Search results for: dynamic of networks.

Authors: Kréhi Serge Agbli, Samuel Portebos, Michaël Salomon

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Here a methodology is considered aiming at evaluating the economic benefit of the provision of a primary frequency control unit using a Battery Energy Storage System (BESS). In this methodology, two control types (basic and hysteresis) are implemented and the corresponding minimum energy storage system power allowing to maintain the frequency drop inside a given threshold under a given contingency is identified and compared using DigSilent’s PowerFactory software. Following this step, the corresponding energy storage capacity (in MWh) is calculated. As PowerFactory is dedicated to dynamic simulation for transient analysis, a first order model related to the IEEE 9 bus grid used for the analysis under PowerFactory is characterized and implemented on MATLAB-Simulink. Primary frequency control is simulated using the two control types over one-month grid's frequency deviation data on this Simulink model. This simulation results in the energy throughput both basic and hysteresis BESSs. It emerges that the 15 minutes operation band of the battery capacity allocated to frequency control is sufficient under the considered disturbances. A sensitivity analysis on the width of the control deadband is then performed for the two control types. The deadband width variation leads to an identical sizing with the hysteresis control showing a better frequency control at the cost of a higher delivered throughput compared to the basic control. An economic analysis comparing the cost of the sized BESS to the potential revenues is then performed.

Keywords: Battery Energy Storage System, electrical network frequency stability, frequency control unit, PowerFactory.

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Authors: David Cobham

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In higher education, a great degree of importance is placed on the internationalisation of the student experience. This is seen as a valuable contributor to elements such as building confidence, broadening knowledge, creating networks, and connections and enhancing employability for current students who will become the next generation of managers in technology and business. The COVID-19 pandemic has affected all areas of people’s lives. The limitations of travel coupled with the fears and concerns generated by the health risks have dramatically reduced the opportunity for students to engage with this agenda. Institutions of higher education have been required to rethink fundamental aspects of their business model from recruitment and enrolment, through learning approaches, assessment methods and the pathway to employment. This paper presents a case study which focuses on student mobility and how the physical experience of being in another country either to study, to work, to volunteer or to gain cultural and social enhancement has of necessity been replaced by alternative approaches. It considers trans-national education as an alternative to physical study overseas, virtual mobility and internships as an alternative to international work experience and adopting collaborative on-line projects as an alternative to in-person encounters. The paper concludes that although these elements have been adopted to address the current situation, the lessons learnt and the feedback gained suggests that they have contributed successfully in new and sometimes unexpected ways, and that they will persist beyond the present to become part of the "new normal" for the future. That being the case, senior leaders of institutions of higher education will be required to revisit their international plans and to rewrite their international strategies to take account of and build upon these changes.

Keywords: Trans-national education, internationalisation, higher education management, virtual mobility.

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Authors: Seyed Saeid Tabaee, Omid Bahar

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Nowadays, energy dissipation devices are commonly used in structures. High rate of energy absorption during earthquakes is the benefit of using such devices, which results in damage reduction of structural elements, specifically columns. The hysteretic damping capacity of energy dissipation devices is the key point that it may adversely make analysis and design process complicated. This effect may be generally represented by Equivalent Viscous Damping (EVD). The equivalent viscous damping might be obtained from the expected hysteretic behavior regarding to the design or maximum considered displacement of a structure. In this paper, the hysteretic damping coefficient of a steel Moment Resisting Frame (MRF), which its performance is enhanced by a Buckling Restrained Brace (BRB) system has been evaluated. Having foresight of damping fraction between BRB and MRF is inevitable for seismic design procedures like Direct Displacement-Based Design (DDBD) method. This paper presents an approach to calculate the damping fraction for such systems by carrying out the dynamic nonlinear time history analysis (NTHA) under harmonic loading, which is tuned to the natural system frequency. Two MRF structures, one equipped with BRB and the other without BRB are simultaneously studied. Extensive analysis shows that proportion of each system damping fraction may be calculated by its shear story portion. In this way, contribution of each BRB in the floors and their general contribution in the structural performance may be clearly recognized, in advance.

Keywords: Buckling restrained brace, Direct displacement based design, Dual systems, Hysteretic damping, Moment resisting frames.

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Authors: Daniel M. Muntean, Viorel Ungureanu

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More than half of the urban population in Romania lives today in residential buildings made out of large prefabricated reinforced concrete panels. Since their initial design was made in the 1960’s, these housing units are now being technically and morally outdated, consuming large amounts of energy for heating, cooling, ventilation and lighting, while failing to meet the needs of the contemporary life-style. Due to their widespread use, the design of a system that improves their energy efficiency would have a real impact, not only on the energy consumption of the residential sector, but also on the quality of life that it offers. Furthermore, with the transition of today’s existing power grid to a “smart grid”, buildings could become an active element for future electricity networks by contributing in micro-generation and energy storage. One of the most addressed issues today is to find locally adapted strategies that can be applied considering the 20-20-20 EU policy criteria and to offer sustainable and innovative solutions for the cost-optimal energy performance of buildings adapted on the existing local market. This paper presents a possible adaptive design scenario towards sustainable retrofitting of these housing units. The apartments are transformed in order to meet the current living requirements and additional extensions are placed on top of the building, replacing the unused roof space, acting not only as housing units, but as active solar energy collection systems. An adaptive building envelope is ensured in order to achieve overall air-tightness and an elevator system is introduced to facilitate access to the upper levels.

Keywords: Adaptive building, energy efficiency, retrofitting, residential buildings, smart grid.

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Authors: Masoud Mahdavi, Mojtaba Farzaneh Moghadam

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The seismic forces caused by the waves created in the depths of the earth during the earthquake hit the structure and cause the building to vibrate. Creating large seismic forces will cause low-strength sections in the structure to suffer extensive surface damage. The use of new steel shear walls in steel structures has caused the strength of the building and its main members (columns) to increase due to the reduction and depreciation of seismic forces during earthquakes. In the present study, an attempt was made to evaluate a type of steel shear wall that has regular holes in the inner sheet by modeling the finite element model with Abacus software. The shear wall of the steel plate, measuring 6000 × 3000 mm (one floor) and 3 mm thickness, was modeled with four different pores with a cross-sectional area. The shear wall was dynamically subjected to a time history of 5 seconds by three accelerators, El Centro, Imperial Valley and Kobe. The results showed that increasing the distance between the geometric center of the hole and the geometric center of the inner plate in the steel shear wall (increasing the R_CS index) caused the total maximum acceleration to be transferred from the perimeter of the hole to horizontal and vertical beams. The results also show that there is no direct relationship between R_CS index and total acceleration in steel shear wall and R_CS index is separate from the peak ground acceleration value of earthquake.

Keywords: Hollow Steel plate shear wall, time history analysis, finite element method, Abaqus Software.

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Authors: Jozef Mindas, Jaroslav Skvarenina, Jana Skvareninova

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Study of the effects of climate change on Norway Spruce (Picea abies) forests has mainly focused on the diversity of tree species diversity of tree species as a result of the ability of species to tolerate temperature and moisture changes as well as some effects of disturbance regime changes. The tree species’ diversity changes in spruce forests due to climate change have been analyzed via gap model. Forest gap model is a dynamic model for calculation basic characteristics of individual forest trees. Input ecological data for model calculations have been taken from the permanent research plots located in primeval forests in mountainous regions in Slovakia. The results of regional scenarios of the climatic change for the territory of Slovakia have been used, from which the values are according to the CGCM3.1 (global) model, KNMI and MPI (regional) models. Model results for conditions of the climate change scenarios suggest a shift of the upper forest limit to the region of the present subalpine zone, in supramontane zone. N. spruce representation will decrease at the expense of beech and precious broadleaved species (Acer sp., Sorbus sp., Fraxinus sp.). The most significant tree species diversity changes have been identified for the upper tree line and current belt of dwarf pine (Pinus mugo) occurrence. The results have been also discussed in relation to most important disturbances (wind storms, snow and ice storms) and phenological changes which consequences are little known. Special discussion is focused on biomass production changes in relation to carbon storage diversity in different carbon pools.

Keywords: Biodiversity, climate change, Norway spruce forests, gap model.

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Authors: I. Abuiziah, A. Oulhaj, K. Sebari, D. Ouazar, A. A. Saber

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In water pipeline systems, the flow control is an integrated part of the operation, for instance, opening and closing the valves, starting and stopping the pumps, when these operations very quickly performed, they shall cause the hydraulic transient phenomena, which may cause pump and, valve failures and catastrophic pipe ruptures. Fluid transient analysis is one of the more challenging and complicated flow problems in the design and the operation of water pipeline systems. Transient control has become an essential requirement for ensuring safe operation of water pipeline systems. An accurate analysis and suitable protection devices should be used to protect water pipeline systems. The fourth-order Runge-Kutta method has been used to solve the dynamic and continuity equations in the rigid column method, while the characteristics method used to solve these equations in the full elastic methods. This paper presents the problem of modeling and simulating of transient phenomena in conveying pipeline systems based on the rigid column and full elastic methods. Also, it provides the influence of using the protection devices to protect the pipeline systems from damaging due to the gain pressure which occur in the transient state. The results obtained provide that the model is an efficient tool for flow transient analysis and provide approximately identical results by using these two methods. Moreover; using the closed surge tank reduces the unfavorable effects of transients.

Keywords: Flow transient, Pipeline, Air chamber, Numerical model, Protection devices, Elastic method, Rigid column method.

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Authors: A.Qaderi, A. Heydarinasab, M. Ardjmand

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Poly-β-hydroxybutyrate (PHB) is one of the most famous biopolymers that has various applications in production of biodegradable carriers. The most important strategy for enhancing efficiency in production process and reducing the price of PHB, is the accurate expression of kinetic model of products formation and parameters that are effective on it, such as Dry Cell Weight (DCW) and substrate consumption. Considering the high capabilities of artificial neural networks in modeling and simulation of non-linear systems such as biological and chemical industries that mainly are multivariable systems, kinetic modeling of microbial production of PHB that is a complex and non-linear biological process, the three layers perceptron neural network model was used in this study. Artificial neural network educates itself and finds the hidden laws behind the data with mapping based on experimental data, of dry cell weight, substrate concentration as input and PHB concentration as output. For training the network, a series of experimental data for PHB production from Hydrogenophaga Pseudoflava by glucose carbon source was used. After training the network, two other experimental data sets that have not intervened in the network education, including dry cell concentration and substrate concentration were applied as inputs to the network, and PHB concentration was predicted by the network. Comparison of predicted data by network and experimental data, indicated a high precision predicted for both fructose and whey carbon sources. Also in present study for better understanding of the ability of neural network in modeling of biological processes, microbial production kinetic of PHB by Leudeking-Piret experimental equation was modeled. The Observed result indicated an accurate prediction of PHB concentration by artificial neural network higher than Leudeking- Piret model.

Keywords: Kinetic Modeling, Poly-β-Hydroxybutyrate (PHB), Hydrogenophaga Pseudoflava, Artificial Neural Network, Leudeking-Piret

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Authors: S. Shakibaei, P. Alpkokin

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The railway network is one of the major components of a transportation system in a country which may be an indicator of the country’s level of economic improvement. Since 2000s on, revival of national railways and development of High Speed Rail (HSR) lines are one of the most remarkable policies of Turkish government in railway sector. Within this trend, the railway age is to be revived and coming decades will be a golden opportunity. Indubitably, major infrastructures such as road and railway networks require sizeable investment capital, precise maintenance and reparation. Traditionally, governments are held responsible for funding, operating and maintaining these infrastructures. However, lack or shortage of financial resources, risk responsibilities (particularly cost and time overrun), and in some cases inefficacy in constructional, operational and management phases persuade governments to find alternative options. Financial power, efficient experiences and background of private sector are the factors convincing the governments to make a collaboration with private parties to develop infrastructures. Public-Private Partnerships (PPP or 3P or P3) and related regulatory issues are born considering these collaborations. In Turkey, PPP approaches have attracted attention particularly during last decade and these types of investments have been accelerated by government to overcome budget limitations and cope with inefficacy of public sector in improving transportation network and its operation. This study mainly tends to present a comprehensive overview of PPP concept, evaluate the regulatory procedure in Europe and propose a general framework for Turkish State Railways (TCDD) as an outlook on privatization, liberalization and deregulation of railway network.

Keywords: Deregulation, high-speed rail, liberalization, privatization, public-private partnership.

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Authors: Faiza Belbachir, Thibault Schienhinski

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The massive development of online social networks allows users to post and share their opinions on various topics. With this huge volume of opinion, it is interesting to extract and interpret these information for different domains, e.g., product and service benchmarking, politic, system of recommendation. This is why opinion detection is one of the most important research tasks. It consists on differentiating between opinion data and factual data. The difficulty of this task is to determine an approach which returns opinionated document. Generally, there are two approaches used for opinion detection i.e. Lexical based approaches and Machine Learning based approaches. In Lexical based approaches, a dictionary of sentimental words is used, words are associated with weights. The opinion score of document is derived by the occurrence of words from this dictionary. In Machine learning approaches, usually a classifier is trained using a set of annotated document containing sentiment, and features such as n-grams of words, part-of-speech tags, and logical forms. Majority of these works are based on documents text to determine opinion score but dont take into account if these texts are really correct. Thus, it is interesting to exploit other information to improve opinion detection. In our work, we will develop a new way to consider the opinion score. We introduce the notion of trust score. We determine opinionated documents but also if these opinions are really trustable information in relation with topics. For that we use lexical SentiWordNet to calculate opinion and trust scores, we compute different features about users like (numbers of their comments, numbers of their useful comments, Average useful review). After that, we combine opinion score and trust score to obtain a final score. We applied our method to detect trust opinions in TRIPADVISOR collection. Our experimental results report that the combination between opinion score and trust score improves opinion detection.

Keywords: Tripadvisor, Opinion detection, SentiWordNet, trust score.

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Authors: Vipul M. Patel, Hemantkumar B. Mehta

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Technological innovations in electronic world demand novel, compact, simple in design, less costly and effective heat transfer devices. Closed Loop Pulsating Heat Pipe (CLPHP) is a passive phase change heat transfer device and has potential to transfer heat quickly and efficiently from source to sink. Thermal performance of a CLPHP is governed by various parameters such as number of U-turns, orientations, input heat, working fluids and filling ratio. The present paper is an attempt to predict the thermal performance of a CLPHP using Artificial Neural Network (ANN). Filling ratio and heat input are considered as input parameters while thermal resistance is set as target parameter. Types of neural networks considered in the present paper are radial basis, generalized regression, linear layer, cascade forward back propagation, feed forward back propagation; feed forward distributed time delay, layer recurrent and Elman back propagation. Linear, logistic sigmoid, tangent sigmoid and Radial Basis Gaussian Function are used as transfer functions. Prediction accuracy is measured based on the experimental data reported by the researchers in open literature as a function of Mean Absolute Relative Deviation (MARD). The prediction of a generalized regression ANN model with spread constant of 4.8 is found in agreement with the experimental data for MARD in the range of ±1.81%.

Keywords: ANN models, CLPHP, filling ratio, generalized regression, spread constant.

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Authors: Sergio Mauricio Pérez López, Luis Rodrigo Valencia Pérez, Juan Manuel Peña Aguilar, Adelina Morita Alexander

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The culture of continuous improvement in organizations is very important as it represents a source of competitive advantage. This article discusses the transfer of knowledge between companies which formed cross-functional teams and used a dynamic model for knowledge creation as a framework. In addition, the article discusses the structure of cognitive assets in companies and the concept of "stickiness" (which is defined as an obstacle to the transfer of knowledge). The purpose of this analysis is to show that an improvement in the attitude of individual members of an organization creates opportunities, and that an exchange of information and knowledge leads to generating continuous improvements in the company as a whole. This article also discusses the importance of creating the proper conditions for sharing tacit knowledge. By narrowing gaps between people, mutual trust can be created and thus contribute to an increase in sharing. The concept of adapting knowledge to new environments will be highlighted, as it is essential for companies to translate and modify information so that such information can fit the context of receiving organizations. Adaptation will ensure that the transfer process is carried out smoothly by preventing "stickiness". When developing the transfer process on cross-functional teams (as opposed to working groups), the team acquires the flexibility and responsiveness necessary to meet objectives. These types of cross-functional teams also generate synergy due to the array of different work backgrounds of their individuals. When synergy is established, a culture of continuous improvement is created.

Keywords: Knowledge transfer, continuous improvement, teamwork, cognitive assets.

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Authors: Anca-Diana Bibiri, Mihaela Mocanu, Adrian Turculeț

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In a language the inventory of greetings is dynamic with frequent input and output, although this is hardly noticed by the speakers. In this register, there are a number of constant, conservative elements that survive different language models (among them, the classic formulae: bună ziua! (good afternoon!), bună seara! (good evening!), noapte bună! (good night!), la revedere! (goodbye!) and a number of items that fail to pass the test of time, according to language use at a time (ciao!, pa!, bai!). The source of innovation depends both of internal factors (contraction, conversion, combination of classic formulae of greetings), and of external ones (borrowings and calques). Their use imposes their frequencies at once, namely the elimination of the use of others. This paper presents a sociolinguistic approach of contemporary Romanian greetings, based on prosodic surveys in two research projects: AMPRom, and SoRoEs. Romanian language presents a rich inventory of questions (especially partial interrogatives questions/WH-Q) which are used as greetings, alone or, more commonly accompanying a proper greeting. The representative of the typical formulae is Ce mai faci? (How are you?), which, unlike its English counterpart How do you do?, has not become a stereotype, but retains an obvious emotional impact, while serving as a mark of sociolinguistic group. The analyzed corpus consists of structures containing greetings recorded in the main Romanian cultural (urban) centers. From the methodological point of view, the acoustic analysis of the recorded data is performed using software tools (GoldWave, Praat), identifying intonation patterns related to three sociolinguistics variables: age, sex and level of education. The intonation patterns of the analyzed statements are at the interface between partial questions and typical greetings.

Keywords: acoustic analysis, greetings, Romanian language, sociolinguistics

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Authors: C. Xavier Mendieta, J. J McArthur

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Governments are playing an increasingly active role in reducing carbon emissions, and a key strategy has been the introduction of mandatory energy disclosure policies. These policies have resulted in a significant amount of publicly available data, providing researchers with a unique opportunity to develop location-specific energy and carbon emission benchmarks from this data set, which can then be used to develop building archetypes and used to inform urban energy models. This study presents the development of such a benchmark using the public reporting data. The data from Ontario’s Ministry of Energy for Post-Secondary Educational Institutions are being used to develop a series of building archetype dynamic building loads and energy benchmarks to fill a gap in the currently available building database. This paper presents the development of a benchmark for college and university residences within ASHRAE climate zone 6 areas in Ontario using the mandatory disclosure energy and greenhouse gas emissions data. The methodology presented includes data cleaning, statistical analysis, and benchmark development, and lessons learned from this investigation are presented and discussed to inform the development of future energy benchmarks from this larger data set. The key findings from this initial benchmarking study are: (1) the importance of careful data screening and outlier identification to develop a valid dataset; (2) the key features used to develop a model of the data are building age, size, and occupancy schedules and these can be used to estimate energy consumption; and (3) policy changes affecting the primary energy generation significantly affected greenhouse gas emissions, and consideration of these factors was critical to evaluate the validity of the reported data.

Keywords: Building archetypes, data analysis, energy benchmarks, GHG emissions.

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Authors: M. R. Homaeinezhad, E. Tavakkoli, M. Habibi, S. A. Atyabi, A. Ghaffari

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This paper describes a new supervised fusion (hybrid) electrocardiogram (ECG) classification solution consisting of a new QRS complex geometrical feature extraction as well as a new version of the learning vector quantization (LVQ) classification algorithm aimed for overcoming the stability-plasticity dilemma. Toward this objective, after detection and delineation of the major events of ECG signal via an appropriate algorithm, each QRS region and also its corresponding discrete wavelet transform (DWT) are supposed as virtual images and each of them is divided into eight polar sectors. Then, the curve length of each excerpted segment is calculated and is used as the element of the feature space. To increase the robustness of the proposed classification algorithm versus noise, artifacts and arrhythmic outliers, a fusion structure consisting of five different classifiers namely as Support Vector Machine (SVM), Modified Learning Vector Quantization (MLVQ) and three Multi Layer Perceptron-Back Propagation (MLP–BP) neural networks with different topologies were designed and implemented. The new proposed algorithm was applied to all 48 MIT–BIH Arrhythmia Database records (within–record analysis) and the discrimination power of the classifier in isolation of different beat types of each record was assessed and as the result, the average accuracy value Acc=98.51% was obtained. Also, the proposed method was applied to 6 number of arrhythmias (Normal, LBBB, RBBB, PVC, APB, PB) belonging to 20 different records of the aforementioned database (between– record analysis) and the average value of Acc=95.6% was achieved. To evaluate performance quality of the new proposed hybrid learning machine, the obtained results were compared with similar peer– reviewed studies in this area.

Keywords: Feature Extraction, Curve Length Method, SupportVector Machine, Learning Vector Quantization, Multi Layer Perceptron, Fusion (Hybrid) Classification, Arrhythmia Classification, Supervised Learning Machine.

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Authors: Perumal Kumar, Rajamohan Ganesan

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Addition of milli or micro sized particles to the heat transfer fluid is one of the many techniques employed for improving heat transfer rate. Though this looks simple, this method has practical problems such as high pressure loss, clogging and erosion of the material of construction. These problems can be overcome by using nanofluids, which is a dispersion of nanosized particles in a base fluid. Nanoparticles increase the thermal conductivity of the base fluid manifold which in turn increases the heat transfer rate. Nanoparticles also increase the viscosity of the basefluid resulting in higher pressure drop for the nanofluid compared to the base fluid. So it is imperative that the Reynolds number (Re) and the volume fraction have to be optimum for better thermal hydraulic effectiveness. In this work, the heat transfer enhancement using aluminium oxide nanofluid using low and high volume fraction nanofluids in turbulent pipe flow with constant wall temperature has been studied by computational fluid dynamic modeling of the nanofluid flow adopting the single phase approach. Nanofluid, up till a volume fraction of 1% is found to be an effective heat transfer enhancement technique. The Nusselt number (Nu) and friction factor predictions for the low volume fractions (i.e. 0.02%, 0.1 and 0.5%) agree very well with the experimental values of Sundar and Sharma (2010). While, predictions for the high volume fraction nanofluids (i.e. 1%, 4% and 6%) are found to have reasonable agreement with both experimental and numerical results available in the literature. So the computationally inexpensive single phase approach can be used for heat transfer and pressure drop prediction of new nanofluids.

Keywords: Heat transfer intensification, nanofluid, CFD, friction factor

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Authors: Kai Qian, Ming Yang, Minzhe Guo, Prabir Bhattacharya, Lixin Tao

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Computer network courses are essential parts of college computer science curriculum and hands-on networking experience is well recognized as an effective approach to help students understand better about the network concepts, the layered architecture of network protocols, and the dynamics of the networks. However, existing networking labs are usually server-based and relatively cumbersome, which require a certain level of specialty and resource to set up and maintain the lab environment. Many universities/colleges lack the resources and build-ups in this field and have difficulty to provide students with hands-on practice labs. A new affordable and easily-adoptable approach to networking labs is desirable to enhance network teaching and learning. In addition, current network labs are short on providing hands-on practice for modern wireless and mobile network learning. With the prevalence of smart mobile devices, wireless and mobile network are permeating into various aspects of our information society. The emerging and modern mobile technology provides computer science students with more authentic learning experience opportunities especially in network learning. A mobile device based hands-on labware can provide an excellent ‘real world’ authentic learning environment for computer network especially for wireless network study. In this paper, we present our mobile device-based hands-on labware (series of lab module) for computer network learning which is guided by authentic learning principles to immerse students in a real world relevant learning environment. We have been using this labware in teaching computer network, mobile security, and wireless network classes. The student feedback shows that students can learn more when they have hands-on authentic learning experience. 

Keywords: Mobile computing, android, network, labware.

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Authors: Domenico Chizzoniti, Monica Moscatelli, Letizia Cattani, Piero Favino, Luca Preis

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A settlement strategy is to anticipate and respond the needs of existing and future communities through the provision of primary health care facilities in marginalized areas. Access to a health care network is important to improving healthcare coverage, often lacking, in developing countries. The study explores that a good sanitary system strategy of rural contexts brings advantages to an existing settlement: improving transport, communication, water and social facilities. The objective of this paper is to define a possible methodology to implement primary health care facilities in disadvantaged areas of emerging countries. In this research, we analyze the case study of Lauro de Freitas, a municipality in the Brazilian state of Bahia, part of the Metropolitan Region of Salvador, with an area of 57,662 km² and 194.641 inhabitants. The health localization system in Lauro de Freitas is an integrated process that involves not only geographical aspects, but also a set of factors: population density, epidemiological data, allocation of services, road networks, and more. Data were collected also using semi-structured interviews and questionnaires to the local population. Synthesized data suggest that moving away from the coast where there is the greatest concentration of population and services, a network of primary health care facilities is able to improve the living conditions of small-dispersed communities. Based on the health service needs of populations, we have developed a methodological approach that is particularly useful in rural and remote contexts in emerging countries.

Keywords: Primary health care, developing countries, policy health planning, settlement strategy.

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Authors: Sara D. Garduño-Diaz, Philippe Y. Garduño-Diaz

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To date, one of the few comprehensive indicators for the measurement of food security is the Global Food Security Index (GFSI). This index is a dynamic quantitative and qualitative benchmarking model, constructed from 28 unique indicators, that measures drivers of food security across both developing and developed countries. Whereas the GFSI has been calculated across a set of 109 countries, in this paper we aim to present and compare, for the Middle East and North Africa (MENA), 1) the Food Security Index scores achieved and 2) the data available on affordability, availability, and quality of food. The data for this work was taken from the latest available report published by the creators of the GFSI, which in turn used information from national and international statistical sources. MENA countries rank from place 17/109 (Israel, although with resent political turmoil this is likely to have changed) to place 91/109 (Yemen) with household expenditure spent in food ranging from 15.5% (Israel) to 60% (Egypt). Lower spending on food as a share of household consumption in most countries and better food safety net programs in the MENA have contributed to a notable increase in food affordability. The region has also, however, experienced a decline in food availability, owing to more limited food supplies and higher volatility of agricultural production. In terms of food quality and safety the MENA has the top ranking country (Israel). The most frequent challenges faced by the countries of the MENA include public expenditure on agricultural research and development as well as volatility of agricultural production. Food security is a complex phenomenon that interacts with many other indicators of a country’s wellbeing; in the MENA it is slowly but markedly improving.

Keywords: Diet, food insecurity, global food security index, nutrition, sustainability.

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Authors: Sultan Alharby, Nick Harris, Alex Weddell, Jeff Reeve

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The concept of the Internet of Things (IoT) has received much attention over the last five years. It is predicted that the IoT will influence every aspect of our lifestyles in the near future. Wireless Sensor Networks are one of the key enablers of the operation of IoTs, allowing data to be collected from the surrounding environment. However, due to limited resources, nature of deployment and unattended operation, a WSN is vulnerable to various types of attack. Security is paramount for reliable and safe communication between IoT embedded devices, but it does, however, come at a cost to resources. Nodes are usually equipped with small batteries, which makes energy conservation crucial to IoT devices. Nevertheless, security cost in terms of energy consumption has not been studied sufficiently. Previous research has used a security specification of 802.15.4 for IoT applications, but the energy cost of each security level and the impact on quality of services (QoS) parameters remain unknown. This research focuses on the cost of security at the IoT media access control (MAC) layer. It begins by studying the energy consumption of IEEE 802.15.4 security levels, which is followed by an evaluation for the impact of security on data latency and throughput, and then presents the impact of transmission power on security overhead, and finally shows the effects of security on memory footprint. The results show that security overhead in terms of energy consumption with a payload of 24 bytes fluctuates between 31.5% at minimum level over non-secure packets and 60.4% at the top security level of 802.15.4 security specification. Also, it shows that security cost has less impact at longer packet lengths, and more with smaller packet size. In addition, the results depicts a significant impact on data latency and throughput. Overall, maximum authentication length decreases throughput by almost 53%, and encryption and authentication together by almost 62%.

Keywords: Internet of Things, IEEE 802.15.4, security cost evaluation, wireless sensor network, energy consumption.

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Authors: L. Mion

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The implementation of quality management systems in higher education in different countries is determined by national regulatory choices and supranational indications (such as the European Standard Guidelines for Quality Assurance). The effective functioning and transformative capacity of these quality management systems largely depend on the organizational context in which they are applied and, more specifically, on the culture of quality developed in single universities or in single countries. The University's concept of quality culture integrates the structural dimension of Quality Assurance (QA) (quality management manuals, process definitions, tools) with the value dimension of an organization (principles, skills, and attitudes). Within the EHEA (European Higher Education Area), countries such as Portugal, the Netherlands, the UK, and Norway demonstrate a greater integration of QA principles in the various organizational levels and areas of competence of university institutions or have greater experience in implementation or scientific and political debate on the matter. Therefore, the study, through an integrative literature review, of the quality management systems of these countries is aimed at determining a framework of the culture of quality, helpful in defining the elements which, both in structural-organizational terms and in terms of values and skills and attitudes, have proved to be factors of success in the effective implementation of quality assurance systems in universities and in the countries considered in the research. In order for a QA system to effectively aim for continuous improvement in a complex and dynamic context such as the university one, it must embrace a holistic vision of quality from an integrative perspective, focusing on the objective of transforming the reality being evaluated.

Keywords: Higher education, quality assurance, quality culture, Portugal, Norway, Netherlands, United Kingdom.

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Authors: Omowunmi E. Isafiade, Isaac O. Osunmakinde, Antoine B. Bagula

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Robots- visual perception is a field that is gaining increasing attention from researchers. This is partly due to emerging trends in the commercial availability of 3D scanning systems or devices that produce a high information accuracy level for a variety of applications. In the history of mining, the mortality rate of mine workers has been alarming and robots exhibit a great deal of potentials to tackle safety issues in mines. However, an effective vision system is crucial to safe autonomous navigation in underground terrains. This work investigates robots- perception in underground terrains (mines and tunnels) using statistical region merging (SRM) model. SRM reconstructs the main structural components of an imagery by a simple but effective statistical analysis. An investigation is conducted on different regions of the mine, such as the shaft, stope and gallery, using publicly available mine frames, with a stream of locally captured mine images. An investigation is also conducted on a stream of underground tunnel image frames, using the XBOX Kinect 3D sensors. The Kinect sensors produce streams of red, green and blue (RGB) and depth images of 640 x 480 resolution at 30 frames per second. Integrating the depth information to drivability gives a strong cue to the analysis, which detects 3D results augmenting drivable and non-drivable regions in 2D. The results of the 2D and 3D experiment with different terrains, mines and tunnels, together with the qualitative and quantitative evaluation, reveal that a good drivable region can be detected in dynamic underground terrains.

Keywords: Drivable Region Detection, Kinect Sensor, Robots' Perception, SRM, Underground Terrains.

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Authors: Kasra Majbouri Yazdi, Adel Majbouri Yazdi, Saeid Khodayi, Jingyu Hou, Wanlei Zhou, Saeed Saedy

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Fake news and false information are big challenges of all types of media, especially social media. There is a lot of false information, fake likes, views and duplicated accounts as big social networks such as Facebook and Twitter admitted. Most information appearing on social media is doubtful and in some cases misleading. They need to be detected as soon as possible to avoid a negative impact on society. The dimensions of the fake news datasets are growing rapidly, so to obtain a better result of detecting false information with less computation time and complexity, the dimensions need to be reduced. One of the best techniques of reducing data size is using feature selection method. The aim of this technique is to choose a feature subset from the original set to improve the classification performance. In this paper, a feature selection method is proposed with the integration of K-means clustering and Support Vector Machine (SVM) approaches which work in four steps. First, the similarities between all features are calculated. Then, features are divided into several clusters. Next, the final feature set is selected from all clusters, and finally, fake news is classified based on the final feature subset using the SVM method. The proposed method was evaluated by comparing its performance with other state-of-the-art methods on several specific benchmark datasets and the outcome showed a better classification of false information for our work. The detection performance was improved in two aspects. On the one hand, the detection runtime process decreased, and on the other hand, the classification accuracy increased because of the elimination of redundant features and the reduction of datasets dimensions.

Keywords: Fake news detection, feature selection, support vector machine, K-means clustering, machine learning, social media.

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Authors: Saif Obaid Alkaabi, Nabil Ayad

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Governments constantly seek to offer faster, more secure, efficient and effective services for their citizens. Recent changes and developments to communication services and technologies, mainly due the Internet, have led to immense improvements in the way governments of advanced countries carry out their interior operations Therefore, advances in e-government services have been broadly adopted and used in various developed countries, as well as being adapted to developing countries. The implementation of advances depends on the utilization of the most innovative structures of data techniques, mainly in web dependent applications, to enhance the main functions of governments. These functions, in turn, have spread to mobile and wireless techniques, generating a new advanced direction called m-government. This paper discusses a selection of available m-government applications and several business modules and frameworks in various fields. Practically, the m-government models, techniques and methods have become the improved version of e-government. M-government offers the potential for applications which will work better, providing citizens with services utilizing mobile communication and data models incorporating several government entities. Developing countries can benefit greatly from this innovation due to the fact that a large percentage of their population is young and can adapt to new technology and to the fact that mobile computing devices are more affordable. The use of models of mobile transactions encourages effective participation through the use of mobile portals by businesses, various organizations, and individual citizens. Although the application of m-government has great potential, it does have major limitations. The limitations include: the implementation of wireless networks and relative communications, the encouragement of mobile diffusion, the administration of complicated tasks concerning the protection of security (including the ability to offer privacy for information), and the management of the legal issues concerning mobile applications and the utilization of services.

Keywords: E-government, m-government, system dependability, system security, trust.

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Authors: I. Kurashvili, G. Darsavelidze, T. Kimeridze, G. Chubinidze, I. Tabatadze

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At present, a number of modern semiconductor devices based on SiGe alloys have been created in which the latest achievements of high technologies are used. These devices might cause significant changes to networking, computing, and space technology. In the nearest future new materials based on SiGe will be able to restrict the A³B⁵ and Si technologies and firmly establish themselves in medium frequency electronics. Effective realization of these prospects requires the solution of prediction and controlling of structural state and dynamical physical –mechanical properties of new SiGe materials. Based on these circumstances, a complex investigation of structural defects and structural-sensitive dynamic mechanical characteristics of SiGe alloys under different external impacts (deformation, radiation, thermal cycling) acquires great importance. Internal friction (IF) and shear modulus temperature and amplitude dependences of the monocrystalline boron-doped Si_1-xGe_x(x≤0.05) alloys grown by Czochralski technique is studied in initial and ⁶⁰Co gamma-irradiated states. In the initial samples, a set of dislocation origin relaxation processes and accompanying modulus defects are revealed in a temperature interval of 400-800 ⁰C. It is shown that after gamma-irradiation intensity of relaxation internal friction in the vicinity of 280 ⁰C increases and simultaneously activation parameters of high temperature relaxation processes reveal clear rising. It is proposed that these changes of dynamical mechanical characteristics might be caused by a decrease of the dislocation mobility in the Cottrell atmosphere enriched by the radiation defects.

Keywords: Gamma-irradiation, internal friction, shear modulus, SiGe alloys.

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Authors: Ali Hamadi Dicko, Nicolas Tong-Yette, Benjamin Gilles, François Faure, Olivier Palombi

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A novel hybrid model of the lumbar spine, allowing fast static and dynamic simulations of the disc pressure and the spine mobility, is introduced in this work. Our contribution is to combine rigid bodies, deformable finite elements, articular constraints, and springs into a unique model of the spine. Each vertebra is represented by a rigid body controlling a surface mesh to model contacts on the facet joints and the spinous process. The discs are modeled using a heterogeneous tetrahedral finite element model. The facet joints are represented as elastic joints with six degrees of freedom, while the ligaments are modeled using non-linear one-dimensional elastic elements. The challenge we tackle is to make these different models efficiently interact while respecting the principles of Anatomy and Mechanics. The mobility, the intradiscal pressure, the facet joint force and the instantaneous center of rotation of the lumbar spine are validated against the experimental and theoretical results of the literature on flexion, extension, lateral bending as well as axial rotation. Our hybrid model greatly simplifies the modeling task and dramatically accelerates the simulation of pressure within the discs, as well as the evaluation of the range of motion and the instantaneous centers of rotation, without penalizing precision. These results suggest that for some types of biomechanical simulations, simplified models allow far easier modeling and faster simulations compared to usual full-FEM approaches without any loss of accuracy.

Keywords: Hybrid, modeling, fast simulation, lumbar spine.

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Authors: Yehjune Heo

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As biometric systems become widely deployed, the security of identification systems can be easily attacked by various spoof materials. This paper contributes to finding a reliable and practical anti-spoofing method using Convolutional Neural Networks (CNNs) based on the types of loss functions and optimizers. The types of CNNs used in this paper include AlexNet, VGGNet, and ResNet. By using various loss functions including Cross-Entropy, Center Loss, Cosine Proximity, and Hinge Loss, and various loss optimizers which include Adam, SGD, RMSProp, Adadelta, Adagrad, and Nadam, we obtained significant performance changes. We realize that choosing the correct loss function for each model is crucial since different loss functions lead to different errors on the same evaluation. By using a subset of the Livdet 2017 database, we validate our approach to compare the generalization power. It is important to note that we use a subset of LiveDet and the database is the same across all training and testing for each model. This way, we can compare the performance, in terms of generalization, for the unseen data across all different models. The best CNN (AlexNet) with the appropriate loss function and optimizers result in more than 3% of performance gain over the other CNN models with the default loss function and optimizer. In addition to the highest generalization performance, this paper also contains the models with high accuracy associated with parameters and mean average error rates to find the model that consumes the least memory and computation time for training and testing. Although AlexNet has less complexity over other CNN models, it is proven to be very efficient. For practical anti-spoofing systems, the deployed version should use a small amount of memory and should run very fast with high anti-spoofing performance. For our deployed version on smartphones, additional processing steps, such as quantization and pruning algorithms, have been applied in our final model.

Keywords: Anti-spoofing, CNN, fingerprint recognition, loss function, optimizer.

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Authors: Promise A. Azor, Avievie Igodo, Esabai M. Ase

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The paper merged the return of premium clause and voluntary contributions to investigate retirees’ investment plan in a defined contributory (DC) pension scheme with a portfolio comprising of a risk-free asset and a risky asset whose price process is described by geometric Brownian motion (GBM). The paper considers additional voluntary contributions paid by members, charge on balance by pension fund administrators and the mortality risk of members of the scheme during the accumulation period by introducing return of premium clause. To achieve this, the Weilbull mortality force function is used to establish the mortality rate of members during accumulation phase. Furthermore, an optimization problem from the Hamilton Jacobi Bellman (HJB) equation is obtained using dynamic programming approach. Also, the Legendre transformation method is used to transform the HJB equation which is a nonlinear partial differential equation to a linear partial differential equation and solves the resultant equation for the value function and the optimal distribution plan under logarithm utility function. Finally, numerical simulations of the impact of some important parameters on the optimal distribution plan were obtained and it was observed that the optimal distribution plan is inversely proportional to the initial fund size, predetermined interest rate, additional voluntary contributions, charge on balance and instantaneous volatility.

Keywords: Legendre transform, logarithm utility, optimal distribution plan, return clause of premium, charge on balance, Weibull mortality function.

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Authors: A. B. Chehreh, M. Grätzel, M. Klein, J. P. Bergmann, F. Walther

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Friction stir welding (FSW) is an advantageous method in the thermal joining processes, featuring the welding of various dissimilar and similar material combinations, joining temperatures below the melting point which prevents irregularities such as pores and hot cracks as well as high strengths mechanical joints near the base material. The FSW process consists of a rotating tool which is made of a shoulder and a probe. The welding process is based on a rotating tool which plunges in the workpiece under axial pressure. As a result, the material is plasticized by frictional heat which leads to a decrease in the flow stress. During the welding procedure, the material is continuously displaced by the tool, creating a firmly bonded weld seam behind the tool. However, the mechanical properties of the weld seam are affected by the design and geometry of the tool. These include in particular microstructural and surface properties which can favor crack initiation. Following investigation compares the dynamic properties of FSW weld seams with conventional and stationary shoulder geometry based on load increase test (LIT). Compared to classical Woehler tests, it is possible to determine the fatigue strength of the specimens after a short amount of time. The investigations were carried out on a robotized welding setup on 2 mm thick EN AW 5754 aluminum alloy sheets. It was shown that an increased tensile and fatigue strength can be achieved by using the stationary shoulder concept. Furthermore, it could be demonstrated that the LIT is a valid method to describe the fatigue behavior of FSW weld seams.

Keywords: Aluminum alloy, fatigue performance, fracture, friction stir welding.

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Authors: V. Santamarina Campos, M. de Miguel Molina, B. de Miguel Molina, M. Á. Carabal Montagud

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With this contribution, we want to show a successful example of the application of the Design Thinking methodology, in the European project 'Technology transfer of Remotely Piloted Aircraft Systems (RPAS) for the creative industry'. The use of this methodology has allowed us to design and build a drone, based on the real needs of prospective users. It has demonstrated that this is a powerful tool for generating innovative ideas in the field of robotics, by focusing its effectiveness on understanding and solving real user needs. In this way, with the support of an interdisciplinary team, comprised of creatives, engineers and economists, together with the collaboration of prospective users from three European countries, a non-linear work dynamic has been created. This teamwork has generated a sense of appreciation towards the creative industries, through continuously adaptive, inventive, and playful collaboration and communication, which has facilitated the development of prototypes. These have been designed to enable filming and photography in interior spaces, within 13 sectors of European creative industries: Advertising, Architecture, Fashion, Film, Antiques and Museums, Music, Photography, Televison, Performing Arts, Publishing, Arts and Crafts, Design and Software. Furthermore, it has married the real needs of the creative industries, with what is technologically and commercially viable. As a result, a product of great value has been obtained, which offers new business opportunities for small companies across this sector.

Keywords: Design thinking, design for effectiveness, methodology, active toolkit, storyboards, storytelling, PAR, focus group, innovation, RPAS, indoor drone, robotics, TRL, aerial film, creative industries, end-users.

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