Search results for: permittivity measurement techniques

Authors: Peng Hao Wang, Garam Kim, Ronald Sterkenburg

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In composite manufacturing, the fabrication of tooling and tooling maintenance contributes to a large portion of the total cost. However, as the applications of composite materials continue to increase, there is also a growing demand for more tooling. The demand for more tooling places heavy emphasis on the industry’s ability to fabricate high quality tools while maintaining the tool’s cost effectiveness. One of the popular techniques of tool fabrication currently being developed utilizes additive manufacturing technology known as 3D printing. The popularity of 3D printing is due to 3D printing’s ability to maintain low material waste, low cost, and quick fabrication time. In this study, a team of Purdue University School of Aviation and Transportation Technology (SATT) faculty and students investigated the effectiveness of a 3D printed composite mold. A steel valve cover from an aircraft reciprocating engine was modeled utilizing 3D scanning and computer-aided design (CAD) to create a 3D printed composite mold. The mold was used to fabricate carbon fiber versions of the aircraft reciprocating engine valve cover. The carbon fiber valve covers were evaluated for dimensional accuracy and quality while the 3D printed composite mold was evaluated for durability and dimensional stability. The data collected from this study provided valuable information in the understanding of 3D printed composite molds, potential improvements for the molds, and considerations for future tooling design.

Keywords: Additive manufacturing, carbon fiber, composite tooling, molds.

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Authors: Mohammad Ali Jabraeil Jamali, Ahmad Khademzadeh

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The success of an electronic system in a System-on- Chip is highly dependent on the efficiency of its interconnection network, which is constructed from routers and channels (the routers move data across the channels between nodes). Since neither classical bus based nor point to point architectures can provide scalable solutions and satisfy the tight power and performance requirements of future applications, the Network-on-Chip (NoC) approach has recently been proposed as a promising solution. Indeed, in contrast to the traditional solutions, the NoC approach can provide large bandwidth with moderate area overhead. The selected topology of the components interconnects plays prime rule in the performance of NoC architecture as well as routing and switching techniques that can be used. In this paper, we present two generic NoC architectures that can be customized to the specific communication needs of an application in order to reduce the area with minimal degradation of the latency of the system. An experimental study is performed to compare these structures with basic NoC topologies represented by 2D mesh, Butterfly-Fat Tree (BFT) and SPIN. It is shown that Cluster mesh (CMesh) and MinRoot schemes achieves significant improvements in network latency and energy consumption with only negligible area overhead and complexity over existing architectures. In fact, in the case of basic NoC topologies, CMesh and MinRoot schemes provides substantial savings in area as well, because they requires fewer routers. The simulation results show that CMesh and MinRoot networks outperforms MESH, BFT and SPIN in main performance metrics.

Keywords: MinRoot, CMesh, NoC, Topology, Performance Evaluation

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Authors: Jameela Ali Alkrimi, Hamid A. Jalab, Loay E. George, Abdul Rahim Ahmad, Azizah Suliman, Karim Al-Jashamy

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Red blood cells (RBC) are the most common types of blood cells and are the most intensively studied in cell biology. The lack of RBCs is a condition in which the amount of hemoglobin level is lower than normal and is referred to as “anemia”. Abnormalities in RBCs will affect the exchange of oxygen. This paper presents a comparative study for various techniques for classifying the RBCs as normal or abnormal (anemic) using WEKA. WEKA is an open source consists of different machine learning algorithms for data mining applications. The algorithms tested are Radial Basis Function neural network, Support vector machine, and K-Nearest Neighbors algorithm. Two sets of combined features were utilized for classification of blood cells images. The first set, exclusively consist of geometrical features, was used to identify whether the tested blood cell has a spherical shape or non-spherical cells. While the second set, consist mainly of textural features was used to recognize the types of the spherical cells. We have provided an evaluation based on applying these classification methods to our RBCs image dataset which were obtained from Serdang Hospital - Malaysia, and measuring the accuracy of test results. The best achieved classification rates are 97%, 98%, and 79% for Support vector machines, Radial Basis Function neural network, and K-Nearest Neighbors algorithm respectively.

Keywords: K-Nearest Neighbors, Neural Network, Radial Basis Function, Red blood cells, Support vector machine.

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Authors: Lina Wu, Ye Li, Jia Liu

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We are interested in solving Liouville-type problems to explore constancy properties for maps or differential forms on Riemannian manifolds. Geometric structures on manifolds, the existence of constancy properties for maps or differential forms, and energy growth for maps or differential forms are intertwined. In this article, we concentrate on discovery of solutions to Liouville-type problems where manifolds are Euclidean spaces (i.e. flat Riemannian manifolds) and maps become real-valued functions. Liouville-type results of vanishing properties for functions are obtained. The original work in our research findings is to extend the q-energy for a function from finite in L^q space to infinite in non-L^q space by applying p-balanced technique where q = p = 2. Calculation skills such as Hölder's Inequality and Tests for Series have been used to evaluate limits and integrations for function energy. Calculation ideas and computational techniques for solving Liouville-type problems shown in this article, which are utilized in Euclidean spaces, can be universalized as a successful algorithm, which works for both maps and differential forms on Riemannian manifolds. This innovative algorithm has a far-reaching impact on research work of solving Liouville-type problems in the general settings involved with infinite energy. The p-balanced technique in this algorithm provides a clue to success on the road of q-energy extension from finite to infinite.

Keywords: Differential Forms, Hölder Inequality, Liouville-type problems, p-balanced growth, p-harmonic maps, q-energy growth, tests for series.

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Authors: Seyed Sina Khamesi, Rana Rafiei

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The extensive aeration process is widely used for wastewater treatment. However, due to the high energy consumption of this process, which is closely related to the issues of environmental sustainability and global climate change, this article presents a simple solution to reduce energy consumption in this process. The amount of required energy is one of the critical considerations for various wastewater treatment techniques. For this purpose, an industrial wastewater treatment plant and all energy-consumer equipment in terms of energy consumption have been analyzed. The investigations and measurements revealed that the aeration unit has the highest energy consumption rate. To address this, an innovative approach is proposed to reduce energy consumption in the identified high-consumer unit. The proposed solution involves introducing baffles to divide the tank into multiple parts and using a tank with a small width and long length to enhance the mixing process. This approach reduces the need for additional equipment and significantly lowers energy consumption. To thoroughly scrutinize the proposed solution and analyze the behavior of the multi-phase fluid inside the tank, the sewage flow has been modeled using the computational fluid dynamics (CFD) method. The study presents an optimal design for the aeration unit based on these findings. The results indicate that implementing the technique suggested in this article can decrease total energy consumption by 33.15% and can be applied to all types of biological treatment plants.

Keywords: Wastewater treatment, aeration, energy consumption, Computational Fluid Dynamics, activated sludge.

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Authors: M. McHugh, D. Lillis

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Mobile applications are being used to perform a wide variety of tasks in day-to-day life, ranging from checking email to controlling your home heating. Application developers have recognized the potential to transform a smart device into a medical device, by using a mobile medical application i.e. a mobile phone or a tablet. When initially conceived these mobile medical applications performed basic functions e.g. BMI calculator, accessing reference material etc.; however, increasing complexity offers clinicians and patients a range of functionality. As this complexity and functionality increases, so too does the potential risk associated with using such an application. Examples include any applications that provide the ability to inflate and deflate blood pressure cuffs, as well as applications that use patient-specific parameters and calculate dosage or create a dosage plan for radiation therapy. If an unapproved mobile medical application is marketed by a medical device organization, then they face significant penalties such as receiving an FDA warning letter to cease the prohibited activity, fines and possibility of facing a criminal conviction. Regulatory bodies have finalized guidance intended for mobile application developers to establish if their applications are subject to regulatory scrutiny. However, regulatory controls appear contradictory with the approaches taken by mobile application developers who generally work with short development cycles and very little documentation and as such, there is the potential to stifle further improvements due to these regulations. The research presented as part of this paper details how by adopting development techniques, such as agile software development, mobile medical application developers can meet regulatory requirements whilst still fostering innovation.

Keywords: Medical, mobile, applications, software Engineering, FDA, standards, regulations, agile.

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Authors: Anwaar Ahmed, Muhammad Bilal Khurshid, Samuel Labi

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The effect of trucks on the level of service is determined by considering passenger car equivalents (PCE) of trucks. The current version of Highway Capacity Manual (HCM) uses a single PCE value for all tucks combined. However, the composition of truck traffic varies from location to location; therefore, a single PCE value for all trucks may not correctly represent the impact of truck traffic at specific locations. Consequently, present study developed separate PCE values for single-unit and combination trucks to replace the single value provided in the HCM on different freeways. Site specific PCE values, were developed using concept of spatial lagging headways (that is the distance between rear bumpers of two vehicles in a traffic stream) measured from field traffic data. The study used data from four locations on a single urban freeway and three different rural freeways in Indiana. Three-stage-leastsquares (3SLS) regression techniques were used to generate models that predicted lagging headways for passenger cars, single unit trucks (SUT), and combination trucks (CT). The estimated PCE values for single-unit and combination truck for basic urban freeways (level terrain) were: 1.35 and 1.60, respectively. For rural freeways the estimated PCE values for single-unit and combination truck were: 1.30 and 1.45, respectively. As expected, traffic variables such as vehicle flow rates and speed have significant impacts on vehicle headways. Study results revealed that the use of separate PCE values for different truck classes can have significant influence on the LOS estimation.

Keywords: Level of Service, Capacity Analysis, Lagging Headway.

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Authors: Enas Elsayed Abutaleb, Mohamed Taher Eldesoky, Shahenda Abd El Rasol

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Background: Muscle Energy Techniques (MET) have been widely used by manual therapists over the past years, but still limited research validated its use and there was limited evidence to substantiate the theories used to explain its effects. Objective: To investigate the effect of Muscle Energy Technique (MET) on anterior pelvic tilt in patients with lumbar spondylosis. Design: Randomized controlled trial. Subjects: Thirty patients with anterior pelvic tilt from both sexes were involved, aged between 35 to 50 years old and they were divided into MET and control groups with 15 patients in each. Methods: All patients received 3sessions/week for 4 weeks where the study group received MET, Ultrasound and Infrared, and the control group received U.S and I.R only. Pelvic angle was measured by palpation meter, pain severity by the visual analogue scale and functional disabilities by the Oswestry disability index. Results: Both groups showed significant improvement in all measured variables. The MET group was significantly better than the control group in pelvic angle, pain severity, and functional disability as p-value were (0.001, 0.0001, 0.0001) respectively. Conclusion and implication: the study group fulfilled greater improvement in all measured variables than the control group which implies that application of MET in combination with U.S and I.R were more effective in improving pelvic tilting angle, pain severity and functional disabilities than using electrotherapy only.

Keywords: Anterior pelvic tilt, lumbar spondylosis, muscle energy technique exercise, palpation meter.

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Authors: Omid A. Zargar

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Vibration analysis of most critical equipment is considered as one of the most challenging activities in preventive maintenance. Utilities are heart of the process in big industrial plants like petrochemical zones. Vibration analysis methods and condition monitoring systems of these kinds of equipments are developed too much in recent years. On the other hand, there are too much operation factors like inlet and outlet pressures and temperatures that should be monitored. In this paper, some of the most effective concepts and techniques related to gas turbine vibration analysis are discussed. In addition, a gas turbine SIEMENS 162MW - V94.2 vibration case history related to Iran power industry in Fars province is explained. Vibration monitoring system and machinery technical specification are introduced. Besides, absolute and relative vibration trends, turbine and compressor orbits, Fast Fourier transform (FFT) in absolute vibrations, vibration modal analysis, turbine and compressor start up and shut down conditions, bode diagrams for relative vibrations, Nyquist diagrams and waterfall or three-dimensional FFT diagrams in startup and trip conditions are discussed with relative graphs. Furthermore, Split Resonance in gas turbines is discussed in details. Moreover, some updated vibration monitoring system, blade manufacturing technique and modern damping mechanism are discussed in this paper.

Keywords: Gas turbine, turbine compressor, vibration data collector, utility, condition monitoring, non-contact probe, Relative Vibration, Absolute Vibration, Split Resonance, Time Wave Form (TWF), Fast Fourier transform (FFT).

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Authors: Erfan Niazi, Marianne Fenech

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Red Blood Cells (RBCs) or erythrocytes tend to form chain-like aggregates under low shear rate called rouleaux. This is a reversible process and rouleaux disaggregate in high shear rates. Therefore, RBCs aggregation occurs in the microcirculation where low shear rates are present but does not occur under normal physiological conditions in large arteries. Numerical modeling of RBCs interactions is fundamental in analytical models of a blood flow in microcirculation. Population Balance Modeling (PBM) is particularly useful for studying problems where particles agglomerate and break in a two phase flow systems to find flow characteristics. In this method, the elementary particles lose their individual identity due to continuous destructions and recreations by break-up and agglomeration. The aim of this study is to find RBCs aggregation in a dynamic situation. Simplified PBM was used previously to find the aggregation rate on a static observation of the RBCs aggregation in a drop of blood under the microscope. To find aggregation rate in a dynamic situation we propose an experimental set up testing RBCs sedimentation. In this test, RBCs interact and aggregate to form rouleaux. In this configuration, disaggregation can be neglected due to low shear stress. A high-speed camera is used to acquire video-microscopic pictures of the process. The sizes of the aggregates and velocity of sedimentation are extracted using an image processing techniques. Based on the data collection from 5 healthy human blood samples, the aggregation rate was estimated as 2.7x10³(±0.3 x10³) 1/s.

Keywords: Red blood cell, Rouleaux, microfluidics, image processing, population balance modeling.

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Authors: Mustafa M. Donma, Orkide Donma

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The impact of metabolic syndrome (MetS) on cognition and functions of the brain is being investigated. Iron deficiency and deficiencies of B9 (folate) as well as B12 (cobalamin) vitamins are best-known nutritional anemias. They are associated with cognitive disorders and learning difficulties. The antidepressant effects of vitamin D are known and the deficiency state affects mental functions negatively. The aim of this study is to investigate possible correlations of MetS with serum brain-derived neurotrophic factor (BDNF), iron, folate, cobalamin and vitamin D in pediatric patients. 30 children, whose age- and sex-dependent body mass index (BMI) percentiles vary between 85 and 15, 60 morbid obese children with above 99^th percentiles constituted the study population. Anthropometric measurements were taken. BMI values were calculated. Age- and sex-dependent BMI percentile values were obtained using the appropriate tables prepared by the World Health Organization (WHO). Obesity classification was performed according to WHO criteria. Those with MetS were evaluated according to MetS criteria. Serum BDNF was determined by enzyme-linked immunosorbent assay. Serum folate was analyzed by an immunoassay analyzer. Serum cobalamin concentrations were measured using electrochemiluminescence immunoassay. Vitamin D status was determined by the measurement of 25-hydroxycholecalciferol [25-hydroxy vitamin D3, 25(OH)D] using high performance liquid chromatography. Statistical evaluations were performed using SPSS for Windows, version 16. The p values less than 0.05 were accepted as statistically significant. Although statistically insignificant, lower folate and cobalamin values were found in MO children compared to those observed for children with normal BMI. For iron and BDNF values, no alterations were detected among the groups. Significantly decreased vitamin D concentrations were noted in MO children with MetS in comparison with those in children with normal BMI (p ≤ 0.05). The positive correlation observed between iron and BDNF in normal-BMI group was not found in two MO groups. In THE MetS group, the partial correlation among iron, BDNF, folate, cobalamin, vitamin D controlling for waist circumference and BMI was r = -0.501; p ≤ 0.05. None was calculated in MO and normal BMI groups. In conclusion, vitamin D should also be considered during the assessment of pediatric MetS. Waist circumference and BMI should collectively be evaluated during the evaluation of MetS in children. Within this context, BDNF appears to be a key biochemical parameter during the examination of obesity degree in terms of mental functions, cognition and learning capacity. The association observed between iron and BDNF in children with normal BMI was not detected in MO groups possibly due to development of inflammation and other obesity-related pathologies. It was suggested that this finding may contribute to mental function impairments commonly observed among obese children.

Keywords: Brain-derived neurotrophic factor, iron, Vitamin B9, Vitamin B12, Vitamin D.

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Authors: Jean Berger, Nassirou Lo, Martin Noel

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Perfectly suited for natural or man-made emergency and disaster management situations such as flood, earthquakes, tornadoes, or tsunami, multi-target search path planning for a team of rescue agents is known to be computationally hard, and most techniques developed so far come short to successfully estimate optimality gap. A novel mixed-integer linear programming (MIP) formulation is proposed to optimally solve the multi-target multi-agent discrete search and rescue (SAR) path planning problem. Aimed at maximizing cumulative probability of successful target detection, it captures anticipated feedback information associated with possible observation outcomes resulting from projected path execution, while modeling agent discrete actions over all possible moving directions. Problem modeling further takes advantage of network representation to encompass decision variables, expedite compact constraint specification, and lead to substantial problem-solving speed-up. The proposed MIP approach uses CPLEX optimization machinery, efficiently computing near-optimal solutions for practical size problems, while giving a robust upper bound obtained from Lagrangean integrality constraint relaxation. Should eventually a target be positively detected during plan execution, a new problem instance would simply be reformulated from the current state, and then solved over the next decision cycle. A computational experiment shows the feasibility and the value of the proposed approach.

Keywords: Search path planning, search and rescue, multi-agent, mixed-integer linear programming, optimization.

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Authors: Pankaj Gupta, Amit Kumar Srivastava, Nitesh Pandey

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This article explores the domain of generative design in order to enhance the development of robot designs for innovative and efficient maintenance approaches for tall buildings. This study aims to optimize the design of robotic hands by focusing on minimizing mass and volume while ensuring they can withstand the specified pressure with equal strength. The research procedure is structured and systematic. The purpose of optimization is to enhance the efficiency of the robot and reduce the manufacturing expenses. The project seeks to investigate the application of generative design in order to optimize products. Autodesk Fusion 360 offers the capability to immediately apply the generative design functionality to the solid model. The effort involved creating a solid model of the Smart Glass Cleaning Robot and optimizing one of its components, the Hand, using generative techniques. The article has thoroughly examined the designs, outcomes, and procedure. These loads serve as a benchmark for creating designs that can endure the necessary level of pressure and preserve their structural integrity. The efficacy of the generative design process is contingent upon the selection of materials, as different materials possess distinct physical attributes. The study utilizes five different materials, namely Steel, Stainless Steel, Titanium, Aluminum, and CFRP (Carbon Fiber Reinforced Polymer), in order to investigate a range of design possibilities.

Keywords: Generative design, mass and volume optimization, material strength analysis, generative design, smart glass cleaning robot.

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Authors: P. Selva, B. Lorrain, J. Alexis, A. Seror, A. Longuet, C. Mary, F. Denard

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Over the past four decades, the fatigue behavior of nickel-based alloys has been widely studied. However, in recent years, significant advances in the fabrication process leading to grain size reduction have been made in order to improve fatigue properties of aircraft turbine discs. Indeed, a change in particle size affects the initiation mode of fatigue cracks as well as the fatigue life of the material. The present study aims to investigate the fatigue behavior of a newly developed nickel-based superalloy under biaxial-planar loading. Low Cycle Fatigue (LCF) tests are performed at different stress ratios so as to study the influence of the multiaxial stress state on the fatigue life of the material. Full-field displacement and strain measurements as well as crack initiation detection are obtained using Digital Image Correlation (DIC) techniques. The aim of this presentation is first to provide an in-depth description of both the experimental set-up and protocol: the multiaxial testing machine, the specific design of the cruciform specimen and performances of the DIC code are introduced. Second, results for sixteen specimens related to different load ratios are presented. Crack detection, strain amplitude and number of cycles to crack initiation vs. triaxial stress ratio for each loading case are given. Third, from fractographic investigations by scanning electron microscopy it is found that the mechanism of fatigue crack initiation does not depend on the triaxial stress ratio and that most fatigue cracks initiate from subsurface carbides.

Keywords: Cruciform specimen, multiaxial fatigue, Nickelbased superalloy.

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Authors: S. Deswal, M. Pal

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Presently various computational techniques are used in modeling and analyzing environmental engineering data. In the present study, an intra-comparison of polynomial and radial basis kernel functions based on Support Vector Regression and, in turn, an inter-comparison with Multi Linear Regression has been attempted in modeling mass transfer capacity of vertical (θ = 90O) and inclined (θ multiple plunging jets (varying from 1 to 16 numbers). The data set used in this study consists of four input parameters with a total of eighty eight cases, forty four each for vertical and inclined multiple plunging jets. For testing, tenfold cross validation was used. Correlation coefficient values of 0.971 and 0.981 along with corresponding root mean square error values of 0.0025 and 0.0020 were achieved by using polynomial and radial basis kernel functions based Support Vector Regression respectively. An intra-comparison suggests improved performance by radial basis function in comparison to polynomial kernel based Support Vector Regression. Further, an inter-comparison with Multi Linear Regression (correlation coefficient = 0.973 and root mean square error = 0.0024) reveals that radial basis kernel functions based Support Vector Regression performs better in modeling and estimating mass transfer by multiple plunging jets.

Keywords: Mass transfer, multiple plunging jets, polynomial and radial basis kernel functions, Support Vector Regression.

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Authors: Hock Chuan, Lim

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This paper presents an approach for identifying interactive effects using Network Science (NS) supported by Social Network Analysis (SNA) techniques. Based on general observations that learning processes and behaviors are shaped by the social relationships and influenced by learning environment, the central idea was to understand both the human and non-human interactive effects for a blended learning mode of delivery of computer science modules. Important findings include (a) the importance of non-human nodes to influence the centrality and transfer; (b) the degree of non-human and human connectivity impacts learning. This project reveals that the NS pattern and connectivity as measured by node relationships offer alternative approach for hypothesis generation and design of qualitative data collection. An iterative process further reinforces the analysis, whereas the experimental simulation option itself is an interesting alternative option, a hybrid combination of both experimental simulation and qualitative data collection presents itself as a promising and viable means to study complex scenario such as blended learning delivery mode. The primary value of this paper lies in the design of the approach for studying interactive effects of human (social nodes) and non-human (learning/study environment, Information and Communication Technologies (ICT) infrastructures nodes) components. In conclusion, this project adds to the understanding and the use of SNA to model and study interactive effects in blended social learning.

Keywords: Blended learning, network science, social learning, social network analysis, study environment.

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Authors: Devanjan Bhattacharya, Jitka Komarkova

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The research describes the implementation of a novel and stand-alone system for dynamic hazard warning. The system uses all existing infrastructure already in place like mobile networks, a laptop/PC and the small installation software. The geospatial dataset are the maps of a region which are again frugal. Hence there is no need to invest and it reaches everyone with a mobile. A novel architecture of hazard assessment and warning introduced where major technologies in ICT interfaced to give a unique WebGIS based dynamic real time geohazard warning communication system. A never before architecture introduced for integrating WebGIS with telecommunication technology. Existing technologies interfaced in a novel architectural design to address a neglected domain in a way never done before – through dynamically updatable WebGIS based warning communication. The work publishes new architecture and novelty in addressing hazard warning techniques in sustainable way and user friendly manner. Coupling of hazard zonation and hazard warning procedures into a single system has been shown. Generalized architecture for deciphering a range of geo-hazards has been developed. Hence the developmental work presented here can be summarized as the development of internet-SMS based automated geo-hazard warning communication system; integrating a warning communication system with a hazard evaluation system; interfacing different open-source technologies towards design and development of a warning system; modularization of different technologies towards development of a warning communication system; automated data creation, transformation and dissemination over different interfaces. The architecture of the developed warning system has been functionally automated as well as generalized enough that can be used for any hazard and setup requirement has been kept to a minimum.

Keywords: Geospatial, web-based GIS, geohazard, warning system.

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Authors: O. Hassanein, Sreenatha G. Anavatti, Tapabrata Ray

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The dynamics of the Autonomous Underwater Vehicles (AUVs) are highly nonlinear and time varying and the hydrodynamic coefficients of vehicles are difficult to estimate accurately because of the variations of these coefficients with different navigation conditions and external disturbances. This study presents the on-line system identification of AUV dynamics to obtain the coupled nonlinear dynamic model of AUV as a black box. This black box has an input-output relationship based upon on-line adaptive fuzzy model and adaptive neural fuzzy network (ANFN) model techniques to overcome the uncertain external disturbance and the difficulties of modelling the hydrodynamic forces of the AUVs instead of using the mathematical model with hydrodynamic parameters estimation. The models- parameters are adapted according to the back propagation algorithm based upon the error between the identified model and the actual output of the plant. The proposed ANFN model adopts a functional link neural network (FLNN) as the consequent part of the fuzzy rules. Thus, the consequent part of the ANFN model is a nonlinear combination of input variables. Fuzzy control system is applied to guide and control the AUV using both adaptive models and mathematical model. Simulation results show the superiority of the proposed adaptive neural fuzzy network (ANFN) model in tracking of the behavior of the AUV accurately even in the presence of noise and disturbance.

Keywords: AUV, AUV dynamic model, fuzzy control, fuzzy modelling, adaptive fuzzy control, back propagation, system identification, neural fuzzy model, FLNN.

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Authors: Ajay Mandal, Achinta Bera

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Nanoemulsions are a class of emulsions with a droplet size in the range of 50–500 nm and have attracted a great deal of attention in recent years because it is unique characteristics. The physicochemical properties of nanoemulsion suggests that it can be successfully used to recover the residual oil which is trapped in the fine pore of reservoir rock by capillary forces after primary and secondary recovery. Oil-in-water nanoemulsion which can be formed by high-energy emulsification techniques using specific surfactants can reduce oil-water interfacial tension (IFT) by 3-4 orders of magnitude. The present work is aimed on characterization of oil-inwater nanoemulsion in terms of its phase behavior, morphological studies; interfacial energy; ability to reduce the interfacial tension and understanding the mechanisms of mobilization and displacement of entrapped oil blobs by lowering interfacial tension both at the macroscopic and microscopic level. In order to investigate the efficiency of oil-water nanoemulsion in enhanced oil recovery (EOR), experiments were performed to characterize the emulsion in terms of their physicochemical properties and size distribution of the dispersed oil droplet in water phase. Synthetic mineral oil and a series of surfactants were used to prepare oil-in-water emulsions. Characterization of emulsion shows that it follows pseudo-plastic behaviour and drop size of dispersed oil phase follows lognormal distribution. Flooding experiments were also carried out in a sandpack system to evaluate the effectiveness of the nanoemulsion as displacing fluid for enhanced oil recovery. Substantial additional recoveries (more than 25% of original oil in place) over conventional water flooding were obtained in the present investigation.

Keywords: Nanoemulsion, Characterization, Enhanced Oil Recovery, Particle Size Distribution

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Authors: R. E. Masto, L. C. Ram, S. K. Verma, V. A. Selvi, J. George, R. C. Tripathi, N. K. Srivastava, D. Mohanty, S. K.Jha, A. K. Sinha, A. Sinha

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There are many sources trough which the soil get enriched and contaminated with REEs. The determination of REEs in environmental samples has been limited because of the lack of sensitive analytical techniques. Soil samples were collected from four sites including open cast coal mine, natural coal burning, coal washery and control in the coal field located in Dhanbad, India. Total concentrations of rare earth elements (REEs) were determined using the inductively coupled plasma atomic absorption spectrometry in order to assess enrichment status in the coal field. Results showed that the mean concentrations of La, Pr, Eu, Tb, Ho, and Tm in open cast mine and natural coal burning sites were elevated compared to the reference concentrations, while Ce, Nd, Sm, and Gd were elevated in coal washery site. When compared to reference soil, heavy REEs (HREEs) were enriched in open cast mines and natural coal burning affected soils, however, the HREEs were depleted in the coal washery sites. But, the Chondrite-normalization diagram showed significant enrichment for light REEs (LREEs) in all the soils. High concentration of Pr, Eu, Tb, Ho, Tm, and Lu in coal mining and coal burning sites may pose human health risks. Factor analysis showed that distribution and relative abundance of REEs of the coal washery site is comparable with the control. Eventually washing or cleaning of coal could significantly decrease the emission of REEs from coal into the environment.

Keywords: Rare earth elements, coal, soil, factor analysis

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Authors: G. Feletti, D. Tedesco, P. Trucco

Abstract:

The present study aims to develop a dashboard of Key Performance Indicators (KPI) to enhance information and predictive capabilities in Emergency Medical Services (EMS) systems, supporting both operational and strategic decisions of different actors. The employed research methodology consists of a first phase of revision of the technical-scientific literature concerning the indicators currently in use for the performance measurement of EMS. It emerges that current studies focus on two distinct areas and independent objectives: the ambulance service, a fundamental component of pre-hospital health treatment, and the patient care in the Emergency Department (ED). Conversely, the perspective proposed by this study is to consider an integrated view of the ambulance service process and the ED process, both essential to ensure high quality of care and patient safety. Thus, the proposal covers the end-to-end healthcare service process and, as such, allows considering the interconnection between the two EMS processes, the pre-hospital and hospital ones, connected by the assignment of the patient to a specific ED. In this way, it is possible to optimize the entire patient management. Therefore, attention is paid even to EMS aspects that in current literature tend to be neglected or underestimated. In particular, the integration of the two processes enables to evaluate the advantage of an ED selection decision having visibility on EDs’ saturation status and therefore considering, besides the distance, the available resources and the expected waiting times. Starting from a critical review of the KPIs proposed in extant literature, the design of the dashboard was carried out: the high number of analyzed KPIs was reduced by eliminating firstly the ones not in line with the aim of the study and then the ones supporting a similar functionality. The KPIs finally selected were tested on a realistic dataset, which draw us to exclude additional indicators due to unavailability of data required for their computation. The final dashboard, that was discussed and validated by experts in the field, includes a variety of KPIs able to support operational and planning decisions, early warning, and citizens’ awareness on EDs accessibility in real time. The association of each KPI to the EMS phase it refers to enabled the design of a well-balanced dashboard, covering both efficiency and effectiveness performance objectives of the entire EMS process. Indeed, just the initial phases related to the interconnection between ambulance service and patient care are covered by traditional KPIs. Future developments could be directed to building a hierarchical dashboard, composed by a high-level minimal set of KPIs for measuring the basic performance of the EMS system, at an aggregate level, and lower levels of KPIs that bring additional and more detailed information on specific performance dimensions or EMS phases.

Keywords: Emergency Medical Services, Key Performance Indicators, Dashboard, Decision Support.

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Authors: Sepideh Samadzadehyazdi, Mohammad Javad Khalili, Sarvenaz Samadzadehyazdi, Mohammad Javad Mahdavinejad

Abstract:

The term ‘Windphil Architecture’ refers to the building that facilitates natural ventilation by architectural elements. Natural ventilation uses the natural forces of wind pressure and stacks effect to direct the movement of air through buildings. Natural ventilation is increasingly being used in contemporary buildings to minimize the consumption of non-renewable energy and it is an effective way to improve indoor air quality. The main objective of this paper is to identify the strategies of using natural ventilation in Iranian modern buildings. In this regard, the research method is ‘descriptive-analytical’ that is based on comparative techniques. To simulate wind flow in the interior spaces of case studies, FLUENT software has been used. Research achievements show that it is possible to use natural ventilation to create a thermally comfortable indoor environment. The natural ventilation strategies could be classified into two groups of environmental characteristics such as public space structure, and architectural characteristics including building form and orientation, openings, central courtyards, wind catchers, roof, wall wings, semi-open spaces and the heat capacity of materials. Having investigated modern buildings of Iran, innovative elements like wind catchers and wall wings are less used than the traditional architecture. Instead, passive ventilation strategies have been more considered in the building design as for the roof structure and openings.

Keywords: Natural ventilation strategies, wind catchers, wind flow, Iranian modern buildings.

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Authors: Mawloud Mosbah, Bachir Boucheham

Abstract:

Color Histogram is considered as the oldest method used by CBIR systems for indexing images. In turn, the global histograms do not include the spatial information; this is why the other techniques coming later have attempted to encounter this limitation by involving the segmentation task as a preprocessing step. The weak segmentation is employed by the local histograms while other methods as CCV (Color Coherent Vector) are based on strong segmentation. The indexation based on local histograms consists of splitting the image into N overlapping blocks or sub-regions, and then the histogram of each block is computed. The dissimilarity between two images is reduced, as consequence, to compute the distance between the N local histograms of the both images resulting then in N*N values; generally, the lowest value is taken into account to rank images, that means that the lowest value is that which helps to designate which sub-region utilized to index images of the collection being asked. In this paper, we make under light the local histogram indexation method in the hope to compare the results obtained against those given by the global histogram. We address also another noteworthy issue when Relying on local histograms namely which value, among N*N values, to trust on when comparing images, in other words, which sub-region among the N*N sub-regions on which we base to index images. Based on the results achieved here, it seems that relying on the local histograms, which needs to pose an extra overhead on the system by involving another preprocessing step naming segmentation, does not necessary mean that it produces better results. In addition to that, we have proposed here some ideas to select the local histogram on which we rely on to encode the image rather than relying on the local histogram having lowest distance with the query histograms.

Keywords: CBIR, Color Global Histogram, Color Local Histogram, Weak Segmentation, Euclidean Distance.

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Authors: A. Rajesh Kanna, G. Suresh Kumar, Sathyanaryana N. Gummadi

Abstract:

There are various sources of energies available worldwide and among them, crude oil plays a vital role. Oil recovery is achieved using conventional primary and secondary recovery methods. In-order to recover the remaining residual oil, technologies like Enhanced Oil Recovery (EOR) are utilized which is also known as tertiary recovery. Among EOR, Microbial enhanced oil recovery (MEOR) is a technique which enables the improvement of oil recovery by injection of bio-surfactant produced by microorganisms. Bio-surfactant can retrieve unrecoverable oil from the cap rock which is held by high capillary force. Bio-surfactant is a surface active agent which can reduce the interfacial tension and reduce viscosity of oil and thereby oil can be recovered to the surface as the mobility of the oil is increased. Research in this area has shown promising results besides the method is echo-friendly and cost effective compared with other EOR techniques. In our research, on laboratory scale we produced bio-surfactant using the strain Pseudomonas putida (MTCC 2467) and injected into designed simple sand packed column which resembles actual petroleum reservoir. The experiment was conducted in order to determine the efficiency of produced bio-surfactant in oil recovery. The column was made of plastic material with 10 cm in length. The diameter was 2.5 cm. The column was packed with fine sand material. Sand was saturated with brine initially followed by oil saturation. Water flooding followed by bio-surfactant injection was done to determine the amount of oil recovered. Further, the injection of bio-surfactant volume was varied and checked how effectively oil recovery can be achieved. A comparative study was also done by injecting Triton X 100 which is one of the chemical surfactant. Since, bio-surfactant reduced surface and interfacial tension oil can be easily recovered from the porous sand packed column.

Keywords: Bio-surfactant, Bacteria, Interfacial tension, Sand column.

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Authors: A. Abdullah, N. Faghih Mirzaei, S. Hany Haron

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Neighbourhood environment walkability on reported physical activity (PA) levels of students of Universiti Sains Malaysia (USM) in Malaysia. Compared with previous generations, today’s young people spend less time playing outdoors and have lower participation rates in PA. Research suggests that negative perceptions of neighbourhood walkability may be a potential barrier to adolescents’ PA. The sample consisted of 200 USM students (to 24 years old) who live outside of the main campus and engage in PA in sport halls and sport fields of USM. The data were analysed using the t-test, binary logistic regression, and discriminant analysis techniques. The present study found that youth PA was affected by neighbourhood environment walkability factors, including neighbourhood infrastructures, neighbourhood safety (crime), and recreation facilities, as well as street characteristics and neighbourhood design variables such as facades of sidewalks, roadside trees, green spaces, and aesthetics. The finding also illustrated that active students were influenced by street connectivity, neighbourhood infrastructures, recreation facilities, facades of sidewalks, and aesthetics, whereas students in the less active group were affected by access to destinations, neighbourhood safety (crime), and roadside trees and green spaces for their PAs. These results report which factors of built environments have more effect on youth PA and they message to the public to create more awareness about the benefits of PA on youth health.

Keywords: Fear of crime, neighbourhood built environment, physical activities, street characteristics design.

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Authors: H. Shayeghi, A. Jalili

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This paper presents a new Hybrid Fuzzy (HF) PID type controller based on Genetic Algorithms (GA-s) for solution of the Automatic generation Control (AGC) problem in a deregulated electricity environment. In order for a fuzzy rule based control system to perform well, the fuzzy sets must be carefully designed. A major problem plaguing the effective use of this method is the difficulty of accurately constructing the membership functions, because it is a computationally expensive combinatorial optimization problem. On the other hand, GAs is a technique that emulates biological evolutionary theories to solve complex optimization problems by using directed random searches to derive a set of optimal solutions. For this reason, the membership functions are tuned automatically using a modified GA-s based on the hill climbing method. The motivation for using the modified GA-s is to reduce fuzzy system effort and take large parametric uncertainties into account. The global optimum value is guaranteed using the proposed method and the speed of the algorithm-s convergence is extremely improved, too. This newly developed control strategy combines the advantage of GA-s and fuzzy system control techniques and leads to a flexible controller with simple stricture that is easy to implement. The proposed GA based HF (GAHF) controller is tested on a threearea deregulated power system under different operating conditions and contract variations. The results of the proposed GAHF controller are compared with those of Multi Stage Fuzzy (MSF) controller, robust mixed H2/H∞ and classical PID controllers through some performance indices to illustrate its robust performance for a wide range of system parameters and load changes.

Keywords: AGC, Hybrid Fuzzy Controller, Deregulated Power System, Power System Control, GAs.

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Authors: First G.M. Karthik, Second Ramachandra.V.Pujeri, Dr.

Abstract:

Generalized Center String (GCS) problem are generalized from Common Approximate Substring problem and Common substring problems. GCS are known to be NP-hard allowing the problems lies in the explosion of potential candidates. Finding longest center string without concerning the sequence that may not contain any motifs is not known in advance in any particular biological gene process. GCS solved by frequent pattern-mining techniques and known to be fixed parameter tractable based on the fixed input sequence length and symbol set size. Efficient method known as Bpriori algorithms can solve GCS with reasonable time/space complexities. Bpriori 2 and Bpriori 3-2 algorithm are been proposed of any length and any positions of all their instances in input sequences. In this paper, we reduced the time/space complexity of Bpriori algorithm by Constrained Based Frequent Pattern mining (CBFP) technique which integrates the idea of Constraint Based Mining and FP-tree mining. CBFP mining technique solves the GCS problem works for all center string of any length, but also for the positions of all their mutated copies of input sequence. CBFP mining technique construct TRIE like with FP tree to represent the mutated copies of center string of any length, along with constraints to restraint growth of the consensus tree. The complexity analysis for Constrained Based FP mining technique and Bpriori algorithm is done based on the worst case and average case approach. Algorithm's correctness compared with the Bpriori algorithm using artificial data is shown.

Keywords: Constraint Based Mining, FP tree, Data mining, GCS problem, CBFP mining technique.

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

Abstract:

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: S. Jalaja, A. M. Vijaya Prakash

Abstract:

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: Ahmad Ali Shahid, Muhammad Shakil Shaukat, Kamran Shehzad Bajwa, Abdul Qayyum Rao, Tayyab Husnain

Abstract:

Agriculture is the backbone of economy of Pakistan and cotton is the major agricultural export and supreme source of raw fiber for our textile industry. To combat severe problems of insect and weed, combination of three genes namely Cry1Ac, Cry2A and EPSPS genes was transferred in locally cultivated cotton variety MNH-786 with the use of Agrobacterium mediated genetic transformation. The present study focused on the molecular screening of transgenic cotton plants at T3 generation in order to confirm integration and expression of all three genes (Cry1Ac, Cry2A and EPSP synthase) into the cotton genome. Initially, glyphosate spray assay was used for screening of transgenic cotton plants containing EPSP synthase gene at T3 generation. Transgenic cotton plants which were healthy and showed no damage on leaves were selected after 07 days of spray. For molecular analysis of transgenic cotton plants in the laboratory, the genomic DNA of these transgenic cotton plants were isolated and subjected to amplification of the three genes. Thus, seventeen out of twenty (Cry1Ac gene), ten out of twenty (Cry2A gene) and all twenty (EPSP synthase gene) were produced positive amplification. On the base of PCR amplification, ten transgenic plant samples were subjected to protein expression analysis through ELISA. The results showed that eight out of ten plants were actively expressing the three transgenes. Real-time PCR was also done to quantify the mRNA expression levels of Cry1Ac and EPSP synthase gene. Finally, eight plants were confirmed for the presence and active expression of all three genes at T3 generation.

Keywords: Agriculture, Cotton, Transformation, Cry Genes, ELISA and PCR.

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