Search results for: trans-european transport network

Authors: Nadia Hammouda, Kamel Belmokre

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Organic coatings are widely employed in the corrosion protection of most metal surfaces, particularly steel. They provide a barrier against corrosive species present in the environment, due to their high resistance to oxygen, water and ions transport. This study focuses on the evaluation of corrosion protection performance of epoxy paint on the carbon steel surface in sea water by Electrochemical Impedance Spectroscopy (EIS). The electrochemical behavior of painted surface was estimated by EIS parameters that contained paint film resistance, paint film capacitance and double layer capacitance. On the basis of calculation using EIS spectrums it was observed that pore resistance (Rpore) decreased with the appearance of doubled layer capacitance (Cdl) due to the electrolyte penetration through the film. This was further confirmed by the decrease of diffusion resistance (Rd) which was also the indicator of the deterioration of paint film protectiveness.

Keywords: epoxy paints, carbon steel, electrochemical impedance spectroscopy, corrosion mechanisms, sea water

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Authors: T. J. Jamaleddine

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Purge columns or degasser vessels are widely used in the polyolefin process for removing trapped hydrocarbons and in-excess catalyst residues from the polymer particles. A uniform distribution of purged gases coupled with a plug-flow characteristic inside the column system is desirable to obtain optimum desorption characteristics of trapped hydrocarbon and catalyst residues. Computational Fluid Dynamics (CFD) approach is a promising tool for design optimization of these vessels. The success of this approach is profoundly dependent on the solution strategy and the choice of geometrical layout at the vessel outlet. Filling the column with solids and initially solving for the solids flow minimized numerical diffusion substantially. Adopting a cylindrical configuration at the vessel outlet resulted in less numerical instability and resembled the hydrodynamics flow of solids in the hopper segment reasonably well.

Keywords: CFD, degasser vessel, gas-solids flow, gas purging, purge column, species transport

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Authors: Eiji Nakamachi, Ryota Sakiyama, Koji Yamamoto, Yusuke Morita, Hidetoshi Sakamoto

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The regeneration of injured central nerve network caused by the cerebrovascular accidents is difficult, because of poor regeneration capability of central nerve system composed of the brain and the spinal cord. Recently, new regeneration methods such as transplant of nerve cells and supply of nerve nutritional factor were proposed and examined. However, there still remain many problems with the canceration of engrafted cells and so on and it is strongly required to establish an efficacious treating method of a central nerve system. Blackman proposed the electromagnetic stimulation method to enhance the axonal nerve extension. In this study, we try to design and fabricate a new three-dimensional (3D) bio-reactor, which can load a uniform AC magnetic field stimulation on PC12 cells in the extracellular environment for enhancement of an axonal nerve extension and 3D nerve network generation. Simultaneously, we measure the morphology of PC12 cell bodies, axons, and dendrites by the multiphoton excitation fluorescence microscope (MPM) and evaluate the effectiveness of the uniform AC magnetic stimulation to enhance the axonal nerve extension. Firstly, we designed and fabricated the uniform AC magnetic field stimulation bio-reactor. For the AC magnetic stimulation system, we used the laminated silicon steel sheets for a yoke structure of 3D chamber, which had a high magnetic permeability. Next, we adopted the pole piece structure and installed similar specification coils on both sides of the yoke. We searched an optimum pole piece structure using the magnetic field finite element (FE) analyses and the response surface methodology. We confirmed that the optimum 3D chamber structure showed a uniform magnetic flux density in the PC12 cell culture area by using FE analysis. Then, we fabricated the uniform AC magnetic field stimulation bio-reactor by adopting analytically determined specifications, such as the size of chamber and electromagnetic conditions. We confirmed that measurement results of magnetic field in the chamber showed a good agreement with FE results. Secondly, we fabricated a dish, which set inside the uniform AC magnetic field stimulation of bio-reactor. PC12 cells were disseminated with collagen gel and could be 3D cultured in the dish. The collagen gel were poured in the dish. The collagen gel, which had a disk shape of 6 mm diameter and 3mm height, was set on the membrane filter, which was located at 4 mm height from the bottom of dish. The disk was full filled with the culture medium inside the dish. Finally, we evaluated the effectiveness of the uniform AC magnetic field stimulation to enhance the nurve axonal extension. We confirmed that a 6.8 increase in the average axonal extension length of PC12 under the uniform AC magnetic field stimulation at 7 days culture in our bio-reactor, and a 24.7 increase in the maximum axonal extension length. Further, we confirmed that a 60 increase in the number of dendrites of PC12 under the uniform AC magnetic field stimulation. Finally, we confirm the availability of our uniform AC magnetic stimulation bio-reactor for the nerve axonal extension and the nerve network generation.

Keywords: nerve regeneration, axonal extension , PC12 cell, magnetic field, three-dimensional bio-reactor

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Authors: Sam Bartlett, Thomas Bacquart, Arul Murugan, Abigail Morris

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Fuel cell electric vehicles provide the potential to decarbonise road transport, create new economic opportunities, diversify national energy supply, and significantly reduce the environmental impacts of road transport. A potential issue, however, is that the catalyst used at the fuel cell cathode is susceptible to degradation by impurities, especially sulphur-containing compounds. A recent European Directive (2014/94/EU) stipulates that, from November 2017, all hydrogen provided to fuel cell vehicles in Europe must comply with the hydrogen purity specifications listed in ISO 14687-2; this includes reactive and toxic chemicals such as ammonia and total sulphur-containing compounds. This requirement poses great analytical challenges due to the instability of some of these compounds in calibration gas standards at relatively low amount fractions and the difficulty associated with undertaking measurements of groups of compounds rather than individual compounds. Without the available reference materials and analytical infrastructure, hydrogen refuelling stations will not be able to demonstrate compliance to the ISO 14687 specifications. The hydrogen purity laboratory at NPL provides world leading, accredited purity measurements to allow hydrogen refuelling stations to evidence compliance to ISO 14687. Utilising state-of-the-art methods that have been developed by NPL’s hydrogen purity laboratory, including a novel method for measuring total sulphur compounds at 4 nmol/mol and a hydrogen impurity enrichment device, we provide the capabilities necessary to achieve these goals. An overview of these capabilities will be given in this paper. As part of the EMPIR Hydrogen co-normative project ‘Metrology for sustainable hydrogen energy applications’, NPL are developing a validated analytical methodology for the measurement of speciated sulphur-containing compounds in hydrogen at low amount fractions pmol/mol to nmol/mol) to allow identification and measurement of individual sulphur-containing impurities in real samples of hydrogen (opposed to a ‘total sulphur’ measurement). This is achieved by producing a suite of stable gravimetrically-prepared primary reference gas standards containing low amount fractions of sulphur-containing compounds (hydrogen sulphide, carbonyl sulphide, carbon disulphide, 2-methyl-2-propanethiol and tetrahydrothiophene have been selected for use in this study) to be used in conjunction with novel dynamic dilution facilities to enable generation of pmol/mol to nmol/mol level gas mixtures (a dynamic method is required as compounds at these levels would be unstable in gas cylinder mixtures). Method development and optimisation are performed using gas chromatographic techniques assisted by cryo-trapping technologies and coupled with sulphur chemiluminescence detection to allow improved qualitative and quantitative analyses of sulphur-containing impurities in hydrogen. The paper will review the state-of-the art gas standard preparation techniques, including the use and testing of dynamic dilution technologies for reactive chemical components in hydrogen. Method development will also be presented highlighting the advances in the measurement of speciated sulphur compounds in hydrogen at low amount fractions.

Keywords: gas chromatography, hydrogen purity, ISO 14687, sulphur chemiluminescence detector

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Authors: Fadwa Jewilli

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A sudden leak of a 6-inch gas line pipe after being in service for one year was observed. The pipe had been designed to transport dry gas. The failure had taken place in 6 o’clock position at the stage discharge of the flow process. Laboratory investigations were conducted to find out the cause of the pipe rupture. Visual and metallographic observations confirmed that the pipe split was due to a crack initiated in circumferential and then turned into longitudinal direction. Sever wall thickness reduction was noticed on the internal pipe surface. Scanning electron microscopy observations at the fracture surface revealed features of ductile fracture mode. Corrosion product analysis showed the traces of iron carbonate and iron sulphate. The laboratory analysis resulted in the conclusion that the pipe failed due to the effect of wet fluid (condensate) caused severe wall thickness dissolution resulted in pipe could not stand the continuation at in-service working condition.

Keywords: gas line pipe, corrosion prediction ductile fracture, ductile fracture, failure analysis

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Authors: Joanna Skopinska-Wisniewska, Anna Bajek, Marta Ziegler-Borowska, Alina Sionkowska

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Hydrogels are a class of materials widely used in medicine for many years. Proteins, such as collagen, due to the presence of a large number of functional groups are easily wettable by polar solvents and can create hydrogels. The supramolecular network capable to swelling is created by cross-linking of the biopolymers using various reagents. Many cross-linking agents has been tested for last years, however, researchers still are looking for a new, more secure reactants. Squaric acid, 3,4-dihydroxy 3-cyclobutene 1,2- dione, is a very strong acid, which possess flat and rigid structure. Due to the presence of two carboxyl groups the squaric acid willingly reacts with amino groups of collagen. The main purpose of this study was to investigate the influence of addition of squaric acid on the chemical, physical and biological properties of collagen materials. The collagen type I was extracted from rat tail tendons and 1% solution in 0.1M acetic acid was prepared. The samples were cross-linked by the addition of 5%, 10% and 20% of squaric acid. The mixtures of all reagents were incubated 30 min on magnetic stirrer and then dialyzed against deionized water. The FTIR spectra show that the collagen structure is not changed by cross-linking by squaric acid. Although the mechanical properties of the collagen material deteriorate, the temperature of thermal denaturation of collagen increases after cross-linking, what indicates that the protein network was created. The lyophilized collagen gels exhibit porous structure and the pore size decreases with the higher addition of squaric acid. Also the swelling ability is lower after the cross-linking. The in vitro study demonstrates that the materials are attractive for 3T3 cells. The addition of squaric acid causes formation of cross-ling bonds in the collagen materials and the transparent, stiff hydrogels are obtained. The changes of physicochemical properties of the material are typical for cross-linking process, except mechanical properties – it requires further experiments. However, the results let us to conclude that squaric acid is a suitable cross-linker for protein materials for medicine and tissue engineering.

Keywords: collagen, squaric acid, cross-linking, hydrogel

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Authors: Sangeeta Singh, Pankaj Kumar, P. N. Kondekar

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In this paper, the transient device performance analysis of n-type Gate Inside Junctionless Transistor (GIJLT)has been evaluated. 3-D Bohm Quantum Potential (BQP)transport device simulation has been used to evaluate the delay and power dissipation performance. GI-JLT has a number of desirable device parameters such as reduced propagation delay, dynamic power dissipation, power and delay product, intrinsic gate delay and energy delay product as compared to Gate-all-around transistors GAA-JLT. In addition to this, various other device performance parameters namely, on/off current ratio, short channel effects (SCE), transconductance Generation Factor(TGF) and unity gain cut-off frequency (fT) and subthreshold slope (SS) of the GI-JLT and Gate-all-around junctionless transistor(GAA-JLT) have been analyzed and compared. GI-JLT shows better device performance characteristics than GAA-JLT for low power and high frequency applications, because of its larger gate electrostatic control on the device operation.

Keywords: gate-inside junctionless transistor GI-JLT, gate-all-around junctionless transistor GAA-JLT, propagation delay, power delay product

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Authors: Salami Akeem Olanrewaju

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The transportation models or problems are primarily concerned with the optimal (best possible) way in which a product produced at different factories or plants (called supply origins) can be transported to a number of warehouses or customers (called demand destinations). The objective in a transportation problem is to fully satisfy the destination requirements within the operating production capacity constraints at the minimum possible cost. The objective of this study is to determine ways of minimizing transport cost in order to maximum profit. Data were gathered from the records of the Distribution Department of 7-Up Bottling Company Plc. Ilorin, Kwara State, Nigeria. The data were analyzed using SPSS (Statistical Package for Social Sciences) while applying the three methods of solving a transportation problem. The three methods produced the same results; therefore, any of the method can be adopted by the company in transporting its final products to the wholesale dealers in order to minimize total production cost.

Keywords: cost minimization, resources utilization, distribution system, allocation problem

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Authors: Mohammad Hossein Mohammadi Sanjani, Ashknaz Oraee, Oriol Gomis Bellmunt, Vinicius Albernaz Lacerda Freitas

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The use of distributed and renewable sources in power systems has grown significantly, recently. One the most popular sources are wind farms which have grown massively. However, ¬wind farms are connected to the grid, this can cause problems such as reduced voltage stability, frequency fluctuations and reduced dynamic stability. Variable speed generators (asynchronous) are used due to the uncontrollability of wind speed specially Doubley Fed Induction Generators (DFIG). The most important disadvantage of DFIGs is its sensitivity to voltage drop. In the case of faults, a large volume of reactive power is induced therefore, use of FACTS devices such as SVC and STATCOM are suitable for improving system output performance. They increase the capacity of lines and also passes network fault conditions. In this paper, in addition to modeling the reactive power control system in a DFIG with converter, FACTS devices have been used in a DFIG wind turbine to improve the stability of the power system containing two synchronous sources. In the following paper, recent optimal control systems have been designed to minimize fluctuations caused by system disturbances, for FACTS devices employed. For this purpose, a suitable method for the selection of nine parameters for MPSH-phase-post-phase compensators of reactive power compensators is proposed. The design algorithm is formulated ¬¬as an optimization problem searching for optimal parameters in the controller. Simulation results show that the proposed controller Improves the stability of the network and the fluctuations are at desired speed.

Keywords: renewable energy sources, optimization wind power plant, stability, reactive power compensator, double-feed induction generator, optimal control, genetic algorithm

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Authors: Mustafa Al Sukar, Azzam Sleit, Abdullatif Abu-Dalhoum, Bassam Al-Kasasbeh

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Use and abuse of drugs by teens is very common and can have dangerous consequences. The drugs contribute to physical and sexual aggression such as assault or rape. Some teenagers regularly use drugs to compensate for depression, anxiety or a lack of positive social skills. Teen resort to smoking should not be minimized because it can be "gateway drugs" for other drugs (marijuana, cocaine, hallucinogens, inhalants, and heroin). The combination of teenagers' curiosity, risk taking behavior, and social pressure make it very difficult to say no. This leads most teenagers to the questions: "Will it hurt to try once?" Nowadays, technological advances are changing our lives very rapidly and adding a lot of technologies that help us to track the risk of drug abuse such as smart phones, Wireless Sensor Networks (WSNs), Internet of Things (IoT), etc. This technique may help us to early discovery of drug abuse in order to prevent an aggravation of the influence of drugs on the abuser. In this paper, we have developed a Decision Support System (DSS) for detecting the drug abuse using Artificial Neural Network (ANN); we used a Multilayer Perceptron (MLP) feed-forward neural network in developing the system. The input layer includes 50 variables while the output layer contains one neuron which indicates whether the person is a drug addict. An iterative process is used to determine the number of hidden layers and the number of neurons in each one. We used multiple experiment models that have been completed with Log-Sigmoid transfer function. Particularly, 10-fold cross validation schemes are used to access the generalization of the proposed system. The experiment results have obtained 98.42% classification accuracy for correct diagnosis in our system. The data had been taken from 184 cases in Jordan according to a set of questions compiled from Specialists, and data have been obtained through the families of drug abusers.

Keywords: drug addiction, artificial neural networks, multilayer perceptron (MLP), decision support system

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Authors: Sonia P. Marrero Duran, Lilian Noya Dominguez, Lisandra Quintana Alvarez, Evert Martinez Perez, Ana Julia Acevedo Urquiaga

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Cuban business and economic policy are in the constant update as well as facing a client ever more knowledgeable and demanding. For that reason become fundamental for companies competitiveness through the optimization of its processes and services. One of the Cuban’s pillars, which has been sustained since the triumph of the Cuban Revolution back in 1959, is the free health service to all those who need it. This service is offered without any charge under the concept of preserving human life, but it implied costly management processes and logistics services to be able to supply the necessary medicines to all the units who provide health services. One of the key actors on the medicine supply chain is the Havana Distribution Center (HDC), which is responsible for the delivery of medicines in the province; as well as the acquisition of medicines from national and international producers and its subsequent transport to health care units and pharmacies in time, and with the required quality. This HDC also carries for all distribution centers in the country. Given the eminent need to create an actor in the supply chain that specializes in the medicines supply, the possibility of centralizing this operation in a logistics service provider is analyzed. Based on this decision, pharmacies operate as clients of the logistic service center whose main function is to centralize all logistics operations associated with the medicine supply chain. The HDC is precisely the logistic service provider in Havana and it is the center of this research. In 2017 the pharmacies had affectations in the availability of medicine due to deficiencies in the distribution routes. This is caused by the fact that they are not based on routing studies, besides the long distribution cycle. The distribution routs are fixed, attend only one type of customer and there respond to a territorial location by the municipality. Taking into consideration the above-mentioned problem, the objective of this research is to optimize the routes system in the Havana Distribution Center. To accomplish this objective, the techniques applied were document analysis, random sampling, statistical inference and tools such as Ishikawa diagram and the computerized software’s: ArcGis, Osmand y MapIfnfo. As a result, were analyzed four distribution alternatives; the actual rout, by customer type, by the municipality and the combination of the two last. It was demonstrated that the territorial location alternative does not take full advantage of the transportation capacities or the distance of the trips, which leads to elevated costs breaking whit the current ways of distribution and the currents characteristics of the clients. The principal finding of the investigation was the optimum option distribution rout is the 4th one that is formed by hospitals and the join of pharmacies, stomatology clinics, polyclinics and maternal and elderly homes. This solution breaks the territorial location by the municipality and permits different distribution cycles in dependence of medicine consumption and transport availability.

Keywords: computerized geographic software, distribution, distribution routs, vehicle problem routing (VPR)

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Authors: Takashi Shimizu, Tomoaki Hashimoto

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Recently, crystal growth technologies have made progress by the requirement for the high quality of crystal materials. To control the crystal growth dynamics actively by external forces is useuful for reducing composition non-uniformity. In this study, a control method based on model predictive control using thermal inputs is proposed for crystal growth dynamics of semiconductor materials. The control system of crystal growth dynamics considered here is governed by the continuity, momentum, energy, and mass transport equations. To establish the control method for such thermal fluid systems, we adopt model predictive control known as a kind of optimal feedback control in which the control performance over a finite future is optimized with a performance index that has a moving initial time and terminal time. The objective of this study is to establish a model predictive control method for crystal growth dynamics of semiconductor materials.

Keywords: model predictive control, optimal control, process control, crystal growth

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Authors: Luis Amador Jimenez, Md. Shohel Amin

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Pavement performance models are based on projections of observed traffic loads, which makes uncertain to study funding strategies in the long run if history does not repeat. Neural networks can be used to estimate deterioration rates but the learning rate and momentum have not been properly investigated, in addition, economic evolvement could change traffic flows. This study addresses both issues through a case study for roads of Montreal that simulates traffic for a period of 50 years and deals with the measurement error of the pavement deterioration model. Travel demand models are applied to simulate annual average daily traffic (AADT) every 5 years. Accumulated equivalent single axle loads (ESALs) are calculated from the predicted AADT and locally observed truck distributions combined with truck factors. A back propagation Neural Network (BPN) method with a Generalized Delta Rule (GDR) learning algorithm is applied to estimate pavement deterioration models capable of overcoming measurement errors. Linear programming of lifecycle optimization is applied to identify M&R strategies that ensure good pavement condition while minimizing the budget. It was found that CAD 150 million is the minimum annual budget to good condition for arterial and local roads in Montreal. Montreal drivers prefer the use of public transportation for work and education purposes. Vehicle traffic is expected to double within 50 years, ESALS are expected to double the number of ESALs every 15 years. Roads in the island of Montreal need to undergo a stabilization period for about 25 years, a steady state seems to be reached after.

Keywords: pavement management system, traffic simulation, backpropagation neural network, performance modeling, measurement errors, linear programming, lifecycle optimization

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Authors: Gobinda Gopal Khan, Ashutosh K. Singh, Debasish Sarkar

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Unique one-dimensional (1D) Ni-NiO and Co-Ni/Co3O4-NiO core/shell nano-heterostructures are fabricated by combining the electrochemical deposition and annealing. The high-performance pseudo-capacitor electrode based on the Ni-NiO and Co-Ni/Co3O4-NiO core/shell nano-heterostructures is designed and demonstrated. The Co-Ni/Co3O4-NiO core/shell nano-heterostructures exhibit high specific capacitance (2013 Fg-1 at 2.5 Ag-1), high energy and power density (23 Wh kg-1 and 5.5 kW kg-1, at the discharge current density of 20.8 A g-1.), good capacitance retention, and long cyclicality. The remarkable electrochemical property of the large surface area nano-heterostructures is demonstrated based on the novel nano-architectural design of the electrode with the coexistence of the two highly redox active materials at the surface supported by highly conducting metal alloy channel at the core for faster charge transport.

Keywords: nano-heterostructures, energy storage, supercapacitors, electrochemical deposition

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Authors: Heichia Wang, Yalan Chao

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Social inequality is a persistent problem. One of the ways to solve this problem is through education. At present, vulnerable groups are often less geographically accessible to educational resources. However, compared with educational resources, communication equipment is easier for vulnerable groups. Now that information and communication technology (ICT) has entered the field of education, today we can accept the convenience that ICT provides in education, and the mobility that it brings makes learning independent of time and place. With mobile learning, teachers and students can start discussions in an online chat room without the limitations of time or place. However, because liquidity learning is quite convenient, people tend to solve problems in short online texts with lack of detailed information in a lack of convenient online environment to express ideas. Therefore, the ICT education environment may cause misunderstanding between teachers and students. Therefore, in order to better understand each other's views between teachers and students, this study aims to clarify the essays of the analysts and classify the students into several types of learning questions to clarify the views of teachers and students. In addition, this study attempts to extend the description of possible omissions in short texts by using external resources prior to classification. In short, by applying a short text classification, this study can point out each student's learning problems and inform the instructor where the main focus of the future course is, thus improving the ICT education environment. In order to achieve the goals, this research uses convolutional neural network (CNN) method to analyze short discussion content between teachers and students in an ICT education environment. Divide students into several main types of learning problem groups to facilitate answering student problems. In addition, this study will further cluster sub-categories of each major learning type to indicate specific problems for each student. Unlike most neural network programs, this study attempts to extend short texts with external resources before classifying them to improve classification performance. In short, by applying the classification of short texts, we can point out the learning problems of each student and inform the instructors where the main focus of future courses will improve the ICT education environment. The data of the empirical process will be used to pre-process the chat records between teachers and students and the course materials. An action system will be set up to compare the most similar parts of the teaching material with each student's chat history to improve future classification performance. Later, the function of short text classification uses CNN to classify rich chat records into several major learning problems based on theory-driven titles. By applying these modules, this research hopes to clarify the main learning problems of students and inform teachers that they should focus on future teaching.

Keywords: ICT education improvement, social equality, short text analysis, convolutional neural network

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Authors: Vimuckthi Charika Wickramaratne, Prasansha Kumari

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Sport tourism refers to travel which involves either observing or participating in a sporting event apart from their usual environment. Sport tourism in a fast growing sector of the Sri Lankan travelling industry since Cricket are more popular sport game in the country. This study intends to analyze the impact of these popular sport events for creating and developing small scale business in the country. Primary data gathered from 100 small entrepreneurs around Keththarama Cricket Ground in Sri Lanka. Collected data analyzed using descriptive research methods. The study revealed that local and international visitors for cricket games had impacted on small scale business activities such as retail, handicraft, transport, vehicle parking, small restaurant, hotels, foods and beverage industry. In addition, it was identified that these type of small business are sessional income generating activities for the short period.

Keywords: sport tourism, small scale business, cricket, entrepreneurs

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Authors: O. Gsib, U. Peirera, C. Egles, S. A. Bencherif

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In skin regenerative medicine, one of the critical issues is to produce a three-dimensional scaffold with optimized porosity for dermal fibroblast infiltration and neovascularization, which exhibits high mechanical properties and displays sufficient wound healing characteristics. In this study, we report on the synthesis and characterization of macroporous sequential interpenetrating polymer networks (IPNs) combining skin wound healing properties of fibrin with the excellent physical properties of polyethylene glycol (PEG). Fibrin fibers serve as a provisional biologically active network to promote cell adhesion and proliferation while PEG provides the mechanical stability to maintain the entire 3D construct. After having modified both PEG and Serum Albumin (used for promoting enzymatic degradability) by adding methacrylate residues (PEGDM and SAM, respectively), Fibrin/PEGDM-SAM sequential IPNs were synthesized as follows: Macroporous sponges were first produced from PEGDM-SAM hydrogels by a freeze-drying technique and then rehydrated by adding the fibrin precursors. Environmental Scanning Electron Microscopy (ESEM) and Confocal Laser Scanning Microscopy (CLSM) were used to characterize their microstructure. Human dermal fibroblasts were cultivated during one week in the constructs and different cell culture parameters (viability, morphology, proliferation) were evaluated. Subcutaneous implantations of the scaffolds were conducted on five-week old male nude mice to investigate their biocompatibility in vivo. We successfully synthesized interconnected and macroporous Fibrin/PEGDM-SAM sequential IPNs. The viability of primary dermal fibroblasts was well maintained (above 90%) after 2 days of culture. Cells were able to adhere, spread and proliferate in the scaffolds suggesting the suitable porosity and intrinsic biologic properties of the constructs. The fibrin network adopted a spider web shape that covered partially the pores allowing easier cell infiltration into the macroporous structure. To further characterize the in vitro cell behavior, cell proliferation (EdU incorporation, MTS assay) is being studied. Preliminary histological analysis of animal studies indicated the persistence of hydrogels even after one-month post implantation and confirmed the absence of inflammation response, good biocompatibility and biointegration of our scaffolds within the surrounding tissues. These results suggest that our Fibrin/PEGDM-SAM IPNs could be considered as potential candidates for dermis regenerative medicine. Histological analysis will be completed to further assess scaffold remodeling including de novo extracellular matrix protein synthesis and early stage angiogenesis analysis. Compression measurements will be conducted to investigate the mechanical properties.

Keywords: fibrin, hydrogels for dermal reconstruction, polyethylene glycol, semi-interpenetrating polymer network

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Authors: Rashima Mahajan, Dipali Bansal, Shweta Singh

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Real time non-invasive Brain Computer Interfaces have a significant progressive role in restoring or maintaining a quality life for medically challenged people. This manuscript provides a comprehensive review of emerging research in the field of cognitive/affective computing in context of human neural responses. The perspectives of different emotion assessment modalities like face expressions, speech, text, gestures, and human physiological responses have also been discussed. Focus has been paid to explore the ability of EEG (Electroencephalogram) signals to portray thoughts, feelings, and unspoken words. An automated workflow-based protocol to design an EEG-based real time Brain Computer Interface system for analysis and classification of human emotions elicited by external audio/visual stimuli has been proposed. The front end hardware includes a cost effective and portable Emotive EEG Neuroheadset unit, a personal computer and a set of external stimulators. Primary signal analysis and processing of real time acquired EEG shall be performed using MATLAB based advanced brain mapping toolbox EEGLab/BCILab. This shall be followed by the development of MATLAB based self-defined algorithm to capture and characterize temporal and spectral variations in EEG under emotional stimulations. The extracted hybrid feature set shall be used to classify emotional states using artificial intelligence tools like Artificial Neural Network. The final system would result in an inexpensive, portable and more intuitive Brain Computer Interface in real time scenario to control prosthetic devices by translating different brain states into operative control signals.

Keywords: brain computer interface, electroencephalogram, EEGLab, BCILab, emotive, emotions, interval features, spectral features, artificial neural network, control applications

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Authors: Nisrine Benzbiria, Mohammed Azzi, Mustapha Zertoubi

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2XXX series of aluminum alloys are widely employed in several applications, such as beverages, automotive, and aerospace industries. However, they are particularly prone to localized corrosion, such as pitting, often induced by a difference in corrosion potential measured for intermetallic phases and pure metal. The galvanic cells comprising Al–Cu– Mn–Fe intermetallic phases control cathodically the dissolution rate as oxygen reduction reaction kinetics are privileged on Al–Cu–Mn–Fe particles. Hence, understanding the properties of cathode sites and the processes involved must be carried out. Our interest is to outline the cathodic behavior of AA2024-T3 in sodium sulfate solution using electrochemical techniques. Oxygen reduction reaction (ORR) was investigated in the mixed charge transfer and mass transport regime using the Koutecky-Levich approach. An environmentally benign inhibitor was considered to slow the ORR on the Cu-rich cathodic phases. The surface morphology of the electrodes was investigated with SEM/EDS and AFM. The obtained results were discussed accordingly.

Keywords: AA2024-T3, neutral medium, ORR kinetics, Koutecky-Levich, DFT

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Authors: Massimo Miccoli, Luca Marangoni, Alberto Aniello Scaringi, Alessandro Marceddu, Alessandro Amicone

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The susceptibility of deep neural networks (DNNs) to adversarial manipulations is a recognized challenge within the computer vision domain. Adversarial examples, crafted by adding subtle yet malicious alterations to benign images, exploit this vulnerability. Various defense strategies have been proposed to safeguard DNNs against such attacks, stemming from diverse research hypotheses. Building upon prior work, our approach involves the utilization of autoencoder models. Autoencoders, a type of neural network, are trained to learn representations of training data and reconstruct inputs from these representations, typically minimizing reconstruction errors like mean squared error (MSE). Our autoencoder was trained on a dataset of benign examples; learning features specific to them. Consequently, when presented with significantly perturbed adversarial examples, the autoencoder exhibited high reconstruction errors. The architecture of the autoencoder was tailored to the dimensions of the images under evaluation. We considered various image sizes, constructing models differently for 256x256 and 512x512 images. Moreover, the choice of the computer vision model is crucial, as most adversarial attacks are designed with specific AI structures in mind. To mitigate this, we proposed a method to replace image-specific dimensions with a structure independent of both dimensions and neural network models, thereby enhancing robustness. Our multi-modal autoencoder reconstructs the spectral representation of images across the red-green-blue (RGB) color channels. To validate our approach, we conducted experiments using diverse datasets and subjected them to adversarial attacks using models such as ResNet50 and ViT_L_16 from the torch vision library. The autoencoder extracted features used in a classification model, resulting in an MSE (RGB) of 0.014, a classification accuracy of 97.33%, and a precision of 99%.

Keywords: adversarial attacks, malicious images detector, binary classifier, multimodal transformer autoencoder

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Authors: Kang Jian Xian, Huda Abdullah, Md. Akhtaruzzaman, Iskandar Yahya, Mohd Hafiz Dzarfan Othman, Brian Yulianto

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The CZTS absorber layer doped with a silver (Ag) is one of the candidates that suggest improving the efficiency of thin films. Silver element functions to reduce antisite defects, increase grain size and create the plasmonic effect. In this work, an experimental study has been done to investigate the electrical and physical properties of CZTS, ACZTS, and AZTS. Ag replaces the Cu in (Cu1-xAgx)2ZnSnS4 (ACZTS) is up to x ≤1. ACZTS thin-films solar cells have been deposited by sol–the gel spin coating method. There are a total of 19 samples done with 11 significant percentages (0%, 10%, 20%… 100%) to show the whole phenomena of efficiency rate and nine specific percentages to find out the best concentration rate for Ag-doped. The obtained results can be helpful for better understanding ACZTS layers.

Keywords: CZTS, ACZTS, AZTS, silver, antisite, efficiency, thin-film solar cell

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Authors: M. Simchi, M. Amiri, E. Rezvani, I. Mirzaei, M. Berahman, A. Simchi, M. Fardmanesh

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Graphene is a single-atomic two-dimensional crystal of carbon atoms that has considerable properties due to its unique structure and physics with applications in different fields. Graphene has sensitive electrical properties due to its atomic-thin structure. Along with the substrate materials and their influence on the transport properties in graphene, design and fabrication of graphene-based devices for biomedical and biosensor applications are challenging. In this work, large-area high-quality graphene nanosheets were prepared by low pressure chemical vapor deposition using methane gas as carbon source on copper foil and transferred on the biocompatible substrates. Through deposition of titanium and gold contacts, current-voltage response of the transferred graphene on four biocompatible substrates, including PDMS, SU-8, Nitrocellulose, and Kapton (Fig. 2) were experimentally determined. The considerable effect of the substrate type on the electrical properties of graphene is shown. The sheet resistance of graphene is changed from 0.34 to 14.5 kΩ/sq, depending on the substrate.

Keywords: biocompatible substrates, electrical properties, graphene, sheet resistance

Procedia PDF Downloads 130

Authors: K. A. Laptinskiy, S. A. Burikov, A. M. Vervald, S. A. Dolenko, T. A. Dolenko

Abstract:

The article presents the results of the application of artificial neural networks to separate the fluorescent contribution of nanodiamonds used as biomarkers, adsorbents and carriers of drugs in biomedicine, from a fluorescent background of own biological fluorophores. The principal possibility of solving this problem is shown. Use of neural network architecture let to detect fluorescence of nanodiamonds against the background autofluorescence of egg white with high accuracy - better than 3 ug/ml.

Keywords: artificial neural networks, fluorescence, data aggregation, biomarkers

Procedia PDF Downloads 704

Authors: Liliana Crăc, Nicolae Giorgi, Gheorghe Fometescu

Abstract:

In Romania, billions of tonnes of wastes are generated yearly, an important amount being stored within industrial dumps that covers high soil areas and affects the environment quality, especially of ground and surface waters. Landfill represents in Romania the most important way for wastes removal, over 75% being generated every year, the costs with the dumps construction being considerable. In most of the cases, the wastes generated mainly by the energy industry, oil exploitation and metallurgy, are still considered wastes with NO-use, and their removal and neutralization represent for transport, handling and storing, high non-productive expenses which raise the cost of the useful products obtained. The paper presents a recycling idea of three types of wastes in order to use them for building materials manufacturing, by promoting ECOWASTES LIFE+ project, whose aim is to demonstrate that the recycling of waste from energy industry (coal combustion waste), petroleum extraction (drilling mud) and metallurgy (steelmaking slag) is technically feasible.

Keywords: fly ash, drilled solid wastes, metallurgical slag, recycling, building materials

Procedia PDF Downloads 309

Authors: T. R. Sreeram, S. Natarajan, C. Jena

Abstract:

Civil engineering construction is a network of tasks involving varying degree of complexity and streamlining, and standardization is the only way to establish a systemic approach to design. While there are off the shelf tools such as AutoCAD that play a role in the realization of design, the repeatable process in which these tools are deployed often is ignored. The present paper addresses this challenge through a sustainable design process and effective standardizations at all stages in the design workflow. The same is demonstrated through a case study in the context of construction, and further improvement points are highlighted.

Keywords: syste, lean, value stream, process improvement

Procedia PDF Downloads 120

Authors: Bliss Singhal

Abstract:

Epilepsy is a prevalent neurological disorder affecting approximately 50 million individuals worldwide and 1.2 million Americans. There exist millions of pediatric patients with intractable epilepsy, a condition in which seizures fail to come under control. The occurrence of seizures can result in physical injury, disorientation, unconsciousness, and additional symptoms that could impede children's ability to participate in everyday tasks. Predicting seizures can help parents and healthcare providers take precautions, prevent risky situations, and mentally prepare children to minimize anxiety and nervousness associated with the uncertainty of a seizure. This research proposes a comprehensive framework to predict seizures in pediatric patients by evaluating machine learning algorithms on unimodal neuroimaging data consisting of electroencephalogram signals. The bandpass filtering and independent component analysis proved to be effective in reducing the noise and artifacts from the dataset. Various machine learning algorithms’ performance is evaluated on important metrics such as accuracy, precision, specificity, sensitivity, F1 score and MCC. The results show that the deep learning algorithms are more successful in predicting seizures than logistic Regression, and k nearest neighbors. The recurrent neural network (RNN) gave the highest precision and F1 Score, long short-term memory (LSTM) outperformed RNN in accuracy and convolutional neural network (CNN) resulted in the highest Specificity. This research has significant implications for healthcare providers in proactively managing seizure occurrence in pediatric patients, potentially transforming clinical practices, and improving pediatric care.

Keywords: intractable epilepsy, seizure, deep learning, prediction, electroencephalogram channels

Procedia PDF Downloads 78

Authors: Mehrdad Abkenari, Orod Zarrinkafsh, Mohsen Ramezan Shirazi

Abstract:

Construction projects initiate in complicated dynamic environments and, due to the close relationships between project parameters and the unknown outer environment, they are faced with several uncertainties and risks. Success in time, cost and quality in large scale construction projects is uncertain in consequence of technological constraints, large number of stakeholders, too much time required, great capital requirements and poor definition of the extent and scope of the project. Projects that are faced with such environments and uncertainties can be well managed through utilization of the concept of risk management in project’s life cycle. Although the concept of risk is dependent on the opinion and idea of management, it suggests the risks of not achieving the project objectives as well. Furthermore, project’s risk analysis discusses the risks of development of inappropriate reactions. Since evaluation and prioritization of construction projects has been a difficult task, the network structure is considered to be an appropriate approach to analyze complex systems; therefore, we have used this structure for analyzing and modeling the issue. On the other hand, we face inadequacy of data in deterministic circumstances, and additionally the expert’s opinions are usually mathematically vague and are introduced in the form of linguistic variables instead of numerical expression. Owing to the fact that fuzzy logic is used for expressing the vagueness and uncertainty, formulation of expert’s opinion in the form of fuzzy numbers can be an appropriate approach. In other words, the evaluation and prioritization of construction projects on the basis of risk factors in real world is a complicated issue with lots of ambiguous qualitative characteristics. In this study, evaluated and prioritization the risk parameters and factors with fuzzy logy method by combination of three method DEMATEL (Decision Making Trial and Evaluation), ANP (Analytic Network Process) and TOPSIS (Technique for Order-Preference by Similarity Ideal Solution) on Construction Management.

Keywords: fuzzy logy, risk, prioritization, assessment

Procedia PDF Downloads 588

Authors: Mohammad Yousefikia, Sara Moridpour, Ehsan Mazloumi

Abstract:

Perceiving track geometry deterioration decisively influences the optimization of track maintenance operations. The effective management of this deterioration and increasingly utilized system with limited financial resources is a significant challenge. This paper provides a review of degradation models relevant for railroad tracks. Furthermore, due to the lack of long term information on the condition development of tram infrastructures, presents the methodology which will be used to derive degradation models from the data of Melbourne tram network.

Keywords: deterioration modeling, asset management, railway, tram

Procedia PDF Downloads 375

Authors: Chenhao Zhu

Abstract:

Quantitative mapping is playing a growing role in guiding urban planning, such as using a heat map created by CFX, CFD2000, or Envi-met, to adjust the master plan. However, there is no effective quantitative link between the mappings and planning formation. So, in many cases, the decision-making is still based on the planner's subjective interpretation and understanding of these mappings, which limits the improvement of scientific and accuracy brought by the quantitative mapping. Therefore, in this paper, an effort has been made to give a methodology of building a parametric link between the mapping and planning formation. A parametric planning process based on radiant mapping has been proposed for creating an urban green system. In the first step, a script is written in Grasshopper to build a road network and form the block, while the Ladybug Plug-in is used to conduct a radiant analysis in the form of mapping. Then, the research creatively transforms the radiant mapping from a polygon into a data point matrix, because polygon is hard to engage in the design formation. Next, another script is created to select the main green spaces from the road network based on the criteria of radiant intensity and connect the green spaces' central points to generate a green corridor. After that, a control parameter is introduced to adjust the corridor's form based on the radiant intensity. Finally, a green system containing greenspace and green corridor is generated under the quantitative control of the data matrix. The designer only needs to modify the control parameter according to the relevant research results and actual conditions to realize the optimization of the green system. This method can also be applied to much other mapping-based analysis, such as wind environment analysis, thermal environment analysis, and even environmental sensitivity analysis. The parameterized link between the mapping and planning will bring about a more accurate, objective, and scientific planning.

Keywords: parametric link, mapping, urban green system, radiant intensity, planning strategy, grasshopper

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Authors: Ashima Anurag Sharma

Abstract:

Optical fiber based networks can deliver performance that can support the increasing demands for high speed connections. One of the new technologies that have emerged in recent years is Passive Optical Networks. This research paper is targeted to show the simultaneous delivery of triple play service (data, voice, and video). The comparison between various data rates is presented. It is demonstrated that as we increase the data rate, number of users to be decreases due to increase in bit error rate.

Keywords: BER, PON, TDMPON, GPON, CWDM, OLT, ONT

Procedia PDF Downloads 523