Search results for: hybrid block methods

Authors: Yi F. Wu, Ai Q. Li, Hao Wang

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Taking a novel type of bridge bearings with the diameter being 100mm as an example, the theoretical analysis, the experimental research as well as the numerical simulation of the bearing were conducted. Since the normal compression-shear machines cannot be applied to the small-size bearing, an improved device to test the properties of the bearing was proposed and fabricated. Besides, the simulation of the bearing was conducted on the basis of the explicit finite element software ANSYS/LS-DYNA, and some parameters of the bearing are modified in the finite element model to effectively reduce the computation cost. Results show that all the research methods are capable of revealing the fundamental properties of the small-size bearings, and a combined use of these methods can better catch both the integral properties and the inner detailed mechanical behaviors of the bearing.

Keywords: ANSYS/LS-DYNA, compression shear, contact analysis, explicit algorithm, small-size

Procedia PDF Downloads 168

Authors: Bahareh Ansari

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Background: The Open Government Data (OGD) movement in the last decade has encouraged many government organizations around the world to make their data publicly available to advance democratic processes. But current open data platforms have not yet reached to their full potential in supporting all interested parties. To make the data useful and understandable for everyone, scholars suggested that opening the data should be supplemented by visualization. However, different visualizations of the same information can dramatically change an individual’s cognitive and emotional experience in working with the data. This study reviews the data visualization literature to create a list of the methods empirically tested to enhance users’ performance and experience in working with a visualization tool. This list can be used in evaluating the OGD visualization practices and informing the future open data initiatives. Methods: Previous reviews of visualization literature categorized the visualization outcomes into four categories including recall/memorability, insight/comprehension, engagement, and enjoyment. To identify the papers, a search for these outcomes was conducted in the abstract of the publications of top-tier visualization venues including IEEE Transactions for Visualization and Computer Graphics, Computer Graphics, and proceedings of the CHI Conference on Human Factors in Computing Systems. The search results are complemented with a search in the references of the identified articles, and a search for 'open data visualization,' and 'visualization evaluation' keywords in the IEEE explore and ACM digital libraries. Articles are included if they provide empirical evidence through conducting controlled user experiments, or provide a review of these empirical studies. The qualitative synthesis of the studies focuses on identification and classifying the methods, and the conditions under which they are examined to positively affect the visualization outcomes. Findings: The keyword search yields 760 studies, of which 30 are included after the title/abstract review. The classification of the included articles shows five distinct methods: interactive design, aesthetic (artistic) style, storytelling, decorative elements that do not provide extra information including text, image, and embellishment on the graphs), and animation. Studies on decorative elements show consistency on the positive effects of these elements on user engagement and recall but are less consistent in their examination of the user performance. This inconsistency could be attributable to the particular data type or specific design method used in each study. The interactive design studies are consistent in their findings of the positive effect on the outcomes. Storytelling studies show some inconsistencies regarding the design effect on user engagement, enjoyment, recall, and performance, which could be indicative of the specific conditions required for the use of this method. Last two methods, aesthetics and animation, have been less frequent in the included articles, and provide consistent positive results on some of the outcomes. Implications for e-government: Review of the visualization best-practice methods show that each of these methods is beneficial under specific conditions. By using these methods in a potentially beneficial condition, OGD practices can promote a wide range of individuals to involve and work with the government data and ultimately engage in government policy-making procedures.

Keywords: best practices, data visualization, literature review, open government data

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Authors: Xu Du, Aparna S. Varde

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In this research, we propose to conduct diagnostic and predictive analysis about the key factors and consequences of urban population relocation. To achieve this goal, urban simulation models extract the urban development trends as land use change patterns from a variety of data sources. The results are treated as part of urban big data with other information such as population change and economic conditions. Multiple data mining methods are deployed on this data to analyze nonlinear relationships between parameters. The result determines the driving force of population relocation with respect to urban sprawl and urban sustainability and their related parameters. Experiments so far reveal that data mining methods discover useful knowledge from the multicity urban data. This work sets the stage for developing a comprehensive urban simulation model for catering to specific questions by targeted users. It contributes towards achieving sustainability as a whole.

Keywords: data mining, environmental modeling, sustainability, urban planning

Procedia PDF Downloads 285

Authors: Sergey N. Ermoliev, Margarita A. Belousova, Aida D. Goncharenko

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Application of the diagnostic complex of highly informative functional methods (electromyography, reodentography, laser Doppler flowmetry, reoperiodontography, vital computer capillaroscopy, optical tissue oximetry, laser fluorescence diagnosis) allows to perform a multifactorial analysis of the dental status and to prescribe complex etiopathogenetic treatment. Introduction. It is necessary to create a complex of innovative highly informative and safe functional diagnostic methods for improvement of the quality of patient treatment by the early detection of stomatologic diseases. The purpose of the present study was to investigate the etiology and pathogenesis of functional disorders identified in the pathology of hard tissue, dental pulp, periodontal, oral mucosa and chewing function, and the creation of new approaches to the diagnosis of dental diseases. Material and methods. 172 patients were examined. Density of hard tissues of the teeth and jaw bone was studied by intraoral ultrasonic densitometry (USD). Electromyographic activity of masticatory muscles was assessed by electromyography (EMG). Functional state of dental pulp vessels assessed by reodentography (RDG) and laser Doppler flowmetry (LDF). Reoperiodontography method (RPG) studied regional blood flow in the periodontal tissues. Microcirculatory vascular periodontal studied by vital computer capillaroscopy (VCC) and laser Doppler flowmetry (LDF). The metabolic level of the mucous membrane was determined by optical tissue oximetry (OTO) and laser fluorescence diagnosis (LFD). Results and discussion. The results obtained revealed changes in mineral density of hard tissues of the teeth and jaw bone, the bioelectric activity of masticatory muscles, regional blood flow and microcirculation in the dental pulp and periodontal tissues. LDF and OTO methods estimated fluctuations of saturation level and oxygen transport in microvasculature of periodontal tissues. With LFD identified changes in the concentration of enzymes (nicotinamide, flavins, lipofuscin, porphyrins) involved in metabolic processes Conclusion. Our preliminary results confirmed feasibility and safety the of intraoral ultrasound densitometry technique in the density of bone tissue of periodontium. Conclusion. Application of the diagnostic complex of above mentioned highly informative functional methods allows to perform a multifactorial analysis of the dental status and to prescribe complex etiopathogenetic treatment.

Keywords: electromyography (EMG), reodentography (RDG), laser Doppler flowmetry (LDF), reoperiodontography method (RPG), vital computer capillaroscopy (VCC), optical tissue oximetry (OTO), laser fluorescence diagnosis (LFD)

Procedia PDF Downloads 267

Authors: Anicet Dansou

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Textile reinforced concrete (TRC)is increasingly used nowadays in various fields, in particular civil engineering, where it is mainly used for the reinforcement of damaged reinforced concrete structures. TRC is a composite material composed of multi- or uni-axial textile reinforcements coupled with a fine-grained cementitious matrix. The TRC composite is an alternative solution to the traditional Fiber Reinforcement Polymer (FRP) composite. It has good mechanical performance and better temperature stability but also, it makes it possible to meet the criteria of sustainable development better.TRCs are highly anisotropic composite materials with nonlinear hardening behavior; their macroscopic behavior depends on multi-scale mechanisms. The characterization of these materials through numerical simulation has been the subject of many studies. Since TRCs are multiscale material by definition, numerical multi-scale approaches have emerged as one of the most suitable methods for the simulation of TRCs. They aim to incorporate information pertaining to microscale constitute behavior, mesoscale behavior, and macro-scale structure response within a unified model that enables rapid simulation of structures. The computational costs are hence significantly reduced compared to standard simulation at a fine scale. The fine scale information can be implicitly introduced in the macro scale model: approaches of this type are called non-classical. A representative volume element is defined, and the fine scale information are homogenized over it. Analytical and computational homogenization and nested mesh methods belong to these approaches. On the other hand, in classical approaches, the fine scale information are explicitly introduced in the macro scale model. Such approaches pertain to adaptive mesh refinement strategies, sub-modelling, domain decomposition, and multigrid methods This research presents the main principles of numerical multiscale approaches. Advantages and limitations are identified according to several criteria: the assumptions made (fidelity), the number of input parameters required, the calculation costs (efficiency), etc. A bibliographic study of recent results and advances and of the scientific obstacles to be overcome in order to achieve an effective simulation of textile reinforced concrete in civil engineering is presented. A comparative study is further carried out between several methods for the simulation of TRCs used for the structural reinforcement of reinforced concrete structures.

Keywords: composites structures, multiscale methods, numerical modeling, textile reinforced concrete

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Authors: Po-Fang Hsu, Chiching Wei

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In this paper, we present a novel neural graph matching approach applied to document comparison. Document comparison is a common task in the legal and financial industries. In some cases, the most important differences may be the addition or omission of words, sentences, clauses, or paragraphs. However, it is a challenging task without recording or tracing the whole edited process. Under many temporal uncertainties, we explore the potentiality of our approach to proximate the accurate comparison to make sure which element blocks have a relation of edition with others. In the beginning, we apply a document layout analysis that combines traditional and modern technics to segment layouts in blocks of various types appropriately. Then we transform this issue into a problem of layout graph matching with textual awareness. Regarding graph matching, it is a long-studied problem with a broad range of applications. However, different from previous works focusing on visual images or structural layout, we also bring textual features into our model for adapting this domain. Specifically, based on the electronic document, we introduce an encoder to deal with the visual presentation decoding from PDF. Additionally, because the modifications can cause the inconsistency of document layout analysis between modified documents and the blocks can be merged and split, Sinkhorn divergence is adopted in our neural graph approach, which tries to overcome both these issues with many-to-many block matching. We demonstrate this on two categories of layouts, as follows., legal agreement and scientific articles, collected from our real-case datasets.

Keywords: document comparison, graph matching, graph neural network, modification similarity, multi-modal

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Authors: Ahmad Mohsin, Irfan Raza Naqvi, Syda Fatima Usamn

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Applications with higher fault tolerance index are considered more reliable and trustworthy to drive quality. In recent years application development has been shifted from traditional desktop and web to native and hybrid application(s) for the web and mobile platforms. With the emergence of Internet of things IOTs, cloud and big data trends, the need for measuring Fault Tolerance for these complex nature applications has increased to evaluate their performance. There is a phenomenal gap between fault tolerance metrics development and measurement. Classic quality metric models focused on metrics for traditional systems ignoring the essence of today’s applications software, hardware & deployment characteristics. In this paper, we have proposed simple metrics to measure fault tolerance considering general requirements for Web and Mobile Applications. We have aligned factors – subfactors, using GQM for metrics development considering the nature of mobile we apps. Systematic Mathematical formulation is done to measure metrics quantitatively. Three web mobile applications are selected to measure Fault Tolerance factors using formulated metrics. Applications are then analysed on the basis of results from observations in a controlled environment on different mobile devices. Quantitative results are presented depicting Fault tolerance in respective applications.

Keywords: web and mobile applications, reliability, fault tolerance metric, quality metrics, GQM based metrics

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Authors: Vinayak Bassi, Rajpreet Singh

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Over the years, with the emergence of sophisticated computers and algorithms, finance has been quantified using computational prowess. Asset valuation has been one of the key components of quantitative finance. In fact, it has become one of the embryonic steps in determining risk related to a portfolio, the main goal of quantitative finance. This study comprises a drawing comparison between valuation output generated by two stochastic dynamic models, namely Black-Scholes and Dupire’s bi-dimensionality model. Both of these models are formulated for computing the valuation function for a portfolio of European options using Monte Carlo simulation methods. Although Monte Carlo algorithms have a slower convergence rate than calculus-based simulation techniques (like FDM), they work quite effectively over high-dimensional dynamic models. A fidelity gap is analyzed between the static (historical) and stochastic inputs for a sample portfolio of underlying assets. In order to enhance the performance efficiency of the model, the study emphasized the use of variable reduction methods and customizing random number generators to implement parallelization. An attempt has been made to further implement the Dupire’s model on a GPU to achieve higher computational performance. Furthermore, ideas have been discussed around the performance enhancement and bottleneck identification related to the implementation of options-pricing models on GPUs.

Keywords: monte carlo, stochastic models, computational finance, parallel programming, scientific computing

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Authors: T. Martini, J. M. Martínez

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An algorithmic acceleration strategy based on quasi-Newton (or secant) methods is displayed for address the practical problem of accelerating the convergence of the Newton-Lagrange method in the case of convergence to critical multipliers. Since the Newton-Lagrange iteration converges locally at a linear rate, it is natural to conjecture that quasi-Newton methods based on the so called secant equation and some minimal variation principle, could converge superlinearly, thus restoring the convergence properties of Newton's method. This strategy can also be applied to accelerate the convergence of algorithms applied to fixed-points problems. Computational experience is reported illustrating the efficiency of this strategy to solve fixed-point problems with linear convergence rate.

Keywords: algorithmic acceleration, fixed-point problems, nonlinear programming, quasi-newton method

Procedia PDF Downloads 476

Authors: Carlos Roncero-Parra, Alfonso Parreño-Torres, Jorge Mateo Sotos, Alejandro L. Borja

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In this research, different methods based on machine/deep learning algorithms are presented for the classification and diagnosis of patients with mental disorders such as alzheimer. For this purpose, the signals obtained from 32 unipolar electrodes identified by non-invasive EEG were examined, and their basic properties were obtained. More specifically, different well-known machine learning based classifiers have been used, i.e., support vector machine (SVM), Bayesian linear discriminant analysis (BLDA), decision tree (DT), Gaussian Naïve Bayes (GNB), K-nearest neighbor (KNN) and Convolutional Neural Network (CNN). A total of 668 patients from five different hospitals have been studied in the period from 2011 to 2021. The best accuracy is obtained was around 93 % in both ADM and ADA classifications. It can be concluded that such a classification will enable the training of algorithms that can be used to identify and classify different mental disorders with high accuracy.

Keywords: alzheimer, machine learning, deep learning, EEG

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Authors: Mosima M. Mabitsela

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Groundnut is preferably grown on light textured soils. Most of these light textured soils tend to be highly weathered and characterized by high soil acidity and low nutrient status. One major soil factor associated with infertility of acidic soils that can negatively depress groundnut yield is aluminium (Al) toxicity. In plants Al toxicity damages root cells, leading to inhibition of root growth as a result of the suppression of cell division, cell elongation and cell expansion in the apical meristem cells of the root. The end result is that roots become stunted and brittle, root hair development is poor, and the root apices become swollen. This study was conducted to determine the effects of aluminium (Al) toxicity on a range of groundnut varieties. Fifteen cultivars were tested in incremental aluminum (Al) supply in an ebb and flow solution culture laid out in a randomized complete block design. There were six aluminium (Al) treatments viz. 0 µM, 1 µM, 5.7 µM, 14.14 µM, 53.18 µM, and 200 µM. At 1 µM there was no inhibitory effect on the growth of groundnut. The inhibition of groundnut growth was noticeable from 5.7 µM to 200 µM, where the severe effect of aluminium (Al) stress was observed at 200 µM. The cultivars varied in their response to aluminium (Al) supply in solution culture. Groundnuts are one of the most important food crops in the world, and its supply is on a decline due to the light-textured soils that they thrive under as these soils are acidic and can easily solubilize aluminium (Al) to its toxic form. Consequently, there is a need to develop groundnut cultivars with high tolerance to soil acidity.

Keywords: aluminium toxicity, cultivars, reduction, root growth

Procedia PDF Downloads 138

Authors: Ernesto Linan, Linda Cruz, Lucero Becerra

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In this paper, a new hybridized algorithm based on Chemical Reaction Optimization and Simulated Annealing is proposed to solve the alignment sequence Problem. The Chemical Reaction Optimization is a population-based meta-heuristic algorithm based on the principles of a chemical reaction. Simulated Annealing is applied to solve a large number of combinatorial optimization problems of general-purpose. In this paper, we propose hybridization between Chemical Reaction Optimization algorithm and Simulated Annealing in order to solve the Sequence Alignment Problem. An initial population of molecules is defined at beginning of the proposed algorithm, where each molecule represents a sequence alignment problem. In order to simulate inter-molecule collisions, the process of Chemical Reaction is placed inside the Metropolis Cycle at certain values of temperature. Inside this cycle, change of molecules is done due to collisions; some molecules are accepted by applying Boltzmann probability. The results with the hybrid scheme are better than the results obtained separately.

Keywords: chemical reaction optimization, sequence alignment problem, simulated annealing algorithm, metaheuristics

Procedia PDF Downloads 202

Authors: Shokoufeh Abrisham, Seyed Mahmoud Hossieni, Elham Pishbin

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In this paper, a hybrid method based on the fault tree analysis (FTA) and Bayesian networks (BNs) are employed to evaluate the team performance quality of advanced cardiac life support (ACLS) procedures in emergency department. According to American Heart Association (AHA) guidelines, a category relying on staff action leading to clinical incidents and also some discussions with emergency medicine experts, a fault tree model for ACLS procedure is obtained based on the human performance. The obtained FTA model is converted into BNs, and some different scenarios are defined to demonstrate the efficiency and flexibility of the presented model of BNs. Also, a sensitivity analysis is conducted to indicate the effects of team leader presence and uncertainty knowledge of experts on the quality of ACLS. The proposed model based on BNs shows that how the results of risk analysis can be closed to reality comparing to the obtained results based on only FTA in medical procedures.

Keywords: advanced cardiac life support, fault tree analysis, Bayesian belief networks, numan performance, healthcare systems

Procedia PDF Downloads 136

Authors: Simon Komesker, Achim Wagner, Martin Ruskowski

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In times of volatile markets with fluctuating demand and the uncertainty of global supply chains, flexible production systems are the key to an efficient implementation of a desired production program. In this publication, the authors present a holistic information concept taking into account various influencing factors for operating towards the global optimum. Therefore, a strategy for the implementation of multi-level planning for a flexible, reconfigurable production system with an alternative production concept in the automotive industry is developed. The main contribution of this work is a system structure mixing central and decentral planning and control evaluated in a simulation framework. The information system structure in current production systems in the automotive industry is rigidly hierarchically organized in monolithic systems. The production program is created rule-based with the premise of achieving uniform cycle time. This program then provides the information basis for execution in subsystems at the station and process execution level. In today's era of mixed-(car-)model factories, complex conditions and conflicts arise in achieving logistics, quality, and production goals. There is no provision for feedback loops of results from the process execution level (resources) and process supporting (quality and logistics) systems and reconsideration in the planning systems. To enable a robust production flow, the complexity of production system control is artificially reduced by the line structure and results, for example in material-intensive processes (buffers and safety stocks - two container principle also for different variants). The limited degrees of freedom of line production have produced the principle of progress figure control, which results in one-time sequencing, sequential order release, and relatively inflexible capacity control. As a result, modularly structured production systems such as modular production according to known approaches with more degrees of freedom are currently difficult to represent in terms of information technology. The remedy is an information concept that supports cross-system and cross-level information processing for centralized and decentralized decision-making. Through an architecture of hierarchically organized but decoupled subsystems, the paradigm of hybrid control is used, and a holonic manufacturing system is offered, which enables flexible information provisioning and processing support. In this way, the influences from quality, logistics, and production processes can be linked holistically with the advantages of mixed centralized and decentralized planning and control. Modular production systems also require modularly networked information systems with semi-autonomous optimization for a robust production flow. Dynamic prioritization of different key figures between subsystems should lead the production system to an overall optimum. The tasks and goals of quality, logistics, process, resource, and product areas in a cyber-physical production system are designed as an interconnected multi-agent-system. The result is an alternative system structure that executes centralized process planning and decentralized processing. An agent-based manufacturing control is used to enable different flexibility and reconfigurability states and manufacturing strategies in order to find optimal partial solutions of subsystems, that lead to a near global optimum for hybrid planning. This allows a robust near to plan execution with integrated quality control and intralogistics.

Keywords: holonic manufacturing system, modular production system, planning, and control, system structure

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Authors: Getaneh Berie Tarekegn, Li-Chia Tai

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With the rapid advancement of artificial intelligence, low-power built-in sensors on Internet of Things devices, and communication technologies, location-aware services have become increasingly popular and have permeated every aspect of people’s lives. Global navigation satellite systems (GNSSs) are the default method of providing continuous positioning services for ground and aerial vehicles, as well as consumer devices (smartphones, watches, notepads, etc.). However, the environment affects satellite positioning systems, particularly indoors, in dense urban and suburban cities enclosed by skyscrapers, or when deep shadows obscure satellite signals. This is because (1) indoor environments are more complicated due to the presence of many objects surrounding them; (2) reflection within the building is highly dependent on the surrounding environment, including the positions of objects and human activity; and (3) satellite signals cannot be reached in an indoor environment, and GNSS doesn't have enough power to penetrate building walls. GPS is also highly power-hungry, which poses a severe challenge for battery-powered IoT devices. Due to these challenges, IoT applications are limited. Consequently, precise, seamless, and ubiquitous Positioning, Navigation and Timing (PNT) systems are crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarms, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Florin Leon, Silvia Curteanu

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Developing complete mechanistic models for polymerization reactors is not easy, because complex reactions occur simultaneously; there is a large number of kinetic parameters involved and sometimes the chemical and physical phenomena for mixtures involving polymers are poorly understood. To overcome these difficulties, empirical models based on sampled data can be used instead, namely regression methods typical of machine learning field. They have the ability to learn the trends of a process without any knowledge about its particular physical and chemical laws. Therefore, they are useful for modeling complex processes, such as the free radical polymerization of methyl methacrylate achieved in a batch bulk process. The goal is to generate accurate predictions of monomer conversion, numerical average molecular weight and gravimetrical average molecular weight. This process is associated with non-linear gel and glass effects. For this purpose, an adaptive sampling technique is presented, which can select more samples around the regions where the values have a higher variation. Several machine learning methods are used for the modeling and their performance is compared: support vector machines, k-nearest neighbor, k-nearest neighbor and random forest, as well as an original algorithm, large margin nearest neighbor regression. The suggested method provides very good results compared to the other well-known regression algorithms.

Keywords: batch bulk methyl methacrylate polymerization, adaptive sampling, machine learning, large margin nearest neighbor regression

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Authors: Mimi Roy, Sriroop Chaudhuri

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Sustainable water supply is among the basic needs for human development, especially in the rural areas of the developing nations where safe water supply and basic sanitation infrastructure is direly needed. In light of the above, we propose a simple methodology to develop a composite water sustainability index (WSI) to assess the collective performance of the existing rural water supply services (RWSS) in India over time. The WSI will be computed by summarizing the details of all the different varieties of water supply schemes presently available in India comprising of 40 liters per capita per day (lpcd), 55 lpcd, and piped water supply (PWS) per household. The WSI will be computed annually, between 2010 and 2016, to elucidate changes in holistic RWSS performances. Results will be integrated within a robust geospatial framework to identify the ‘hotspots’ (states/districts) which have persistent issues over adequate RWSS coverage and warrant spatially-optimized policy reforms in future to address sustainable human development. Dataset will be obtained from the National Rural Drinking Water Program (NRDWP), operating under the aegis of the Ministry of Drinking Water and Sanitation (MoDWS), at state/district/block levels to offer the authorities a cross-sectional view of RWSS at different levels of administrative hierarchy. Due to simplistic design, complemented by spatio-temporal cartograms, similar approaches can also be adopted in other parts of the world where RWSS need a thorough appraisal.

Keywords: rural water supply services, piped water supply, sustainability, composite index, spatial, drinking water

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Authors: Mohammadjavad Mahdavinejad, Hadi Yazdi

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The greatest influence we have from the world is shaped through the visual form, thus light is an inseparable element in human life. The use of daylight in visual perception and environment readability is an important issue for users. With regard to the hazards of greenhouse gas emissions from fossil fuels, and in line with the attitudes on the reduction of energy consumption, the correct use of daylight results in lower levels of energy consumed by artificial lighting, heating and cooling systems. Windows are usually the starting points for analysis and simulations to achieve visual comfort and energy optimization; therefore, attention should be paid to the orientation of buildings to minimize electrical energy and maximize the use of daylight. In this paper, by using the Design Builder Software, the effect of the orientation of an 18m²(3m*6m) room with 3m height in city of Tehran has been investigated considering the design constraint limitations. In these simulations, the dimensions of the building have been changed with one degree and the window is located on the smaller face (3m*3m) of the building with 80% ratio. The results indicate that the orientation of building has a lot to do with energy efficiency to meet high-performance architecture and planning goals and objectives.

Keywords: daylight, window, orientation, energy consumption, design builder

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Authors: Neritan Shkodrani, Klearta Rrushi, Anxhela Shaha

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Generally, the design of axial load capacity of deep foundations is based on the data provided from field tests, such as SPT (Standard Penetration Test) and CPT (Cone Penetration Test) tests. This paper reports the results of axial load capacity analysis of drilled shafts at a construction site at Semani, in Fier county, Fier prefecture in Albania. In this case, the axial load capacity analyses are based on the data of 416 SPT tests and 12 CPTU tests, which are carried out in this site construction using 12 boreholes (10 borings of a depth 30.0 m and 2 borings of a depth of 80.0m). The considered foundation widths range from 0.5m to 2.5 m and foundation embedment lengths is fixed at a value of 25m. SPT – based analytical methods from the Japanese practice of design (Building Standard Law of Japan) and CPT – based analytical Eslami and Fellenius methods are used for obtaining axial ultimate load capacity of drilled shafts. The considered drilled shaft (25m long and 0.5m - 2.5m in diameter) is analyzed for the soil conditions of each borehole. The values obtained from sets of calculations are shown in different charts. Then the reported axial load capacity values acquired from SPT and CPTU data are compared and some conclusions are found related to the mentioned methods of calculations.

Keywords: deep foundations, drilled shafts, axial load capacity, ultimate load capacity, allowable load capacity, SPT test, CPTU test

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Authors: Negar Sartipzadeh

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Energy-conscious design, which coordinates with the Earth ecological systems during its life cycle, has the least negative impact on the environment with the least waste of resources. Due to the increasing in world population as well as the consumption of fossil fuels that cause the production of greenhouse gasses and environmental pollution, mankind is looking for renewable and also sustainable energies. The Iranian native construction is a clear evidence of energy-aware designing. Our predecessors were forced to rely on the natural resources and sustainable energies as well as environmental issues which have been being considered in the recent world. One of these endless energies is wind energy. Iranian traditional architecture foundations is a appropriate model in solving the environmental crisis and the contemporary energy. What will come in this paper is an effort to recognition and introduction of the unique characteristics of the Iranian architecture in the application of aerodynamic and hydraulic energies derived from the wind, which are the most common and major type of using sustainable energies in the traditional architecture of Iran. Therefore, the recent research attempts to offer a hybrid system suggestions for application in new constructions designing in a region such as Nashtifan, which has potential through reviewing windmills and how they deal with sustainable energy sources, as a model of Iranian native construction.

Keywords: renewable energy, sustainable building, windmill, Iranian architecture

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Authors: Yulin Liang

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Under the background of protecting ecology, natural education is an effective way for people to understand nature. At the same time, it is a new means of sustainable development of eco-tourism, which can improve the functions of China 's protected areas and develop new business formats for the development of national parks. This study takes national park gateway communities as the research object and uses literature review, inductive reasoning and other research methods to sort out the development process of natural education in China and the research progress of natural education design in national park gateway communities. Finally, it discuss how gateway communities can use natural education to transform their development methods and provide theoretical and practical basis for the development of gateway communities in national parks.

Keywords: nature education, gateway communities, national park, sustainable development

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Authors: Daniela Velichová

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Plenty of ideas on how to adopt active learning methods in education are available nowadays. Mathematics is a subject where the active involvement of students is required in particular in order to achieve desirable results regarding sustainable knowledge and deep understanding. The present article is based on the outcomes of an Erasmus+ project DrIVE-MATH, that was aimed at developing a novel and integrated framework to teach maths classes in engineering courses at the university level. It is fundamental for students from the early years of their academic life to have agile minds. They must be prepared to adapt to their future working environments, where enterprises’ views are always evolving, where all collaborate in teams, and relations between peers are thought for the well-being of the whole - workers and company profit. This reality imposes new requirements on higher education in terms of adaptation of different pedagogical methods, such as project-based and active-learning methods used within the course curricula. Active learning methodologies are regarded as an effective way to prepare students to meet the challenges posed by enterprises and to help them in building critical thinking, analytic reasoning, and insight to the solved complex problems from different perspectives. Fostering learning-by-doing activities in the pedagogical process can help students to achieve learning independence, as they could acquire deeper conceptual understanding by experimenting with the abstract concept in a more interesting, useful, and meaningful way. Clear information about learning outcomes and goals might help students to take more responsibility for their learning results. Active learning methods implemented by the project team members in their teaching practice, eduScrum and Jigsaw in particular, proved to provide better scientific and soft skills support to students than classical teaching methods. EduScrum method enables teachers to generate a working environment that stimulates students' working habits and self-initiative as they become aware of their responsibilities within the team, their own acquired knowledge, and their abilities to solve problems independently, though in collaboration with other team members. This method enhances collaborative learning, as students are working in teams towards a common goal - knowledge acquisition, while they are interacting with each other and evaluated individually. Teams consisting of 4-5 students work together on a list of problems - sprint; each member is responsible for solving one of them, while the group leader – a master, is responsible for the whole team. A similar principle is behind the Jigsaw technique, where the classroom activity makes students dependent on each other to succeed. Students are divided into groups, and assignments are split into pieces, which need to be assembled by the whole group to complete the (Jigsaw) puzzle. In this paper, analysis of students’ perceptions concerning the achievement of deeper conceptual understanding in mathematics and the development of soft skills, such as self-motivation, critical thinking, flexibility, leadership, responsibility, teamwork, negotiation, and conflict management, is presented. Some new challenges are discussed as brought by introducing active learning methods in the basic mathematics courses. A few examples of sprints developed and used in teaching basic maths courses at technical universities are presented in addition.

Keywords: active learning methods, collaborative learning, conceptual understanding, eduScrum, Jigsaw, soft skills

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Authors: Assia Belfar, Mohamed Hadjadj, Messaouda Dakmouche, Zineb Ghiaba

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Introduction: This study aims to phytochemical screening; Extracting the active compounds and estimate the effectiveness of antioxidant in Medicinal plants desert Limoniastrum guyonianum (Zeïta) from South Algeria. Methods: Total phenolic content and total flavonoid content using Folin-Ciocalteu and aluminum chloride colorimetric methods, respectively. The total antioxidant capacity was estimated by the following methods: DPPH (1.1-diphenyl-2-picrylhydrazyl radical) and reducing power assay. Results: Phytochemical screening of the plant part reveals the presence of phenols, saponins, flavonoids and tannins. While alkaloids and Terpenoids were absent. The acetonic extract of L. guyonianum was extracted successively with ethyl acetate and butanol. Extraction of yield varied widely in the L. guyonianum ranging from (0.9425 %to 11.131%). The total phenolic content ranged from 53.33 mg GAE/g DW to 672.79 mg GAE/g DW. The total flavonoid concentrations varied from 5.45 to 21.71 mg/100g. IC50 values ranged from 0.02 ± 0.0004 to 0.13 ± 0.002 mg/ml. All extracts showed very good activity of ferric reducing power, the higher power was in butanol fraction (23.91 mM) more effective than BHA, BHT and VC. Conclusions: Demonstrated this study that the acetonic extract of L. guyonianum contain a considerable quantity of phenolic compounds and possess a good antioxidant activity. Can be used as an easily accessible source of Natural Antioxidants and as a possible food supplement and in the pharmaceutical industry.

Keywords: limoniastrum guyonianum, phenolics compounds, flavonoid compound, antioxidant activity

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Authors: Nhabhat Chaimongkol

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Human capital is one of the factors that are vital for economic growth. This is especially true as humans will face increasingly more forms of disruptive technology in the near future. Therefore, there is a need to develop human capital in order to overcome the current uncertainty in the global economy and the future of jobs. In recent years, Thailand has increasingly devoted more attention to developing its human capital. The Thai government has raised this issue in its national agenda, which is part of its 20-year national strategy. Currently, there are multiple challenges and solutions regarding this issue. This study aims to find out what are the challenges and solutions to human capital development in Thailand. The research in this study uses mixed methods consisting of quantitative and qualitative research methods. The results show that while Thailand has many plans to develop human capital, it is still lacking the necessary actions and integrations that are required to achieve its goals. Finally, the challenges and solutions will be discussed in detail.

Keywords: challenges, human capital, solutions, Thailand

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Authors: Bong Jae Lee, Jeong Il Lee, Hyo Su Kim

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Both developed and developing countries have adopted the decision to join the Paris agreement to reduce greenhouse gas (GHG) emissions at the Conference of the Parties (COP) 21 meeting in Paris. As a result, the developed and developing countries have to submit the Intended Nationally Determined Contributions (INDC) by 2020, and each country will be assessed for their performance in reducing GHG. After that, they shall propose a reduction target which is higher than the previous target every five years. Therefore, an accurate method for calculating greenhouse gas emissions is essential to be presented as a rational for implementing GHG reduction measures based on the reduction targets. Non-CO2 GHGs (CF4, NF3, N2O, SF6 and so on) are being widely used in fabrication process of semiconductor manufacturing, and etching/deposition process of display manufacturing process. The Global Warming Potential (GWP) value of Non-CO2 is much higher than CO2, which means it will have greater effect on a global warming than CO2. Therefore, GHG calculation methods of the electronics industry are provided by Intergovernmental Panel on climate change (IPCC) and U.S. Environmental Protection Agency (EPA), and it will be discussed at ISO/TC 146 meeting. As discussed earlier, being precise and accurate in calculating Non-CO2 GHG is becoming more important. Thus this study aims to discuss the implications of the calculating methods through comparing the methods of IPCC and EPA. As a conclusion, after analyzing the methods of IPCC & EPA, the method of EPA is more detailed and it also provides the calculation for N2O. In case of the default emission factor (by IPCC & EPA), IPCC provides more conservative results compared to that of EPA; The factor of IPCC was developed for calculating a national GHG emission, while the factor of EPA was specifically developed for the U.S. which means it must have been developed to address the environmental issue of the US. The semiconductor factory ‘A’ measured F gas according to the EPA Destruction and Removal Efficiency (DRE) protocol and estimated their own DRE, and it was observed that their emission factor shows higher DRE compared to default DRE factor of IPCC and EPA Therefore, each country can improve their GHG emission calculation by developing its own emission factor (if possible) at the time of reporting Nationally Determined Contributions (NDC). Acknowledgements: This work was supported by the Korea Evaluation Institute of Industrial Technology (No. 10053589).

Keywords: non-CO2 GHG, GHG emission, electronics industry, measuring method

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Authors: Marta Fonseca, Pedro Marvão, Beatriz Oliveira, Bruno Heleno, Pedro Carreiro-Martins, Nuno Neuparth, António Rendas

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Background: Concept maps (CMs) visually represent hierarchical connections among related ideas. They foster logical organization and clarify idea relationships, potentially aiding medical students in critical thinking (to think clearly and rationally about what to do or what to believe). However, there are inconsistent claims about the use of CMs in undergraduate medical education. Our three research questions are: 1) What studies have been published on concept mapping in undergraduate medical education? 2) What was the impact of CMs on students’ critical thinking? 3) How and why have these interventions had an educational impact? Methods: Eight databases were systematically searched (plus a manual and an additional search were conducted). After eliminating duplicate entries, titles, and abstracts, and full-texts were independently screened by two authors. Data extraction and quality assessment of the studies were independently performed by two authors. Qualitative and quantitative data were integrated using mixed-methods. The results were reported using the structured approach to the reporting in healthcare education of evidence synthesis statement and BEME guidance. Results: Thirty-nine studies were included from 26 journals (19 quantitative, 8 qualitative and 12 mixed-methods studies). CMs were considered as a tool to promote critical thinking, both in the perception of students and tutors, as well as in assessing students’ knowledge and/or skills. In addition to their role as facilitators of knowledge integration and critical thinking, CMs were considered both teaching and learning methods. Conclusions: CMs are teaching and learning tools which seem to help medical students develop critical thinking. This is due to the flexibility of the tool as a facilitator of knowledge integration, as a learning and teaching method. The wide range of contexts, purposes, and variations in how CMs and instruments to assess critical thinking are used increase our confidence that the positive effects are consistent.

Keywords: concept map, medical education, undergraduate, critical thinking, meaningful learning

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Authors: Mustafa Elfituri, Jonathan Cook

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Recently, graph-based computations have become more important in large-scale scientific computing as they can provide a methodology to model many types of relations between independent objects. They are being actively used in fields as varied as biology, social networks, cybersecurity, and computer networks. At the same time, graph problems have some properties such as irregularity and poor locality that make their performance different than regular applications performance. Therefore, parallelizing graph algorithms is a hard and challenging task. Initial evidence is that standard computer architectures do not perform very well on graph algorithms. Little is known exactly what causes this. The Graph500 benchmark is a representative application for parallel graph-based computations, which have highly irregular data access and are driven more by traversing connected data than by computation. In this paper, we present results from analyzing the performance of various example implementations of Graph500, including a shared memory (OpenMP) version, a distributed (MPI) version, and a hybrid version. We measured and analyzed all the factors that affect its performance in order to identify possible changes that would improve its performance. Results are discussed in relation to what factors contribute to performance degradation.

Keywords: graph computation, graph500 benchmark, parallel architectures, parallel programming, workload characterization.

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Authors: G. R. Hashemi Tabar, G. R. Razmi, F. Mirshekar

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Echinococcus granulosus have ten strains from G1 to G9. Each strain is related to special intermediated host. The morphology, epidemiology, treatment and control in these strains are different. There are many morphological and molecular methods to differentiate of Echinococcus strains. However, using both methods were provided better information about identification of each strain. The aim of study was to identify Echinococcus granulosus strain of hydrated cysts in slaughtered sheep using morphological and molecular methods in Mashhad area. In the present study, the infected liver and lung with hydatid cysts were collected and transferred to laboratory. The hydatid cyst liquid was extracted and morphological characters of rostellar hook protosclocies were measured using micrometer ocular. The total length of large blade length of large hooks, total length of small and blade length of small hooks, and number of hooks per protoscolex were 23± 0.3μm, 11.7±0.5 μm, 19.3±1.1 μm,8±1.1 and 33.7±0.7 μm, respectively. In molecular section of the study, DNA each samples was extracted with MBST Kit and development of PCR using special primers (EgF, EgR) which amplify fragment of ITS1 gen. The PCR product was digested with Bsh1236I enzyme. Based on pattern of PCR-RLFP results (four band forming), G1, G2 and G3 strain of Echinococcus granulosus were obtained. Differentiation of three strains was done using sequencing analysis and G1 strain was diagnosed. The agreement between the molecular results with morphometric characters of rosetellar hook was confirmed the presence of G1 strain of Echinococcus in the slaughtered sheep of Mashhad area.

Keywords: Echinococcus granulosus, Hydatid cyst, PCR, sheep

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Authors: Ekaterina Lukianchenko

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This article sums up a six-year experience of teaching English as a foreign language to over 900 university students at MGIMO (Moscow University of International Relations, Russia), all of them native speakers of Russian aged 16 to 23. By combining modern communicative approach to teaching with cognitive linguistics theories, one can deal more effectively with deeply rooted mistakes which particular students have of which conventional methods have failed to eliminate. If language items are understood as concepts and frames, and classroom activities as meaningful parts of language competence development, this might help to solve such problems as incorrect use of words, unsuitable register, and confused tenses - as well as logical or structural mistakes, and even certain psychological issues concerning essay writing. Along with classic teaching methods, such classroom practice includes plenty of interaction between students - playing special classroom games aimed at eliminating particular mistakes, working in pairs and groups, integrating all skills in one class. The main conclusions that the author of the experiment makes consist in an assumption that academic essay writing classes demand a balanced plan. This should not only include writing as such, but additionally feature elements of listening, reading, speaking activities specifically chosen according to the skills and language students will need to write the particular type of essay.

Keywords: academic essay writing, creative teaching, cognitive linguistics, competency-based approach, communicative language teaching, frame, concept

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Authors: Areti Angeliki Veroniki, Sofia Tsokani, Evangelos Paraskevaidis, Dimitris Mavridis

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The plethora of diagnostic test accuracy (DTA) studies has led to the increased use of systematic reviews and meta-analysis of DTA studies. Clinicians and healthcare professionals often consult DTA meta-analyses to make informed decisions regarding the optimum test to choose and use for a given setting. For example, the human papilloma virus (HPV) DNA, mRNA, and cytology can be used for the cervical intraepithelial neoplasia grade 2+ (CIN2+) diagnosis. But which test is the most accurate? Studies directly comparing test accuracy are not always available, and comparisons between multiple tests create a network of DTA studies that can be synthesized through a network meta-analysis of diagnostic tests (DTA-NMA). The aim is to summarize the DTA-NMA methods for at least three index tests presented in the methodological literature. We illustrate the application of the methods using a real data set for the comparative accuracy of HPV DNA, HPV mRNA, and cytology tests for cervical cancer. A search was conducted in PubMed, Web of Science, and Scopus from inception until the end of July 2019 to identify full-text research articles that describe a DTA-NMA method for three or more index tests. Since the joint classification of the results from one index against the results of another index test amongst those with the target condition and amongst those without the target condition are rarely reported in DTA studies, only methods requiring the 2x2 tables of the results of each index test against the reference standard were included. Studies of any design published in English were eligible for inclusion. Relevant unpublished material was also included. Ten relevant studies were finally included to evaluate their methodology. DTA-NMA methods that have been presented in the literature together with their advantages and disadvantages are described. In addition, using 37 studies for cervical cancer obtained from a published Cochrane review as a case study, an application of the identified DTA-NMA methods to determine the most promising test (in terms of sensitivity and specificity) for use as the best screening test to detect CIN2+ is presented. As a conclusion, different approaches for the comparative DTA meta-analysis of multiple tests may conclude to different results and hence may influence decision-making. Acknowledgment: This research is co-financed by Greece and the European Union (European Social Fund- ESF) through the Operational Programme «Human Resources Development, Education and Lifelong Learning 2014-2020» in the context of the project “Extension of Network Meta-Analysis for the Comparison of Diagnostic Tests ” (MIS 5047640).

Keywords: colposcopy, diagnostic test, HPV, network meta-analysis

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