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|| Announcement ! || * CALL FOR PAPERS * Volume.3, Issue.4, Dec, 2019 is OPEN (Deadline for manuscript submission is Dec 05, 2018) < ESTIRJ-Engineering Science and Technology International Research Journal is scholarly blind peer review multidisciplinary International Journal (ISSN: (e) 2520-7393 (p) 2521-5027)||

ESTIRJ Volume 3, Issue 3 Sept 2019

Paper 1: COMPUTER ASSISTED DETECTION OF ELBOW DEFORMATION IN DIGITAL X-RAYS(1-7)

Abstract: Bones play a vital role in human skeleton and a large amount of emergency department visits are related with orthopedic abnormalities. Among these, one common issue of visit is elbow deformation which can be easily diagnosed through X-ray images. In this worth, we have anticipated an approach for digitizing the deformation detection in elbow X-ray images. The technique is practiced on publically available MURA dataset for elbow X-ray images. Initially, the images available in dataset for elbow X-ray were labelled and pre-processed. Later, by using 3-class probabilistic segmentation we have suppressed the background and flash in the image. Finally, we have extracted our region of interest that is the elbow bone. Moreover, using edge detection method we have distinguished the bone from the background and detected the capitulum inside elbow bone where two other bones are connected. Subsequently, with respect to capitulum, we have recorded intensity for different bone to categorize them as normal or abnormal. The technique is practiced on the available dataset and the efficiency around 82% has been scrutinized.

Author 1: Mashal Afzal
Author 2: M. Moazzam Jawaid
Author 3: Dr. Shahnawaz Talpur

Keywords: Data Acquisition; Image enhancement; Object Segmentation; Edge detection; Circle detection; Deformation Detection

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Paper 2:USE OF SUGARCANE BAGASSE ASH AS A FINE AGGREGATE IN CEMENT CONCRETE (8-11)

Abstract:In this experimental study, Sugarcane bagasse ash (SCBA) was used as a partial simulation for fine aggregate in concrete to reduce its cost, and different processing methods using agricultural/industrial waste were formed. The main focus of this research work was to examine the fresh property and mechanical (compressive strength and splitting tensile strength ) concrete properties by replacing 0%, 10%, 20%, 30% and 40% of SCBA by dry weight of fine aggregates. A total of 60 concrete cylinders were prepared with 1:2:4 proportion with 0.50 water-cement ratio and immerged in water on 7 and 28 days. Finally, these concrete cylinders were tested on UTM. Three concrete samples were cast for each proportion and ultimately the average of the three concrete samples was taken as the final result. The slump value of concrete decreased with increases in the amount of SCBA in cement concrete. The results analyzed that the compressive and tensile strength of the concrete samples increased by 7.90 % and 14% at 10% of SCBA as sand substitute materials in cement concrete after 28 days)

Author 1: Ali Aizaz Dayo
Author 2: Dr. Aneel Kumar
Author 3: Anees Raja/div>

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Paper 3: SIMULATION OF CELLULOSE ACETATE MEMBRANE MODULE FOR CO2 SEPARATION FROM NATURAL GAS(12-18)

Abstract: In this work, a mathematical numeric model is suggested to estimate the CO2 separation from CH4/CO2 gas mixture via solution diffusion method using Cellulose Acetate based polymer membrane via CFD approach by means of numerical finite element method in order solve the principal equation of model. Influence of various parameters on removal efficiency of CO2 from the mixture is investigated. The achieved modelling results then matched with the available industrial data to confirm the validation of the model results. Comparison of simulation extracted data with industrial results shown that the established model can calculate the CO2 removal performance. Results indicated that increment of gas flow rate and inlet gas temperature reduces the of CO2 removal efficiency. In contrast, CO2 removal efficiency can be augmented by increasing the membrane area requirement.

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Paper 4:BIOENERGY; AN ALTERNATIVE ENERGY SOURCE FOR THE BANANA VALUE ADDITION IN DISTRICT KHAIRPUR, PAKISTAN (19-22)

Abstract: Agroindustry plays a significant role in agricultural and industrial relationship, but it is badly affected by energy crisis. Case study taken in research work is about this problem. Bioenergy system resulted as potential alternative energy source that can fill the energy requirements of value addition of agricultural commodities. 2.42 cubic meter (2.5 kg) biogas produced from 102 kg concentrated slurry of banana waste/ biomass. The generated amount of biogas in batch digester biogas plant gives 97 minutes burning time which is sufficient for steaming and frying processes of banana value addition. Other processes such as drying, grinding, de-oiling and flavour mixing involved electricity which can be generated with large amount of biogas through flow thru/ continuous type biogas plants on daily basis. Experiment was conducted in Government established banana value addition facility which can process daily 04 bunches of bananas. The daily banana waste generated in the centre is utilized in this experiment.

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Paper 5: PREDICTING KSE 100 INDEX BY USING ARTIFICIAL NEURAL NETWORK (23-29)

Abstract: Predicting a stock exchange movement is becoming a new trend. Nowadays in finance because if it is better predicted, investors will get a more exact or ideal predictions and carry economic benefits as well. Recently, an artificial neural network have been popularly used to prediction of Stock Exchange movements. The key objective of this paper is to predict stock exchange movements by using NARX model with the help of Neural Network toolbox Tests and MATLAB. This study uses a non-linear autoregressive network with exogenous inputs (NARX) for period of July 2008 to July 2017 and data gathered from Karachi Stock Exchange website. The set of training comprises of 70% of data, 15% of validation and 15% used for testing respectively. Results demonstrate that the KSE-100 Index is forecast successfully by using ANNs with NARX methodology. Hence, this model gives more accurate, effective and optimal results as compared to other neural networks.

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Paper 6: BANK CREDIT RISK ANALYSES USING MACHINE LEARNING ALGORITHMS (30-34)

Abstract: : : Earlier computers was just categorized as a want of an individual but now it becomes a need of an individual. Machine learning serves as a major part in field of computer, machine is not able to think over different situations but it can draw different sort of relationships between different features and characteristics. The major part of our life is to avoid fraudulent activities but till now we are unable to control over it. Loan business is one of the major businesses of commercial banks. Fraudulent activities can be handle through embedding machine learning algorithms in our daily life. In this research we have used supervised machine learning and for that we have to provide labeled data to the machine learning algorithm, and we have used SVM classifier algorithm. In this research we have analyze the credit data in different perspectives.

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Paper 7:ENERGY OPTIMIZATION FOR AMINE GAS SWEETENING PROCESS BY MIXED AMINES USING SIMULATIONS(35-40)

Abstract: Pakistan produces 26% of its energy through natural gas and this seems to be increasing every year. However, as natural gas is produced from deep underground reservoirs it contains significant amount of acid gas components as H2S and CO2. Natura gas sweetening through chemical absorption is a most commonly known process in gas processing industry which is known for its efficiency and capacity to remove acid gases however, the process requires heavy operating cost, which tend to be reduced by using various theoretical approaches to improve and optimize the process. It has been proved by different scholars about the positive effect of using blended or mixed amines on the efficiency of amine gas sweetening process in terms of acid gas removal and reduction in operation costs. This work reviews the current operation of Hala Gas Field, Tando Adam, Sindh. The facility processes gas from two wells Adam X-1 and Adam West X-1, both having different feed composition. The plant uses standardized MDEA 45% solution to treat natural gas. A model amine gas processing unit was developed using a simulator Aspen HYSYS to study the effects of using different amine blends to enhance the CO2 capture capacity of the plant incorporating the high reactivity of primary and secondary amines towards acid gases. The results conclude that by the use of these blends it is possible to increase CO2 capture capacity by 2.62%.

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Paper 8:COST ANALYSIS AND IMPLEMENTATION OF SMART GRID IN PAKISTAN (41-48)

Abstract: In Pakistan the transmission system has capacity of 22,000 MW and demand is 25,000MW, it means our present transmission system cannot bear more energy production. The renewable energy sources of Pakistan have the potential to generate the energy more than the demand. Renewable energy sources of Pakistan are hydropower, wind, solar and biomass. Also under the project of CPEC electricity of 10,400 MW will be added in the country. Rising population of Pakistan is increasing the demands of diapers; the recycling of waste diapers will produce 5000kcal/yr, energy which is useful for both industrial and domestic sectors. Main two problems of implementation of smart grids are cost and management. OELC method is used for calculating loads and costs; also OELC scheme proposes the solution to control the cost problems. Cost benefit analysis (CBA) give complete picture of investments and benefits. Case study with Pakistan’s potential for renewable sources is discussed. There is cost to benefit ratio of 1.9 for Pakistan, so this is cost effective process. As there are three main parts of electricity system (generation, distribution, billing), the smart planning at these parts will manage the whole system. Pakistan is at its initial level of implementation of smart grid so with the proper planning and mutual collaboration of departments will make Pakistan an energy abundant country.