bluuebunny/crossref_metadata_2025 huggingface dataset:
The Country of Origin (COO) Model of the Indonesian and Chinese Printed Batik Products
Authors: Mahrinasari M.S.
Published: April 2020

Indonesia has become one of the destination countries to market their products and services, and there are various products that are quite widely available in the Indonesian market. The country of origin (COO) model in this research is a new developed model that aims to analyze the moderating role of Ethnocentrism in the effect of the COO and brand preference (BP) on purchase intention toward the Indonesian and Chinese Batik. To address this research purpose, 414 respondents took part in the survey, and the data obtained were analyzed by Structural Equation Model (SEM) with Lisrel 8.80 application. The result of this study shows that Ethnocentrism plays a role as the moderating variable in the effect of COO on purchase intention. However, whenever the effect of the brand preference on purchase intention exists, there is no moderating role of Ethnocentrism. Consumer Ethnocentrism shows that the Chinese batik is purchased in the case if the Indonesian batik is unavailable. It implies that consumer preference to the Chinese Batik exists, because it has a superior quality, a unique or authentic design, and more experience, as the impact of Global Business aspect. The study concluded that the company management must apply global Brand Repositioning Strategy in terms of the superior quality and unique design in fulfilling the global consumers’ needs.
Real-Time Color Image Classification Based On Deep Learning Network
Authors: Abed Mohammed Hamzah , Al-Rammahi Atheer Hadi Issa , Radif Mustafa Jawad
Published: April 2020

Real-time image classification is one of the most challenging issues in understanding images and computer vision domain. Deep learning methods, especially Convolutional Neural Network (CNN), has increased and improved the performance of image processing and understanding. The performance of real-time image classification based on deep learning achieves good results because the training style, and features that are used and extracted from the input image. This work proposes an interesting model for real-time image classification architecture based on deep learning with fully connected layers to extract proper features. The classification is based on the hybrid GoogleNet pre-trained model. The datasets that are used in this work are 15 scene and UC Merced Land-Use datasets, used to test the proposed model. The proposed model achieved 92.4 and 98.8 as a higher accuracy.
Wood Lathe Machine Analysis Using Taguchi Robust Method
Authors: Naje Jenan Mohammed
Published: April 2020

This paper presents the use of Taguchi method in investigating the use of a wood lathe machine (turning operations) in dynamic systems for obtaining the optimum cutting parameters. Two generic functions characterize the woodturning process: The specific energy of cutting is connected linearly with the power of cutting and with the quantity of the cut. These parameters have been measured on the basis of the cutting depth and the rotational cutting speed. The optimization of the rough woodturning relies upon the ratios of dynamic signal to noise and the sensitivities that tolerate superior performance and efficiency.
Under Test Filtered-OFDM And UFMC 5g Waveform Using Cellular Network
Authors: Hammoodi Ahmed Talaat , Shawqi Farooq Sijal , Audaha Lukman , Qasim Abdullah Ali , Falih Ammar Ahmed
Published: April 2020

In this study, filtered orthogonal frequency division multiplexing (F-OFDM) and universal filtered multicarrier (UFMC) were proposed for complexity reduction in the 5G waveform. Cyclic prefix orthogonal frequency division multiplexing (CP_OFDM) is well suited for 4G; however, the major problem of the 4G modulation methods is their susceptibility to high peak to average power ratio (PAPR). Another problem of OFDM is the issue of sideband leakage. The existing 4G systems mainly depend on the CP_OFDM waveform, which cannot support the host of applications provided by the 5G platform. 5G-generated traffic is likely to exhibit different features and requirements compared to the existing wireless technology. Consequently, investigations have been devoted to other multiple access schemes. The existing limitations of OFDM can be mitigated by using the UFMC technique. To ensure that the demands and requirements of the upcoming 5G cellular networks are satisfied, this study presents an enabler called filtered-OFDM (f-OFDM) for flexible waveform configurations. Contrarily, the assigned bandwidth in the f-OFDM is split into various sub-bands to accommodate different services in each sub-band using the most suited waveform, thereby enhancing the spectrum utilization using a different filter. Additionally, the advantages of F-OFDM and UFMC were portrayed via a wide comparison with the current 5G waveforms.
Tackling Graphical Natural Language Processing’s Problems with Recurrent Neural Networks
Authors: Sosa Ali Sami , Mohammed Saja Majeed , Abbas Haider Hadi , Al Barazanchi Israa
Published: April 2020

Recent years have witnessed the success of artificial intelligence–based automated systems that use deep learning, especially recurrent neural network-based models, on many natural language processing problems, including machine translation and question answering. Besides, recurrent neural networks and their variations have been extensively studied with respect to several graph problems and have shown preliminary success. Despite these successes, recurrent neural network -based models continue to suffer from several major drawbacks. First, they can only consume sequential data; thus, linearization is required to serialize input graphs, resulting in the loss of important structural information. In particular, graph nodes that are originally located closely to each other can be very far away after linearization, and this introduces great challenges for recurrent neural networks to model their relation. Second, the serialization results are usually very long, so it takes a long time for recurrent neural networks to encode them. In the methodology of this study, we made the resulting graphs more densely connected so that more useful facts could be inferred, and the problem of graphical natural language processing could be easily decoded with graph recurrent neural network. As a result, the performances with single-typed edges were significantly better than the Local baseline, whereas the combination of all types of edges achieved a much better accuracy than just that of the Local using recurrent neural network. In this paper, we propose a novel graph neural network, named graph recurrent network.
Multi -Focus Image Fusion Based on Stationary Wavelet Transform and PCA on YCBCR Color Space
Authors: Abdullatif Alaa A. , Abdullatif Firas A. , Al Safar Amna
Published: April 2020

The multi-focus image fusion method can fuse more than one focused image to generate a single image with more accurate description. The purpose of image fusion is to generate one image by combining information from many source images of the same scene. In this paper, a multi-focus image fusion method is proposed with a hybrid pixel level obtained in the spatial and transform domains. The proposed method is implemented on multi-focus source images in YCbCr color space. As the first step two-level stationary wavelet transform was applied on the Y channel of two source images. The fused Y channel is implemented by using many fusion rule techniques. The Cb and Cr channels of the source images are fused using principal component analysis (PCA). The proposed method performance is evaluated in terms of PSNR, RMSE and SSIM. The results show that the fusion quality of the proposed algorithm is better than obtained by several other fusion methods, including SWT, PCA with RGB source images and PCA with YCbCr source images.
The Implications of Overcrowding for Fostering Prisoners in Prison: Management and Systems Problems
Authors: Ravena Dey , Mahmud Ade
Published: April 2020

The problem of overcrowding stems from the overcrowding capacity of the Penitentiary, thus raising various problems and relegating correctional goals to a forgotten concept. Against this backdrop, the current study is aimed at determining the implications of correctional overcrowding of prison institutions in the process of fostering inmates and finding solutions in order to improve management and correctional systems in the future. This study adopts a normative approach using qualitatively analyzed secondary data. The results show that the overcrowding problem has seriously adverse implications for coaching programs, causing illness, triggering disturbances between prisoners, burdening state finances each year, and transferring prisoners to other prisons, which, in turn, makes it difficult for families to visit inmates. These problems are preventing the coaching process from achieving the goal of criminal justice. Efforts to overcome the problem of overcrowding include reducing the use of imprisonment sanctions and making replacements in the form of other sanctions that have deterrent power, building new buildings accompanied by facilities that support the basic needs of prisoners, reforming management or a system starting from strengthening the prison officers' integrity, improving the quality of coaching programs, and ensuring welfare of officers.
Integrated Algorithm for Unsupervised Data Clustering Problems in Data Mining
Authors: Wahid Nibras Othman Abdul , Fadhil Saif Aamer , Jasim Noor Abbood
Published: April 2020

Unsupervised data clustering investigation is a standout amongst the most valuable apparatuses and an enlightening undertaking in data mining that looks to characterize homogeneous gatherings of articles depending on likeness and is utilized in numerous applications. One of the key issues in data mining is clustering data that have pulled in much consideration. One of the famous clustering algorithms is K-means clustering that has been effectively connected to numerous issues. Scientists recommended enhancing the nature of K-means, optimization algorithms were hybridized. In this paper, a heuristic calculation, Lion Optimization Algorithm (LOA), and Genetic Algorithm (GA) were adjusted for K-Means data clustering by altering the fundamental parameters of LOA calculation, which is propelled from the characteristic enlivened calculations. The uncommon way of life of lions and their participation attributes has been the essential inspiration for the advancement of this improvement calculation. The GA is utilized when it is required to reallocate the clusters using the genetic operators, crossover, and mutation. The outcomes of the examination of this calculation mirror the capacity of this methodology in clustering examination on the number of benchmark datasets from UCI Machine Learning Repository.
Computer Science Teacher’s Perception and Needs towards E-Learning in Iraq
Authors: Radif Mustafa , Mohammed Nora Ahmed
Published: April 2020

With the advent of technology, electronic learning (e-learning) has become a key aspect of distance learning, making it easier, faster, and more global. With e-learning, teachers have found it easy to deliver education, while students have found new opportunities to learn. There have been several advances to e-learning as a resource for distance learning, with its major features being the use of electronic mediums to facilitate learning. This study is the first of its kind in Iraq that aims to explore the instructional needs of teachers with regards to e-learning for computer science at the secondary school level in Iraq. The study aims to identify the perceptions of secondary school teachers of computer science towards the use of e- learning methods and to also investigate the training needs of teachers for the use of e-learning for teaching of computer science in Iraq. Results indicated that e-learning resources available in the schools surveyed are not enough and the teachers are not making adequate use of e-learning resources. Also, while teachers were aware of the efficiency of e-learning for pedagogy, the schools do not have adequate support mechanisms in place. Teachers were also aware of the competitive edge that e-learning offers them, but did not have adequate training to enable them to use it effectively. Therefore, authorities have to establish a training plan to get teachers comfortable with technology. Such training should start with the basics of e-learning, so that teachers with no knowledge of technology can be carried along.
Synthesis of Nano-Silver Using the Fruit Extract of Jerusalem Artichoke Plant and Its Use as an Antibiotic
Authors: Shabaa Ghusoon Jawad , Ali Luma Ahmed Mohammed , Kadhim Shaymaa Abdul Hadi , Jassim Yazi Abdullah , AL-Obaidy Saba S. M. , Taha Dakhil Nassir
Published: April 2020

In this study, we examined the preparation of silver nanoparticles using plant extracts abundantly available in the country. We combined nano-silver from the product of the silver nitrate reaction with the extract of the Jerusalem artichoke, a plant commonly grown in central Iraq. Using UV-Vis spectroscopy, we investigated the creation of silver nanoparticles produced from silver nitrate with a Jerusalem artichoke fruit extract and found that the maxima absorption was 430 nm. After taking a series of different concentrations of silver nitrate for the synthesis of nanoparticles, the best concentration was 2.5 × 10-3 M. We also studied the change in the FTIR spectrum of both the extract and the resulting nanoparticle compound. The silver nanoparticles in the Jerusalem artichoke extract showed sensitivity and yielded positive results as an anti-bacterial E.coli and Staphylococcus. Also, the synthesized nano-silver was analyzed by SEM.
Performance of Self-Compacting Geopolymer Concrete Containing Nano Silica and Ground Waste Ceramic Tiles as a Fine Aggregate
Authors: Alhashimi Mohammed Noori Hussein , Jasim Fadhil Abbas , Ahmed Ghassan Nasir , Najim Wisam Abdullah
Published: April 2020

The waste produced from the remnants of construction projects, such as construction of houses, roads, bridges, and multi-story buildings, clearly constitutes a major environmental danger and has become a concern in many countries. In Iraq, the great economic growth taking place and the development of modern means of construction has led to the spread of large quantities of waste that must be disposed of. Numerous studies have focused on the disposal of these wastes, with the most important process being recycling. The possibility of using pulverized waste ceramic tiles (PWCT) as a sand replacement to produce high-strength, self-compacting geopolymer concrete (HSSCGPC) was investigated in the present study. HSSCGPC specimens were prepared using ground granulated blast furnace slag (GGBFS) and nano silica (NS) as an alternative to cement. The performance of the produced HSSCGPC was evaluated by subjecting it to several laboratory tests, including workability, compressive strength, splitting tensile strength, flexure, and durability tests, to determine its conformance to the EFNARC standard. The results demonstrated the possibility of using both NS and GGBFS together as a full substitute for cement, with PWCT as a full substitute fornatural sand, although the use of PWCT decreased the workability and strength of the final product. PWCT was established as a prospective candidate for replacement of up to 50% of the sand in cement in terms of environmental friendliness, cost effectiveness, and conservation of natural resources. HSSCGPC had high durability when compared with normal types of concrete.
Assessment of M-Service Acceptance in Educational Context
Authors: Al-Shaher Mohamed Adel
Published: April 2020

The paper investigates students’ perspective regarding the role of Smartphones in an educational context. The method consists in conducting a questionnaire among 80 respondents – final-year students from four universities in Baghdad, Iraq; and data processing through Statistical Package for Social Sciences (SPSS 22.0) by applying recurrence, rate, mean score, standard deviation, autonomous example t-test and One Way ANOVA. Such a blended approach allows demonstrating that smartphones play a positive role in helping students learn and get educated. This study is significant for E-learners as it offers an innovative method of teaching; however a sound pedagogical infrastructure and training is needed.
Voltage Stability Of South Sulawesi Power System Using Fuzzy Logic Method Based On The Linguistic Variable
Authors: Sugianto  , Nojeng Syarifuddin , Sombolayuk Yustinus Upa
Published: April 2020

This study aims to apply a new method for controlling voltage stability in electric power systems, using new modeling with linguistic variables of cryptic logic. The method can easily carry out appropriate control measures in accordance with human thinking and acting. The Fuzzy Logic Stabilizer periodically checks the voltage in real time at each bus and maps into linguistic variables, analyzes its control decisions, then calculates how much stability control is sent to all mobile operator numbers that have been registered at the short message service center, so that appropriate control measures are carried out on the On Load Tap Changer, or On Load Voltage Regulator at each substation, according to the contents of the short message it receives. Application of fuzzy logic stabilizer in the 46 bus electricity system of South Sulawesi will increase the quality of bus voltage from an average of 0.08% to 0.5% of the nominal voltage.
New Authentication Model for Multimodal Biometrics Based on Shape Features Vectors
Authors: Alazawi Sundos Abdulameer , Abdulaaliabdulbaqi Huda , Mohialden Yasmin Makki
Published: April 2020

Biometrics is the science and technology dealing with the measurement and analysis of the biological features of the human body. The analysis is based on comparing the value of certain measured features with the form features in the database. Unimodal Biometric Systems have many limitations regarding precision in the identification/authentication of personal data. To accurately identify a person, a multimodal biometrics system such as combining face and fingerprint characteristic is used. Many such multi-biometrics fusion possibilities exist that can be utilized as an authentication system. In this paper, we present a new authentication system of the multimodal biometrics method for both face and fingerprint characteristics based on general shape feature fusion vectors. There are two main phases in our method: first, the fused shape features for both face and fingerprint images are extracted in accordance with central moments, and second, these features were recognized for retrieval of an authorized person using direct Euclidian distance. Experimentally, we tested about 100 shape features vectors, and observed that our method allows to improve the multimodal biometrics model when we are using the same features for two biometric images. A new method has a high-performance precision when invariant moments are used to extract shape features vectors and when similarity measurements computed based on direct Euclidean distance in the experiments are performed. We recorded False Acceptance Rate, False Rejection Rate, and Accuracy, FAR and FRR where the accuracy of the model is 91 %.
Effect of Saturation Levels on Shear Strength and Bearing Capacity Properties of Soil Types
Authors: Ahmed Mahmood D. , Almurshedi Alaa D. , Alwan Hayder H.
Published: April 2020

This study presents a comprehensive set of laboratory works for the examined soil layers extracted from Baghdad city (specifically from Alkadhimya, Alaitaifiya, and Alhurriya) to illustrate their engineering properties. The researchers have adopted the unified soil classification system for soil classification purposes. Also, the direct shear test was performed for soil samples with various degrees of saturation (0%, 25%, 50%, 75%, and 100%). The test results have shown a significant reduction in cohesion property with higher moisture content within soil samples. Also, a noticeable reduction in angle of internal friction value has occurred with such changes. Furthermore, it has been found that the bearing capacity of unsaturated soils ranged between 2000 and 3000 KPa, and about 500-700 KPa for the soaked soil samples.
Evaluating the Antibacterial Activity of AgGO Nanocomposite Against Clinical Isolate Bacteria
Authors: Al-Ogaidi Marwah , Al-Ogaidi Israa
Published: April 2020

This study discusses the synthesis, characterization, and activity of silver nanoparticles, along with silver graphene oxide, against pathogenic bacteria. Silver nanoparticles are prepared by laser ablation and fabricated with silver graphene oxide. The synthesized silver nanoparticles and silver graphene oxide were characterized through UV-Vis spectrophotometer, Fourier-transforms spectroscopy, and zeta potential. The antimicrobial performance of silver nanoparticles and silver graphene oxide nanoparticles were monitored by the contradiction of gram-negative bacteria (Escherichia.coli and Acenetobacter bumannii), and gram positive bacteria: Staphylococcus aureus. Different concentrations of silver and silver graphene oxide have been investigated to monitor their antibacterial activity against bacterial isolates. The results indicate that the nanocomposites have antibacterial activity and the antibacterial effect increases with increased concentration of nanocomposites. Laser ablation method, a fast synthesis technique, has been used in the current study to prepare silver nanoparticle and silver nanoparticle-graphene oxide nanocomposites.
Proposed Hybrid Algorithm for Image Steganography in Text Security Using Fish Algorithm
Authors: Aldabagh Ghada Mohammad Tahir Kasim
Published: April 2020

The rapid growth of various technologies makes secure data transmission a very important issue. The cryptography technique is the most popular method in several security cases. The major issue is putting the security in place without disturbing the personal data. In such a case, steganography can be used as the most suitable alternative technique. Essentially, steganography is the art of hiding important data that we want to send over a channel or transmission medium. The hiding of information is made with the carrier, making the hacking of data difficult. Hiding the important data provides security and privacy at a high level. In general, there are five types of steganograph: text, audio, video, image and protocol. The carrier plays an important role in steganography. The selection of the carrier depends on the level of security. We proposed an algorithm which is useful for multi-level steganography, and is more advantageous than the standard, less significant, bit algorithm. In this paper, we used multi-level steganography. We focused on image steganography along with a fish algorithm in order to secure the text. We aimed to compare the performance of a basic algorithm to the proposed algorithm. The parameters which have been taken into consideration to compare these two algorithms are execution time and peak signal to noise ratio. We achieved the expected result which shows the applied security for the important data. We used MATLAB 10 software to get these results.
Comparison between Physiological and Behavioral Characteristics of Biometric System
Authors: Habeeb Azal
Published: April 2020

Biometrics is a technical aspect to identify each person from others. It is one of the ways to distinguish a person’s identity. The biometric system plays a vital role in data security. There are two types of biometric systems, i.e., physiological and behavioral biometrics. Physiological biometrics involves the fingerprint, iris, and face, while behavioral biometrics includes the signature, stroke, and voice. This paper discussed the iris recognition technique using the Canny edge detector and Hough transform to separate iris region from the eye images. The voice recognition technique was discussed using mel-frequency cepstral coefficient (MFCC) method. Finally, the paper compared iris recognition and voice recognition according to their properties and their performance.
Strongly ∩ –Reversible Extending Acts over Monoids
Authors: Al-Saadi Saad A. , Kareem Darya J. Abdul , Dahash Angham A.
Published: April 2020

In this work, we present and investigate the class of acts that are strongly extending relative to -reversible subacts in the category of S-acts with zero element. Many characterizations and properties of -reversible extending acts are described. Many results which are known for strongly uniform extending modules and strongly uniform continuous modules are generalized to S-acts with zero element.
On Locally Injective Acts over Monoids
Authors: Al-Saadi Saad Abdulkadhim
Published: April 2020

In this paper, a new generalization of injective acts over a monoid, namely locally injective, are introduced and studied. Using examples, we exhibit that this generalization is proper. Various characterizations of locally injective acts are provided. For example, we show that an act is locally injective if it is locally retracted from each of its extensions. Additionally, we generalize some of the well-known results of injective acts. We prove that every locally injective act has a zero element and is divisible. The relationship among locally injective acts and other known generalizations if injective acts like as principally S-acts, finitely injective S-acts and divisible S-acts are discussed. In fact, we get the following implications: injective S-acts finitely injective S-acts locally injective S-acts principally injective S-acts. Moreover, we assert that locally injective property is closed under product and retracts. Finally, we characterize a monoid by their local injectivity.
Certain Concepts by Using ωpre-Open Sets
Authors: Hussain Kasim Abbas , Ali Haider Jebur , Soady Alaa Malik
Published: April 2020

The aim of this paper is to add new types of continuous functions and results in the specialization field, where we merge two important terms of open sets that are pre-open and ω-open to get a new set named ωp-open set, where we introduce new functions by using this set, such as Mωpc, ωpMc, ωpMωpc, ωp-continuous, ωp*-continuous, and ωp-irresolute function. We clarify the relationship between these types and illustrate their relationship with some other types of continuous functions. Also we define some new types of spaces such as, ωp-compact, ωp-Lindelöf, and Cωp-Lindelöf. In addition, we submit important results like, the ωp*-continuous image of compact space being ωp-compact, and if X is a ωp-regular space, hence it is Cωp-Lindelöf, as well as we provide the composition between most of the new functions that we defined. Many other results have been found in this our work and they are supported by many examples.
Facial Recognition Based on DWT – HOG – PCA Features with MLP Classifier
Authors: Luaibi Morooj K. , Mohammed Faisel G.
Published: April 2020

Facial Recognition System has been widely used in various applications. Nevertheless, their efficiency rate fell dramatically when they were applied under unrestrained environments like the position of face, expression or illumination change. Because of these factors, it is essential to measure and calculate the performance rate of the dissimilar feature extraction techniques robust to such transformations in order to further integrate to a Facial Recognition System. This paper studies and evaluates the Histogram of Oriented Gradients method as a feature extraction method in order to deal with the abovementioned transformations. The study consists of four main phases: face detection, preprocessing, features extraction, and classification. Preprocessing is used to enhance the images by using the techniques of digital image processing. Feature extraction is used to get features from facial images based on the concept of Histogram Oriented Gradient feature that is applied to the facial image after conversion by means of the Discrete Wavelet Transform and vector reduction with the help of the Principle Component Analysis technique. Artificial neural network with the Back Propagation algorithm is used in training and testing as a classifier of the facial images to help recognize the face. To measure the performance of the method under consideration, some experiments were implemented using two datasets: ORL containing 400 facial images of 40 individuals that achieved the accuracy rate about 99.1%, and FERET containing 912 facial images of 152 individuals, which helped achieve accuracy rate about 94.5% at the multilayer perceptron neural network classifier.
Community Culture Improvisation Regarding Waste Management Systems and Per Capita Income Increase
Authors: Prasetya Dwi Arman , Sanusi Anwar , Chandrarin Grahi , Roikhah Elfiatur , Mujahidin Irfan , Arifuddin Rahman
Published: April 2020

The contributions of micro, small, and medium enterprises concerning the formation of small and medium enterprise gross regional domestic product are instrumental to achieve a country’s sustainability development goals. Malang is the second-largest city in East Java and the biggest contributor to Indonesia’s provincial gross regional domestic product, with 65% of its food and beverage sector producing an ever-increasing amount of waste. Indeed, its enhancement is not balanced by appropriate waste management, owing to the inhibiting factors stated in the form of variables, to increase the competitiveness of a community and improve its culture with respect to waste management, leading to an increase in the per capita income. This paper adopts a quantitative and descriptive approach to describe the phenomena and conditions pertaining to the research objective, accompanied by quantitative data processing. The primary data collected via surveys is processed, including data on the availability of waste treatment regulations and facilities, along with infrastructure and statistical analyses (as output from the survey results) to provide solutions for increasing the productivity of micro, small, and medium enterprises in Malang.
Mechanical Properties of Nanocomposite Materials: A Review
Authors: Fathi Mohammed Shaalan Abed
Published: April 2020

Working with nanomaterials requires descending to the atomic level of materials. Hence, the development of SEM and TEM played a large part in the rise of the science and technology of nanomaterials. A lot of research has focused on nanoscience and nanotechnology in the last two decades. There is ongoing development of nanomaterials with unique advantageous properties. This research looked at the problems associated with the production and preparation of nanomaterials and the improvement in the mechanical, physical, thermal, electrical, and chemical properties of the classical materials (metals, polymers, composites, etc.) that may be made into nanomaterials. This paper explains some of the basics of nanomaterials and reviews the behavior of the traditional mechanical properties in nanocomposites with different reinforcements and matrices.
Urban Air Quality Assessment Using Integrated Artificial Intelligence Algorithms and Geographic Information System Modeling in a Highly Congested Area, Iraq
Authors: Jasim Oday Zakariya , Hamed Noor Hashim , Abid Mohammed Abdullah
Published: April 2020

Pollutant emissions are considered to be a major threat to air quality and human health in urban areas. Therefore, accurate modeling and assessment tools are required. In this study, a model was done by the integration of machine learning algorithms and a geographic information system model. This model included the optimization of the support vector regression model by using the principal component analysis algorithm. Then, the integration of the regression model with spatial analysis modeling via a grid (100 x 100 m) was done in order to generate prediction maps during holidays and workdays in the daytime and at nighttime in a highly congested area in Baghdad city, Iraq. The data used in this study categorized into two categories. The first category is the data acquired through field surveying that includes temperature, humidity, wind speed, wind direction, and traffic flow data (e.g., the number of light and heavy vehicles), as well as carbon monoxide samples by using mobile equipment. The second category is the information derived from geographic information system data, such as land use, road network, and building height. The accuracy of the proposed model is 81%, and the lowest value of root mean square error was 0.067 ppm. The integration between air pollution models and geographic information system techniques could be a promising tool for urban air quality assessment and urban planning. These tools effectively utilized by stakeholders and decision-makers to outline proper plans and strategies to mitigate air pollutants in urban areas.
A Smart Traffic Control System Using Image Processing: A Review
Authors: Al-Abaid Shaimaa Abbas Fahdel
Published: April 2020

The global population and number of vehicles on the road are continuously increasing. Currently, most countries around the world face traffic problems. One of the major causes of such problems is ineffective traffic management such as greenhouse emissions, traffic accidents, health damages and time spent, resulting in frequent traffic congestion at major intersections. Therefore, an effective management system is needed to smartly handle traffic congestion on streets, highways, and roads. In the present study, we aimed to evaluate different traffic control systems and their image processing techniques to help manage traffic density. We created a model for a traffic control system based on information received from images of roads taken by a video camera and image processing techniques used to control traffic congestion on roads.
Morphologic and Engineering Characteristics of East Wasit Watersheds Feeding the Al-Shewicha Trough in Iraq
Authors: Shamkhi Mohammed S. , Azee Jasim Mohammed Ridha , Abdul-Sahib Ali A.
Published: April 2020

The Al-Shewicha Trough represents a serious flood hazard to Kut City (the capital of Wasit Province, Iraq) and to the other cities along the Tigris River downstream Kut Barrage, especially in heavy monsoon years. In this study, The Geographic Information System software ArcGIS was used in the morphologic analysis of six river basins that represent the main feeding sources for the Al-Shewicha Trough. The results revealed that the high values for the greatest length of Basins 1, 5, and 6 meant that these watersheds had high concentration time (tc) values, which delay peak flow. All basins consisted of very coarse and permeable subsurface strata that were of coarse texture. Circularity ratio form factor and elongation ratio suggested an elongated shape for all basins with lower peak flow and long duration. Analyses of soil data demonstrated that the soil type that covered a large area was loam soil (classified as hydrologic soil group B), which indicates that all basins had low permeability and high runoff. The predominant land use was bare soil, and all basins had a covering of poor vegetation, which highlighted the fact that basins were highly susceptible to erosion, thus resulting in the generation of higher sedimentation.
Solving a System of Singular Perturbation Problems via Neural Networks
Authors: Shwayaa Rana Taleb , Hazar Manar Joundy , Radif Mustafa , Dahi Jmal Aldeen
Published: April 2020

In this work, we will introduce a new procedure to solve a system of singular perturbation problems (SSPPs) via artificial neural networks. The neural networks use the code of back propagation with altered training algorithms such as quasi-Newton, Levenberg-Marquardt, and Bayesian regularization. In our research, we provide examples of two different types of systems, showing the accuracy, speed, resolution, and convergence of the new technology, the effectiveness of using the network techniques for solving this type of equations. The convergence properties of the technique and accuracy of the interpolation technique are considered.
Energy Consumption, Income, Trading Openness, and Environmental Pollution: Testing Environmental Kuznets Curve Hypothesis
Authors: Chien Nguyen Van
Published: April 2020

The purpose of this study is to examine the effects of energy consumption, economic growth, and trade openness on environmental pollution in a developing country, especially in the case of Vietnam. The study was conducted on the basis of time-series data collected in the period of time between the years 1990 and 2014. By a method of autoregressive distributed lag and testing the hypothesis of the environmental Kuznets curve, our result demonstrated that environmental Kuznets curve could be found in both the long run and short run. There existed an inverted U-shaped relationship between different pollutants and per capita income. Further, energy consumption could positively affect carbon dioxide (CO2) emissions in the short run, but negatively could affect CO2 emissions in the long run because of transformation from non-renewable energy sources to renewable energy sources. In addition, environmental pollution converged on its long-run equilibrium by at least 29.4% with the speed adjustment via the channel of income, energy consumption, and trade openness. In terms of trade openness, the country has a positive and significant effect on CO2 emissions in both the long run and short run.
Evaluation of Photovoltaic Solar Power of a Dual-Axis Solar Tracking System
Authors: Allw Ali Sabri , Shallal Ikhlas Hameem
Published: April 2020

In this research project, a tip-tilting angle of a photovoltaic solar cell was developed to increase generated electrical power output. An active, accurate, and simple dual-axis tracking system was designed by using an Arduino Uno microprocessor. The system consisted of two sections: software and apparatus (hardware). It was modified by using a group of light-dependent resistor sensors, and two DC servo motors were utilized to rotate the solar panel to a location with maximum sunlight. These components were arranged in a mechanical configuration with the gearbox. The three locations of the solar cell were chosen according to the tilt angle values, at zero angles, which included an optimal 33-degree angle for the Baghdad location and a variable angle with the dual-axis tracking system. For maximum value of the extracted solar energy, a photovoltaic solar panel that collects sunlight should be in normal position onto this radiation. Solar trackers relocated the panel toward the path of the Sun to ensure that the collector rotated at an optimal tilt angle. The results showed that the generated power at the dual-axis position was 3.384 watts per hour (W/h), the 33-degree angle yielded 2.237 W/h, and the zero-degree angle yielded 1.09 W/h. The results confirmed that the performance of a dual-axis solar tracking system is active and efficient.
Resilience Strategy In Contemporary Iraqi City: Baghdad City as a Case Study
Authors: Hadi Enas Dhiyaa , Alaskary Abdul Hussain
Published: April 2020

Over the past decade, the resilience concept has gained great importance in climate change, sustainability, and city disaster researches. To tackle the problem that follows the concept, this dissertation posits a formal theory of resilience. In this sense, resilience provides a semantic reference frame for city risks and disasters. Key terms, which fall under the purview of resilience, are defined. The research problem was crystallized to be formulated as “Our cities of today face many challenges and sudden shocks that are difficult to be predicted,” and “Negligence of the disparities in spatial competence has caused difficult situations to face sudden challenges and shocks to reach the more resilient city.” The aims of this research: 1) to build a conceptual framework for the concept of resilient cities, as well as the determination of spatial competence that has a significant impact on varying levels of resilience in places; 2) to reach a resilient Iraqi city strategy by adopting five more vital areas in Baghdad city. The research hypothesis is as follows: Adopting the presence of spatial competence in the area will facilitate the process of making resilient cities to face risks and sudden shocks. To achieve the research objective, the theoretical framework, built to consist the main research conclusion, was that there is spatial competence and place efficiency in any spatial dimension, which makes it difficult to deal with each place in the same way; every place has its own privacy and accessibility to its best strategies in temporal and spatial dimensions.
Deep Learning-Based Character Gesture Recognition
Authors: Al-Behadili Husam , Ahmed Alaa H. , Kadhim Hasan M.A.
Published: April 2020

The article describes a new text input method based on gesture recognition, which enables direct physical-to-digital text input. This enables hand-free and in-air writing without any need for keyboards, mice, etc. This is done with the help of state-of-the-art deep learning methods and a single Kinect sensor. The authors were able to achieve a high-accuracy recognition rate by using any wearable device, in contrast to the existing methods, and utilizing a single sensor. Furthermore, among several existing deep learning structures, the authors determined that the best deep learning structure suitable for the character-based gesture data is the DenseNet Convolutional neural network. For instance, the training loss curve shows that DenseNet has the fastest converging curve compared to the others despite maintaining the highest accuracy rate. Our proposed method allows for the improvement of the recognition rate from 96.6% (in the existing algorithms) to 98.01% when the DenseNet structure is used despite using only a single sensor instead of multiple cameras. The use of the Kinect sensor not only reduces the number of cameras to one but also overrides the necessity for any additional hand detection algorithms. These results aid in improving the speed and the efficiency of the character-based gesture recognition. The proposed system can be used in applications that require accurate decision making, such as in operation rooms.
Оrganizational and methodological bases for improving the planning of state budget expenditure on the social protection of families with children
Authors: Lobodina Zoryana , Demianyshyn Vasyl , Kizyma Tatiana
Published: April 2020

Introduction. The fulfillment of social obligations of the state and realization of the constitutional rights of citizens for social protection are possible provided that a sound social policy and effective use of budgetary resources aimed at the realization of its goals are implemented. In view of this, there is an urgent need for an in-depth study of the theoretical and practical bases for the implementation of expenditures of the State and local budgets of Ukraine for social protection of the population, substantiation of expediency and development of recommendations for improvement of this process. Methods.The theoretical basis of the research is the scientific development of domestic and foreign scientists on public finance and social policy. The following methods of scientifick nowledge were used in the research: induction and deduction, analysis and synthesis, comparison, generalization, associations, analogies and others.The purpose is evaluation of the state of budget financing of social protection of the population in Ukraine, identification of the main problems and development of proposals concerning improvement of budget expenditures of the state for social protection of families with children in the context of ensuring inclusive sustainable development of the state. On the basis of the analysis and evaluation of the state of budget provision of social protection of the population in Ukraine, the main problems of its organization have been defined in the article. The necessity has been grounded and the directions of improvement of the order of realization of the state budget expenditures on social protection of the population have been substantiated. Conclusions. In order to ensure the realization of social rights of citizens, the scientific and methodological approach to improving the planning of the state budget expenditures for social protection of families with children has been proposed, which foresees changing of the order of state assistance at birth of a child, taking into account certain parameters (the value of the statutory / actual minimum subsistence level for children up to 6 years of age and for able-bodied persons, the number of children under 3 years of age with one recipient of state aid at birth of a child; the number of recipients of the stated aid) and allows to improve the efficiency of spending of budgetary resources. Discussion. Theprospectoffurtherresearchistodevelopmeasuresaimedatensuring a de centstandardoflivingforallcitizens.
The strategy of marketing as a tool of competitiveness management
Authors: Temchenko Hanna , Astafieva Kateryna , Bondarchuk Olga
Published: April 2020

Introduction. Efficient management is the necessary component of improving the efficiency and production competitiveness, creation, development and realization of competitive advantages of enterprises in the market conditions. In order to exist the enterprise must clearly define and perform its mission. Competition encourages the enterprise to think of effective means to accomplish its mission and its competitive status. The main task of marketing strategy isthe competitive advantageformation. Thus, definite mission, competitive status and competitive advantage, the principles, rules, norms andthe firm’sobjectivesgive a stable basis for making any decisions in the organization and development of the strategy integrity that is acceptable for the external and the internal enterprise environment. Purpose. The purpose of the article is to find the strategic basis of marketing to manage the competitiveness of the enterpriseeffectively. Methods. The methods of abstraction, analysis, idealization, systematization, institutional analysis are used in the research work. Results. The mathematical model of the indicator which characterizes the economic return from the rational formation and the application of the marketing mechanism in combination with the material-resource potential and real potential capabilities of the organization are proposed for consideration. The application of the proposed model allows to calculate the parameters of the organization competitiveness in the following sequence: product competitiveness, enterprise competitiveness, industry competitiveness. Perspectives. It is necessary to find and approve new ways of enterprises’ competitivenessenhancement that consider the sectoral and regional peculiarities of the developmentin the current situation. In our opinion, it is necessary to implementthe positive experience of foreign countries in improving the competitiveness of the economy, in particular, cluster theory of the economic development.