mA), the process consists two steps; first step is electrochemical desulfurization by using electrochemical cell contains two graphite electrodes while the used electrolyte is NaCl to enhance electrolyte electrical conductivity, and hydrogen peroxide as an oxidant agent, second step is extraction with acetonitrile. Optimization of process parameters was done by applying response surface methodology RSM combined with Box –Behnken experimental method, in which the sulfur removal efficiency was acted as response function while the reaction temperature, NaCl concentration and time were selected as controllable (studied) variables. The sulfur removal efficiency was ranged from 55.84 % to 88.07%. The results were analyzed with Design-Expert software by fitting with second order polynomial model and the empirical model was exhibited high correlation factor (R2=0.9966) and the estimated optimization solution stated that maximum sulfur removal efficiency is 88.611% at temperature (57.656 °C), NaCl concentration (0.106 M) and, time (51.46 min.).
Compression-based Block Truncation Coding technique to Enhance the Lifetime of the Underwater Wireless Sensor Networks
Authors: M. Jawad Ghufran Ali , M. Al-Qurabat Ali Kadhum , Kadhum Idrees Ali 
Published: November 2020

Abstract
Minimizing the number of transmitted/received data represents a big challenge in Underwater Wireless Sensor Networks (UWSNs). Since the data sending/receiving represents the most energy consumer in the Underwater Wireless Sensor. Therefore, it is important to decrease it to save energy and improve the UWSN lifetime. This paper proposes a Compression based Block Truncation Coding (CBBTC) technique to minimize the volume of the transmitted measurements, save energy, thus improve UWSN’s lifetime while maintaining the accuracy of the measurements received at the base station. The proposed approach operates inside the sensor nodes and designed to reduce data within each sensor node by compressing it, rather than transmitting the data raw to the cluster head (CH) to conserve the sensor energy. Our suggested technique is verified through experiments on actual data of UWSN and our proposed method is compared with other current approaches to show the superiority in terms of energy- saving, increasing UWSN’s lifespan while the fidelity of data is kept.
Developed JPEG Algorithm Applied in Image Compression
Authors: Hussain Abdullah A. , AL-Khafaji Ghadah K. , Siddeq Mohammed M. 
Published: November 2020

Abstract
JPEG is most popular image compression and encoding, this technique is widely used in many applications (images, videos and 3D animations). Meanwhile, researchers are very interested to develop this massive technique to compress images at higher compression ratios with keeping image quality as much as possible. For this reason in this paper we introduce a developed JPEG based on fast DCT and removed most of zeros and keeps their positions in a transformed block. Additionally, arithmetic coding applied rather than Huffman coding. The results showed up, the proposed developed JPEG algorithm has better image quality than traditional JPEG techniques.
Rider Optimization Algorithm implemented on the AVR Control System using MATLAB with FOPID
Authors: Mohamadwasel N B 
Published: November 2020

AbstractConsidering the higher flexibility in tuning procedure and better control movement of the fractional-order proportional integral derivative (FOPID) controller over the traditional proportional integral derivative (PID) controller, this paper explores its application in the automatic voltage regulator system. FOPID contains five tuning boundaries when it appeared differently concerning three in the standard PID controller. The additional tuning handles in FOPID give extended control versatility and careful control action, in any case, their thought makes the tuning system progressively erratic and monotonous. Thusly, the knowledge of the Artificial Intelligent (AI) strategy called Rider Optimization Algorithm (ROA) is utilized to get a perfect mix of FOPID gains which further incited the perfect transient response and improved adequacy of the considered AVR system. To favor the introduction pervasiveness of the proposed approach its relating structure’s dynamic response is differentiated and that of the other striking AI-based philosophies researched in progressing composing. Besides, the quality examination of the proposed AVR structure is finished by evaluating its pole/zero and bode maps. Finally, the intensity of the proposed overhauled AVR system against the structure’s boundary assortment is evaluated by moving the time constants of all the four pieces of AVR: amplifier, exciter, generator, and sensor) from - 50 to +50% self-governing.
An Improvement of ECDSA Weak Randomness in Blockchain
Authors: Hussein Nisreen T. , Kashmar Ali H. 
Published: November 2020

Abstract
Blockchain technology has already changed industry and commercial enterprises remarkably. It is the underlying mechanism of a very well-known cryptocurrencies such as Bitcoin and Ethereum, and many other business applications. Therefore, its security draws the researchers’ attention more and more recently. One of Blockchain vulnerabilities is caused by weak randomness in ECDSA. A random number is not secure, cryptographically, which leads to a leakage in private key and even the user’s fund theft. As well the spam transaction attack may exploit the ECDSA weak randomness. This problem in security has been well known in cryptocurrencies community such as Bitcoin and fixed by applying RFC 6979 update in 2013. However, the problem is not entirely solved.
The elliptic curve digital signature algorithm (ECDSA) was the first successful algorithm based on elliptic curve. This algorithm security depends on complexity of elliptic curve discrete logarithm problem (ECDLP). This algorithm applied in blockchain mechanism as a result of its low computational cost and short key.
In this paper, we analyze the ECDSA weakness in blockchain and enhance its scheme by generating the signature with two secret keys. Using two secret keys will reduce the risk probability of revealing the secret key by knowing two messages. Therefore, the improved scheme can improve the security of the ECDSA.
Development of an Optimized Botnet Detection Framework based on Filters of Features and Machine Learning Classifiers using CICIDS2017 Dataset
Authors: Jabbar Aaya F. , Mohammed Imad J. 
Published: November 2020

Abstract
Botnet is a malicious activity that tries to disrupt traffic of service in a server or network and causes great harm to the network. In modern years, Botnets became one of the threads that constantly evolving. IDS (intrusion detection system) is one type of solutions used to detect anomalies of networks and played an increasing role in the computer security and information systems. It follows different events in computer to decide to occur an intrusion or not, and it used to build a strategic decision for security purposes. The current paper suggests a hybrid detection Botnet model using machine learning approach, performed and analyzed to detect Botnet attacks using CICIDS2017 dataset. The proposed model designed based on two types of filters to the botnet features; Correlation Attribute Eval and Principal Component deployed to reduce the dataset dimensions and to decrease the time complexity of the botnet detection process. The detection enhancement achieved by reducing the features of the dataset from 85 to 9. The training stage of classifiers is developed and compared based on six classifiers called (Random Forest, IBK, JRip, Multilayer Perceptron, Naive Bayes and OneR) evaluated to accomplish an optimized detection model. The performance and results of the proposed framework are validated using well-known metrics such as Accuracy (ACC), Precision (Pr), Recall (Rc) and F-Measure (F1). The consequence is that the combination of Correlation Attribute Eval (filter) with JRip (classifier) together can satisfy significant improvement in the Botnet detection process using CICIDS2017 dataset.
Feature Extraction and Classification of ECG Signal Based on The Standard Extended Wavelet Transform Technique: Cardiology Based Telemedicine
Authors: Abdulbaqi Azmi Shawkat , Al-din M. N Saif , Yusuf Panessai Ismail@Ismail 
Published: November 2020

Abstract
For early detection of cardiac abnormalities, an ECGs cardiac signal is relied upon due to it includes a lot of information that can be utilized for heart disease classification. The ECG signal is too sensitive to various types of noise since it is low frequency and has a small amplitude, these noises decrease the diagnostic accuracy and may outcome in a wrong decision by the clinician. Therefore, rejecting the ECG signal is a necessary condition for successful diagnosis of heart attacks. In this manuscript, the standard extended of Discrete Wavelet Transformc called Dual-Tree Complex Wavelet Transform (Dual-Tree (CWT)) method is utilized to denoise the noisy ECG signal and extract the key features followed by the implementation of the peak detection algorithm. The quality is measured based on performance metrics, and an increase in Signal to Noise Ratio ( SNR) is achieved utilizing the technique. The heart rate (HR) calculation is in line with the gold standard of the various benchmark databases utilized for the proposed procedure and precise heart failure has been calculated.
Prediction Breast Cancer as Benign or Malignant in Apache Spark Framework
Authors: Albaldawi Wafaa S. , Almuttairi Rafah M. 
Published: November 2020

Abstract
There are number of diseases that increase the number of deaths over the world. Breast cancer can be considered as the most common of them. Therefore, there is a need to use classification and others data mining methods to study the health datasets in order to diagnosis and make decisions. In this paper, Support Vector Classifier model, Logistic Regression algorithm, and Random Forest algorithm are conducted on the public available Wisconsin Breast Cancer dataset. The experiment is executed in a Scala environment. Moreover, in single and multi-nodes spark cluster. The results show the high accuracy in Support Vector Classifier model and the low error rate in less time consumed when compared with other studies. The authentication in spark are applied in the application by using shared secrete method.
A novel Face Recognition System based on Jetson Nano developer kit
Authors: salih Thair A. , Basman Gh. Mohammad 
Published: November 2020

Abstract
Real_time face recognition became more important in the last two decade, it is adopted universally for attacking crime, stopping fraud, ensuring public safety. It proves that it is one of the most reliable biometrics security systems because frames can be taken from cameras without touching or interacting, and those images recorded and spontaneously validated with existing databases. The methodology achieved in this work will deal with several challenges like real_time recognition, cheap, portable, and reliable system. NVIDIA Jetson Nano is used in this work. It is a tiny, powerful AI computer that delivers the estimated performance to run advanced AI workloads with a small size, low-power, and low-cost. The main goal of this research is to deploy a deep learning model for face recognition in Jetson Nano, with the intention of real-time performance and high accuracy. The results of this study have shown great real-time performance in face recognition using Jetson Nano, Where it was processing 8.9 FPS in comparison with the latest raspberry pi edition 2.6 FPS.
Water Quality Monitoring System Based on IOT Platform
Authors: Abbas Fadel Ahmed , Ibrahim Shujaa Mohamed 
Published: November 2020

Abstract
Water treatment monitoring systems are presently divided into manual and dynamic systems. Due to, the constant changes in water, either due to seasonal changes in water chemistry or due to the operative conditions of the industrial environment, the dynamic systems have to be utilized by the water manufacturers. However, water is very beneficial for life and human health, therefore to reduce the endangerment of pollution, by improving and increasing the plant operation in addition to production. This paper suggests a new technique for water factory manufacturers by adopting wireless sensor nodes. The monitor node connected with a microcontroller device using Esp32 as transmitter and receiver nodes. The node sends its statues over the wireless network utilizing a defined internet protocol (IP). The proposed system shows its effectiveness in water monitoring systems through synchronous water monitoring and simple configuration compared to traditional systems.