Search results for: process performance index.

Authors: Maíra O. Palm, Cintia Marangoni, Ozair Souza, Noeli Sellin

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Wastes from a vegetal extracts industry (cocoa, oak, Guarana and mate) were characterized by particle size, proximate and ultimate analysis, lignocellulosic fractions, high heating value, thermal analysis (Thermogravimetric analysis – TGA, and Differential thermal analysis - DTA) and energy density to evaluate their potential as biomass in the form of briquettes for power generation. All wastes presented adequate particle sizes to briquettes production. The wastes showed high moisture content, requiring previous drying for use as briquettes. Cocoa and oak wastes had the highest volatile matter contents with maximum mass loss at 310 ºC and 450 ºC, respectively. The solvents used in the aroma extraction process influenced in the moisture content of the wastes, which was higher for mate due to water has been used as solvent. All wastes showed an insignificant loss mass after 565 °C, hence resulting in low ash content. High carbon and hydrogen contents and low sulfur and nitrogen contents were observed ensuring a low generation of sulfur and nitrous oxides. Mate and cocoa exhibited the highest carbon and lignin content, and high heating value. The dried wastes had high heating value, from 17.1 MJ/kg to 20.8 MJ/kg. The results indicate the energy potential of wastes for use as fuel in power generation.

Keywords: Agro-industrial waste, biomass, briquettes, combustion.

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Authors: Inder K. Purohit, M. Nazrul Islam, K. Vijayan Asari, Mohammad A. Karim

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A new target detection technique is presented in this paper for the identification of small boats in coastal surveillance. The proposed technique employs an adaptive progressive thresholding (APT) scheme to first process the given input scene to separate any objects present in the scene from the background. The preprocessing step results in an image having only the foreground objects, such as boats, trees and other cluttered regions, and hence reduces the search region for the correlation step significantly. The processed image is then fed to the shifted phase-encoded fringe-adjusted joint transform correlator (SPFJTC) technique which produces single and delta-like correlation peak for a potential target present in the input scene. A post-processing step involves using a peak-to-clutter ratio (PCR) to determine whether the boat in the input scene is authorized or unauthorized. Simulation results are presented to show that the proposed technique can successfully determine the presence of an authorized boat and identify any intruding boat present in the given input scene.

Keywords: Adaptive progressive thresholding, fringe adjusted filters, image segmentation, joint transform correlation, synthetic discriminant function

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Authors: Abdolghani Ebrahimi, Diego Klabjan, Chenxi Ge, Daniela Ladner, Parker Stride

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In this work, we use machine learning and data analysis techniques to predict the one-year mortality of cirrhotic patients. Data from 2,322 patients with liver cirrhosis are collected at a single medical center. Different machine learning models are applied to predict one-year mortality. A comprehensive feature space including demographic information, comorbidity, clinical procedure and laboratory tests is being analyzed. A temporal pattern mining technic called Frequent Subgraph Mining (FSM) is being used. Model for End-stage liver disease (MELD) prediction of mortality is used as a comparator. All of our models statistically significantly outperform the MELD-score model and show an average 10% improvement of the area under the curve (AUC). The FSM technic itself does not improve the model significantly, but FSM, together with a machine learning technique called an ensemble, further improves the model performance. With the abundance of data available in healthcare through electronic health records (EHR), existing predictive models can be refined to identify and treat patients at risk for higher mortality. However, due to the sparsity of the temporal information needed by FSM, the FSM model does not yield significant improvements. Our work applies modern machine learning algorithms and data analysis methods on predicting one-year mortality of cirrhotic patients and builds a model that predicts one-year mortality significantly more accurate than the MELD score. We have also tested the potential of FSM and provided a new perspective of the importance of clinical features.

Keywords: machine learning, liver cirrhosis, subgraph mining, supervised learning

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Authors: R. Parameshwaran, R. Karunakaran, S. Iniyan, Anand A. Samuel

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The objective of this study is to present the test results of variable air volume (VAV) air conditioning system optimized by two objective genetic algorithm (GA). The objective functions are energy savings and thermal comfort. The optimal set points for fuzzy logic controller (FLC) are the supply air temperature (Ts), the supply duct static pressure (Ps), the chilled water temperature (Tw), and zone temperature (Tz) that is taken as the problem variables. Supply airflow rate and chilled water flow rate are considered to be the constraints. The optimal set point values are obtained from GA process and assigned into fuzzy logic controller (FLC) in order to conserve energy and maintain thermal comfort in real time VAV air conditioning system. A VAV air conditioning system with FLC installed in a software laboratory has been taken for the purpose of energy analysis. The total energy saving obtained in VAV GA optimization system with FLC compared with constant air volume (CAV) system is expected to achieve 31.5%. The optimal duct static pressure obtained through Genetic fuzzy methodology attributes to better air distribution by delivering the optimal quantity of supply air to the conditioned space. This combination enhanced the advantages of uniform air distribution, thermal comfort and improved energy savings potential.

Keywords: Energy savings, fuzzy logic, Genetic algorithm, Thermal Comfort

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Authors: Satyanadh Gundimada, Vijayan K Asari

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A novel feature selection strategy to improve the recognition accuracy on the faces that are affected due to nonuniform illumination, partial occlusions and varying expressions is proposed in this paper. This technique is applicable especially in scenarios where the possibility of obtaining a reliable intra-class probability distribution is minimal due to fewer numbers of training samples. Phase congruency features in an image are defined as the points where the Fourier components of that image are maximally inphase. These features are invariant to brightness and contrast of the image under consideration. This property allows to achieve the goal of lighting invariant face recognition. Phase congruency maps of the training samples are generated and a novel modular feature selection strategy is implemented. Smaller sub regions from a predefined neighborhood within the phase congruency images of the training samples are merged to obtain a large set of features. These features are arranged in the order of increasing distance between the sub regions involved in merging. The assumption behind the proposed implementation of the region merging and arrangement strategy is that, local dependencies among the pixels are more important than global dependencies. The obtained feature sets are then arranged in the decreasing order of discriminating capability using a criterion function, which is the ratio of the between class variance to the within class variance of the sample set, in the PCA domain. The results indicate high improvement in the classification performance compared to baseline algorithms.

Keywords: Discriminant analysis, intra-class probability distribution, principal component analysis, phase congruency.

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Authors: Mohammed Shatnawi, Qusai Abuein, Susumu Shibusawa

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Signature amortization schemes have been introduced for authenticating multicast streams, in which, a single signature is amortized over several packets. The hash value of each packet is computed, some hash values are appended to other packets, forming what is known as hash chain. These schemes divide the stream into blocks, each block is a number of packets, the signature packet in these schemes is either the first or the last packet of the block. Amortization schemes are efficient solutions in terms of computation and communication overhead, specially in real-time environment. The main effictive factor of amortization schemes is it-s hash chain construction. Some studies show that signing the first packet of each block reduces the receiver-s delay and prevents DoS attacks, other studies show that signing the last packet reduces the sender-s delay. To our knowledge, there is no studies that show which is better, to sign the first or the last packet in terms of authentication probability and resistance to packet loss. In th is paper we will introduce another scheme for authenticating multicast streams that is robust against packet loss, reduces the overhead, and prevents the DoS attacks experienced by the receiver in the same time. Our scheme-The Multiple Connected Chain signing the First packet (MCF) is to append the hash values of specific packets to other packets,then append some hashes to the signature packet which is sent as the first packet in the block. This scheme is aspecially efficient in terms of receiver-s delay. We discuss and evaluate the performance of our proposed scheme against those that sign the last packet of the block.

Keywords: multicast stream authentication, hash chain construction, signature amortization, authentication probability.

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Authors: Javier Roca, Etienne Pugnaghi, Gaëtan Libert

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We introduce an extended resource leveling model that abstracts real life projects that consider specific work ranges for each resource. Contrary to traditional resource leveling problems this model considers scarce resources and multiple objectives: the minimization of the project makespan and the leveling of each resource usage over time. We formulate this model as a multiobjective optimization problem and we propose a multiobjective genetic algorithm-based solver to optimize it. This solver consists in a two-stage process: a main stage where we obtain non-dominated solutions for all the objectives, and a postprocessing stage where we seek to specifically improve the resource leveling of these solutions. We propose an intelligent encoding for the solver that allows including domain specific knowledge in the solving mechanism. The chosen encoding proves to be effective to solve leveling problems with scarce resources and multiple objectives. The outcome of the proposed solvers represent optimized trade-offs (alternatives) that can be later evaluated by a decision maker, this multi-solution approach represents an advantage over the traditional single solution approach. We compare the proposed solver with state-of-art resource leveling methods and we report competitive and performing results.

Keywords: Intelligent problem encoding, multiobjective decision making, evolutionary computing, RCPSP, resource leveling.

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Authors: Yesubai Rubavathi Charles, Ravi Ramraj

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In order to retrieve images efficiently from a large database, a unique method integrating color and texture features using genetic programming has been proposed. Opponent color histogram which gives shadow, shade, and light intensity invariant property is employed in the proposed framework for extracting color features. For texture feature extraction, fast discrete curvelet transform which captures more orientation information at different scales is incorporated to represent curved like edges. The recent scenario in the issues of image retrieval is to reduce the semantic gap between user’s preference and low level features. To address this concern, genetic algorithm combined with relevance feedback is embedded to reduce semantic gap and retrieve user’s preference images. Extensive and comparative experiments have been conducted to evaluate proposed framework for content based image retrieval on two databases, i.e., COIL-100 and Corel-1000. Experimental results clearly show that the proposed system surpassed other existing systems in terms of precision and recall. The proposed work achieves highest performance with average precision of 88.2% on COIL-100 and 76.3% on Corel, the average recall of 69.9% on COIL and 76.3% on Corel. Thus, the experimental results confirm that the proposed content based image retrieval system architecture attains better solution for image retrieval.

Keywords: Content based image retrieval, Curvelet transform, Genetic algorithm, Opponent color histogram, Relevance feedback.

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Authors: M. Yadegari

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The thyroid gland is the largest classic endocrine organ that effects many organs of the body and plays a significant role in the process of Metabolism in animals. The aim of this study was to investigate the prevalence of thyroid disorders diagnosed by ultrasound and microscopic Lesions of the thyroid during the slaughter of apparently healthy One Humped Camels (Camelus dromedarius) in Iran. Randomly, 520 male camels (With an age range of 4 to 8 years), were studied in 2012 to 2013. The Camels’ thyroid glands were evaluated by sonographic examination. In both longitudinal and transverse view and then tissue sections were provide and stained with H & E and finally examined by light microscopy. The results obtained indicated the following: hyperplastic goiter (21%), degenerative changes (12%), follicular cysts (8%), follicular atrophy (4%), nodular hyperplasia (3%), adenoma (1%), carcinoma (1%) and simple goiter colloid (1%). Ultrasound evaluation of thyroid gland in adenoma and carcinoma showed enlargement and irregular of the gland, decreased echogenicity, and the heterogeneous thyroid parenchyma. Also, in follicular cysts were observed in the enlarged gland with no echo structures of different sizes and decreased echogenicity as a local or general. In nodular hyperplasia, increase echogenicity and heterogeneous parenchymal were seen. These findings suggest the use of sonography and pathology as a screening test in the diagnosis of complications of thyroid disorders.

Keywords: One humped camel, pathology, sonography, thyroid gland.

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Authors: N. Gigauri, V. Kukhalashvili, A. Surmava, L. Intskirveli, L. Gverdtsiteli

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Tbilisi, a large city of the South Caucasus, is a junction point connecting Asia and Europe, Russia and republics of the Asia Minor. Over the last years, its atmosphere has been experienced an increasing anthropogenic load. Numerical modeling method is used for study of Tbilisi atmospheric air pollution. By means of 3D non-linear non-steady numerical model a peculiarity of city atmosphere pollution is investigated during background western light air. Dust concentration spatial and time changes are determined. There are identified the zones of high, average and less pollution, dust accumulation areas, transfer directions etc. By numerical modeling, there is shown that the process of air pollution by the dust proceeds in four stages, and they depend on the intensity of motor traffic, the micro-relief of the city, and the location of city mains. In the interval of time 06:00-09:00 the intensive growth, 09:00-15:00 a constancy or weak decrease, 18:00-21:00 an increase, and from 21:00 to 06:00 a reduction of the dust concentrations take place. The highly polluted areas are located in the vicinity of the city center and at some peripherical territories of the city, where the maximum dust concentration at 9PM is equal to 2 maximum allowable concentrations. The similar investigations conducted in case of various meteorological situations will enable us to compile the map of background urban pollution and to elaborate practical measures for ambient air protection.

Keywords: Numerical modelling, source of pollution, dust propagation, western light air.

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Authors: Lāsma Cielava, Daina Jonkus, Līga Paura

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The age of first calving (AFC) is one of the most important factors that have a significant impact on cow productivity in different lactations and its whole life. A belated AFC leads to reduced reproductive performance and it is one of the main reasons for reduced longevity. Cows that calved in time period from 2001-2007 and in this time finished at least four lactations were included in the database. Data were obtained from 68841 crossbred Holstein Black and White (HM), crossbred Latvian Brown (LB), and Latvian Brown genetic resources (LBGR) cows. Cows were distributed in four groups depending on age at first calving. The longest lifespan was conducted for LBGR cows, but they were also characterized with lowest lifetime milk yield and life day milk yield. HM breed cows had the shortest lifespan, but in the lifespan of 2862.2 days was obtained in average 37916.4 kg milk accordingly 13.2 kg milk in one life day. HM breed cows were also characterized with longer calving intervals (CI) in first four lactations, but LBGR cows had the shortest CI in the study group. Age at first calving significantly affected the length of CI in different lactations (p<0.05). HM cows that first time calved >30 months old in the fourth lactation had the longest CI in all study groups (421.4 days). The LBGR cows were characterized with the shortest CI, but there was slight increase in second and third lactation. Age at first calving had a significant impact on cows’ age in each calving time. In the analysis, cow group was conducted that cows with age at first calving <24 months or in average 580.5 days at the time of fifth calving were 2156.7 days (5.9 years) old, but cows with age at first calving >30 months (932.6 days) at the time of fifth calving were 2560.9 days (7.3 years) old.

Keywords: Age at first calving, calving interval, longevity, milk yield.

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Authors: Kyoung-jae Kim

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Recommender systems are usually regarded as an important marketing tool in the e-commerce. They use important information about users to facilitate accurate recommendation. The information includes user context such as location, time and interest for personalization of mobile users. We can easily collect information about location and time because mobile devices communicate with the base station of the service provider. However, information about user interest can-t be easily collected because user interest can not be captured automatically without user-s approval process. User interest usually represented as a need. In this study, we classify needs into two types according to prior research. This study investigates the usefulness of data mining techniques for classifying user need type for recommendation systems. We employ several data mining techniques including artificial neural networks, decision trees, case-based reasoning, and multivariate discriminant analysis. Experimental results show that CHAID algorithm outperforms other models for classifying user need type. This study performs McNemar test to examine the statistical significance of the differences of classification results. The results of McNemar test also show that CHAID performs better than the other models with statistical significance.

Keywords: Customer need type, Data mining techniques, Recommender system, Personalization, Mobile user.

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Authors: S. Jalaja, A. M. Vijaya Prakash

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Recursive combination of an algorithm based on Karatsuba multiplication is exploited to design a generalized transpose and parallel Finite Impulse Response (FIR) Filter. Mid-range Karatsuba multiplication and Carry Save adder based on Karatsuba multiplication reduce time complexity for higher order multiplication implemented up to n-bit. As a result, we design modified N-tap Transpose and Parallel Symmetric FIR Filter Structure using Karatsuba algorithm. The mathematical formulation of the FFA Filter is derived. The proposed architecture involves significantly less area delay product (APD) then the existing block implementation. By adopting retiming technique, hardware cost is reduced further. The filter architecture is designed by using 90 nm technology library and is implemented by using cadence EDA Tool. The synthesized result shows better performance for different word length and block size. The design achieves switching activity reduction and low power consumption by applying with and without retiming for different combination of the circuit. The proposed structure achieves more than a half of the power reduction by adopting with and without retiming techniques compared to the earlier design structure. As a proof of the concept for block size 16 and filter length 64 for CKA method, it achieves a 51% as well as 70% less power by applying retiming technique, and for CSA method it achieves a 57% as well as 77% less power by applying retiming technique compared to the previously proposed design.

Keywords: Carry save adder Karatsuba multiplication, mid-range Karatsuba multiplication, modified FFA, transposed filter, retiming.

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Authors: Chi-Fang Huang, Yun-Shiow Chen, Yun-Kung Chung

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In the past decade, artificial neural networks (ANNs) have been regarded as an instrument for problem-solving and decision-making; indeed, they have already done with a substantial efficiency and effectiveness improvement in industries and businesses. In this paper, the Back-Propagation neural Networks (BPNs) will be modulated to demonstrate the performance of the collaborative forecasting (CF) function of a Collaborative Planning, Forecasting and Replenishment (CPFR®) system. CPFR functions the balance between the sufficient product supply and the necessary customer demand in a Supply and Demand Chain (SDC). Several classical standard BPN will be grouped, collaborated and exploited for the easy implementation of the proposed modular ANN framework based on the topology of a SDC. Each individual BPN is applied as a modular tool to perform the task of forecasting SKUs (Stock-Keeping Units) levels that are managed and supervised at a POS (point of sale), a wholesaler, and a manufacturer in an SDC. The proposed modular BPN-based CF system will be exemplified and experimentally verified using lots of datasets of the simulated SDC. The experimental results showed that a complex CF problem can be divided into a group of simpler sub-problems based on the single independent trading partners distributed over SDC, and its SKU forecasting accuracy was satisfied when the system forecasted values compared to the original simulated SDC data. The primary task of implementing an autonomous CF involves the study of supervised ANN learning methodology which aims at making “knowledgeable" decision for the best SKU sales plan and stocks management.

Keywords: CPFR, artificial neural networks, global logistics, supply and demand chain.

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Authors: Oliver Marunțălu, Elena Elisabeta Manea, Lăcrămioara Diana Robescu, Mihai Necșoiu, Gheorghe Lăzăroiu, Dana Andreya Bondrea

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In order to obtain efficient pollutants removal in small-scale wastewater treatment plants, uniform water flow has to be achieved. The experimental setup, designed for treating high-load wastewater (leachate), consists of two aerobic biological reactors and a lamellar settler. Both biological tanks were aerated by using three different types of aeration systems - perforated pipes, membrane air diffusers and tube ceramic diffusers. The possibility of homogenizing the water mass with each of the air diffusion systems was evaluated comparatively. The oxygen concentration was determined by optical sensors with data logging. The experimental data was analyzed comparatively for all three different air dispersion systems aiming to identify the oxygen concentration variation during different operational conditions. The Oxygenation Capacity was calculated for each of the three systems and used as performance and selection parameter. The global mass transfer coefficients were also evaluated as important tools in designing the aeration system. Even though using the tubular porous diffusers leads to higher oxygen concentration compared to the perforated pipe system (which provides medium-sized bubbles in the aqueous solution), it doesn’t achieve the threshold limit of 80% oxygen saturation in less than 30 minutes. The study has shown that the optimal solution for the studied configuration was the radial air diffusers which ensure an oxygen saturation of 80% in 20 minutes. An increment of the values was identified when the air flow was increased.

Keywords: Flow, aeration, bioreactor, oxygen concentration.

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Authors: Seyyed Yasser Hashemi, Khalil Monfaredi

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Automatic transformation of paper documents into electronic documents requires document segmentation at the first stage. However, some parameters restrictions such as variations in character font sizes, different text line spacing, and also not uniform document layout structures altogether have made it difficult to design a general-purpose document layout analysis algorithm for many years. Thus in most previously reported methods it is inevitable to include these parameters. This problem becomes excessively acute and severe, especially in Persian/Arabic documents. Since the Persian/Arabic scripts differ considerably from the English scripts, most of the proposed methods for the English scripts do not render good results for the Persian scripts. In this paper, we present a novel parameter-free method for segmenting the Persian/Arabic document images which also works well for English scripts. This method segments the document image into maximal homogeneous regions and identifies them as texts and non-texts based on a pyramidal image structure. In other words the proposed method is capable of document segmentation without considering the character font sizes, text line spacing, and document layout structures. This algorithm is examined for 150 Arabic/Persian and English documents and document segmentation process are done successfully for 96 percent of documents.

Keywords: Persian/Arabic document, document segmentation, Pyramidal Image Structure, skew detection and correction.

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Authors: Sama’ila Idi Ningi, Abubakar Yusuf Dutse

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The banking sector poses a lot of problems in Nigeria in general and the non-oil export sector in particular. The banks' lack effectiveness in handling small, medium or long-term credit risk (lack of training of loan officers, lack of information on borrowers and absence of a reliable credit registry) results in non-oil exporters being burdened with high requirements, such as up to three years of financial statements, enough collateral to cover both the loan principal and interest (including a cash deposit that may be up to 30% of the loans' net present value), and to provide every detail of the international trade transaction in question. The stated problems triggered this research. Consequently, information on bank financing of non-oil exports was collected from 100 respondents from the 20 Deposit Money Banks (DMBs) in Nigeria. The data was analysed by the use of descriptive statistics correlation and regression. It is found that, Nigerian banks are participants in the financing of non-oil exports. Despite their participation, the rate of interest for credit extended to non-oil export is usually high, ranging between 15-20%. Small and medium sized non-oil export businesses lack the credit history for banks to judge them as reputable. Banks also consider the non-oil export sector very risky for investment. The banks actually do grant less credit than the exporters may require and therefore are not properly funded by banks. Banks grant very low volume of foreign currency loan in addition to, unfavorable exchange rate at which Naira is exchanged to the Dollar and other currencies in the country. This makes importation of inputs costly and negatively impacted on the non-oil export performance in Nigeria.

Keywords: Supply Side Factors, Bank Financing, Non-Oil Exports.

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Authors: Thossaporn Thossansin

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This paper presents the development of a mobile application for students at the Faculty of Information Technology, Rangsit University (RSU), Thailand. RSU upgrades an enrollment process by improving its information systems. Students can download the RSU APP easily in order to access the RSU substantial information. The reason of having a mobile application is to help students to access the system regardless of time and place. The objectives of this paper include: 1. To develop an application on iOS platform for those students at the Faculty of Information Technology, Rangsit University, Thailand. 2. To obtain the students’ perception towards the new mobile app. The target group is those from the freshman year till the senior year of the faculty of Information Technology, Rangsit University. The new mobile application, called as RSU APP, is developed by the department of Information Technology, Rangsit University. It contains useful features and various functionalities particularly on those that can give support to students. The core contents of the app consist of RSU’s announcement, calendar, events, activities, and ebook. The mobile app is developed on the iOS platform. The user satisfaction is analyzed from the interview data from 81 interviewees as well as a Google application like a Google form which 122 interviewees are involved. The result shows that users are satisfied with the application as they score it the most satisfaction level at 4.67 SD 0.52. The score for the question if users can learn and use the application quickly is high which is 4.82 SD 0.71. On the other hand, the lowest satisfaction rating is in the app’s form, apps lists, with the satisfaction level as 4.01 SD 0.45.

Keywords: Mobile application, development of mobile application, framework of mobile development, software development for mobile devices.

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Authors: O. Alelweet, S. Pavia

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In order to face current compelling environmental problems affecting the planet, the construction industry needs to adapt. It is widely acknowledged that there is a need for durable, high-performance, low-greenhouse gas emission binders that can be used as an alternative to Portland cement (PC) to lower the environmental impact of construction. Alkali activated materials (AAMs) are considered a more sustainable alternative to PC materials. The binders of AAMs result from the reaction of an alkali metal source and a silicate powder or precursor which can be a calcium silicate or an aluminosilicate-rich material. This paper evaluates the particle size, specific surface area, chemical and mineral composition and amorphousness of silicate materials (most industrial waste locally produced in Ireland and Saudi Arabia) to develop alkali-activated binders that can replace PC resources in specific applications. These include recycled ceramic brick, bauxite, illitic clay, fly ash and metallurgical slag. According to the results, the wastes are reactive and comply with building standards requirements. The study also evidenced that the reactivity of the Saudi bauxite (with significant kaolinite) can be enhanced on thermal activation; and high calcium in the slag will promote reaction; which should be possible with low alkalinity activators. The wastes evidenced variable water demands that will be taken into account for mixing with the activators. Finally, further research is proposed to further determine the reactive fraction of the clay-based precursors.

Keywords: Reactivity, water demand, alkali-activated materials, brick, bauxite, illitic clay, fly ash, slag.

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Authors: Hanadi Mubarak AL-Mubaraki, Michael Busler

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Innovation is the process of making changes, differences, and novelties in the products and services, adding values and business practices to create economic and social benefit. The purpose of this paper is to identify the strengths and weaknesses of innovation programs in developed and developing countries. We used a mixed-methods approach, quantitative as survey and qualitative as a multi-case study to examine innovation best practices in developed and developing countries. In addition, four case studies of innovation organisations based on the best practices and successful implementation in the developed and developing countries are selected for examination. The research findings provide guidance, suggestions, and recommendations for future implementation in developed and developing countries for practitioners such as policy makers, governments, funded organizations, and strategic institutions. In conclusion, innovation programs are vital tools for economic growth, knowledge, and technology transfer based on the several indicators such as creativity, entrepreneurship, role of government, role of university, strategic focus, new products, survival rate, job creation, start-up companies, and number of patents. The authors aim to conduct future research which will include a comparative study of innovation case studies between developed and developing countries for policy implications worldwide. The originality of this study makes a contribution to the current literature about the innovation best practice in developed and developing countries.

Keywords: Economic development, entrepreneurship, developed countries, innovation program.

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Authors: Oluyemi O. Awolusi, Abimbola M. Enitan, Sheena Kumari, Faizal Bux

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Nitrification is essential to biological processes designed to remove ammonia and/or total nitrogen. It removes excess nitrogenous compound in wastewater which could be very toxic to the aquatic fauna or cause serious imbalance of such aquatic ecosystem. Efficient nitrification is linked to an in-depth knowledge of the structure and dynamics of the nitrifying community structure within the wastewater treatment systems. In this study, molecular technique was employed for characterizing the microbial structure of activated sludge [ammonia oxidizing bacteria (AOB) and nitrite oxidizing bacteria (NOB)] in a municipal wastewater treatment with intention of linking it to the plant efficiency. PCR based phylogenetic analysis was also carried out. The average operating and environmental parameters as well as specific nitrification rate of plant was investigated during the study. During the investigation the average temperature was 23±1.5oC. Other operational parameters such as mixed liquor suspended solids and chemical oxygen demand inversely correlated with ammonia removal. The dissolved oxygen level in the plant was constantly lower than the optimum (between 0.24 and 1.267 mg/l) during this study. The plant was treating wastewater with influent ammonia concentration of 31.69 and 24.47 mg/L. The influent flow rates (ML/Day) was 96.81 during period. The dominant nitrifiers include: Nitrosomonas spp. Nitrobacter spp. and Nitrospira spp. The AOB had correlation with nitrification efficiency and temperature. This study shows that the specific ammonia oxidizing rate and the specific nitrate formation rates can serve as good indicator of the plant overall nitrification performance.

Keywords: Ammonia monooxygenase α-subunit (amoA) gene, ammonia-oxidizing bacteria (AOB), nitrite-oxidizing bacteria (NOB), specific nitrification rate, PCR.

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Authors: Rosa Buxeda, Lorenzo Saliceti-Piazza, Rodolfo J. Romañach, Luis Ríos, Sandra L. Maldonado-Ramírez

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Biopharmaceuticals manufacturing is one of the major economic activities worldwide. Ninety-three percent of the workforce in a biomanufacturing environment concentrates in production-related areas. As a result, strategic collaborations between industry and academia are crucial to ensure the availability of knowledgeable workforce needed in an economic region to become competitive in biomanufacturing. In the past decade, our institution has been a key strategic partner with multinational biotechnology companies in supplying science and engineering graduates in the field of industrial biotechnology. Initiatives addressing all levels of the educational pipeline, from K-12 to college to continued education for company employees have been established along a ten-year span. The Amgen BioTalents Program was designed to provide undergraduate science and engineering students with training in biomanufacturing. The areas targeted by this educational program enhance their academic development, since these topics are not part of their traditional science and engineering curricula. The educational curriculum involved the process of producing a biomolecule from the genetic engineering of cells to the production of an especially targeted polypeptide, protein expression and purification, to quality control, and validation. This paper will report and describe the implementation details and outcomes of the first sessions of the program.

Keywords: Biomanufacturing curriculum, interdisciplinary learning, workforce development, industry-academia partnering.

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Authors: Jerry Szatko, Edan L. Jorgensen, Stacia Jorgensen

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A crucial component to the success of any financial advising relationship is for the financial professional to understand the perceptions, preferences and thought-processes carried by the financial clients they serve. Armed with this information, financial professionals are more quickly able to understand how they can tailor their approach to best match the individual preferences and needs of each personal investor. Our research explores the use of a quantitative assessment tool in the financial services industry to assist in the identification of the personal investor’s consumer behaviors, especially in terms of financial risk tolerance, as it relates to their financial decision making. Through this process, the Unitifi Consumer Insight Tool (UCIT) was created and refined to capture and categorize personal investor financial behavioral categories and the financial personality tendencies of individuals prior to the initiation of a financial advisement relationship. This paper discusses the use of this tool to place individuals in one of four behavior-based financial risk tolerance categories. Our discoveries and research were aided through administration of a web-based survey to a group of over 1,000 individuals. Our findings indicate that it is possible to use a quantitative assessment tool to assist in predicting the behavioral tendencies of personal consumers when faced with consumer financial risk and decisions.

Keywords: Behavior based advising, behavioral finance, financial advising, financial advisor tools, financial risk tolerance.

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Authors: N. Guru Prasath, Sangjin Ma, Chang-Wan Kim

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A butterfly valve is a quarter turn valve which is used to control the flow of a fluid through a section of pipe. Generally, butterfly valve is used in wide range of applications such as water distribution, sewage, oil and gas plants. In particular, butterfly valve with larger diameter finds its immense applications in hydro power plants to control the fluid flow. In-lieu with the constraints in cost and size to run laboratory setup, analysis of large diameter values will be mostly studied by computational method which is the best and inexpensive solution. For fluid and structural analysis, CFD and FEM software is used to perform large scale valve analyses, respectively. In order to perform above analysis in butterfly valve, the CAD model has to recreate and perform mesh in conventional software’s for various dimensions of valve. Therefore, its limitation is time consuming process. In-order to overcome that issue, python code was created to outcome complete pre-processing setup automatically in Salome software. Applying dimensions of the model clearly in the python code makes the running time comparatively lower and easier way to perform analysis of the valve. Hence, in this paper, an attempt was made to study the fluid-structure interaction (FSI) of butterfly valves by varying the valve angles and dimensions using python code in pre-processing software, and results are produced.

Keywords: Butterfly valve, fluid-structure interaction, automatic CFD analysis, flow coefficient.

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Authors: Jalal M. Abdallah

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This paper presents an experimental investigation of transformer dielectric response and solid insulation water content. The dielectric response was carried out on the base of Hybrid Frequency Dielectric Spectroscopy and Polarization Current measurements method (FDS &PC). The calculation of the water content in paper is based on the water content in oil and the obtained equilibrium curves. A reference measurements were performed at equilibrium conditions for water content in oil and paper of transformer at different stable temperatures (25, 50, 60 and 70°C) to prepare references to evaluate the insulation behavior at the not equilibrium conditions. Some measurements performed at the different simulated normal working modes of transformer operation at the same temperature where the equilibrium conditions. The obtained results show that when transformer temperature is mach more than the its ambient temperature, the transformer temperature decreases immediately after disconnecting the transformer from the network and this temperature reduction influences the transformer insulation condition in the measuring process. In addition to the oil temperature at the near places to the sensors, the temperature uniformity in transformer which can be changed by a big change in the load of transformer before the measuring time will influence the result. The investigations have shown that the extremely influence of the time between disconnecting the transformer and beginning the measurements on the results. And the online monitoring for water content in paper measurements, on the basis of the oil water content on line monitoring and the obtained equilibrium curves. The measurements where performed continuously and for about 50 days without any disconnection in the prepared the adiabatic room.

Keywords: Conductivity, Moisture, Temperature, Oil-paperinsulation, Online monitoring, Water content in oil.

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Authors: Z. Mazrouei-Sebdani, A. Khoddami, H. Hadadzadeh, M. Zarrebini

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In this research, waterglass based aerogel powder was prepared by sol–gel process and ambient pressure drying. Inspired by limited dust releasing, aerogel powder was introduced to the PET electrospinning solution in an attempt to create required bulk and surface structure for the nanofibers to improve their hydrophobic and insulation properties. The samples evaluation was carried out by measuring density, porosity, contact angle, heat transfer, FTIR, BET, and SEM. According to the results, porous silica aerogel powder was fabricated with mean pore diameter of 24 nm and contact angle of 145.9º. The results indicated the usefulness of the aerogel powder confined into nanofibers to control surface roughness for manipulating superhydrophobic nanowebs with water contact angle of 147º. It can be due to a multi-scale surface roughness which was created by nanowebs structure itself and nanofibers surface irregularity in presence of the aerogels while a layer of fluorocarbon created low surface energy. The wettability of a solid substrate is an important property that is controlled by both the chemical composition and geometry of the surface. Also, a decreasing trend in the heat transfer was observed from 22% for the nanofibers without any aerogel powder to 8% for the nanofibers with 4% aerogel powder. The development of thermal insulating materials has become increasingly more important than ever in view of the fossil energy depletion and global warming that call for more demanding energysaving practices.

Keywords: Superhydrophobicity, Insulation, Sol-gel, Surface energy, Roughness.

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Authors: Kamel K. Alzboon, Khalid N.Mahasneh

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The aim of this work is to study the possible use of stone cutting sludge waste in concrete production, which would reduce both the environmental impact and the production cost .Slurry sludge was used a source of water in concrete production, which was obtained from Samara factory/Jordan, The physico-chemical and mineralogical characterization of the sludge was carried out to identify the major components and to compare it with the typical sand used to produce concrete. Samples analysis showed that 96% of slurry sludge volume is water, so it should be considered as an important source of water. Results indicated that the use of slurry sludge as water source in concrete production has insignificant effect on compression strength, while it has a sharp effect on the slump values. Using slurry sludge with a percentage of 25% of the total water content obtained successful concrete samples regarding slump and compression tests. To clarify slurry sludge, settling process can be used to remove the suspended solid. A settling period of 30 min. obtained 99% removal efficiency. The clarified water is suitable for using in concrete mixes, which reduce water consumption, conserve water recourses, increase the profit, reduce operation cost and save the environment. Additionally, the dry sludge could be used in the mix design instead of the fine materials with sizes < 160 um. This application could conserve the natural materials and solve the environmental and economical problem caused by sludge accumulation.

Keywords: Concrete, recycle, sludge, slurry waste, stone cutting waste, waste.

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Authors: Sharifah Sumayyah Engku Alwi, Masrah Azrifah Azmi Murad

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The development of the information technology and Internet has been transforming the healthcare industry. The internet is continuously accessed to seek for health information and there are variety of sources, including search engines, health websites, and social networking sites. Providing more and better information on health may empower individuals, however, ensuring a high quality and trusted health information could pose a challenge. Moreover, there is an ever-increasing amount of information available, but they are not necessarily accurate and up to date. Thus, this paper aims to provide an insight of the models and frameworks related to online health information seeking of consumers. It begins by exploring the definition of information behavior and information seeking to provide a better understanding of the concept of information seeking. In this study, critical factors such as performance expectancy, effort expectancy, and social influence will be studied in relation to the value of seeking health information. It also aims to analyze the effect of age, gender, and health status as the moderator on the factors that influence online health information seeking, i.e. trust and information quality. A preliminary survey will be carried out among the health professionals to clarify the research problems which exist in the real world, at the same time producing a conceptual framework. A final survey will be distributed to five states of Malaysia, to solicit the feedback on the framework. Data will be analyzed using SPSS and SmartPLS 3.0 analysis tools. It is hoped that at the end of this study, a novel framework that can improve online health information seeking is developed. Finally, this paper concludes with some suggestions on the models and frameworks that could improve online health information seeking.

Keywords: Information behavior, information seeking, online health information, technology acceptance model, the theory of planned behavior, UTAUT.

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Authors: Mojibul Sajjad, Mohammad G. Rasul, Md. Sharif Imam Ibne Amir

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The rate of natural gas dissociation from the Coal Matrix depends on depressurization of reservoir through removing of the cleat water from the coal seam. These waters are similar to brine and aged of very long years. For improving the connectivity through fracking /fracturing, high pressure liquids are pumped off inside the coal body. A significant quantity of accumulated water, a combined mixture of cleat water and fracking fluids (back flow water) is pumped out through gas well. In Queensland, Australia Coal Seam Gas (CSG) industry is in booming state and estimated of 30,000 wells would be active for CSG production forecasting life span of 30 years. Integrated water management along with water softening programs is practiced for subsequent treatment and later on discharge to nearby surface water catchment. Water treatment is an important part of the CSG industry. A case study on a CSG site and review on the test results are discussed for assessing the Standards & Practices for management of CSG by-product water and their subsequent disposal activities. This study was directed toward (i) water management and softening process in Spring Gully CSG field, (ii) Comparative analysis on experimental study and standards and (iii) Disposal of the treated water. This study also aimed for alternative usages and their impact on vegetation, living species as well as long term effects.

Keywords: Coal Seam Gas (CSG), Cleat Water, Hydro-Fracking, Desalination, Reverse Osmosis.

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Authors: David Halley, Tyra Oseng-Rees, Luca Pagano, Juan A Ferriz-Papi

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Recycled glass material is made from 100% recycled bottle glass and consumes less energy than re-melt technology. It also uses no additives in the manufacturing process allowing the recycled glass material, in principal, to go back to the recycling stream after end-of-use, contributing to the circular economy with a low ecological impact. The aim of this paper is to investigate the procedure for testing the recycled glass material for impact resistance, so it can be applied to pavements and other surfaces which are at risk of impact during service. A review of different impact test procedures for construction materials was undertaken, comparing methodologies and international standards applied to other materials such as natural stone, ceramics and glass. A drop weight impact testing machine was designed and manufactured in-house to perform these tests. As a case study, samples of the recycled glass material were manufactured with two different thicknesses and tested. The impact energy was calculated theoretically, obtaining results with 5 and 10 J. The results on the material were subsequently discussed. Improvements on the procedure can be made using high speed video technology to calculate velocity just before and immediately after the impact to know the absorbed energy. The initial results obtained in this procedure were positive although repeatability needs to be developed to obtain a correlation of results and finally be able to validate the procedure. The experiment with samples showed the practicality of this procedure and application to the recycled glass material impact testing although further research needs to be developed.

Keywords: Construction materials, drop weight impact, impact testing, recycled glass.

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