Search results for: hybrid adhesives

Authors: M. Boudjerda, B. Touaibia, M. K. Mihoubi

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In Algeria agricultural irrigation is the primary water consuming sector followed by the domestic and industrial sectors. Economic development in the last decade has weighed heavily on water resources which are relatively limited and gradually decreasing to the detriment of agriculture. The research presented in this paper focuses on the optimization of irrigation water demand. Dynamic Programming-Neural Network (DPNN) method is applied to investigate reservoir optimization. The optimal operation rule is formulated to minimize the gap between water release and water irrigation demand. As a case study, Foum El-Gherza dam’s reservoir system in south of Algeria has been selected to examine our proposed optimization model. The application of DPNN method allowed increasing the satisfaction rate (SR) from 12.32% to 55%. In addition, the operation rule generated showed more reliable and resilience operation for the examined case study.

Keywords: water management, agricultural demand, dam and reservoir operation, Foum el-Gherza dam, dynamic programming, artificial neural network

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Authors: Cavidan Yakupoglu, Kurt Rohloff

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In this study, we aim to provide a novel parameter selection model for the BFVrns scheme, which is one of the prominent FHE schemes. Parameter selection in lattice-based FHE schemes is a practical challenges for experts or non-experts. Towards a solution to this problem, we introduce a hybrid principles-based approach that combines theoretical with experimental analyses. To begin, we use regression analysis to examine the parameters on the performance and security. The fact that the FHE parameters induce different behaviors on performance, security and Ciphertext Expansion Factor (CEF) that makes the process of parameter selection more challenging. To address this issue, We use a multi-objective optimization algorithm to select the optimum parameter set for performance, CEF and security at the same time. As a result of this optimization, we get an improved parameter set for better performance at a given security level by ensuring correctness and security against lattice attacks by providing at least 128-bit security. Our result enables average ~ 5x smaller CEF and mostly better performance in comparison to the parameter sets given in [1]. This approach can be considered a semiautomated parameter selection. These studies are conducted using the PALISADE homomorphic encryption library, which is a well-known HE library. The abstract goes here.

Keywords: lattice cryptography, fully homomorphic encryption, parameter selection, LWE, RLWE

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Authors: Deepika Christopher, Garima Anand

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To determine the best model for churn prediction in the telecom industry, this paper compares 11 machine learning algorithms, namely Logistic Regression, Support Vector Machine, Random Forest, Decision Tree, XGBoost, LightGBM, Cat Boost, AdaBoost, Extra Trees, Deep Neural Network, and Hybrid Model (MLPClassifier). It also aims to pinpoint the top three factors that lead to customer churn and conducts customer segmentation to identify vulnerable groups. According to the data, the Logistic Regression model performs the best, with an F1 score of 0.6215, 81.76% accuracy, 68.95% precision, and 56.57% recall. The top three attributes that cause churn are found to be tenure, Internet Service Fiber optic, and Internet Service DSL; conversely, the top three models in this article that perform the best are Logistic Regression, Deep Neural Network, and AdaBoost. The K means algorithm is applied to establish and analyze four different customer clusters. This study has effectively identified customers that are at risk of churn and may be utilized to develop and execute strategies that lower customer attrition.

Keywords: attrition, retention, predictive modeling, customer segmentation, telecommunications

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Authors: Enver Kucukkulahli, Pakize Erdogmus, Kemal Polat

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The 2D image segmentation is a significant process in finding a suitable region in medical images such as MRI, PET, CT etc. In this study, we have focused on 2D MRI images for image segmentation process. We have designed a GUI (graphical user interface) written in MATLABTM for 2D MRI images. In this program, there are two different interfaces including data pre-processing and image clustering or segmentation. In the data pre-processing section, there are median filter, average filter, unsharp mask filter, Wiener filter, and custom filter (a filter that is designed by user in MATLAB). As for the image clustering, there are seven different image segmentations for 2D MR images. These image segmentation algorithms are as follows: PSO (particle swarm optimization), GA (genetic algorithm), Lloyds algorithm, k-means, the combination of Lloyds and k-means, mean shift clustering, and finally BBO (Biogeography Based Optimization). To find the suitable cluster number in 2D MRI, we have designed the histogram based cluster estimation method and then applied to these numbers to image segmentation algorithms to cluster an image automatically. Also, we have selected the best hybrid method for each 2D MR images thanks to this GUI software.

Keywords: image segmentation, clustering, GUI, 2D MRI

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Authors: Alireza Alizadeh, Hossein Ghadimi, Oveis Abedinia, Noradin Ghadimi

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A Particle Swarm Optimization with Time Varying Acceleration Coefficients (PSO-TVAC) is proposed to determine optimal economic load dispatch (ELD) problem in this paper. The proposed methodology easily takes care of solving non-convex economic load dispatch problems along with different constraints like transmission losses, dynamic operation constraints and prohibited operating zones. The proposed approach has been implemented on the 3-machines 6-bus, IEEE 5-machines 14-bus, IEEE 6-machines 30-bus systems and 13 thermal units power system. The proposed technique is compared to solve the ELD problem with hybrid approach by using the valve-point effect. The comparison results prove the capability of the proposed method giving significant improvements in the generation cost for the economic load dispatch problem.

Keywords: PSO-TVAC, economic load dispatch, non-convex cost function, prohibited operating zone, transmission losses

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Authors: Bernard Doherty, Andrew Jelfs, Aveek Dasgupta, Patrick Holden

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Many companies have moved to agile and hybrid agile methodologies where portions of the Software Design Life-cycle (SDLC) and Software Test Life-cycle (STLC) can be time boxed in order to enhance delivery speed, quality and to increase flexibility to changes in software requirements. Despite widespread proliferation of agile practices, implementation often fails due to lack of adequate project management support, decreased motivation or fear of increased interaction. Consequently, few organizations effectively adopt agile processes with tailoring often required to integrate agile methodology in large scale environments. This paper provides an overview of the challenges in implementing an innovative large-scale tailored realization of the agile methodology termed the Agile Factory Model (AFM), with the aim of comparing and contrasting issues of specific importance to organizations undertaking large scale agile development. The conclusions demonstrate that agile practices can be effectively translated to a globally distributed development environment.

Keywords: agile, agile factory model, globally distributed development, large-scale agile

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Authors: Nesreddine Djafar Henni, Nassim Djedoui, Rachid Chebili

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Recent decades have witnessed significant efforts being made to optimize different types of structures and components. The concept of cost optimization in reinforced concrete structures, which aims at minimizing financial resources while ensuring maximum building safety, comprises multiple materials, and the objective function for their optimal design is derived from the construction cost of the steel as well as concrete that significantly contribute to the overall weight of reinforced concrete (RC) structures. To achieve this objective, this work has been devoted to optimizing the structural design of 3D RC frame buildings which integrates, for the first time, the Algerian regulations. Three different test examples were investigated to assess the efficiency of our work in optimizing RC frame buildings. The hybrid GWOPSO algorithm is used, and 30000 generations are made. The cost of the building is reduced by iteration each time. Concrete and reinforcement bars are used in the building cost. As a result, the cost of a reinforced concrete structure is reduced by 30% compared with the initial design. This result means that the 3D cost-design optimization of the framed structure is successfully achieved.

Keywords: optimization, automation, API, Malab, RC structures

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Authors: Abdellahi Cheikh

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With the emergence of quantum computers with very powerful capabilities, the security of the exchange of shared keys between two interlocutors poses a big problem in terms of the rapid development of technologies such as computing power and computing speed. Therefore, the Diffie-Hellmann (DH) algorithm is more vulnerable than ever. No mechanism guarantees the security of the key exchange, so if an intermediary manages to intercept it, it is easy to intercept. In this regard, several studies have been conducted to improve the security of key exchange between two interlocutors, which has led to interesting results. The modification made on our model Diffie-Hellman-RSA-AES (DRA), which encrypts the information exchanged between two users using the three-encryption algorithms DH, RSA and AES, by using stenographic photos to hide the contents of the p, g and ClesAES values that are sent in an unencrypted state at the level of DRA model to calculate each user's public key. This work includes a comparative study between the DRA model and all existing solutions, as well as the modification made to this model, with an emphasis on the aspect of reliability in terms of security. This study presents a simulation to demonstrate the effectiveness of the modification made to the DRA model. The obtained results show that our model has a security advantage over the existing solution, so we made these changes to reinforce the security of the DRA model.

Keywords: Diffie-Hellmann, DRA, RSA, advanced encryption standard

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Authors: Rabia Korkmaz Tan, Şebnem Bora

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The major problem encountered when modeling complex systems with agent-based modeling and simulation techniques is the existence of large parameter spaces. A complex system model cannot be expected to reflect the whole of the real system, but by specifying the most appropriate parameters, the actual system can be represented by the model under certain conditions. When the studies conducted in recent years were reviewed, it has been observed that there are few studies for parameter tuning problem in agent based simulations, and these studies have focused on tuning parameters of a single model. In this study, an approach of parameter tuning is proposed by using metaheuristic algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Artificial Bee Colonies (ABC), Firefly (FA) algorithms. With this hybrid structured study, the parameter tuning problems of the models in the different fields were solved. The new approach offered was tested in two different models, and its achievements in different problems were compared. The simulations and the results reveal that this proposed study is better than the existing parameter tuning studies.

Keywords: parameter tuning, agent based modeling and simulation, metaheuristic algorithms, complex systems

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Authors: Ismail Rahama Adam Hamid

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This paper presents the development of a thermal model for a flat, double-sided linear generator designed for use in free-piston engines. The study conducted in this paper examines the influence of temperature on the performance of the permeant magnet linear generator, an integral and pivotal component within the system. This research places particular emphasis on the Neodymium Iron Boron (NdFeB) permanent magnet, which serves as a source of magnetic field for the linear generator. In this study, an internal combustion engine that tends to produce heat is connected to a generator. Considering the temperatures rise from both the combustion process and the thermal contributions of current-carrying conductors and frictional forces. Utilizing Computational Fluid Dynamics (CFD) method, a thermal model of the (NdFeB) magnet within the linear generator is constructed and analyzed. Furthermore, the temperature field is examined to ensure that the linear generator operates under stable conditions without the risk of demagnetization.

Keywords: free piston engine, permanent magnet, linear generator, demagnetization, simulation

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Authors: Emilie Gout, Mathias Monnot, Olivier Boutin, Pierre Vanloot, Philippe Moulin

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Water is a precious resource. Treating industrial wastewater remains a considerable technical challenge of our century. The effluent considered for this study is landfill leachate treated by reverse osmosis (RO). Nowadays, in most developed countries, sanitary landfilling is the main method to deal with municipal solid waste. Rainwater percolates through solid waste, generating leachates mostly comprised of organic and inorganic matter. Whilst leachate ages, its composition varies, becoming more and more bio-refractory. RO is already used for landfill leachates as it generates good quality permeate. However, its mains drawback is the production of highly polluted concentrates that cannot be discharged in the environment or reused, which is an important industrial issue. It is against this background that the study of coupling RO with wet air oxidation (WAO) was set to intensify and optimize processes to meet current regulations for water discharge in the environment. WAO is widely studied for effluents containing bio-refractory compounds. Oxidation consists of a destruction reaction capable of mineralizing the recalcitrant organic fraction of pollution into carbon dioxide and water when complete. WAO process in subcritical conditions requires a high-energy consumption, but it can be autothermic in a certain range of chemical oxygen demand (COD) concentrations (10-100 g.L⁻¹). Appropriate COD concentrations are reached in landfill leachate RO concentrates. Therefore, the purpose of this work is to report the performances of mineralization during WAO on RO concentrates. The coupling of RO/WAO has shown promising results in previous works on both synthetic and real effluents in terms of organic carbon (TOC) reduction by WAO and retention by RO. Non-catalytic WAO with air as oxidizer was performed in a lab-scale stirred autoclave (1 L) on landfill leachates RO concentrates collected in different seasons in a sanitary landfill in southern France. The yield of WAO depends on operating parameters such as total pressure, temperature, and time. Compositions of the effluent are also important aspects for process intensification. An experimental design methodology was used to minimize the number of experiments whilst finding the operating conditions achieving the best pollution reduction. The simulation led to a set of 18 experiments, and the responses to highlight process efficiency are pH, conductivity, turbidity, COD, TOC, and inorganic carbon. A 70% oxygen excess was chosen for all the experiments. First experiments showed that COD and TOC abatements of at least 70% were obtained after 90 min at 300°C and 20 MPa, which attested the possibility to treat RO leachate concentrates with WAO. In order to meet French regulations and validate process intensification with industrial effluents, some continuous experiments in a bubble column are foreseen, and some further analyses will be performed, such as biological oxygen demand and study of gas composition. Meanwhile, other industrial effluents are treated to compare RO-WAO performances. These effluents, coming from pharmaceutical, petrochemical, and tertiary wastewater industries, present different specific pollutants that will provide a better comprehension of the hybrid process and prove the intensification and feasibility of the process at an industrial scale. Acknowledgments: This work has been supported by the French National Research Agency (ANR) for the Project TEMPO under the reference number ANR-19-CE04-0002-01.

Keywords: hybrid process, landfill leachates, process intensification, reverse osmosis, wet air oxidation

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Authors: Muhammad Babar Suleman

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Transgressing the boundaries of the real and the virtual, the temporal and the spatial and the personal and the political, Four Broken Hearts is a hybrid storyworld encompassing film, live performance, location-based experiences and social media. The project is scheduled for launch early next year and is currently a work-in-progress undergoing initial user testing. The story of Four Broken Hearts is being told by taking each of the classic elements of fiction- character, setting, exposition, climax and denouement - and bringing them ‘to life’ in the medium that conveys them to the highest degree of mimesis: Characters are built and explored through social media, Setting is experienced through location-based storytelling, the Backstory is fleshed out using film and the Climax is performed as an immersive drama. By taking advantage of what each medium does best while complementing the other mediums, Four Broken Hearts is presented in the form of a rich transmedia experience that allows audiences to explore the story world across many different platforms while still tying it all together within a cohesive narrative. This article presents an investigation of the project’s narrative outputs produced so far.

Keywords: narratology, storyworld, transmedia, narrative, storytelling

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Authors: Amin Sedighfar, M. R. Moniri

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Determination of state of charge (SOC) in today’s world becomes an increasingly important issue in all the applications that include a battery. In fact, estimation of the SOC is a fundamental need for the battery, which is the most important energy storage in Hybrid Electric Vehicles (HEVs), smart grid systems, drones, UPS and so on. Regarding those applications, the SOC estimation algorithm is expected to be precise and easy to implement. This paper presents an online method for the estimation of the SOC of Valve-Regulated Lead Acid (VRLA) batteries. The proposed method uses the well-known Kalman Filter (KF), and Neural Networks (NNs) and all of the simulations have been done with MATLAB software. The NN is trained offline using the data collected from the battery discharging process. A generic cell model is used, and the underlying dynamic behavior of the model has used two capacitors (bulk and surface) and three resistors (terminal, surface, and end), where the SOC determined from the voltage represents the bulk capacitor. The aim of this work is to compare the performance of conventional integration-based SOC estimation methods with a mixed algorithm. Moreover, by containing the effect of temperature, the final result becomes more accurate. 

Keywords: Kalman filter, neural networks, state-of-charge, VRLA battery

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Authors: Bandar Alkahlan

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The King Abdulaziz City for Science and Technology (KACST) created the Saudi Future Dwelling (SFD) initiative to identify, localize and commercialize a scalable home manufacturing technology suited to deployment across the Kingdom of Saudi Arabia (KSA). This paper outlines the journey, the creation of the international project delivery team, the product design, the selection of the process technologies, and the outcomes. A target was set to remove 85% of the construction and finishing processes from the building site as these activities could be more efficiently completed in a factory environment. Therefore, integral to the SFD initiative is the successful industrialization of the home building process using appropriate technologies, automation, robotics, and manufacturing logistics. The technologies proposed for the SFD housing system are designed to be energy efficient, economical, fit for purpose from a Saudi cultural perspective, and will minimize the use of concrete, relying mainly on locally available Saudi natural materials derived from the local resource industries. To this end, the building structure is comprised of a hybrid system of structural insulated panels (SIP), combined with a light gauge steel framework manufactured in a large format panel system. The paper traces the investigative process and steps completed by the project team during the selection process. As part of the SFD Project, a pathway was mapped out to include a proof-of-concept prototype housing module and the set-up and commissioning of a lab-factory complete with all production machinery and equipment necessary to simulate a full-scale production environment. The prototype housing module was used to validate and inform current and future product design as well as manufacturing process decisions. A description of the prototype design and manufacture is outlined along with valuable learning derived from the build and how these results were used to enhance the SFD project. The industrial engineering concepts and lab-factory detailed design and layout are described in the paper, along with the shop floor I.T. management strategy. Special attention was paid to showcase all technologies within the lab-factory as part of the engagement strategy with private investors to leverage the SFD project with large scale factories throughout the Kingdom. A detailed analysis is included in the process surrounding the design, specification, and procurement of the manufacturing machinery, equipment, and logistical manipulators required to produce the SFD housing modules. The manufacturing machinery was comprised of a combination of standardized and bespoke equipment from a wide range of international suppliers. The paper describes the selection process, pre-ordering trials and studies, and, in some cases, the requirement for additional research and development by the equipment suppliers in order to achieve the SFD objectives. A set of conclusions is drawn describing the results achieved thus far, along with a list of recommended ongoing operational tests, enhancements, research, and development aimed at achieving full-scale engagement with private sector investment and roll-out of the SFD project across the Kingdom.

Keywords: automation, dwelling, manufacturing, product design

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Authors: Tabrej Khan, Tamer A. Sebaey, Balbir Singh, M. A. Umarfarooq

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Spread-tow thin-ply-based technology has resulted in the progress of optimized reinforced composite plies with ultra-low thicknesses. There is wide use of composite bolted joints in the aircraft industry for load-bearing structures, and they are regarded as the primary source of stress concentration. The purpose of this study is to look into the bearing strength and structural performance of single shear bolt joint configurations in composite laminates, which are basically a combination of conventional thin-plies and thick-plies in some specific stacking sequence. The placement effect of thin-ply within the configured stack on bearing strength, as well as the potential damages, were investigated. Mechanical tests were used to understand the disfigurement mechanisms of the plies and their reciprocity, as well as to reflect on the single shear bolt joint properties and its load-bearing capacity. The results showed that changing the configuration of laminates by inserting the thin plies inside improved the bearing strength by up to 19%.

Keywords: hybrid composites, delamination, stress concentrations, mechanical testing, single bolt joint, thin-plies

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Authors: Rui Sang, Fei Deng, Alexander Engel, Ewa M. Goldys, Wei Deng

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In this study, we brought together X-ray induced photodynamic therapy (X-PDT) and chemo-drug (5-FU) for the treatment on colorectal cancer cells. This was achieved by developing a lipid-polymer hybrid nanoparticle delivery system (FA-LPNPs-VP-5-FU). It was prepared by incorporating a photosensitizer (verteporfin), chemotherapy drug (5-FU), and a targeting moiety (folic acid) into one platform. The average size of these nanoparticles was around 100 nm with low polydispersity. When exposed to clinical doses of 4 Gy X-ray radiation, FA-LPNPs-VP-5-FU generated sufficient amounts of reactive oxygen species, triggering the apoptosis and necrosis pathway of cancer cells. Our combined X-PDT and chemo-drug strategy was effective in inhibiting cancer cells’ growth and proliferation. Cell cycle analyses revealed that our treatment induced G2/M and S phase arrest in HCT116 cells. Our results indicate that this combined treatment provides better antitumour effect in colorectal cancer cells than each of these modalities alone. This may offer a novel approach for effective colorectal cancer treatment with reduced off-target effect and drug toxicity.

Keywords: pdt, targeted lipid-polymer nanoparticles, verteporfin, colorectal cancer

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Authors: Xiongxiong You, Zhanwen Niu

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Choosing an appropriate surrogate model plays an important role in surrogates-assisted evolutionary algorithms (SAEAs) since there are many types and different kernel functions in the surrogate model. In this paper, an adaptive selection of the best suitable surrogate model method is proposed to solve different kinds of expensive optimization problems. Firstly, according to the prediction residual error sum of square (PRESS) and different model selection strategies, the excellent individual surrogate models are integrated into multiple ensemble models in each generation. Then, based on the minimum root of mean square error (RMSE), the best suitable surrogate model is selected dynamically. Secondly, two methods with dynamic number of models and selection strategies are designed, which are used to show the influence of the number of individual models and selection strategy. Finally, some compared studies are made to deal with several commonly used benchmark problems, as well as a rotor system optimization problem. The results demonstrate the accuracy and robustness of the proposed method.

Keywords: adaptive selection, expensive optimization, rotor system, surrogates assisted evolutionary algorithms

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Authors: Ehsan Abshirini

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Rivers as one of the most important topographic factors have played a strategic role not only on the appearance of cities but they also affect the structure and morphology of cities. In this paper author intends to find out how a city in its physical network interacts with a river flowing inside. The pilot study is Angers, a city in western France, in which it is influenced by the Maine River. To this purpose space syntax method integrating with GIS is used to extract the properties of physical form of cities in terms of global and local integration value, accessibility and choice value. Simulating the state of absence of river in this city and comparing the result to the current state of city according to the effect of river on the morphology of areas located in different banks of river is also part of interest in this paper. The results show that although a river is not comparable to the city based on size and the area occupied by, it has a significant effect on the form of the city in both global and local properties. In addition, this study endorses that tracking the effect of river-cities and their interaction to rivers in a hybrid of space syntax and GIS may lead researchers to improve their interpretation of physical form of these types of cities.

Keywords: river-cities, Physical form, space syntax properties, GIS, topographic factor

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Authors: Tamar Beridze, Elisa Boscari, Fleur Scheele, Tamari Edisherashvili, Cort Anderson, Leonardo Congiu

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The eastern part of the Black Sea and its tributaries are suitable habitats for several sturgeon species, among which Acipenser gueldenstaedtii, A. stellatus, A. nudiventris, A. persicus, A. sturio, and H. huso are well documented. However, different threats have led these species to a dramatic decline; all of them are currently listed as Critically Endangered and some Locally Extinct in that area. We tested 94 wild sturgeon samples from the Black Sea and Rioni River by analyzing the mitochondrial Control Region and nuclear markers for hybrid identification. The data analyses (1) assessed mitochondrial diversity among samples, (2) identified their species, as well as (3) indicated instances of hybridization. The data collected, besides confirming a sharp decrease of catches of Beluga and Stellate sturgeon in recent years, also revealed four juvenile hybrids between Russian and Stellate sturgeon, providing the first evidence of natural interspecific hybridization in the Rioni. The present communication raises concerns about the status of sturgeon species in this area and underlines the urgent need for conservation programs to restore self-sustaining populations.

Keywords: black sea, sturgeon, Rioni river, interspecific hybridization

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Authors: Monika Kamocka, Radoslaw Mania

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The design of Fiber Metal Laminates - combining thin aluminum sheets and prepreg layers, allows creating a hybrid structure with high strength to weight ratio. This feature makes FMLs very attractive for aerospace industry, where thin-walled structures are commonly used. Nevertheless, those structures are prone to buckling phenomenon. Buckling could occur also under static load as well as dynamic pulse loads. In this paper, the problem of dynamic buckling of open cross-section FML profiles under axial dynamic compression in the form of pulse load of finite duration is investigated. In the numerical model, material properties of FML constituents were assumed as nonlinear elastic-plastic aluminum and linear-elastic glass-fiber-reinforced composite. The influence of pulse shape was investigated. Sinusoidal and rectangular pulse loads of finite duration were compared in two ways, i.e. with respect to magnitude and force pulse. The dynamic critical buckling load was determined based on Budiansky-Hutchinson, Ari Gur, and Simonetta dynamic buckling criteria.

Keywords: dynamic buckling, dynamic stability, Fiber Metal Laminate, Finite Element Method

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Authors: Muhamad Azani Yahya, Umi Nadiah Nor Ali, Mohammed Alias Yusof, Norazman Mohamad Nor, Vikneswaran Munikanan

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In construction, concrete is one of the materials that can commonly be used as for structural elements. Concrete consists of cement, sand, aggregate and water. Concrete can be added with admixture in the wet condition to suit the design purpose such as to prolong the setting time to improve workability. For strength improvement, concrete is being added with other hybrid materials to increase strength; this is because the tensile strength of concrete is very low in comparison to the compressive strength. This paper shows the usage of a waterproofing agent in concrete to enhance the tensile strength. High tensile concrete is expensive because the concrete mix needs fiber and also high cement content to be incorporated in the mix. High tensile concrete being used for structures that are being imposed by high impact dynamic load such as blast loading that hit the structure. High tensile concrete can be defined as a concrete mix design that achieved 30%-40% tensile strength compared to its compression strength. This research evaluates the usage of a waterproofing agent in a concrete mix as an element of reinforcement to enhance the tensile strength. According to the compression and tensile test, it shows that the concrete mix with a waterproofing agent enhanced the mechanical properties of the concrete. It is also show that the composite concrete with waterproofing is a high tensile concrete; this is because of the tensile is between 30% and 40% of the compression strength. This mix is economical because it can produce high tensile concrete with low cost.

Keywords: high tensile concrete, waterproofing agent, concrete, rheology

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Authors: Lukas Munster, Pavel Bazant, Ivo Kuritka

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Zinc oxide sub-micro particles and metallic silver nano particles (Ag/ZnO) were deposited on micro crystalline cellulose surface by a fast, simple and environmentally friendly one-pot microwave assisted solvo thermal synthesis in an open vessel system equipped with an external reflux cooler. In order to increase the interaction between the surface of cellulose and the precipitated Ag/ZnO particles, oxidized form of cellulose (cellulose dialdehyde, DAC) prepared by periodate oxidation of micro crystalline cellulose was added to the reaction mixture of Ag/ZnO particle precursors and untreated micro crystalline cellulose. The structure and morphology of prepared hybrid powder materials were analysed by X-ray diffraction (XRD), energy dispersive analysis (EDX), scanning electron microscopy (SEM) and nitrogen absorption method (BET). Microscopic analysis of the prepared materials treated by ultra-sonication showed that Ag/ZnO particles deposited on the cellulose/DAC sample exhibit increased adhesion to the surface of the cellulose substrate which can be explained by the DAC adhesive effect in comparison with the material prepared without DAC addition.

Keywords: microcrystalline cellulose, microwave synthesis, silver nanoparticles, zinc oxide sub-microparticles, cellulose dialdehyde

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Authors: Pedro Gómez-del-Hoyo, Jose-Luis Bárcena-Humanes, Nerea del-Rey-Maestre, María-Pilar Jarabo-Amores, David Mata-Moya

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A study of achievable coverages using passive radar systems in terrestrial traffic monitoring applications is presented. The study includes the estimation of the bistatic radar cross section of different commercial vehicle models that provide challenging low values which make detection really difficult. A semi-urban scenario is selected to evaluate the impact of excess propagation losses generated by an irregular relief. A bistatic passive radar exploiting UHF frequencies radiated by digital video broadcasting transmitters is assumed. A general method of coverage estimation using electromagnetic simulators in combination with estimated car average bistatic radar cross section is applied. In order to reduce the computational cost, hybrid solution is implemented, assuming free space for the target-receiver path but estimating the excess propagation losses for the transmitter-target one.

Keywords: bistatic radar cross section, passive radar, propagation losses, radar coverage

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Authors: Didem Can

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Scheduling problems are one of the most fundamental issues of production systems. Many different approaches and models have been developed according to the production processes of the parts and the main purpose of the problem. In this study, one of the bottleneck stations of a company serving in the aerospace industry is analyzed and considered as a single machine scheduling problem with sequence-dependent setup times. The objective of the problem is assigning a large number of similar parts to the same shift -to reduce chemical waste- while minimizing the number of tardy jobs. The goal programming method will be used to achieve two different objectives simultaneously. The assignment of parts to the shift will be expressed using the integer programming method. Finally, the constraint programming method will be used as it provides a way to find a result in a short time by avoiding worse resulting feasible solutions with the defined variables set. The model to be established will be tested and evaluated with real data in the application part.

Keywords: constraint programming, goal programming, integer programming, sequence-dependent setup, single machine scheduling

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Authors: William Whiteley, Jens Gregor

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In recent developments of direct neural network based positron emission tomography (PET) reconstruction, two prominent architectures have emerged for converting measurement data into images: 1) networks that contain fully-connected layers; and 2) networks that primarily use a convolutional encoder-decoder architecture. In this paper, we present a multi-modal direct PET reconstruction method called MDPET, which is a hybrid approach that combines the advantages of both types of networks. MDPET processes raw data in the form of sinograms and histo-images in concert with attenuation maps to produce high quality multi-slice PET images (e.g., 8x440x440). MDPET is trained on a large whole-body patient data set and evaluated both quantitatively and qualitatively against target images reconstructed with the standard PET reconstruction benchmark of iterative ordered subsets expectation maximization. The results show that MDPET outperforms the best previously published direct neural network methods in measures of bias, signal-to-noise ratio, mean absolute error, and structural similarity.

Keywords: deep learning, image reconstruction, machine learning, neural network, positron emission tomography

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Authors: Angel Daniel Muñoz Guzmán

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E-learning is becoming more and more common every day. For online, hybrid or traditional face-to-face programs, there are some e-teaching platforms like Google classroom, Blackboard, Moodle and Canvas, and there are platforms for full e-learning like Coursera, edX or Udemy. These tools are changing the way students acquire knowledge at schools; however, in today’s changing world that is not enough. As students’ needs and skills change and become more complex, new tools will need to be added to keep them engaged and potentialize their learning. This is especially important in the current global situation that is changing everything: the Covid-19 pandemic. Due to Covid-19, education had to make an unexpected switch from face-to-face courses to digital courses. In this study, the students’ learning experience is analyzed by applying different e-tools and following the Tec21 Model and a flexible and digital model, both developed by the Tecnologico de Monterrey University. The evaluation of the students’ learning experience has been made by the quantitative PrEmo method of emotions. Findings suggest that the quantity of e-tools used during a course does not affect the students’ learning experience as much as how a teacher links every available tool and makes them work as one in order to keep the student engaged and motivated.

Keywords: student, experience, e-learning, e-teaching, e-tools, technology, education

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Authors: Pravat Ranjan Pati, Alok Satapathy

Abstract:

Linz-Donawitz (LD) slag a major solid waste generated in huge quantities during steel making. It comes from slag formers such as burned lime/dolomite and from oxidizing of silica, iron etc. while refining the iron into steel in the LD furnace. Although a number of ways for its utilization have been suggested, its potential as a filler material in polymeric matrices has not yet been explored. The present work reports the possible use of this waste in glass fiber reinforced epoxy composites as a filler material. Hybrid composites consisting of bi-directional e-glass-fiber reinforced epoxy filled with different LD slag content (0, 7.5, 15, 22.5 wt%) are prepared by simple hand lay-up technique. The composites are characterized in regard to their density, porosity, micro-hardness and strength properties. X-ray diffractography is carried out in order to ascertain the various phases present in LDS. This work shows that LD slag, in spite of being a waste, possesses fairly good filler characteristics as it modifies the strength properties and improves the composite micro-hardness of the polymeric resin.

Keywords: characterization, glass-epoxy composites, LD slag, waste utilization

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Authors: Milad Golshan, Wim Zeiler

Abstract:

During the last decade research was done to clarify the importance of good Indoor Air Quality in schools. As a result, measurements were undertaken in different types of schools to see whether naturally ventilated schools could provide adequate indoor conditions. Also, a comparison was made between schools with hybrid ventilation and those with complete mechanical ventilation systems. Recently a large survey was undertaken at 60 schools to establish the average current situation of schools in the Netherlands. The results of the questionnaires were compared with those of earlier measured schools. This allowed us to compare different types of schools as well as schools of different periods. Overall it leads to insights about the actual current perceived quality by the teachers as well as the pupils and enables to draw some conclusions about the typical performances of specific types of school ventilation systems. Also, the perceived thermal comfort and controllability were researched. It proved that in around 50% of the schools there were major complains about the indoor air quality causing concentration problems and headaches by the pupils at the end of class. Although the main focus of the latest research was focused more on the quality of recently finished nearly Zero Energy schools, this research showed that especially the main focus school be on the renovation and upgrading of the existing 10.000 schools in the Netherlands.

Keywords: school ventilation, indoor air quality, perceiver thermal comfort, comparison different types

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Authors: A. U. Haque, W. Asrar, A. A Omar, E. Sulaeman, J. S. M. Ali

Abstract:

Buoyancy force applied on deformable symmetric bodies can be estimated by using Archimedes Principle. Such bodies like ellipsoidal bodies have high volume to surface ratio and are isometrically scaled for mass, length, area and volume to follow square cube law. For scaling up such bodies, it is worthwhile to find out the scaling relationship between the other physical quantities that represent thermodynamic, structural and inertial response etc. So, dimensionless similarities to find an allometric scale can be developed by using Bukingham π theorem which utilizes physical dimensions of important parameters. Base on this fact, physical dependencies of buoyancy system are reviewed to find the set of physical variables for deformable bodies of revolution filled with expandable gas like helium. Due to change in atmospheric conditions, this gas changes its volume and this change can effect the stability of elongated bodies on the ground as well as in te air. Special emphasis was given on the existing similarity parameters which can be used in the design of experiments of such bodies whose shape is affected by the external force like a drag, surface tension and kinetic loads acting on the surface. All these similarity criteria are based on non-dimensionalization, which also needs to be consider for scaling up such bodies.

Keywords: Bukhigham pi theorem, similitude, scaling, buoyancy

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Authors: Victor Arokia Doss, Kuberapandian Dharaniyambigai, K. Julia Rose Mary

Abstract:

Advanced Glycation End (AGE) products are the end products due to the reaction between excess reducing sugar present in diabetes and free amino group in protein lipids and nucleic acids. Thus, non-enzymic glycation of molecules such as hemoglobin, collagen, and other structurally and functionally important proteins add to the pathogenic complications such as diabetic retinopathy, neuropathy, nephropathy, vascular changes, atherosclerosis, Alzheimer's disease, rheumatoid arthritis, and chronic heart failure. The most common non-cross linking AGE, carboxymethyl lysine (CML) is formed by the oxidative breakdown of fructosyllysine, which is a product of glucose and lysine. CML is formed in a wide variety of tissues and is an index to assess the extent of glycoxidative damage. Thus we have constructed a mathematical and computational model that predicts the effect of temperature differences in vivo, on the formation of CML, which is now being considered as an important intracellular milieu. This hybrid model that had been tested for its parameter fitting and its sensitivity with available experimental data paves the way for designing novel laboratory experiments that would throw more light on the pathological formation of AGE adducts and in the pathophysiology of diabetic complications.

Keywords: advanced glycation end-products, CML, mathematical model, computational model

Procedia PDF Downloads 111