Search results for: cluster model approach

Authors: Kassahun Birhanu Tadesse, Megersa Olumana Dinka

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Reliable future river flow information is basic for planning and management of any river systems. For data scarce river system having only a river flow records like the Waterval River, a univariate time series models are appropriate for river flow forecasting. In this study, a univariate Seasonal Autoregressive Integrated Moving Average (SARIMA) model was applied for forecasting Waterval River flow using GRETL statistical software. Mean monthly river flows from 1960 to 2016 were used for modeling. Different unit root tests and Mann-Kendall trend analysis were performed to test the stationarity of the observed flow time series. The time series was differenced to remove the seasonality. Using the correlogram of seasonally differenced time series, different SARIMA models were identified, their parameters were estimated, and diagnostic check-up of model forecasts was performed using white noise and heteroscedasticity tests. Finally, based on minimum Akaike Information (AIc) and Hannan-Quinn (HQc) criteria, SARIMA (3, 0, 2) x (3, 1, 3)12 was selected as the best model for Waterval River flow forecasting. Therefore, this model can be used to generate future river information for water resources development and management in Waterval River system. SARIMA model can also be used for forecasting other similar univariate time series with seasonality characteristics.

Keywords: heteroscedasticity, stationarity test, trend analysis, validation, white noise

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Authors: Ahmed Emad Ahmed

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This paper aims to address the concept of human resources information systems (HRIS) and how to link it to new technologies such as artificial intelligence (AI) to be implemented in two human resources processes. A literature view has been collected to cover the main points related to HRIS, AI, and BC. A study case has been presented by generating a random HRIS to apply some AI operations to it. Then, an algorithm was applied to the database to complete some human resources processes, including training and performance appraisal, using a pre-trained AI model. After that, outputs and results have been presented and discussed briefly. Finally, a conclusion has been introduced to show the ability of new technologies such as AI and ML to be applied to the human resources management processes.

Keywords: human resources new technologies, HR artificial intelligence, HRIS AI models, construction AI HRIS

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Authors: Kristina Pflug, Markus Busch

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Being able to predict polymer properties and processing behavior based on the applied operating reaction conditions in one of the key challenges in modern polymer reaction engineering. Especially, for cost-intensive processes such as the high-pressure polymerization of low-density polyethylene (LDPE) with high safety-requirements, the need for simulation-based process optimization and product design is high. A multi-scale modelling approach was set-up and validated via a series of high-pressure mini-plant autoclave reactor experiments. The approach starts with the numerical modelling of the complex reaction network of the LDPE polymerization taking into consideration the actual reaction conditions. While this gives average product properties, the complex polymeric microstructure including random short- and long-chain branching is calculated via a hybrid Monte Carlo-approach. Finally, the processing behavior of LDPE -its melt flow behavior- is determined in dependence of the previously determined polymeric microstructure using the branch on branch algorithm for randomly branched polymer systems. All three steps of the multi-scale modelling approach can be independently validated against analytical data. A triple-detector GPC containing an IR, viscosimetry and multi-angle light scattering detector is applied. It serves to determine molecular weight distributions as well as chain-length dependent short- and long-chain branching frequencies. 13C-NMR measurements give average branching frequencies, and rheological measurements in shear and extension serve to characterize the polymeric flow behavior. The accordance of experimental and modelled results was found to be extraordinary, especially taking into consideration that the applied multi-scale modelling approach does not contain parameter fitting of the data. This validates the suggested approach and proves its universality at the same time. In the next step, the modelling approach can be applied to other reactor types, such as tubular reactors or industrial scale. Moreover, sensitivity analysis for systematically varying process conditions is easily feasible. The developed multi-scale modelling approach finally gives the opportunity to predict and design LDPE processing behavior simply based on process conditions such as feed streams and inlet temperatures and pressures.

Keywords: low-density polyethylene, multi-scale modelling, polymer properties, reaction engineering, rheology

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Authors: Melaku Takele Abate, Abbi Lemma Wodajo, Adula Bekele Hunde

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This study aimed at exploring mathematics teachers' reactions, learning, school leaders’ support, and use of the Lesson Study for Transformative Assessment (LSforTA) program ideas in practice. The LSforTA program was new, and therefore, a local and grounded approach was needed to examine teachers’ knowledge and skills acquired using LSforTA. So, a design-based research approach was selected to evaluate and refine the LSforTA approach. The results showed that LSforTA increased teachers' knowledge and use of different levels of mathematics assessment tasks. The program positively affected teachers' practices of transformative assessment and enhanced their knowledge and skills in assessing students in a transformative way. The paper concludes how the LSforTA procedures were adapted in response to this evaluation and provides suggestions for future development and research.

Keywords: classroom assessment, feedback practices, lesson study, mathematics, design-based research

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Authors: Devleminck Steven, Debackere Boris

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This research is about the ways artists and scientists deal with (and endure) new meaning and comprehend and construct the world. The project reflects on the intense connection between comprehension and construction and their place of creation – the ‘locus of action’. It seeks to define a liquid form of understanding and analysis capable of approaching our complex liquid world as discussed by Zygmunt Bauman. The aim is to establish a multi-viewpoint theoretical approach based on the dynamic concept of the Flâneur as introduced by Baudelaire, replacing single viewpoint categorization. This is coupled with the concept of thickening as proposed by Clifford Geertz with its implication of interaction between multi-layers of meaning. Here walking and looking is introduced as a method or strategy, a model or map, providing a framework of understanding in conditions of hybridity and change.

Keywords: action, art, liquid, locus, negotiation, place, science

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Authors: Rute Faria, Digo Moraes, Amanda Santos, Dione Morais, Maria Sartori

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Seed vigor is a fundamental component for the good performance of the entire soybean production process. Seeds with mechanical damage at harvest time will be more susceptible to fungal and insect attack during storage, which will invariably reduce their vigor to the field, compromising uniformity and final stand performance. Harvesters, even the most modern ones, when not properly regulated or operated, can cause irreversible damages to the seeds, compromising even their commercialization. Therefore, the control of an efficient harvest is necessary in order to guarantee a good quality final product. In this work, the damage caused by two different harvesters (one rented, and another one) was evaluated, traveling in two speeds (4 and 8 km / h). The design was completely randomized in 2 x 2 factorial, with four replications. To evaluate the physiological quality seed germination and vigor tests were carried out over a period of six months. A multivariate analysis of Principal Components (PCA) and clustering allowed us to verify that the leased machine had better performance in the incidence of immediate damages in the seeds, but after a storage period of 6 months the vigor of these seeds reduced more than own machine evidencing that such a machine would bring more damages to the seeds.

Keywords: Glycine max (L.), cluster analysis, PCA, vigor

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Authors: Saba Gachpaz, Hamid Reza Heidari

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The sharp increase in population growth leads to more pressure on agricultural areas to satisfy the food supply. To achieve this, more resources should be consumed and, besides other environmental concerns, highlight sustainable agricultural development. Land-use management is a crucial factor in obtaining optimum productivity. Machine learning is a widely used technique in the agricultural sector, from yield prediction to customer behavior. This method focuses on learning and provides patterns and correlations from our data set. In this study, nine physical control factors, namely, soil classification, electrical conductivity, normalized difference water index (NDWI), groundwater level, elevation, annual precipitation, pH of water, annual mean temperature, and slope in the alluvial plain in Khuzestan (an agricultural hotspot in Iran) are used to decide the best agricultural land use for both rainfed and irrigated agriculture for ten different crops. For this purpose, each variable was imported into Arc GIS, and a raster layer was obtained. In the next level, by using training samples, all layers were imported into the python environment. A random forest model was applied, and the weight of each variable was specified. In the final step, results were visualized using a digital elevation model, and the importance of all factors for each one of the crops was obtained. Our results show that despite 62% of the study area being allocated to agricultural purposes, only 42.9% of these areas can be defined as a suitable class for cultivation purposes.

Keywords: land suitability, machine learning, random forest, sustainable agriculture

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Authors: Yoon-Cheol Park

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This research focuses on examining the Chinese character-Korean language translation of the Vajrachedika-prajna-paramita sutra by a pragmatic approach. The background of this research is that there were no previous researches which looked into the Vajrachedika-prajna-paramita translation by pragmatic approach until now. Even though it is composed of conversational structures between Buddha and his disciple unlike other Buddhist sutras, most of its translation could find the traces to have pursued literal translation and still has now overlooked pragmatic elements in it. Accordingly, it is meaningful to examine the messages through speaker and hearer relation and between speaker intention and utterance meaning. Practically, the Vajrachedika-prajna-paramita sutra includes pragmatic elements, such as speech acts, presupposition, conversational implicature, the cooperative principle and politeness. First, speech acts in its sutra text show the translation to reveal obvious performance meanings of language to the target text. And presupposition in their dialogues is conveyed by paraphrasing or substituting abstruse language with easy expressions. Conversational implicature in utterances makes it possible to understand the meanings of holy words by relying on utterance contexts. In particular, relevance results in an increase of readability in the translation owing to previous utterance contexts. Finally, politeness in the target text is conveyed with natural stylistics through the honorific system of the Korean language. These elements mean that the pragmatic approach can function as a useful device in conveying holy words in a specific, practical and direct way depending on utterance contexts. Therefore, we expect that taking a pragmatic approach in translating the Vajrachedika-prajna-paramita sutra will provide a theoretical foundation for seeking better translation methods than the literal translations of the past. And it implies that the translation of Buddhist sutra needs to convey messages by translation methods which take into account the characteristic of sutra text like the Vajrachedika-prajna-paramita.

Keywords: buddhist sutra, Chinese character-Korean language translation, pragmatic approach, utterance context

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Authors: Odoh Dickson Akpegi

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The paper is about the need for an indigenous language in order to meaningfully harness both our human and material resources for the nation’s integration. It then examines the notty issue of the national language question and advocates a piece meal approach in solving the problem. This approach allows for the development and use of local languages in minority areas, especially in Benue State, as a way of preparing them for consideration as possible replacement for English language as Nigeria’s national or official language. Finally, an arrangement to follow to prepare the languages for such competition at the national level is presented.

Keywords: indigenous language, English language, official language, National integration

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Authors: Quoc Van Nguyen, Behzad Fatahi, Aslan S. Hokmabadi

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Performance based seismic design is a modern approach to earthquake-resistant design shifting emphasis from “strength” to “performance”. Soil-Structure Interaction (SSI) can influence the performance level of structures significantly. In this paper, a fifteen storey moment resisting frame sitting on a shallow foundation (footing) with different sizes is simulated numerically using ABAQUS software. The developed three dimensional numerical simulation accounts for nonlinear behaviour of the soil medium by considering the variation of soil stiffness and damping as a function of developed shear strain in the soil elements during earthquake. Elastic-perfectly plastic model is adopted to simulate piles and structural elements. Quiet boundary conditions are assigned to the numerical model and appropriate interface elements, capable of modelling sliding and separation between the foundation and soil elements, are considered. Numerical results in terms of base shear, lateral deformations, and inter-storey drifts of the structure are compared for the cases of soil-structure interaction system with different foundation sizes as well as fixed base condition (excluding SSI). It can be concluded that conventional design procedures excluding SSI may result in aggressive design. Moreover, the size of the foundation can influence the dynamic characteristics and seismic response of the building due to SSI and should therefore be given careful consideration in order to ensure a safe and cost effective seismic design.

Keywords: soil-structure-interaction, seismic response, shallow foundation, abaqus, rayleigh damping

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Authors: S. K. Ashiquer Rahman

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Recently, oil has become more influential in almost every economic sector as a key material. As can be seen from the news, when there are some changes in an oil price or OPEC announces a new strategy, its effect spreads to every part of the economy directly and indirectly. That’s a reason why people always observe the oil price and try to forecast the changes of it. The most important factor affecting the price is its supply which is determined by the number of wildcats drilled. Therefore, a study about the number of wellheads and other economic variables may give us some understanding of the mechanism indicated by the amount of oil supplies. In this paper, we will consider a relationship between the number of wellheads and three key factors: the price of the wellhead, domestic output, and GNP constant dollars. We also add trend variables in the models because the consumption of oil varies from time to time. Moreover, this paper will use an econometrics method to estimate parameters in the model, apply some tests to verify the result we acquire, and then conclude the model.

Keywords: price, domestic output, GNP, trend variable, wildcat activity

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Authors: Jin Woo Hwang, Byung Kwan Oh, Yousok Kim, Hyo Seon Park

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As greenhouse effect has been recognized as serious environmental problem of the world, interests in carbon dioxide (CO₂) emission which comprises major part of greenhouse gas (GHG) emissions have been increased recently. Since construction industry takes a relatively large portion of total CO₂ emissions of the world, extensive studies about reducing CO₂ emissions in construction and operation of building have been carried out after the 2000s. Also, performance based design (PBD) methodology based on nonlinear analysis has been robustly developed after Northridge Earthquake in 1994 to assure and assess seismic performance of building more exactly because structural engineers recognized that prescriptive code based design approach cannot address inelastic earthquake responses directly and assure performance of building exactly. Although CO₂ emissions and PBD approach are recent rising issues on construction industry and structural engineering, there were few or no researches considering these two issues simultaneously. Thus, the objective of this study is to minimize the CO₂ emissions and cost of building designed by PBD approach in structural design stage considering structural materials. 4 story and 4 span reinforced concrete building optimally designed to minimize CO₂ emissions and cost of building and to satisfy specific seismic performance (collapse prevention in maximum considered earthquake) of building satisfying prescriptive code regulations using non-dominated sorting genetic algorithm-II (NSGA-II). Optimized design result showed that minimized CO₂ emissions and cost of building were acquired satisfying specific seismic performance. Therefore, the methodology proposed in this paper can be used to reduce both CO₂ emissions and cost of building designed by PBD approach.

Keywords: CO2 emissions, performance based design, optimization, sustainable design

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Authors: Emma Serwaa Obobisaa, Haibo Chen

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International trade and outward foreign direct investment are important factors which are generally recognized in the economic growth and development. Though several scholars have struggled to reveal the influence of trade and outward foreign direct investment (FDI) on economic growth, most studies utilized common econometric models such as vector autoregression and aggregated the variables, which for the most part prompts, however, contradictory and mixed results. Thus, there is an exigent need for the precise study of the trade and FDI effect of economic growth while applying strong econometric models and disaggregating the variables into its separate individual variables to explicate their respective effects on economic growth. This will guarantee the provision of policies and strategies that are geared towards individual variables to ensure sustainable development and growth. This study, therefore, seeks to examine the causal effect of China-Africa trade and Outward Foreign Direct Investment on the economic growth of Africa using a robust and recent econometric approach such as system dynamics model. Our study impanels and tests an ensemble of a group of vital variables predominant in recent studies on trade-FDI-economic growth causality: Foreign direct ınvestment, international trade and economic growth. Our results showed that the system dynamics method provides accurate statistical inference regarding the direction of the causality among the variables than the conventional method such as OLS and Granger Causality predominantly used in the literature as it is more robust and provides accurate, critical values.

Keywords: economic growth, outward foreign direct investment, system dynamics model, international trade

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Authors: Rouhollah Radjabi, Mojtaba Zarei, Elham Sanatgar, Hossein Shouhani

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RAPD molecular markers in order to discrimination of the Iranian native Bombyx mori silkworm breeds were used. DNA extraction using phenol - chloroform was and the qualitative and quantitative measurements of extracted DNA and its dilution, the obtained bands on agarose gel 1.5 percent were marked and analyzed. Results showed that the bands are observed between 250-2500 bp and most bands have been observed as Gilani-orange, the lowest bands observed are Khorasani-lemon. Primer 3 with 100% polymorphism with the highest polymorphism and primer 2 with 61.5 polymorphism had the lowest percentage of polymorphism. Cluster analysis of races and placed them in three main groups, races Gilani - orange, Baghdad and Khorasani -pink if the first group, camel's thorn, Herati - yellow race was alone in the second group and Khorasani – lemon was alone in the third group. The greatest similarity between the races, between Khorasani- pink and Baghdad (0.64). RAPD markers have been determined different silkworm races based on various morphological or economic characteristics except geographic origin.

Keywords: silkworm, molecular marker, RAPD, Iran

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Authors: Tina Wu, Andrew Martin

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The expansion of the Internet of Things (IoT) brings a new level of threat. Attacks on IoT are already being used by criminals to form botnets, launch Distributed Denial of Service (DDoS) and distribute malware. This opens a whole new digital forensic arena to develop forensic methodologies in order to have the capability to investigate IoT related crimes. However, existing proposed IoT forensic models are still premature requiring further improvement and validation, many lack details on the acquisition and analysis phase. This paper proposes an enhanced theoretical IoT digital forensic model focused on identifying and acquiring the main sources of evidence in a methodical way. In addition, this paper presents a theoretical acquisition framework of the different stages required in order to be capable of acquiring evidence from IoT devices.

Keywords: acquisition, Internet of Things, model, zoning

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Authors: Julio Franco

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Water is used, directly and indirectly, in all activities of the construction productive chain, making it a subject of worldwide relevance for sustainable development. The ongoing expansion of urban areas leads to a high demand for natural resources, which in turn cause significant environmental impacts. The present work proposes the application of BIM tools to assist the measurement of the water footprint (WF) of civil construction supplies. Data was inserted into the model as element properties, allowing them to be analyzed by element or in the whole model. The WF calculation was automated using parameterization in Autodesk Revit software. Parameterization was associated to the materials of each element in the model so that any changes in these elements directly alter the results of WF calculations. As a case study, we applied into a building project model to test the parameterized calculus of WF. Results show that the proposed parameterization successfully automated WF calculations according to design changes. We envision this tool to assist the measurement and rationalization of the environmental impact in terms of WF of construction projects.

Keywords: building information modeling, BIM, sustainable development, water footprint

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Authors: M. Duk, L. Grabowski, P. Magryta

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Today's very important element relating to air transport is the environment impact issues. Nowadays there are no emissions standards for turbine and piston engines used in air transport. However, it should be noticed that the environmental effect in the form of exhaust gases from aircraft engines should be as small as possible. For this purpose, R&D centers often use special software to simulate and to estimate the negative effect of engine working process. For cooperation between the Lublin University of Technology and the Polish aviation company WSK "PZL-KALISZ" S.A., to achieve more effective operation of the ASz62IR engine, one of such tools have been used. The AVL Boost software allows to perform 1D simulations of combustion process of piston engines. ASz62IR is a nine-cylinder aircraft engine in a radial configuration. In order to analyze the impact of its working process on the environment, the mathematical model in the AVL Boost software have been made. This model contains, among others, model of the operation cycle of the cylinders. This model was based on a volume change in combustion chamber according to the reciprocating movement of a piston. The simplifications that all of the pistons move identically was assumed. The changes in cylinder volume during an operating cycle were specified. Those changes were important to determine the energy balance of a cylinder in an internal combustion engine which is fundamental for a model of the operating cycle. The calculations for cylinder thermodynamic state were based on the first law of thermodynamics. The change in the mass in the cylinder was calculated from the sum of inflowing and outflowing masses including: cylinder internal energy, heat from the fuel, heat losses, mass in cylinder, cylinder pressure and volume, blowdown enthalpy, evaporation heat etc. The model assumed that the amount of heat released in combustion process was calculated from the pace of combustion, using Vibe model. For gas exchange, it was also important to consider heat transfer in inlet and outlet channels because of much higher values there than for flow in a straight pipe. This results from high values of heat exchange coefficients and temperature coefficients near valves and valve seats. A Zapf modified model of heat exchange was used. To use the model with the flight scenarios, the impact of flight altitude on engine performance has been analyze. It was assumed that the pressure and temperature at the inlet and outlet correspond to the values resulting from the model for International Standard Atmosphere (ISA). Comparing this model of operation cycle with the others submodels of the ASz62IR engine, it could be noticed, that a full analysis of the performance of the engine, according to the ISA conditions, can be made. This work has been financed by the Polish National Centre for Research and Development, INNOLOT, under

Keywords: aviation propulsion, AVL Boost, engine model, operation cycle, aircraft engine

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Authors: M. R. Ghasemi, R. Ghiasi, H. Varaee

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Model updating method has received increasing attention in damage detection structures based on measured modal parameters. Therefore, a probability-based damage detection (PBDD) procedure based on a model updating procedure is presented in this paper, in which a one-stage model-based damage identification technique based on the dynamic features of a structure is investigated. The presented framework uses a finite element updating method with a Monte Carlo simulation that considers the uncertainty caused by measurement noise. Enhanced ideal gas molecular movement (EIGMM) is used as the main algorithm for model updating. Ideal gas molecular movement (IGMM) is a multiagent algorithm based on the ideal gas molecular movement. Ideal gas molecules disperse rapidly in different directions and cover all the space inside. This is embedded in the high speed of molecules, collisions between them and with the surrounding barriers. In IGMM algorithm to accomplish the optimal solutions, the initial population of gas molecules is randomly generated and the governing equations related to the velocity of gas molecules and collisions between those are utilized. In this paper, an enhanced version of IGMM, which removes unchanged variables after specified iterations, is developed. The proposed method is implemented on two numerical examples in the field of structural damage detection. The results show that the proposed method can perform well and competitive in PBDD of structures.

Keywords: enhanced ideal gas molecular movement (EIGMM), ideal gas molecular movement (IGMM), model updating method, probability-based damage detection (PBDD), uncertainty quantification

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Authors: Rafael Alvarenga, Hubert Herbaux, Laurent Linguet

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The uncertainty concerning the power production of intermittent renewable energy is one of the main barriers to the integration of such assets into the power grid. Efforts have thus been made to develop methods to quantify this uncertainty, allowing producers to ensure more reliable and profitable engagements related to their future power delivery. Even though a diversity of probabilistic approaches was proposed in the literature giving promising results, the added value of adopting such methods for scheduling intermittent power plants is still unclear. In this study, the profits obtained by a decision-making model used to optimally schedule an existing PV power plant connected to batteries are compared when the model is fed with deterministic and probabilistic forecasts generated with two of the most recent methods proposed in the literature. Moreover, deterministic forecasts with different accuracy levels were used in the experiments, testing the utility and the capability of probabilistic methods of modeling the progressively increasing uncertainty. Even though probabilistic approaches are unquestionably developed in the recent literature, the results obtained through a study case show that deterministic forecasts still provide the best performance if accurate, ensuring a gain of 14% on final profits compared to the average performance of probabilistic models conditioned to the same forecasts. When the accuracy of deterministic forecasts progressively decreases, probabilistic approaches start to become competitive options until they completely outperform deterministic forecasts when these are very inaccurate, generating 73% more profits in the case considered compared to the deterministic approach.

Keywords: PV power forecasting, uncertainty quantification, optimal scheduling, power systems

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Authors: Revanth Rallapalli

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Manually dispensing powders can be difficult as it requires gradually pouring and checking the amount on the scale to be dispensed. Current systems are manual and non-continuous in nature and are user-dependent and difficult to control powder dispensation. Recurrent dosing of powdered medicines in precise amounts quickly and accurately has been an all-time challenge. Various new powder dispensing mechanisms are being designed to overcome these challenges. A battery-operated screw conveyor mechanism is being innovated to overcome the above problems faced. These inventions are numerically evaluated at the concept development level by employing Computational Fluid Dynamics (CFD) of gas-solids multiphase flow systems. CFD has been very helpful in the development of such devices saving time and money by reducing the number of prototypes and testing. This paper describes a simulation of powder dispensation from the trocar’s end by considering the powder as secondary flow in the air, is simulated by using the technique called Dense Discrete Phase Model incorporated with Kinetic Theory of Granular Flow (DDPM-KTGF). By considering the volume fraction of powder as 50%, the transportation of powder from the inlet side to the trocar’s end side is done by rotation of the screw conveyor. The performance is calculated for a 1-sec time frame in an unsteady computation manner. This methodology will help designers in developing design concepts to improve the dispensation and the effective area within a quick turnaround time frame.

Keywords: multiphase flow, screw conveyor, transient, dense discrete phase model (DDPM), kinetic theory of granular flow (KTGF)

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Authors: Kien-Trinh Thi Bui, Cuong Manh Nguyen

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In order to simulate and reproduce the operational characteristics of a dam visually, it is necessary to capture the displacement at different measurement points and analyze the observed movement data promptly to forecast the dam safety. The accuracy of forecasts is further improved by applying machine learning methods to data analysis progress. In this study, the horizontal displacement monitoring data of the Ialy hydroelectric dam was applied to machine learning algorithms: Gaussian processes, multi-layer perceptron neural networks, and the M5-rules algorithm for modelling and forecasting of horizontal displacement of the Ialy hydropower dam (Vietnam), respectively, for analysing. The database which used in this research was built by collecting time series of data from 2006 to 2021 and divided into two parts: training dataset and validating dataset. The final results show all three algorithms have high performance for both training and model validation, but the MLPs is the best model. The usability of them are further investigated by comparison with a benchmark models created by multi-linear regression. The result show the performance which obtained from all the GP model, the MLPs model and the M5-Rules model are much better, therefore these three models should be used to analyze and predict the horizontal displacement of the dam.

Keywords: Gaussian processes, horizontal displacement, hydropower dam, Ialy dam, M5-Rules, multi-layer perception neural networks

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Authors: Yun Zhang

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Urban housing in China is typified by residential districts that occupy 25 to 40 percentage of the urban land. In residential districts, squares, roads, and building facades, as well as plants, usually form a four-grade spatial structure: district entrances, central landscapes, housing cluster entrances, green spaces between dwellings. This spatial structure and its elements not only compose the visible residential landscape but also play a major role of carrying rain water. These elements, therefore, imply ecological significance to urban fitness. Based upon theories of landscape ecology, residential landscape can be understood as a pattern typified by minor soft patch of planted area and major hard patch of buildings and squares, as well as hard corridors of roads. Use five landscape districts in Hangzhou as examples; this paper finds that the size, shape and slope direction of soft patch, the bend of roads, and the form of the four-grade spatial structure are influential for adapting to natural rainwater circulation.

Keywords: Hangzhou China, rainwater, residential landscape, spatial character, urban housing

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Authors: Jaehwan Jung, Sung-Ah Kim

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Building Information Modeling (BIM) provides project stakeholders with various information about property and geometry of entire component as a 3D object-based parametric building model. BIM represents a set of Information and solutions that are expected to improve collaborative work process and quality of the building design. To improve collaboration among project participants, the BIM model should provide the necessary information to remote participants in real time and manage the information in the process. The purpose of this paper is to propose a process model that can apply effective architectural design collaborative work process in architectural design education in BIM-Cloud environment.

Keywords: BIM, cloud computing, collaborative design, digital design education

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Authors: Shishir Lamichhane, Saurav Dulal, Bibek Gautam, Madan Thapa Magar, Indraman Tamrakar

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Renewable energies such as wind turbines and solar photovoltaic have gained significance as a result of global environmental pollution and energy crises. These sources of energy are converted into electrical energy and delivered to end-users through the utility system. As a result of the widespread use of power electronics-based grid-interfacing technologies to accommodate renewable sources of energy, the prevalence of converters has expanded as well. As a result, the power system's rotating inertia is decreasing, endangering the utility grid's stability. The use of Virtual Synchronous Machine (VSM) technology has been proposed to overcome the grid stability problem due to low rotating inertia. The grid-connected inverter used in VSM can be controlled to emulate inertia, which replicates the external features of a synchronous generator. As a result, the rotating inertia is increased to support the power system's stability. A power angle control strategy is proposed in this paper and its model is simulated in MATLAB/Simulink to study the effects of parameter disturbances on the active power and frequency for a VSM. The system consists of a synchronous generator, which is modeled in such a way that the frequency drops to an unacceptable region during transient conditions due to a lack of inertia when VSM is not used. Then, the suggested model incorporating VSM emulates rotating inertia, injecting a controllable amount of energy into the grid during frequency transients to enhance transient stability.

Keywords: damping constant, inertia–constant, ROCOF, transient stability, distributed sources

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Authors: M. Vlahovic

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This paper presents a model of public finances, which combines three concepts: participatory budgeting, crowdfunding and blockchain technology. Participatory budgeting is defined as a process in which community members decide how to spend a part of community’s budget. Crowdfunding is a practice of funding a project by collecting small monetary contributions from a large number of people via an Internet platform. Blockchain technology is a distributed ledger that enables efficient and reliable transactions that are secure and transparent. In this hypothetical model, the government or authorities on local/regional level would set up a platform where they would propose public projects to citizens. Citizens would browse through projects and support or vote for those which they consider justified and necessary. In return, they would be entitled to a tax relief in the amount of their monetary contribution. Since the blockchain technology enables tracking of transactions, it can be used to mitigate corruption, money laundering and lack of transparency in public finances. Models of its application have already been created for e-voting, health records or land registries. By presenting a model of application of blockchain technology in public finances, this paper takes into consideration the potential of blockchain technology to disrupt governments and make processes more democratic, secure, transparent and efficient. The framework for this paper consists of multiple streams of research, including key concepts of direct democracy, public finance (especially the voluntary theory of public finance), information and communication technology, especially blockchain technology and crowdfunding. The framework defines rules of the game, basic conditions for the implementation of the model, benefits, potential problems and development perspectives. As an oversimplified map of a new form of public finances, the proposed model identifies primary factors, that influence the possibility of implementation of the model, and that could be tracked, measured and controlled in case of experimentation with the model.

Keywords: blockchain technology, distributed ledger, participatory budgeting, crowdfunding, direct democracy, internet platform, e-government, public finance

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Authors: Serge Rohmer

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This paper proposes a progressive participatory observation that can be used as a sociological investigation within communities. The usefulness of participant observation in sociological projects is first asserted, particularly in an urban context. Competencies, know-how and interpersonal skills are then explained before to detail the progressive approach, consisting of four levels of observation. The progressive participatory observation is applied to an experimental project to set up a permaculture urban micro-farm with residents of a priority neighbourhood. Feedback on the experiment has identified several key recommendations for implementing the approach.

Keywords: participatory observation, observation scale, priority neighbourhood, urban sociology

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Authors: Alexandre Barbosa de Almeida, Telma Woerle de Lima Soares

Abstract:

Protein structure prediction is a challenging task in the bioinformatics field. The biological function of all proteins majorly relies on the shape of their three-dimensional conformational structure, but less than 1% of all known proteins in the world have their structure solved. This work proposes a deep learning model to address this problem, attempting to predict some aspects of the protein conformations. Throughout a process of multiobjective dominance, a recurrent neural network was trained to abstract the particular bias of each individual multiobjective algorithm, generating a heuristic that could be useful to predict some of the relevant aspects of the three-dimensional conformation process formation, known as protein folding.

Keywords: Ab initio heuristic modeling, multiobjective optimization, protein structure prediction, recurrent neural network

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Authors: Roland F. Karthaus, Rachel S. O'Brien

Abstract:

Over the past decade, the authors have undertaken applied research aimed at enabling transformation within the prison service to improve conditions and outcomes for those living, working and visiting in prisons in the UK and the communities they serve. The research has taken place against a context of reducing resources and public discontent at increasing levels of violence, deteriorating conditions and persistently high levels of re-offending. Top-down governmental policies have mainly been ineffectual and in some cases counter-productive. The prison service is characterised by hierarchical organisation, and the research has applied design thinking at multiple levels to challenge and precipitate change: top-down, middle-out and bottom-up. The research employs three distinct but related approaches, system design (top-down): working at the national policy level to analyse the changing policy context, identifying opportunities and challenges; engaging with the Ministry of Justice commissioners and sector organisations to facilitate debate, introducing new evidence and provoking creative thinking, place-based design (middle-out): working with individual prison establishments as pilots to illustrate and test the potential for local empowerment, creative change, and improved architecture within place-specific contexts and organisational hierarchies, everyday design (bottom-up): working with individuals in the system to explore the potential for localised, significant, demonstrator changes; including collaborative design, capacity building and empowerment in skills, employment, communication, training, and other activities. The research spans a series of projects, through which the methodological approach has developed responsively. The projects include a place-based model for the re-purposing of Ministry of Justice land assets for the purposes of rehabilitation; an evidence-based guide to improve prison design for health and well-being; capacity-based employment, skills and self-build project as a template for future open prisons. The overarching research has enabled knowledge to be developed and disseminated through policy and academic networks. Whilst the research remains live and continuing; key findings are emerging as a basis for a new methodological approach to effecting change in the UK prison service. An interdisciplinary approach is necessary to overcome the barriers between distinct areas of the prison service. Sometimes referred to as total environments, prisons encompass entire social and physical environments which themselves are orchestrated by institutional arms of government, resulting in complex systems that cannot be meaningfully engaged through narrow disciplinary lenses. A scalar approach is necessary to connect strategic policies with individual experiences and potential, through the medium of individual prison establishments, operating as discrete entities within the system. A reflexive process is necessary to connect research with action in a responsive mode, learning to adapt as the system itself is changing. The role of individuals in the system, their latent knowledge and experience and their ability to engage and become agents of change are essential. Whilst the specific characteristics of the UK prison system are unique, the approach is internationally applicable.

Keywords: architecture, design, policy, prison, system, transformation

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Authors: Waleed A. Basuliman, Khalid S. AlSaleh, Mohamed Z. Ramadan

Abstract:

Applying the anthropometric dimensions is considered one of the important factors when designing any human-machine system. In this study, the estimation of anthropometric dimensions has been improved by developing artificial neural network that aims to predict the anthropometric measurements of the male in Saudi Arabia. A total of 1427 Saudi males from age 6 to 60 participated in measuring twenty anthropometric dimensions. These anthropometric measurements are important for designing the majority of work and life applications in Saudi Arabia. The data were collected during 8 months from different locations in Riyadh City. Five of these dimensions were used as predictors variables (inputs) of the model, and the remaining fifteen dimensions were set to be the measured variables (outcomes). The hidden layers have been varied during the structuring stage, and the best performance was achieved with the network structure 6-25-15. The results showed that the developed Neural Network model was significantly able to predict the body dimensions for the population of Saudi Arabia. The network mean absolute percentage error (MAPE) and the root mean squared error (RMSE) were found 0.0348 and 3.225 respectively. The accuracy of the developed neural network was evaluated by compare the predicted outcomes with a multiple regression model. The ANN model performed better and resulted excellent correlation coefficients between the predicted and actual dimensions.

Keywords: artificial neural network, anthropometric measurements, backpropagation, real anthropometric database

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Authors: Choumous Mannoubi, Dahlia Kairy, Brigitte Vachon

Abstract:

The use of technology allows clinicians to provide an individualized approach in a cost-effective manner and to reach a broader client base more easily. Such interventions can be effective in ensuring self-management and follow-up of people with diabetes, reducing the risk of complications by improving accessibility to care services, and better adherence to health recommendations. Consideration of users' opinions and fears to inform the design and implementation stages of these telehealth services seems to be essential to improve their acceptance and usability. The objective of this study is to describe the telepractice of nutritionists supporting the therapeutic management of diabetic patients and document the functional requirements of nutritionists for the design of a tele-nutrition platform. To best identify the requirements and constraints of nutritionists, we conducted individual semi-structured interviews with 10 nutritionists who offered tele-nutrition services. Using a qualitative design with a descriptive approach based on the Nutrition Care Process Model (mNCP) framework, we explored in depth the state of nutritionists' telepractice in public and private health care settings, as well as their requirements for teleconsultation. Qualitative analyses revealed that nutritionists primarily used telephone calls during the COVID 19 pandemic to provide teleconsultations. Nutritionists identified the following important features for the design of a tele-nutrition platform: it should support interprofessional collaboration, allow for the development and monitoring of a care plan, integrate with the existing IT environment, be easy to use, accommodate different levels of patient literacy, and allow for easy sharing of educational materials to support nutrition education.

Keywords: telehealth, nutrition, diabetes, telenutrition, teleconsultation, telemonitoring

Procedia PDF Downloads 133