Search results for: economic efficiency

Authors: V. M. Mmbengwa, J. R. M. Mabuso, C. P. Du Plooy, S. Laurrie, H. D. van Schalkwyk

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Sweet potato products are necessary for the provision of essential nutrients in every household, regardless of their poverty status. Their consumption appears to be highly influenced by socioeconomic factors, such as malnutrition, food insecurity and unemployment. Therefore, market availability is crucial for these cultivars to resolve some of the socio-economic factors. The aim of the study was to investigate market availability of sweet potato cultivars in the North West Province. In this study, both qualitative and quantitative research methodologies were used. Qualitative methodology was used to explain the quantitative outcomes of the variables. On the other hand, quantitative results were used to test the hypothesis. The study used SPSS software to analyse the data. Crosstabulation and Chi-square statistics were used to obtain the descriptive and inferential analyses, respectively. The study found that the Blesbok cultivar is dominating the markets of the North West Province, with the Monate cultivar dominating in the Bojanala Platinum (75%) and Dr Ruth Segomotsi Mompati (25%) districts. It is also found that a unit increase in the supply of sweet potato cultivars in both local and district municipal markets is accompanied by a reduced demand of 28% and 33% at district and local markets, respectively. All these results were found to be significant at p<0.05. The results further revealed that in four out of nine local municipality markets, the Blesbok cultivar seems to be solely available in those four local municipal markets of North West Province. It can be concluded that Blesbok, relative to other cultivars, is the most commercialised sweet potato variety and that consumers across this Province are highly aware of it. For other cultivars to assume market prominence in this Province, a well-designed marketing campaign for creating awareness may be required. This campaign may be based on nutritional advantages of different cultivars, of which Blesbok is relatively inferior, compared to orange-fleshed sweet potato varieties.

Keywords: Cultivar, malnutrition, markets, sweet potato.

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Authors: Anatoly Krivinsh

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The results of dissertation research "Preventing and  combating corruption in public procurement" are presented in this  publication. The study was conducted 2011 till 2013 in a Member  State of the European Union– in the Republic of Latvia.  Goal of the thesis is to explore corruption prevention and  combating issues in public procurement sphere, to identify the  prevalence rates, determinants and contributing factors and  prevention opportunities in Latvia.  In the first chapter the author analyzes theoretical aspects of  understanding corruption in public procurement, with particular  emphasis on corruption definition problem, its nature, causes and  consequences. A separate section is dedicated to the public  procurement concept, mechanism and legal framework. In the first  part of this work the author presents cognitive methodology of  corruption in public procurement field, based on which the author has  carried out an analysis of corruption situation in public procurement  in Republic of Latvia.  In the second chapter of the thesis, the author analyzes the  problem of corruption in public procurement, including its historical  aspects, typology and classification of corruption subjects involved,  corruption risk elements in public procurement and their  identification. During the development of the second chapter author's  practical experience in public procurements was widely used.  The third and fourth chapter deals with issues related to the  prevention and combating corruption in public procurement, namely  the operation of the concept, principles, methods and techniques,  subjects in Republic of Latvia, as well as an analysis of foreign  experience in preventing and combating corruption. The fifth chapter  is devoted to the corruption prevention and combating perspectives  and their assessment. In this chapter the author has made the  evaluation of corruption prevention and combating measures  efficiency in Republic of Latvia, assessment of anti-corruption  legislation development stage in public procurement field in Latvia. 

Keywords: Prevention of corruption, public purchases.

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Authors: Insaf Ajili, Malik Mallem, Jean-Yves Didier

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Human motion recognition has been extensively increased in recent years due to its importance in a wide range of applications, such as human-computer interaction, intelligent surveillance, augmented reality, content-based video compression and retrieval, etc. However, it is still regarded as a challenging task especially in realistic scenarios. It can be seen as a general machine learning problem which requires an effective human motion representation and an efficient learning method. In this work, we introduce a descriptor based on Laban Movement Analysis technique, a formal and universal language for human movement, to capture both quantitative and qualitative aspects of movement. We use Discrete Hidden Markov Model (DHMM) for training and classification motions. We improve the classification algorithm by proposing two DHMMs for each motion class to process the motion sequence in two different directions, forward and backward. Such modification allows avoiding the misclassification that can happen when recognizing similar motions. Two experiments are conducted. In the first one, we evaluate our method on a public dataset, the Microsoft Research Cambridge-12 Kinect gesture data set (MSRC-12) which is a widely used dataset for evaluating action/gesture recognition methods. In the second experiment, we build a dataset composed of 10 gestures(Introduce yourself, waving, Dance, move, turn left, turn right, stop, sit down, increase velocity, decrease velocity) performed by 20 persons. The evaluation of the system includes testing the efficiency of our descriptor vector based on LMA with basic DHMM method and comparing the recognition results of the modified DHMM with the original one. Experiment results demonstrate that our method outperforms most of existing methods that used the MSRC-12 dataset, and a near perfect classification rate in our dataset.

Keywords: Human Motion Recognition, Motion representation, Laban Movement Analysis, Discrete Hidden Markov Model.

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Authors: A. M. Pashayev, C. Ardil, D. D. Askerov, R. A. Sadiqov, P. S. Abdullayev

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In this paper is shown that the probability-statistic methods application, especially at the early stage of the aviation gas turbine engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence is considered the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods. Training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. Thus for GTE technical condition more adequate model making are analysed dynamics of skewness and kurtosis coefficients' changes. Researches of skewness and kurtosis coefficients values- changes show that, distributions of GTE work parameters have fuzzy character. Hence consideration of fuzzy skewness and kurtosis coefficients is expedient. Investigation of the basic characteristics changes- dynamics of GTE work parameters allows to draw conclusion on necessity of the Fuzzy Statistical Analysis at preliminary identification of the engines' technical condition. Researches of correlation coefficients values- changes shows also on their fuzzy character. Therefore for models choice the application of the Fuzzy Correlation Analysis results is offered. For checking of models adequacy is considered the Fuzzy Multiple Correlation Coefficient of Fuzzy Multiple Regression. At the information sufficiency is offered to use recurrent algorithm of aviation GTE technical condition identification (Hard Computing technology is used) on measurements of input and output parameters of the multiple linear and non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stage-bystage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine temperature condition was made.

Keywords: Gas turbine engines, neural networks, fuzzy logic, fuzzy statistics.

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Authors: Francis William S, Imtiaz Ahmed Choudhury, Ananda Kumar Eriki, A. John Rajan

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Diesel Engines emit complex mixtures of inorganic and organic compounds in the form of both solid and vapour phase particles. Most of the particulates released are ultrafine nanoparticles which are detrimental to human health and can easily enter the body by respiration. The emissions standards on particulate matter release from diesel engines are constantly upgraded within the European Union and with future regulations based on the particles numbers released instead of merely mass, the need for effective aftertreatment devices will increase. Standard particulate filters in the form of wall flow filters can have problems with high soot accumulation, producing a large exhaust backpressure. A potential solution would be to combine the standard filter with a flow through filter to reduce the load on the wall flow filter. In this paper soot particle trapping has been simulated in different continuous flow filters of monolithic structure including the use of promoters, at laminar flow conditions. An Euler Lagrange model, the discrete phase model in Ansys used with user defined functions for forces acting on particles. A method to quickly screen trapping of 5 nm and 10 nm particles in different catalysts designs with tracers was also developed. Simulations of square duct monoliths with promoters show that the strength of the vortices produced are not enough to give a high amount of particle deposition on the catalyst walls. The smallest particles in the simulations, 5 and 10 nm particles were trapped to a higher extent, than larger particles up to 1000 nm, in all studied geometries with the predominant deposition mechanism being Brownian diffusion. The comparison of the different filters designed with a wall flow filter does show that the options for altering a design of a flow through filter, without imposing a too large pressure drop penalty are good.

Keywords: Diesel Engine trap, thermophoresis, Exhaust pipe, PM-Simulation modeling.

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Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

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The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning (ML) archetypal that could forecast the COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID-19 cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organization (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data are split into 8:2 ratio for training and testing purposes to forecast future new COVID-19 cases. Support Vector Machine (SVM), Random Forest (RF), and linear regression (LR) algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID-19 cases is evaluated. RF outperformed the other two ML algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n = 30. The mean square error obtained for RF is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis, RF algorithm can perform more effectively and efficiently in predicting the new COVID-19 cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest.

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Authors: Raquib Ahsan, Md. Mahir Asif, Md. Zahidul Alam

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A huge portion of old masonry buildings in Bangladesh are vulnerable to earthquake. In most of the cases these buildings contain unreinforced masonry wall which are most likely to be subjected to earthquake damages. Due to deterioration of mortar joint and aging, shear resistance of these unreinforced masonry walls dwindle. So, retrofitting of these old buildings has become an important issue. Among many researched and experimented techniques, ferrocement retrofitting can be a low cost technique in context of the economic condition of Bangladesh. This study aims at investigating the behavior of ferrocement retrofitted unconfined URM walls under different types of cyclic loading. Four 725 mm × 725 mm masonry wall units were prepared with bricks jointed by stretcher bond with 12.5 mm mortar between two adjacent layers of bricks. To compare the effectiveness of ferrocement retrofitting a particular type wire mesh was used in this experiment which is 20 gauge woven wire mesh with 12.5 mm × 12.5 mm square opening. After retrofitting with ferrocement these wall units were tested by applying cyclic deformation along the diagonals of the specimens. Then a comparative study was performed between the retrofitted specimens and control specimens for both partially reversed cyclic load condition and cyclic compression load condition. The experiment results show that ultimate load carrying capacities of ferrocement retrofitted specimens are 35% and 27% greater than the control specimen under partially reversed cyclic loading and cyclic compression respectively. And before failure the deformations of ferrocement retrofitted specimens are 43% and 33% greater than the control specimen under reversed cyclic loading and cyclic compression respectively. Therefore, the test results show that the ultimate load carrying capacity and ductility of ferrocement retrofitted specimens have improved.

Keywords: Cyclic compression, ferrocement, masonry wall, partially reversed cyclic load, retrofitting.

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Authors: Yusuf Garba Baba

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The construction industry and housing subsector are fraught with risks that have the potential of negatively impacting on the achievement of project objectives. The success or otherwise of most construction projects depends to large extent on how well these risks have been managed. The recent paradigm shift by the subsector to use of formal risk management approach in contrast to hitherto developed rules of thumb means that risks must not only be identified but also properly assessed and responded to in a systematic manner. The study focused on identifying risks associated with housing development projects and prioritisation assessment of the identified risks in order to provide basis for informed decision. The study used a three-step identification framework: review of literature for similar projects, expert consultation and questionnaire based survey to identify potential risk factors. Delphi survey method was employed in carrying out the relative prioritization assessment of the risks factors using computer-based Analytical Hierarchical Process (AHP) software. The results show that 19 out of the 50 risks significantly impact on housing development projects. The study concludes that although significant numbers of risk factors have been identified as having relevance and impacting to housing construction projects, economic risk group and, in particular, ‘changes in demand for houses’ is prioritised by most developers as posing a threat to the achievement of their housing development objectives. Unless these risks are carefully managed, their effects will continue to impede success in these projects. The study recommends the adoption and use of the combination of multi-technique identification framework and AHP prioritization assessment methodology as a suitable model for the assessment of risks in housing development projects.

Keywords: Risk identification, risk assessment, analytical hierarchical process, multi-criteria decision.

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Authors: Guclu Insel, Efe Gumuslu, Gulten Yuksek, Nilay Sayi Ucar, Emine Ubay Cokgor, Tugba Olmez Hanci, Didem Okutman Tas, Fatos Germirli Babuna, Derya Firat Ertem, Okmen Yildirim, Ozge Erturan, Betul Kirci

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In order to eliminate water scarcity problems, effective precautions must be taken. Growing competition for water is increasingly forcing facilities to tackle their own water scarcity problems. At this point, application of wastewater reclamation and reuse results in considerable economic advantageous. In this study, an enamel coating facility, which is one of the high water consumed facilities, is evaluated in terms of its wastewater reuse potential. Wastewater reclamation and reuse can be defined as one of the best available techniques for this sector. Hence, process and pollution profiles together with detailed characterization of segregated wastewater sources are appraised in a way to find out the recoverable effluent streams arising from enamel coating operations. Daily, 170 m³ of process water is required and 160 m³ of wastewater is generated. The segregated streams generated by two enamel coating processes are characterized in terms of conventional parameters. Relatively clean segregated wastewater streams (reusable wastewaters) are separately collected and experimental treatability studies are conducted on it. The results reflected that the reusable wastewater fraction has an approximate amount of 110 m³/day that accounts for 68% of the total wastewaters. The need for treatment applicable on reusable wastewaters is determined by considering water quality requirements of various operations and characterization of reusable wastewater streams. Ultra-filtration (UF), Nano-filtration (NF) and Reverse Osmosis (RO) membranes are subsequently applied on reusable effluent fraction. Adequate organic matter removal is not obtained with the mentioned treatment sequence.

Keywords: enamel coating, membrane, reuse, wastewater

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Authors: Arash Parehkar, S. Jamshid Mousavi, Shoubo Bayazidi, Vahid Karami, Laleh Shahidi, Arash Azaranfar, Ali Moridi, M. Shabakhti, Tayebeh Ariyan, Mitra Tofigh, Kaveh Masoumi, Alireza Motahari

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Water resource systems modeling has constantly been a challenge through history for human beings. As the innovative methodological development is evolving alongside computer sciences on one hand, researches are likely to confront more complex and larger water resources systems due to new challenges regarding increased water demands, climate change and human interventions, socio-economic concerns, and environment protection and sustainability. In this research, an automatic calibration scheme has been applied on the Gilan’s large-scale water resource model using mathematical programming. The water resource model’s calibration is developed in order to attune unknown water return flows from demand sites in the complex Sefidroud irrigation network and other related areas. The calibration procedure is validated by comparing several gauged river outflows from the system in the past with model results. The calibration results are pleasantly reasonable presenting a rational insight of the system. Subsequently, the unknown optimized parameters were used in a basin-scale linear optimization model with the ability to evaluate the system’s performance against a reduced inflow scenario in future. Results showed an acceptable match between predicted and observed outflows from the system at selected hydrometric stations. Moreover, an efficient operating policy was determined for Sefidroud dam leading to a minimum water shortage in the reduced inflow scenario.

Keywords: Auto-calibration, Gilan, Large-Scale Water Resources, Simulation.

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Authors: Mohanapriya Subramanian, V. Raj

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Direct methanol fuel cells (DMFCs) are considered to be one of the most promising candidates for portable and stationary applications in the view of their advantages such as high energy density, easy manipulation, high efficiency and they operate with liquid fuel which could be used without requiring any fuel-processing units. Electrolyte membrane of DMFC plays a key role as a proton conductor as well as a separator between electrodes. Increasing concern over environmental protection, biopolymers gain tremendous interest owing to their eco-friendly bio-degradable nature. Pectin is a natural anionic polysaccharide which plays an essential part in regulating mechanical behavior of plant cell wall and it is extracted from outer cells of most of the plants. The aim of this study is to develop and demonstrate pectin based polymer composite membranes as methanol impermeable polymer electrolyte membranes for DMFCs. Pectin based nanocomposites membranes are prepared by solution-casting technique wherein pectin is blended with chitosan followed by the addition of optimal amount of sulphonic acid modified Titanium dioxide nanoparticle (S-TiO2). Nanocomposite membranes are characterized by Fourier Transform-Infra Red spectroscopy, Scanning electron microscopy, and Energy dispersive spectroscopy analyses. Proton conductivity and methanol permeability are determined into order to evaluate their suitability for DMFC application. Pectin-chitosan blends endow with a flexible polymeric network which is appropriate to disperse rigid S-TiO2 nanoparticles. Resulting nanocomposite membranes possess adequate thermo-mechanical stabilities as well as high charge-density per unit volume. Pectin-chitosan natural polymeric nanocomposite comprising optimal S-TiO2 exhibits good electrochemical selectivity and therefore desirable for DMFC application.

Keywords: Biopolymers, fuel cells, nanocomposite, methanol crossover.

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Authors: T. Chaiechi, N. Stoeckl

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Scarcity of resources for biodiversity conservation gives rise to the need of strategic investment with priorities given to the cost of conservation. While the literature provides abundant methodological options for biodiversity conservation; estimating true cost of conservation remains abstract and simplistic, without recognising dynamic nature of the cost. Some recent works demonstrate the prominence of economic theory to inform biodiversity decisions, particularly on the costs and benefits of biodiversity however, the integration of the concept of true cost into biodiversity actions and planning are very slow to come by, and specially on a farm level. Conservation planning studies often use area as a proxy for costs neglecting different land values as well as protected areas. These literature consider only heterogeneous benefits while land costs are considered homogenous. Analysis with the assumption of cost homogeneity results in biased estimation; since not only it doesn’t address the true total cost of biodiversity actions and plans, but also it fails to screen out lands that are more (or less) expensive and/or difficult (or more suitable) for biodiversity conservation purposes, hindering validity and comparability of the results. Economies of scope” is one of the other most neglected aspects in conservation literature. The concept of economies of scope introduces the existence of cost complementarities within a multiple output production system and it suggests a lower cost during the concurrent production of multiple outputs by a given farm. If there are, indeed, economies of scope then simplistic representation of costs will tend to overestimate the true cost of conservation leading to suboptimal outcomes. The aim of this paper, therefore, is to provide first road review of the various theoretical ways in which economies of scope are likely to occur of how they might occur in conservation. Consequently, the paper addresses gaps that have to be filled in future analysis.

Keywords: Cost, biodiversity conservation, Multi-output production systems, Empirical techniques.

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Authors: Kung-Jen Tu, Danny Vernatha

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To assist individual departments within universities in their energy management tasks, this study explores the application of Building Information Modeling in establishing the ‘BIM based Energy Management Support System’ (BIM-EMSS). The BIM-EMSS consists of six components: (1) sensors installed for each occupant and each equipment, (2) electricity sub-meters (constantly logging lighting, HVAC, and socket electricity consumptions of each room), (3) BIM models of all rooms within individual departments’ facilities, (4) data warehouse (for storing occupancy status and logged electricity consumption data), (5) building energy management system that provides energy managers with various energy management functions, and (6) energy simulation tool (such as eQuest) that generates real time 'standard energy consumptions' data against which 'actual energy consumptions' data are compared and energy efficiency evaluated. Through the building energy management system, the energy manager is able to (a) have 3D visualization (BIM model) of each room, in which the occupancy and equipment status detected by the sensors and the electricity consumptions data logged are displayed constantly; (b) perform real time energy consumption analysis to compare the actual and standard energy consumption profiles of a space; (c) obtain energy consumption anomaly detection warnings on certain rooms so that energy management corrective actions can be further taken (data mining technique is employed to analyze the relation between space occupancy pattern with current space equipment setting to indicate an anomaly, such as when appliances turn on without occupancy); and (d) perform historical energy consumption analysis to review monthly and annually energy consumption profiles and compare them against historical energy profiles. The BIM-EMSS was further implemented in a research lab in the Department of Architecture of NTUST in Taiwan and implementation results presented to illustrate how it can be used to assist individual departments within universities in their energy management tasks.

Keywords: Sensor, electricity sub-meters, database, energy anomaly detection.

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Authors: Mohammed Agbali, Claudia Trillo, Yusuf Arayici, Terrence Fernando

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The wide-spread adoption of the Smart City concept has introduced a new era of computing paradigm with opportunities for city administrators and stakeholders in various sectors to re-think the concept of urbanization and development of healthy cities. With the world population rapidly becoming urban-centric especially amongst the emerging economies, social innovation will assist greatly in deploying emerging technologies to address the development challenges in core sectors of the future cities. In this context, sustainable health-care delivery and improved quality of life of the people is considered at the heart of the healthy city agenda. This paper examines the Boston innovation landscape from the perspective of smart services and innovation ecosystem for sustainable development, especially in transportation and healthcare. It investigates the policy implementation process of the Healthy City agenda and eHealth economy innovation based on the experience of Massachusetts’s City of Boston initiatives. For this purpose, three emerging areas are emphasized, namely the eHealth concept, the innovation hubs, and the emerging technologies that drive innovation. This was carried out through empirical analysis on results of public sector and industry-wide interviews/survey about Boston’s current initiatives and the enabling environment. The paper highlights few potential research directions for service integration and social innovation for deploying emerging technologies in the healthy city agenda. The study therefore suggests the need to prioritize social innovation as an overarching strategy to build sustainable Smart Cities in order to avoid technology lock-in. Finally, it concludes that the Boston example of innovation economy is unique in view of the existing platforms for innovation and proper understanding of its dynamics, which is imperative in building smart and healthy cities where quality of life of the citizenry can be improved.

Keywords: Smart city, social innovation, eHealth, innovation hubs, emerging technologies, equitable healthcare, healthy cities.

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Authors: Sareh Rajabi, Taha Anjamrooz, Salwa Bheiry

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Sustainability of construction projects is an important issue to be addressed since the sector will continue to be developed in the coming years, especially in developing countries. Thus, it is significant to discover approaches and solutions for improving sustainability. Currently, the construction industry is the largest consumer of natural resources. This is the same in other countries in the Gulf region, and the United Arab Emirates (UAE) has limited natural resources such as water, electricity, etc. Recently, the UAE has taken several actions in order to implement sustainable initiatives within its construction industry. Within the industry, the contractors’ role is significant in promoting sustainable development by taking the responsibility to minimize their negative impacts on the environment and society, and maximize their economic distribution. In this research, sustainability will be studied as an important key to bring competitive advantages to contracting organizations. The contractors should understand the need to improve their sustainable performance in order to expand their business competitiveness. Competitiveness at the construction project level refers to a contractor’s ability to compete for a project. There is less focus on how to improve contractors’ competitiveness by implementing sustainable construction practices. Based on an inclusive literature review on the relationship between sustainability performance and business competitiveness, this research will conduct a study of sustainable practice in the construction industry and the relationship between sustainability performance and business competitiveness in order to develop a framework for evaluating how contractors can improve their competitiveness in terms of more efficient processes, enhancements in productivity, and lower costs of compliance in order to reduce the initial project cost and obtain market opportunities in the UAE. The research findings will provide a framework that can be a useful guideline for contractors to develop their sustainability policy, strategy and practice for meeting the increased requirements for sustainable development in construction.

Keywords: Sustainable construction practice, sustainability, competitiveness, construction industry, contractors.

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Authors: Ekin Kıpçak, Mesut Akgün

Abstract:

Recently, a growing interest has emerged on the development of new and efficient energy sources, due to the inevitable extinction of the nonrenewable energy reserves. One of these alternative sources which have a great potential and sustainability to meet up the energy demand is biomass energy. This significant energy source can be utilized with various energy conversion technologies, one of which is biomass gasification in supercritical water.

Water, being the most important solvent in nature, has very important characteristics as a reaction solvent under supercritical circumstances. At temperatures above its critical point (374.8^oC and 22.1MPa), water becomes more acidic and its diffusivity increases. Working with water at high temperatures increases the thermal reaction rate, which in consequence leads to a better dissolving of the organic matters and a fast reaction with oxygen. Hence, supercritical water offers a control mechanism depending on solubility, excellent transport properties based on its high diffusion ability and new reaction possibilities for hydrolysis or oxidation.

In this study the gasification of a real biomass, namely olive mill wastewater (OMW), in supercritical water conditions is investigated with the use of Ru/Al₂O₃ catalyst. OMW is a by-product obtained during olive oil production, which has a complex nature characterized by a high content of organic compounds and polyphenols. These properties impose OMW a significant pollution potential, but at the same time, the high content of organics makes OMW a desirable biomass candidate for energy production.

The catalytic gasification experiments were made with five different reaction temperatures (400, 450, 500, 550 and 600°C) and five reaction times (30, 60, 90, 120 and 150s), under a constant pressure of 25MPa. Through these experiments, the effects of reaction temperature and time on the gasification yield, gaseous product composition and OMW treatment efficiency were investigated.

Keywords: Catalyst, Gasification, Olive mill wastewater, Ru/Al2O3, Supercritical water.

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Authors: Pooja Jain

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Art education is often ignored in syllabus of developing countries like India and in educational planning for development but now days Indian Art with a global recognition is becoming an integral part of the education at all levels. The term art, widely used in all parts of the modern world, carried varied significance in India as its meaning was continuously being extended, covering the many varieties of creative expression such as painting, sculpture, commercial art, design, poetry, music, dance, and architecture. Over the last 100 years Indian artists of all forms have evolved a wide variety of expressive styles. With the recommendations and initiatives by Government of India, Art Education has subsequently gained pace at the school level as a mandatory subject for all making a path way for students with a creative bend of mind. This paper investigates curriculum in various schools of the country at secondary and senior secondary levels along with some eminent institutions running the program. Findings depicted the role of art education and justified its importance primarily with commercial art being perceived to be essential for students learning skills for economic gain in their career ahead. With so many art colleges spread across India, emerging artists and designers are being trained and are creating art of infinite variety and style and have opened up many career avenues. Commercial Art being a plethora of artistic expressions has confidently come of age wherein a creative perception is mixed with an introspective imagination to bring out multi faceted career options with a significant future enveloped in art. Visual arts in education thus is an expanding field of result assured research.

Keywords: Modern art, commercial art, introspective imagination, career.

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Authors: H. Omrani, P. Gerber

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Success is a European project that will implement several clean transport offers in three European cities and evaluate the environmental impacts. The goal of these measures is to improve urban mobility or the displacement of residents inside cities. For e.g. park and ride, electric vehicles, hybrid bus and bike sharing etc. A list of 28 criteria and 60 measures has been established for evaluation of these transport projects. The evaluation criteria can be grouped into: Transport, environment, social, economic and fuel consumption. This article proposes a decision support system based that encapsulates a hybrid approach based on fuzzy logic, multicriteria analysis and belief theory for the evaluation of impacts of urban mobility solutions. A web-based tool called DeSSIA (Decision Support System for Impacts Assessment) has been developed that treats complex data. The tool has several functionalities starting from data integration (import of data), evaluation of projects and finishes by graphical display of results. The tool development is based on the concept of MVC (Model, View, and Controller). The MVC is a conception model adapted to the creation of software's which impose separation between data, their treatment and presentation. Effort is laid on the ergonomic aspects of the application. It has codes compatible with the latest norms (XHTML, CSS) and has been validated by W3C (World Wide Web Consortium). The main ergonomic aspect focuses on the usability of the application, ease of learning and adoption. By the usage of technologies such as AJAX (XML and Java Script asynchrones), the application is more rapid and convivial. The positive points of our approach are that it treats heterogeneous data (qualitative, quantitative) from various information sources (human experts, survey, sensors, model etc.).

Keywords: Decision support tool, hybrid approach, urban mobility.

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Authors: H. Shayeghi, H. A. Shayanfar, G. Azimi

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The quality of short term load forecasting can improve the efficiency of planning and operation of electric utilities. Artificial Neural Networks (ANNs) are employed for nonlinear short term load forecasting owing to their powerful nonlinear mapping capabilities. At present, there is no systematic methodology for optimal design and training of an artificial neural network. One has often to resort to the trial and error approach. This paper describes the process of developing three layer feed-forward large neural networks for short-term load forecasting and then presents a heuristic search algorithm for performing an important task of this process, i.e. optimal networks structure design. Particle Swarm Optimization (PSO) is used to develop the optimum large neural network structure and connecting weights for one-day ahead electric load forecasting problem. PSO is a novel random optimization method based on swarm intelligence, which has more powerful ability of global optimization. Employing PSO algorithms on the design and training of ANNs allows the ANN architecture and parameters to be easily optimized. The proposed method is applied to STLF of the local utility. Data are clustered due to the differences in their characteristics. Special days are extracted from the normal training sets and handled separately. In this way, a solution is provided for all load types, including working days and weekends and special days. The experimental results show that the proposed method optimized by PSO can quicken the learning speed of the network and improve the forecasting precision compared with the conventional Back Propagation (BP) method. Moreover, it is not only simple to calculate, but also practical and effective. Also, it provides a greater degree of accuracy in many cases and gives lower percent errors all the time for STLF problem compared to BP method. Thus, it can be applied to automatically design an optimal load forecaster based on historical data.

Keywords: Large Neural Network, Short-Term Load Forecasting, Particle Swarm Optimization.

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Authors: Rawia M. Khalil, Ahmed A. Abd El Rahman, Mahfouz A. Kassem, Mohamed S. El Ridi, Mona M. Abou Samra, Ghada E. A. Awad, Soheir S. Mansy

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Solid lipid nanoparticles (SLNs) have gained great attention for the topical treatment of skin associated fungal infection as they facilitate the skin penetration of loaded drugs. Our work deals with the preparation of nystatin loaded solid lipid nanoparticles (NystSLNs) using the hot homogenization and ultrasonication method. The prepared NystSLNs were characterized in terms of entrapment efficiency, particle size, zeta potential, transmission electron microscopy, differential scanning calorimetry, rheological behavior and in vitro drug release. A stability study for 6 months was performed. A microbiological study was conducted in male rats infected with Candida albicans, by counting the colonies and examining the histopathological changes induced on the skin of infected rats. The results showed that SLNs dispersions are spherical in shape with particle size ranging from 83.26±11.33 to 955.04±1.09 nm. The entrapment efficiencies are ranging from 19.73±1.21 to 72.46±0.66% with zeta potential ranging from -18.9 to -38.8 mV and shear-thinning rheological Behavior. The stability studies done for 6 months showed that nystatin (Nyst) is a good candidate for topical SLN formulations. A least number of colony forming unit/ ml (cfu/ml) was recorded for the selected NystSLN compared to the drug solution and the commercial Nystatin® cream present in the market. It can be fulfilled from this work that SLNs provide a good skin targeting effect and may represent promising carrier for topical delivery of Nyst offering the sustained release and maintaining the localized effect, resulting in an effective treatment of cutaneous fungal infection.

Keywords: Candida infections, Hot homogenization, Nystatin, Solid lipid nanoparticles, Stability, Topical delivery.

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Authors: Raif Parlakkaya, Mustafa Nihat Demirci, Mehmet Nuri Salur

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Environmental pollution has detrimental effects on the quality of our life and its scope has reached such an extent that measures are being taken both at the national and international levels to reduce, prevent and mitigate its impact on social, economic and political spheres. Therefore, awareness of environmental problems has been increasing among stakeholders and accordingly among companies. It is seen that corporate reporting is expanding beyond environmental performance. Primary purpose of publishing an environmental report is to provide specific audiences with useful, meaningful information. This paper is intended to analyze the extent and qualification of environmental disclosures of Turkish publicly quoted firms and see how it varies from one sector to another. The data for the study were collected from annual activity reports of companies, listed on the corporate governance index (BIST-XKURY) of Istanbul Stock Exchange. Content analysis was the research methodology used to measure the extent of environmental disclosure. Accordingly, 2015 annual activity reports of companies that carry out business in some particular fields were acquired from Capital Market Board, websites of Public Disclosure Platform and companies’ own websites. These reports were categorized into five main aspects: Environmental policies, environmental management systems, environmental protection and conservation activities, environmental awareness and information on environmental lawsuits. Subsequently, each component was divided into several variables related to what each firm is supposed to disclose about environmental information. In this context, the nature and scope of the information disclosed on each item were assessed according to five different ways (N.I: No Information; G.E.: General Explanations; Q.E.: Qualitative Detailed Explanations; N.E.: Quantitative (numerical) Detailed Explanations; Q.&N.E.: Both Qualitative and Quantitative Explanations).

Keywords: Environmental accounting, disclosure, corporate governance, content analysis.

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Authors: Angelo Corallo, Maria Elena Latino, Marta Menegoli

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Agri-food value chain involves various stakeholders with different roles. All of them abide by national and international rules and leverage marketing strategies to advance their products. Food products and related processing phases carry with it a big mole of data that are often not used to inform final customer. Some data, if fittingly identified and used, can enhance the single company, and/or the all supply chain creates a math between marketing techniques and voluntary traceability strategies. Moreover, as of late, the world has seen buying-models’ modification: customer is careful on wellbeing and food quality. Food citizenship and food democracy was born, leveraging on transparency, sustainability and food information needs. Internet of Things (IoT) and Analytics, some of the innovative technologies of Industry 4.0, have a significant impact on market and will act as a main thrust towards a genuine ‘4.0 change’ for agriculture. But, realizing a traceability system is not simple because of the complexity of agri-food supply chain, a lot of actors involved, different business models, environmental variations impacting products and/or processes, and extraordinary climate changes. In order to give support to the company involved in a traceability path, starting from business model analysis and related business process a Framework to Manage Product Data in Agri-Food Supply Chain for Voluntary Traceability was conceived. Studying each process task and leveraging on modeling techniques lead to individuate information held by different actors during agri-food supply chain. IoT technologies for data collection and Analytics techniques for data processing supply information useful to increase the efficiency intra-company and competitiveness in the market. The whole information recovered can be shown through IT solutions and mobile application to made accessible to the company, the entire supply chain and the consumer with the view to guaranteeing transparency and quality.

Keywords: Agriculture 4.0, agri-food supply chain, Industry 4.0, voluntary traceability.

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Authors: Mohammad Reza Pirestani, Hamid Reza Vosoghifar, Pegah Jazayeri

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In designing river intakes and diversion structures, it is paramount that the sediments entering the intake are minimized or, if possible, completely separated. Due to high water velocity, sediments can significantly damage hydraulic structures especially when mechanical equipment like pumps and turbines are used. This subsequently results in wasting water, electricity and further costs. Therefore, it is prudent to investigate and analyze the performance of lateral intakes affected by sediment control structures. Laboratory experiments, despite their vast potential and benefits, can face certain limitations and challenges. Some of these include: limitations in equipment and facilities, space constraints, equipment errors including lack of adequate precision or mal-operation, and finally, human error. Research has shown that in order to achieve the ultimate goal of intake structure design – which is to design longlasting and proficient structures – the best combination of sediment control structures (such as sill and submerged vanes) along with parameters that increase their performance (such as diversion angle and location) should be determined. Cost, difficulty of execution and environmental impacts should also be included in evaluating the optimal design. This solution can then be applied to similar problems in the future. Subsequently, the model used to arrive at the optimal design requires high level of accuracy and precision in order to avoid improper design and execution of projects. Process of creating and executing the design should be as comprehensive and applicable as possible. Therefore, it is important that influential parameters and vital criteria is fully understood and applied at all stages of choosing the optimal design. In this article, influential parameters on optimal performance of the intake, advantages and disadvantages, and efficiency of a given design are studied. Then, a multi-criterion decision matrix is utilized to choose the optimal model that can be used to determine the proper parameters in constructing the intake.

Keywords: Diversion structures lateral intake, multi criteria decision making, optimal design, sediment control.

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Authors: Fanny Guay

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Building resilience, sustainable buildings, urbanization, climate change, resilient cities, are just a few examples of where the focus of research has been in the last few years. It is obvious that there is a need to rethink how we are building our cities and how we are renovating our existing buildings. However, the question remaining is how can we assure that we are building sustainable yet resilient cities? There are many aspects one can touch upon when discussing resilience in cities, but after the event of Grenfell in June 2017, it has become clear that fire resilience must be a priority. We define resilience as a holistic approach including communities, society and systems, focusing not only on resisting the effects of a disaster, but also how it will cope and recover from it. Cities are an example of such a system, where components such as buildings have an important role to play. A building on fire will have an impact on the community, the economy, the environment, and so the entire system. Therefore, we believe that fire and resilience go hand in hand when we discuss building resilient cities. This article aims at discussing the current state of the concept of fire resilience and suggests actions to support the built of more fire resilient buildings. Using the case of Grenfell and the fire safety regulations in the UK, we will briefly compare the fire regulations in other European countries, more precisely France, Germany and Denmark, to underline the difference and make some suggestions to increase fire resilience via regulation. For this research, we will also include other types of resilience such as technological resilience, discussing the structure of buildings itself, as well as community resilience, considering the role of communities in building resilience. Our findings demonstrate that to increase fire resilience, amending existing regulations might be necessary, for example, how we performed reaction to fire tests and how we classify building products. However, as we are looking at national regulations, we are only able to make general suggestions for improvement. Another finding of this research is that the capacity of the community to recover and adapt after a fire is also an essential factor. Fundamentally, fire resilience, technological resilience and community resilience are closely connected. Building resilient cities is not only about sustainable buildings or energy efficiency; it is about assuring that all the aspects of resilience are included when building or renovating buildings. We must ask ourselves questions as: Who are the users of this building? Where is the building located? What are the components of the building, how was it designed and which construction products have been used? If we want to have resilient cities, we must answer these basic questions and assure that basic factors such as fire resilience are included in our assessment.

Keywords: Buildings, cities, fire, resilience.

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Authors: Carmen Maria Moraru, Iuliana Stefan, Ovidiu Balteanu, Ciprian Bucur, Liviu Stefan, Anisia Bornea, Ioan Stefanescu

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The implementation of the new software and hardware-s technologies for tritium processing nuclear plants, and especially those with an experimental character or of new technology developments shows a coefficient of complexity due to issues raised by the implementation of the performing instrumentation and equipment into a unitary monitoring system of the nuclear technological process of tritium removal. Keeping the system-s flexibility is a demand of the nuclear experimental plants for which the change of configuration, process and parameters is something usual. The big amount of data that needs to be processed stored and accessed for real time simulation and optimization demands the achievement of the virtual technologic platform where the data acquiring, control and analysis systems of the technological process can be integrated with a developed technological monitoring system. Thus, integrated computing and monitoring systems needed for the supervising of the technological process will be executed, to be continued with the execution of optimization system, by choosing new and performed methods corresponding to the technological processes within the tritium removal processing nuclear plants. The developing software applications is executed with the support of the program packages dedicated to industrial processes and they will include acquisition and monitoring sub-modules, named “virtually" as well as the storage sub-module of the process data later required for the software of optimization and simulation of the technological process for tritium removal. The system plays and important role in the environment protection and durable development through new technologies, that is – the reduction of and fight against industrial accidents in the case of tritium processing nuclear plants. Research for monitoring optimisation of nuclear processes is also a major driving force for economic and social development.

Keywords: Monitoring system, process simulation.

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Authors: Hind Bouami, Patrick Millot

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Medication dispensing system is a life-critical system whose failure may result in preventable adverse events leading to longer patient stays in hospitals or patient death. Automation has led to great improvements in life-critical systems as it increased safety, efficiency, and comfort. However, critical risks related to medical organization complexity and automated solutions integration can threaten drug dispensing security and performance. Knowledge about the system’s complexity aspects and human machine parameters to control for automated equipment’s security and performance will help operators to secure their automation process and to optimize their system’s reliability. In this context, this study aims to document the operator’s situation awareness about automation risks and parameters involved in automation security and performance. Our risk management approach has been deployed in the North Luxembourg hospital center’s pharmacy, which is equipped with automated drug dispensing systems since 2009. With more than 4 million euros of gains generated, North Luxembourg hospital center’s success story was enabled by the management commitment, pharmacy’s involvement in the implementation and improvement of the automation project, and the close collaboration between the pharmacy and Sinteco’s firm to implement the necessary innovation and organizational actions for automated solutions integration security and performance. An analysis of the actions implemented by the hospital and the parameters involved in automated equipment’s integration security and performance has been made. The parameters to control for automated equipment’s integration security and performance are human aspects (6.25%), technical aspects (50%), and human-machine interaction (43.75%). The implementation of an anthropocentric analysis system before automation would have prevented and optimized the control of risks related to automation.

Keywords: Automated drug delivery systems, hospitals, human-centered automated system, risk management.

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Authors: Jefferson Camacho Mejía, Jenny Paola Forero Pachón, Luis Carlos Gómez Flórez

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Action research is a qualitative research methodology, which leads the researcher to delve into the problems of a community in order to understand its needs in depth and finally, to propose actions that lead to a change of social paradigm. Although this methodology had its beginnings in the human sciences, it has attracted increasing interest and acceptance in the field of information systems research since the 1990s. The countless possibilities offered nowadays by the use of Information Technologies (IT) in the development of different socio-economic activities have meant a change of social paradigm and the emergence of the so-called information and knowledge society. According to this, governments, large corporations, small entrepreneurs and in general, organizations of all kinds are using IT to virtualize their processes, taking them from the physical environment to the digital environment. However, there is a potential risk for organizations related with exposing valuable information without an appropriate framework for protecting it. This paper shows progress in the development of a methodological design to manage the information security risks associated with the IT-based processes virtualization, by applying the principles of the action research methodology and it is the result of a systematic review of the scientific literature. This design consists of seven fundamental stages. These are distributed in the three stages described in the action research methodology: 1) Observe, 2) Analyze and 3) Take actions. Finally, this paper aims to offer an alternative tool to traditional information security management methodologies with a view to being applied specifically in the planning stage of IT-based process virtualization in order to foresee risks and to establish security controls before formulating IT solutions in any type of organization.

Keywords: Action research, information security, information technology, methodological design, process virtualization, risk management.

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Authors: John Lamb, Robert Epstein, Vasundhara L. Bhupathi, Sanjeev Kumar Marimekala

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As we enter the new era of Artificial Intelligence (AI) and cloud computing, we mostly rely on the machine and natural language processing capabilities of AI, and energy efficient hardware and software devices in almost every industry sector. In these industry sectors, much emphasis is on developing new and innovative methods for producing and conserving energy and to sustain the depletion of natural resources. The core pillars of sustainability are Economic, Environmental, and Social, which are also informally referred to as 3 P's (People, Planet and Profits). The 3 P's play a vital role in creating a core sustainability model in the enterprise. Natural resources are continually being depleted, so there is more focus and growing demand for renewable energy. With this growing demand there is also a growing concern in many industries on how to reduce carbon emission and conserve natural resources while adopting sustainability in the corporate business models and policies. In our paper, we would like to discuss the driving forces such as climate changes, natural disasters, pandemic, disruptive technologies, corporate policies, scaled business models and emerging social media and AI platforms that influence the 3 main pillars of sustainability (3P’s). Through this paper, we would like to bring an overall perspective on enterprise strategies and the primary focus on bringing cultural shifts in adapting energy efficient operational models. Overall, many industries across the globe are incorporating core sustainability principles such as reducing energy costs, reducing greenhouse gas (GHG) emissions, reducing waste and increase recycling, adopting advanced monitoring and metering infrastructure, reducing server footprint and compute resources (shared IT services, cloud computing and application modernization) with the vision for a sustainable environment.

Keywords: AI, cloud computing, machine learning, social media platform.

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Authors: Nguyen Thi Thu Trang

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Climate change and sea level rise is one of the greatest challenges facing human beings in the 21^st century. Because of sea level rise, several low-lying coastal areas around the globe are at risk of being completely submerged, disappearing under water. Particularly in Viet Nam, the rise in sea level is predicted to result in more frequent and even permanently inundated coastal plains. As a result, land reserving fund of coastal cities is going to be narrowed in near future, while construction ground is becoming increasingly limited due to a rapid growth in population. Faced with this reality, the solutions are being discussed not only in tradition view such as accommodation is raised or moved to higher areas, or “living with the water”, but also forwards to “living on the water”. Therefore, the concept of a sustainable floating community with floating houses based on the precious value of long term historical tradition of water dwellings in Viet Nam would be a sustainable solution for adaptation of climate change and sea level rise in the coastal areas. The sustainable floating community is comprised of sustainability in four components: architecture, environment, socio-economic and living quality. This research paper is focused on sustainability in architectural component of floating community. Through detailed architectural analysis of current floating houses and floating communities in Viet Nam, this research not only accumulates precious values of traditional architecture that need to be preserved and developed in the proposed concept, but also illustrates its weaknesses that need to address for optimal design of the future sustainable floating communities. Based on these studies the research would provide guidelines with appropriate architectural solutions for the concept of sustainable floating community with floating housing units that are adapted to climate change and sea level rise in Viet Nam.

Keywords: Climate change, floating houses, floating community, Viet Nam.

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Authors: Serkan Solmaz, Jean-Baptiste Gouriet, Nicolas Van de Wyer, Christophe Schram

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Efficiency of the cooling process for cryogenic propellant boiling in engine cooling channels on space applications is relentlessly affected by the phase change occurs during the boiling. The effectiveness of the cooling process strongly pertains to the type of the boiling regime such as nucleate and film. Geometric constraints like a non-transparent cooling channel unable to use any of visualization methods. The ultrasonic (US) technique as a non-destructive method (NDT) has therefore been applied almost in every engineering field for different purposes. Basically, the discontinuities emerge between mediums like boundaries among different phases. The sound wave emitted by the US transducer is both transmitted and reflected through a gas-liquid interface which makes able to detect different phases. Due to the thermal and structural concerns, it is impractical to sustain a direct contact between the US transducer and working fluid. Hence the transducer should be located outside of the cooling channel which results in additional interfaces and creates ambiguities on the applicability of the present method. In this work, an exploratory research is prompted so as to determine detection ability and applicability of the US technique on the cryogenic boiling process for a cooling cycle where the US transducer is taken place outside of the channel. Boiling of the cryogenics is a complex phenomenon which mainly brings several hindrances for experimental protocol because of thermal properties. Thus substitute materials are purposefully selected based on such parameters to simplify experiments. Aside from that, nucleate and film boiling regimes emerging during the boiling process are simply simulated using non-deformable stainless steel balls, air-bubble injection apparatuses and air clearances instead of conducting a real-time boiling process. A versatile detection algorithm is perennially developed concerning exploratory studies afterward. According to the algorithm developed, the phases can be distinguished 99% as no-phase, air-bubble, and air-film presences. The results show the detection ability and applicability of the US technique for an exploratory purpose.

Keywords: Ultrasound, ultrasonic, multiphase flow, boiling, cryogenics, detection algorithm.

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