Showing papers in "International journal of engineering and technology in 2018"
TL;DR: A survey of various models based on supervised learning algorithms such as Support Vector Machines (SVM), K-Nearest Neighbour (KNN), NaïveBayes, Decision Trees (DT), Random Forest (RF) and ensemble models are found very popular among the researchers.
Abstract: Heart related diseases or Cardiovascular Diseases (CVDs) are the main reason for a huge number of death in the world over the last few decades and has emerged as the most life-threatening disease, not only in India but in the whole world. So, there is a need of reliable, accurate and feasible system to diagnose such diseases in time for proper treatment. Machine Learning algorithms and techniques have been applied to various medical datasets to automate the analysis of large and complex data. Many researchers, in recent times, have been using several machine learning techniques to help the health care industry and the professionals in the diagnosis of heart related diseases. This paper presents a survey of various models based on such algorithms and techniques andanalyze their performance. Models based on supervised learning algorithms such as Support Vector Machines (SVM), K-Nearest Neighbour (KNN), NaïveBayes, Decision Trees (DT), Random Forest (RF) and ensemble models are found very popular among the researchers.
141 citations
TL;DR: In this paper, the authors highlight the top technologies for tourism and Hospitality with regard to AR and VR, and highlight the most useful applications that are attracting greater attention from tourism researchers and professionals.
Abstract: Virtual Reality and Augmented Reality, these days, is offering many useful applications that is attracting greater attention from tourism researchers and professionals. As, AR and VR technologies are evolving, the number of scientific applications is also at increase. VR and AR are proving their worth especially when planning, marketing, education, tourist sport preservation coming to light. The aim of this research paper is to highlight top technologies for Tourism and Hospitality with regard to AR and VR.
103 citations
TL;DR: The paper proposes that learning analytics is dependent on personalised approach for both educators and students, and defines the characterising features that represents the relationship between learning analytics and personalised learning environment.
Abstract: This paper presents learning analytics as a mean to improve students’ learning. Most learning analytics tools are developed by in-house individual educational institutions to meet the specific needs of their students. Learning analytics is defined as a way to measure, collect, analyse and report data about learners and their context, for the purpose of understanding and optimizing learning. The paper concludes by highlighting framework of learning analytics in order to improve personalised learning. In addition, it is an endeavour to define the characterising features that represents the relationship between learning analytics and personalised learning environment. The paper proposes that learning analytics is dependent on personalised approach for both educators and students. From a learning perspective, students can be supported with specific learning process and reflection visualisation that compares their respective performances to the overall performance of a course. Furthermore, the learners may be provided with personalised recommendations for suitable learning resources, learning paths, or peer students through recommending system. The paper’s contribution to knowledge is in consider ing personalised learning within the context framework of learning analytics
86 citations
TL;DR: This paper addresses few techniques of Semi-supervised learning such as self-training, co- training, multi-view learning, TSVMs methods, which achieves better accuracy than traditional supervised and unsupervisedLearning techniques.
Abstract: Most of the application domain suffers from not having sufficient labeled data whereas unlabeled data is available cheaply. To get labeled instances, it is very difficult because experienced domain experts are required to label the unlabeled data patterns. Semi-supervised learning addresses this problem and act as a half way between supervised and unsupervised learning. This paper addresses few techniques of Semi-supervised learning (SSL) such as self-training, co-training, multi-view learning, TSVMs methods. Traditionally SSL is classified in to Semi-supervised Classification and Semi-supervised Clustering which achieves better accuracy than traditional supervised and unsupervised learning techniques. The paper also addresses the issue of scalability and applications of Semi-supervised learning.
77 citations
TL;DR: In this article, a three-blade horizontal axis wind turbine (HAWT) and a Darrieus-type vertical axis wind turbines (VAWT) have been designed with CATIA software and constructed using a 3D-printing method.
Abstract: As the demand for green technology is rising rapidly worldwide, it is important that Malaysian researchers take advantage of Malaysia’s windy climates and areas to initiate more power generation projects using wind. The main objectives of this study are to build a functional wind turbine and to compare the performance of two types of design for wind turbine under different speeds and behaviours of the wind. A three-blade horizontal axis wind turbine (HAWT) and a Darrieus-type vertical axis wind turbine (VAWT) have been designed with CATIA software and constructed using a 3D-printing method. Both wind turbines have undergone series of tests before the voltage and current output from the wind turbines are collected. The result of the test is used to compare the performance of both wind turbines that will imply which design has the best efficiency and performance for Malaysia’s tropical climate. While HAWT can generate higher voltage (up to 8.99 V at one point), it decreases back to 0 V when the wind angle changes. VAWT, however, can generate lower voltage (1.4 V) but changes in the wind angle does not affect its voltage output at all. The analysis has proven that VAWT is significantly more efficient to be built and utilized for Malaysia’s tropical and windy climates. This is also an initiative project to gauge the possibility of building wind turbines, which could be built on the extensive and windy areas surrounding Malaysian airports.
74 citations
TL;DR: This work used decision trees and combination of algorithms for the prediction of heart disease based on the above attributes and shown that when the dataset is small naive Bayes algorithm gives the accurate results and when the datasets is large decision trees gives the inaccurate results.
Abstract: Heart disease is the one of the most common disease. This disease is quite common now a days we used different attributes which can relate to this heart diseases well to find the better method to predict and we also used algorithms for prediction. Naive Bayes, algorithm is analyzed on dataset based on risk factors. We also used decision trees and combination of algorithms for the prediction of heart disease based on the above attributes. The results shown that when the dataset is small naive Bayes algorithm gives the accurate results and when the dataset is large decision trees gives the accurate results.
65 citations
TL;DR: The results of this study found that interactive multimedia applications based on computer valid and suitable for use in teaching and learning activities in primary schools.
Abstract: Computer-based learning media is the use of a computer to help present learning materials to students, monitor the progress of learning or choose additional learning materials in accordance with student learning needs individually or is a form of application and use of computers that are applied in student learning directly to convey the content of the lesson, providing student learning exercises. The purpose of this study is the development of interactive multimedia computer-based on the subject of civic education in elementary education. This research method using an approach of research and development with stages: requirement analysis, design, and validation expert. The results of this study found that interactive multimedia applications based on computer valid and suitable for use in teaching and learning activities in primary schools.
61 citations
TL;DR: In this article, the authors improved the calculation methodology of metal temperature loss during hot rolling process at continuous mills, which can be implemented at hot strip mills with various in-line equipment arrangements within the temperature ranges appropriate for processes simulation of hot rolling, normalized rolling and Thermo-Mechanical Control Process of carbon and microalloyed steels.
Abstract: The paper improves the calculation methodology of metal temperature loss during hot rolling process at continuous mills. The proposed methodology can be implemented at hot strip mills with various in-line equipment arrangements within the temperature ranges appropriate for processes simulation of hot rolling, normalized rolling and Thermo-Mechanical Control Process of carbon and microalloyed steels. It provides engineering analysis of unaccounted temperature losses of feed by means of radiation and convection, which, in the first time, through the time factor, additionally accounts for strip motion speed factors, roller table length and feed length, and also length of rolls contact arc with metal. The accountability of the above mentioned factors in the various compositions depending on the rolling method increases the engineering simulation accuracy, ensures the versatility of the elaborated method with respect to different types of mills and makes the scientific novelty of the study. The equations were developed to calculate the metal temperature loss while coiling at the CoilBox unit. The equations accounts for the influence on the temperature of strip length, coiling and uncoiling speed, strip thickness, inside radius of the reeling coil, the time the feed rests being coiled. The improved model was verified based on actual data.
52 citations
TL;DR: A mini review on studies done over the span of ten years regarding plant-based natural coagulants is provided to identify several potential research gaps to provide platform towards the need of further study.
Abstract: Natural coagulants have been increasingly popular in the past few years due to its benefits and the fact that it resolves mos t of the associated problems when using chemical coagulants. Plant-based natural coagulants perform coagulation either by polymer bridging or charge neutralization, it can be extracted from various plant components. Concerted research and development efforts have been conducted in discovering new plant species and constituents that can be used as natural coagulants, which further boosting the effectiveness of existing plant-based natural coagulants. The objective of this paper is to provide a mini review on studies done over the span of ten years regarding plant-based natural coagulants. This paper also includes advantages and disadvantages of natural coagulants prior to identify sever al potential research gaps to provide platform towards the need of further study.
52 citations
TL;DR: In this paper, the authors developed a method for the calculation of the required force of shaping of a horizontal shape-forming machine used in the pre-production workflow of wheel steel rims, which is significant under the conditions of frequent alteration of the product nomenclature.
Abstract: The objective of the paper is the development of the method for the calculation of the required force of shaping of a horizontal shape-forming machine used in the preproduction workflow. The design of a machine for horizontal shape-forming of wheel steel rims enables quick readjusting and transfer to another rim shape, which is significant under the conditions of frequent alteration of the product nomenclature. We developed the calculation method based on the assumptions of the deformations continuity, the constancy of the volume at plastic deformation and axisymmetric stressed state as well as the local application of the load. The research resulted in obtaining the analytical dependences for the calculation of the force of shaping of a wheel rim, taking into account the degree of deformation, the mechanical characteristics of the metal, hardening as well as the design and technological factors of the process. The topicality of the development consists in the necessity for the high-quality and the least expensive choice of the equipment of the required rated power when designing a new workflow. The experimental data, carried out both under the production and laboratory conditions, confirmed the adequacy of the theoretical formulas. It is determined by the assumptions and solutions obtained based on the mathematical apparatus of the technical theory of the shells of revolution. The clearness of the method will make it possible to algorithmize the calculation process quite easily and to use it as a subprogram in an applied complex of technical preproduction. It will also allow determining the shaping process most significant factors influencing the value of the force without the direct use of the calculation. We recommend to use it at enterprises producing vehicle steel wheels by the method of radial-rotation shaping.
50 citations
TL;DR: The basic knowledge and classification of bidirectional dc to dc converters on the basis of galvanic isolation, the comparison between their voltage conversion ratio and output current ripple along with various topologies researched in recent years are presented.
Abstract: Bidirectional dc to dc converter is used as a key device for interfacing the storage devices between source and load in renewable energy system for continuous flow of power because the output of the renewable energy system fluctuates due to change in weather conditions. In electric vehicles also, bidirectional converter is used between energy source and motor for power supply from battery to motor. Thus, bidirectional dc to dc converters are getting more and more attention in academic research and in industrial applications. Bidirectional dc to dc converters work in both buck and boost mode and can manage the flow of power in both the direction between two dc sources and load by using specific switching scheme and phase shifted control strategy and hence generated excess energy can be stored in batteries/super capacitors. Therefore, the basic knowledge and classification of bidirectional dc to dc converters on the basis of galvanic isolation, the comparison between their voltage conversion ratio and output current ripple along with various topologies researched in recent years are presented in this paper. Finally, zero current and zero voltage soft switching schemes and phase shifted controlling techniques are also highlighted.
TL;DR: In this article, the authors proposed the extension of TAM to identify the potential factors that influence consumers' intention to adopt FinTech products and services in Malaysia, namely usefulness, ease of use, competitive advantage, perceived risk, and perceived cost.
Abstract: “FinTech” or a compound term of Financial Technology refers as a newly emerged industry that utilizes IT-centered technologies which aims to boost the efficiency of the financial ecosystem. Since its inception, FinTech has successfully established its presence in the global financial industry due to the benefits and advantages of the system. However, the research studies that highlight the importance of FinTech are scarce. Specifically, the study pertaining to the consumers’ attitude towards FinTech products and services in the context of Malaysia remains unexplored by most of the studies. This preliminary study proposed the extension of Technology Acceptance Model (TAM) to identify the potential factors that influence consumers’ intention to adopt FinTech products and services in Malaysia. This study reviewed the factors, namely the usefulness, ease of use, competitive advantage, perceived risk, and perceived cost that can potentially influence the attitude of customers towards the product and services of FinTech. This study also proposes the potential mediating effect of attitude towards using FinTech products and the intention to adopt FinTech. This study attempts to create new knowledge geared towards the behavior to utilize FinTech products in Malaysia.
TL;DR: In this article, the authors describe the influence of the degree of preliminary deformation on the kinetics of fatigue failure of metals and alloys and evaluate the manufacturing of parts with a weld seam at the design stage of the technological process.
Abstract: The purpose of the article is to develop an apparatus providing maximum or predicted durability of parts treated during their manufacture by plastic deformation. In these terms, the parameters of the technological process should provide the maximum or expected increase of the endurance limit in comparison with the initial parts values before the strengthening by the surface plastic deformation or after plastic forming. The article describes the influence of the degree of preliminary deformation on the kinetics of fatigue failure of metals and alloys. Experimental data of the ultimate deformations of welded workpieces were obtained, which make it possible to evaluate the manufacturing of parts with a weld seam at the design stage of the technological process. The developed method made it possible to determine the nonstationary field of stresses in the deformation region, ultimate deformations and the most rational scheme of the stress-strain state, which excludes the localization of deformations and destruction of the weld zone of a welded cylindrical workpieces.
TL;DR: One of Google Apps for Education products is Google Classroom being a learning media between for Lecturers and Students to build interactive communication to improve the engagement for the students themselves.
Abstract: Google Apps for Education (GAFE) is a technology is provided and designed for college by promoting the use of information technology and collaboration. One of Google Apps for Education products is Google Classroom being a learning media between for Lecturers and Students to build interactive communication. Interactive communication leads to good feedback in the form of educational transformation from learning source to learner. This is what improves the engagement for the students themselves. By the concept of digital classroom, students no longer just sit passively in the classroom, they are interested in themselves to explore the things offered by technology. Building interactive communication among students need a good strategy. Strategy not only serves as a concept map that shows only direction, but is able to demonstrate operational tactics to achieve the established goals. A teacher or lecturer who does not have a good teaching strategy will not be able to create good communication with students. Building interactive communication among students need a good strategy. Strategy not only serves as a concept map that shows only direction, but is able to demonstrate operational tactics to achieve the established goals. A teacher or lecturer who does not have a good teaching strategy will not be able to create good communication with students.
TL;DR: This project tends to reduce time and cost of image recognition systems using deep learning and proposes Deep Learning approach in this project.
Abstract: Most of the existing image recognitions systems are based on physical parameters of the images whereas image processing methodologies relies on extraction of color, shape and edge features. Thus Transfer Learning is an efficient approach of solving classification problem with little amount of data. There are many deep learning algorithms but most tested one is AlexNet. It is well-known Convolution Neural Network (AlexNet CNN) for recognition of images using deep learning. So for recognition and detection of the image we have proposed Deep Learning approach in this project which can analyse thousands of images which may take a lot for a human to do. Pretrained convolutional neural network i.e. AlexNet is trained by using the features such as textures, colors and shape. The model is trained on more than 1000 images and can classify images into categories which we have defined. The trained model is tested on various standard and own recorded datasets consist of rotational, translated and shifted images. Thus when a image is passed to the system it will apply AlexNet and return the results with a image category in which the image lies with high accuracy. Thus our project tends to reduce time and cost of image recognition systems using deep learning.
TL;DR: In this article, the authors used Contextual Teaching and Learning (CTL) based on Lesson Study for Learning Community (LSLC) on "Sequence and Series" Learning Material for the tenth grade students of vocational school as well as to know its effect on the students' high-order thinking skill.
Abstract: This research aimed to develop Mathematics instructional instruments by using Contextual Teaching and Learning (CTL) Based on Lesson Study for Learning Community (LSLC) on “Sequence and Series” Learning Material for the tenth grade students of vocational school as well as to know its effect on the students’ high-order thinking skill. The method used is mixed methods with concurrent triangulation strategy model namely research and development method with Thiagarajan model combined with quantitative method using non equivalent control group design quasi experimental pretest-posttest. The research subjects were the students of SMKN 1 Panji of Situbondo regency, from which two classes were chosen as research sample, class X Accounting 2 as the control class and class X Accounting 3 as the ex-perimental class. High-order thinking skill is measured by using essay test. Assumption test of normality and homogeneity of variance was tested before analyzing the data. The result of the first test showed that the data were not normally distributed. Therefore, the data were ana-lyzed by using Mann-Whitney analysis. The research results showed that: (1) the instructional instruments resulted is valid, the implementa-tion of the instructional instruments is in practical and effective; (2) the significance value (2-tailed) is 0.000 (p < 0.05), which indicated that the application of learning by using CTL Based on LSLC had a significant effect on the students’ high-order thinking skill.
TL;DR: In this paper, Gumbel copula was used for the assessment of the geographical distribution of flood risk in the Kelantan river basin, where seven univariate distribution functions of flood variables were fitted with flood variables such as peak flow, flood volume, and flood duration.
Abstract: Bivariate frequency analysis of flood variables of different station locations of Kelantan river basin was conducted using copula for the assessment of the geographical distribution of flood risk. Seven univariate distribution functions of flood variables were fitted with flood variables such as peak flow, flood volume, and flood duration to find the best-fitted distributions. The joint dependent structures of flood variables were modeled using Gumbel copula. The results of the study revealed that different variables fit with different distributions. The correlation analysis among variables showed a strong association. Joint distribution functions of peak-flow and volume, peak-flow and duration, and volume and duration revealed that the joint return periods were much higher than univariate return periods of same flood variables. The flood risk analysis based on joint return period of flood variables revealed the highest risk of devastating flood in the downstream. The locations identified as highly susceptible to flood risk by joint distributing of flood variables had experienced most severe floods in recent history, which indicates the effectiveness of the method for the analysis of flood risk. It is expected that this procedure can be helpful for better assessment of flood impacts.
TL;DR: This research review paper serves as a guideline for researchers who are new to machine learning area and want to contribute to it, provide state-of-the-art survey of machine learning, and provides further research directions required into health prediction system using machine learning.
Abstract: Humans are considered to be the most intelligent species on the mother earth and are inherently more health conscious. Since Centuries mankind has discovered various proven healthcare systems. To automate the process and predict diseases more accurately machine learning methods are gaining popularity in research community. Machine Learning methods facilitate development of the intelligence into a machine, so that it can perform better in the future using the learned experience. Machine learning methods application on electronic health record dataset could provide valuable information and predication of health risks. The aim of this research review paper are four-fold: i) serve as a guideline for researchers who are new to machine learning area and want to contribute to it, ii) provide state-of-the-art survey of machine learning, iii) application of machine learning techniques in the health prediction, and iv) provides further research directions required into health prediction system using machine learning.
TL;DR: The application of fuzzy logic method in determining the potential value of the village in accordance with the criteria has been successfully established, so that the fuzzy Logic method is suitable for the calculation of the search results from the potential of Bulurejo village.
Abstract: This paper presents the potential owned by the Bulurejo village in the field of Agriculture and Livestock field. The authors conducted a study to determine the outcomes of potential Bulurejo village based on criteria such as potential in the field of agriculture, field of large cattle and small livestock and poultry using fuzzy logic method. So from the results of these studies there are results of th e value of 74.29 which is included in the potential of a good village. The application of fuzzy logic method in determining the potential value of the vil- lage in accordance with the criteria has been successfully established, so that the fuzzy logic method is suitable for the calculation of the search results from the potential of Bulurejo village
TL;DR: In this study a comparative thyroid disease diagnosis were performed by using Machine learning techniques that is Support Vector Machine (SVM), Multiple Linear Regression, Naïve Bayes, Decision Trees, and so on.
Abstract: Thyroid illness is a medicinal state that influences the functionality of the thyroid organ that is thyroid gland [1](Guyton, 2011).The indications of thyroid ailment differ basing upon the type. There are four most common varieties: hypothyroidism (low capacity) which is caused due to the insufficiency of the thyroid hormones; hyperthyroidism (high capacity) which is caused due to the existence of the thyroid hormones more than just sufficient, basic variations from the norm, most normally an augmentation of the thyroid organ; and tumors which can be benign or can cause cancer. It is additionally conceivable to have irregular thyroid capacity tests with no clinical side effects [2](Bauer & al, 2013). In this study a comparative thyroid disease diagnosis were performed by using Machine learning techniques that is Support Vector Machine (SVM), Multiple Linear Regression, Naïve Bayes, Decision Trees. For this purpose, thyroid disease dataset gathered from the UCI machine learning database was used.
TL;DR: Analysis approach of SE need is formulated so that it is easily modified, adaptive to growing software complexity, and connected with the analysis of hardware.
Abstract: Software Engineering (SE) is a discipline, concept, method that focus on all aspects related to software production. SE must adapt organized system and approach in building software. The objective of this article is to discuss needs elicitation in SE, so that the design can be done through utilizing appropriate tools and techniques based on the problem to be solved, restrictions and need that must be met, as well as resource availability. The method used in this article is literature review as a major source of problem analy-sis. In the next phase, the main topic of the article is clarified, validated, and verified by the model of the Focus Group Discussion (FGD). The respondents of FGD are lecturers of Informatics Department at UIN Sunan Gunung Djati Bandung. Requirements elici-tation is in-dept and comprehensive process of finding information from all stakeholders in relation to the built software. The result of requirements elicitation is the explanation from every stakeholder with natural language related to the will and interest of the built software. The mechanism of finding information can be done through observation, questionnaire, interview, and documentary study, which are then tested with data validation and verification in FGD. The product of requirements elicitation is the User Re-quirement Document (URD) that can be used as an early artifact in software development process. Furthermore, URD is used as a reference in tracking the suitability between the function of software and the needs of stakeholder. This article formulated analysis approach of SE need, so that it is easily modified, adaptive to growing software complexity, and connected with the analysis of hardware.
TL;DR: An ASR based Airport enquiry system has been developed natively for telugu language and Convolutional Neural Network has been used for training and testing of the database.
Abstract: Automatic speech recognition (ASR) is the process of converting the vocal speech signals into text using transcripts. In the present era of computer revolution, the ASR plays a major role in enhancing the user experience, in a natural way, while communicating with the machines. It rules out the use of traditional devices like keyboard and mouse, and the user can perform an endless array of applications like controlling of devices and interaction with customer care. In this paper, an ASR based Airport enquiry system is presented. The system has been developed natively for telugu language. The database is created based on the most frequently asked questions in an airport enquiry. Because of its high performance, Convolutional Neural Network (CNN) has been used for training and testing of the database. The salient feature of weight connectivity, local connectivity and polling result is a through training of the system, thus resulting in a superior testing performance. Experiments performed on wideband speech signals results in significant improvement in the performance of the system in comparison to the traditional techniques.
TL;DR: In this paper, a review paper focusing on the influence of different variables on the properties of geopolymer concrete and the progress in the field of geopolymer concrete is presented.
Abstract: Geopolymer concrete is proved to have high strength, lesser shrinkage, resistance against reinforcement corrosion, acid and sulphate resistance, freeze-thaw resistance, fire resistance and resistance to alkali-aggregate reaction. There are many parameters which influence the strength characteristics of Geopolymer Concrete. They are types and fineness of Source alumino silicate material used, concentration and type of alkaline activators used, curing temperature and curing time, utilization of M-sand etc. High performance characteristics could be achieved through the correct choice of these parameters. This review paper focuses on the influence of different variables on the properties of geopolymer concrete and the progress in the field of geopolymer concrete. Consequently many research papers pertaining to the geopolymer have been reviewed in this state of art paper.
TL;DR: This decision support system can perform the process of calculating employee performance appraisal so that it can realize a fair assessment based on existing criteria calculations on this system using weighted product weighting (WP) that can produce the best Employee performance appraisal system calculation.
Abstract: The decision support system of employee performance index appraisal is a decision support system that can assist decision makers for employee performance appraisal at the Pringsewu district revenue department. As for the purpose of this DSS namely 1. To make decisions in the field of human resources to come, 2. To evaluate the performance of each employee in achieving the target work that has been determined , 3. For improve employee performance in the future. The problems to be solved are: 1. How to change the assessment process that used to still use manual way by computerization. 2. How to apply the progress of change in today's sophisticated technology. In this decision system using Weighted Product (WP) weighting method of WP method is the choice of method on decision support system of employee performance appraisal index at revenue department of Pringsewu district. Weighted product method is a method of completion by using multiplication to attribute attribute rating in which rating must be prefixed with bob ot attribute in question. This decision support system can perform the process of calculating employee performance appraisal so that it can realize a fair assessment based on existing criteria calculations on this system using weighted product weighting (WP) that can produce the best employee performance appraisal system calculation from the highest value of 0.250 to the lowest value of 0.133 . The highest score is the best employee while the lowest score is the worst employee performance. This system can present employee performance appraisal reports quickly and clearly so that more effective and efficient.
TL;DR: In this article, a solar radiation map is provided of all Jordan governorates and a solar energy potential in Jordan is enormous as it lies within the solar belt of the world with average solar radiation between 4 and 8 KWh/m2, which implies a potential of 1400-2300 GWh per year annually.
Abstract: The solar energy potential in Jordan is enormous as it lies within the solar belt of the world with average solar radiation between 4 and 8 KWh/m2, which implies a potential of 1400-2300 GWh per year annually. Electricity demand in Jordan plays a significant role in the high amount of energy consumption to cover the needs of heating, cooling, lighting, etc. For that, the availability of the solar radiation information becomes essential to help in the design and building of the solar energy application. In this study, a solar radiation map is provided of all Jordan governorates.
TL;DR: In this paper, the authors proposed an environmental (a minimum instream) flow of 145 cms and several engineering works on the lower parts of the Euphrates and the Tigris rivers to assure the delivery of the proposed flow.
Abstract: Shatt al-Arab River is originated at the confluence of Tigris and Euphrates in al-Qurna town in southern Iraq. Two other tributaries; the Karun and the Karkheh rivers; join the river downstream from the eastern bank. The length of Shatt al-Arab is about 192 km from its origin to its mouth in the Gulf. The width of the Shatt varies between 250 m at Qurna and 750 m at its mouth at Rass al-Bisha. The salinity of Shat al-Arab has increased steadily for the last four decades. High salinity of the shatt waters hindered their use and made them unfit for most domestic, agricultural and industrial uses. Salinity as high as 18500 ppm was recorded in the City of Basra on the year 2009. The prime cause of the salinity problem is the reduction of fresh water inflow from all the contributing rivers; the high salinity of the inflow from the Euphrates; the marshes; and Garmat Ali River. The research paper recommends an environmental (a minimum instream) flow of 145 cms and several engineering works on the lower parts of the Euphrates and the Tigris rivers to assure the delivery of the proposed flow.