Search results for: choice models

Authors: Shahul Hamid Khan, S. Santhosh, Abhinav Kumar Sharma

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Environmental performance along with social performance is becoming vital factors for industries to achieve global standards. With a good environmental policy global industries are differentiating them from their competitors. This paper concentrates on multi stage, multi product and multi period manufacturing network. Bi-objective mathematical models for total cost and total emission for the entire forward supply chain are considered. Here five different problems are considered by varying the number of suppliers, manufacturers, and environmental levels, for illustrating the taken mathematical model. GA, and Random search are used for finding the optimal solution. The input parameters of the optimal solution are used to find the tradeoff between the initial investment by the industry and the long term benefit of the environment.

Keywords: closed loop supply chain, genetic algorithm, random search, green supply chain

Procedia PDF Downloads 549

Authors: Rami Al Jafar, Paul Elliott, Konstantinos K. Tsilidis, Abbas Dehghan

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Although Ramadan fasting is a ritual that is practiced every year by millions of Muslims, studies on Ramadan fasting are still scarce. To the best of our knowledge, none of the previous studies comprehensively explored the effect on the metabolic profile. In London Ramadan Fasting Study, blood samples were collected from 81 participants before and 10-14 days after Ramadan. Blood samples were analysed using nuclear magnetic resonance (NMR) spectroscopy which covers 249 metabolites. Mixed-effects models were used to analyse collected data and assess the effect of Ramadan fasting on the metabolic profile. Our observational study involved 85 individuals with a mean age of 45.2 years, and 53.1% of them were males. After Ramadan, forty metabolites were affected significantly by Ramadan fasting. Most of these metabolites were metabolites ratios (24), and the rest were three Glycolysis, three ketone bodies, nine Lipoprotein subclasses and one inflammation marker. This study suggests that Ramadan fasting is significantly associated with changes in the metabolic profile. However, the changes are assumed to be temporary, and the long-term effect of these changes is unknown.

Keywords: metabolic profile, Ramadan fasting, metabolites, intermittent fasting

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Authors: Amelia J. McFarland, Andrew K. Davey, Shailendra Anoopkumar-Dukie

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Microglia are the resident macrophage population of the central nervous system (CNS), contributing to both innate and adaptive immune response, and brain homeostasis. Activation of microglia occurs in response to a multitude of pathogenic stimuli in their microenvironment; this induces morphological and functional changes, resulting in a state of acute neuroinflammation which facilitates injury resolution. Adequate microglial function is essential for the health of the neuroparenchyma, with microglial dysfunction implicated in numerous CNS pathologies. Given the critical role that these macrophage-derived cells play in CNS homeostasis, there is a high demand for microglial models suitable for use in neuroscience research. The isolation of primary human microglia, however, is both difficult and costly, with microglial activation an unwanted but inevitable result of the extraction process. Consequently, there is a need for the development of alternative experimental models which exhibit morphological, biochemical and functional characteristics of human microglia without the difficulties associated with primary cell lines. In this study, our aim was to evaluate whether THP-1 human peripheral blood monocytes would display microglial-like qualities following an induced differentiation, and, therefore, be suitable for use as surrogate microglia. To achieve this aim, THP-1 human peripheral blood monocytes from acute monocytic leukaemia were differentiated with a range of phorbol 12-myristate 13-acetate (PMA) concentrations (50-200 nM) using two different protocols: a 5-day continuous PMA exposure or a 3-day continuous PMA exposure followed by a 5-day rest in normal media. In each protocol and at each PMA concentration, microglial-like cell morphology was assessed through crystal violet staining and the presence of CD-14 microglial / macrophage cell surface marker. Lipopolysaccharide (LPS) from Escherichia coli (055: B5) was then added at a range of concentrations from 0-10 mcg/mL to activate the PMA-differentiated THP-1 cells. Functional microglial-like behavior was evaluated by quantifying the release of prostaglandin (PG)-E2 and pro-inflammatory cytokines interleukin (IL)-1β and tumour necrosis factor (TNF)-α using mediator-specific ELISAs. Furthermore, production of global reactive oxygen species (ROS) and nitric oxide (NO) were determined fluorometrically using dichlorodihydrofluorescein diacetate (DCFH-DA) and diaminofluorescein diacetate (DAF-2-DA) respectively. Following PMA-treatment, it was observed both differentiation protocols resulted in cells displaying distinct microglial morphology from 10 nM PMA. Activation of differentiated cells using LPS significantly augmented IL-1β, TNF-α and PGE2 release at all LPS concentrations under both differentiation protocols. Similarly, a significant increase in DCFH-DA and DAF-2-DA fluorescence was observed, indicative of increases in ROS and NO production. For all endpoints, the 5-day continuous PMA treatment protocol yielded significantly higher mediator levels than the 3-day treatment and 5-day rest protocol. Our data, therefore, suggests that the differentiation of THP-1 human monocyte cells with PMA yields a homogenous microglial-like population which, following stimulation with LPS, undergo activation to release a range of pro-inflammatory mediators associated with microglial activation. Thus, the use of PMA-differentiated THP-1 cells represents a suitable microglial model for in vitro research.

Keywords: differentiation, lipopolysaccharide, microglia, monocyte, neuroscience, THP-1

Procedia PDF Downloads 389

Authors: Lu Zhao, Nadir Farhi, Yeltsin Valero, Zoi Christoforou, Nadia Haddadou

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In this paper, a long short-term memory (LSTM) neural network model is proposed to replicate simultaneously car-following and lane-changing behaviors in road networks. By combining two kinds of LSTM layers and three input designs of the neural network, six variants of the LSTM model have been created. These models were trained and tested on the NGSIM 101 dataset, and the results were evaluated in terms of longitudinal speed and lateral position, respectively. Then, we compared the LSTM model with a classical car-following model (the intelligent driving model (IDM)) in the part of speed decision. In addition, the LSTM model is compared with a model using classical neural networks. After the comparison, the LSTM model demonstrates higher accuracy than the physical model IDM in terms of car-following behavior and displays better performance with regard to both car-following and lane-changing behavior compared to the classical neural network model.

Keywords: traffic modeling, neural networks, LSTM, car-following, lane-change

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Authors: Gyorgy Folk

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A finite set of cardinal needs define the human core of living well shaped on the evolutionary time scale as attested by social and life sciences of the last decades. Well-being is the purported state of living well. Living of humans akin any other living beings involves the exchange of vital substance with nature, maintaining a supportive symbiosis with an array of other living beings, living up to bonds to kin and exerting efforts to sustain living. A supportive natural environment, access to material resources, the nearness to fellow beings, and life sustaining activity are prerequisites of well-being. Well-living is prone to misinterpretation as an individual achievement, one lives well only and only if bonded to human relationships, related to a place, incorporated in nature. Akin all other forms of it, human life is a self-sustaining arrangement. One may say that the substance of life is life, and not materials, products, and services converted into life. The human being remains shaped on an evolutionary time scale and is enabled within the non-altering core of human being, invariant of cultural differences in earthly space and time. Present paper proposes the introduction of weal, the missing link in the causal chain of societal performance and the goodness of life. Interpreted differently over the ages, cultures and disciplines, instead of well-being, the construct in general use, weal is proposed as the underlying foundation of well-being. Weal stands for the totality of socialised reality as framing well-being for the individual beyond the possibility of deliberate choice. The descriptive approach to weal, mapping it under the guidance of discrete scientific disciplines reveals a limited set of cardinal aspects, labeled here the cardinal needs. Cardinal expresses the fundamental reorientation weal can bring about, needs deliver the sense of sine qua non. Weal is conceived as a oneness mapped along eight cardinal needs. The needs, approached as aspects instead of analytically isolated factors do not require mutually exclusive definitions. To serve the purpose of reorientation, weal is operationalised as a domain in multidimensional space, each dimension encompassing an optimal level of availability of the fundamental satisfiers between the extremes of drastic insufficiency and harmful excess, ensured by actual human effort. Weal seeks balance among the material and social aspects of human being while allows for cultural and individual uniqueness in attaining human flourishing.

Keywords: human well-being, development, economic theory, human needs

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Authors: Salima Smiti, Ines Gasmi, Makram Soui

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Credit risk is the most important issue for financial institutions. Its assessment becomes an important task used to predict defaulter customers and classify customers as good or bad payers. To this objective, numerous techniques have been applied for credit risk assessment. However, to our knowledge, several evaluation techniques are black-box models such as neural networks, SVM, etc. They generate applicants’ classes without any explanation. In this paper, we propose to assess credit risk using rules classification method. Our output is a set of rules which describe and explain the decision. To this end, we will compare seven classification algorithms (JRip, Decision Table, OneR, ZeroR, Fuzzy Rule, PART and Genetic programming (GP)) where the goal is to find the best rules satisfying many criteria: accuracy, sensitivity, and specificity. The obtained results confirm the efficiency of the GP algorithm for German and Australian datasets compared to other rule-based techniques to predict the credit risk.

Keywords: credit risk assessment, classification algorithms, data mining, rule extraction

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Authors: Khalil Abdullah Ahmed Khalil, Elsadig Mohamed Ahmed

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Extracts of various plants material capable of decreasing blood sugar have been tested in experimental animal models and their effects confirmed. Neem or Margose (Azadirachta Indica) is an indigenous plant believed to have antiviral, antifungal, antidiabetic and many other properties. This paper deals with a comparative study of the effect of aqueous Neem leaves extract alone or in combination with glibenclamide on alloxan diabetic rabbits. Administration of crude aqueous Neem extract (CANE) alone (1.5 ml/kg/day), as well as the combination of CANE (1.5 ml/kg/day) with glibenclamide (0.25 mg/kg/day) significantly, decreased (P<0.05) the concentrations of serum lipids, blood glucose and lipoprotein VLDL(very low-density lipoproteins) and LDL(low-density lipoproteins) but significantly increased (P<0.05) the concentration of HDL(high-density lipoprotein). The change was observed significantly greater when the treatment was given in combination of CANE and glibenclamid than with CANE alone.

Keywords: neem, hypoglycemic, hypolipidemic, cholesterol

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Authors: G. Santamato, M. Solazzi, A. Frisoli

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Systems for detection of damages in railway pantographs effectively reduce the cost of maintenance and improve time scheduling. In this paper, we present an approach to design a monitoring tool fitting strong customer requirements such as portability and ease of use. Pantograph has been modeled to estimate its dynamical properties, since no data are available. With the aim to focus on suspensions health, a two Degrees of Freedom (DOF) scheme has been adopted. Parameters have been calculated by means of analytical dynamics. A Finite Element Method (FEM) modal analysis verified the former model with an acceptable error. The detection strategy seeks phase-plots topology alteration, induced by defects. In order to test the suitability of the method, leakage in the dashpot was simulated on the lumped model. Results are interesting because changes in phase plots are more appreciable than frequency-shift. Further calculations as well as experimental tests will support future developments of this smart strategy.

Keywords: pantograph models, phase plots, structural health monitoring, damage detection

Procedia PDF Downloads 363

Authors: Dua K. S. Y. Klaas, Monzur A. Imteaz, Ika Sudiayem, Elkan M. E. Klaas, Eldav C. M. Klaas

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Properly selecting the most suitable and effective geostatistics method in the parameterization step of groundwater modeling is critical to attain a satisfactory model. In this paper, two geostatistics methods, i.e., Grid-Based Pilot Point (GB-PP) and Head-Zonation Based Pilot Point (HZB-PP) methods, were applied in an eogenetic karst catchment and compared using as model performances and computation time the criteria. Overall, the results show that appropriate selection of method is substantial in the parameterization of physically-based groundwater models, as it influences both the accuracy and simulation times. It was found that GB-PP method performed comparably superior to HZB-PP method. However, reflecting its model performances, HZB-PP method is promising for further application in groundwater modeling.

Keywords: groundwater model, geostatistics, pilot point, parameterization step

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Authors: Sarita Agarwal, Deepika Delsa Dean

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Like the task of transferring photo images to artistic images, image-to-image translation aims to translate the data to the imitated data which belongs to the target domain. Neural Style Transfer and CycleGAN are two well-known deep learning architectures used for photo image-to-art image transfer. However, studies involving these two models concentrate on one-to-one domain translation, not one-to-multi domains translation. Our study tries to investigate deep learning architectures, which can be controlled to yield multiple artistic style translation only by adding a conditional vector. We have expanded CycleGAN and constructed Conditional CycleGAN for 5 kinds of categories translation. Our study found that the architecture inserting conditional vector into the middle layer of the Generator could output multiple artistic images.

Keywords: genetic counseling, FMR1 gene, fragile x-associated primary ovarian insufficiency, premutation

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Authors: Shih-Pin Chen, Shih-Syuan You

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This study proposes a regression model with flexible spreads for fuzzy input-output data to cope with the situation that the existing measures cannot reflect the actual estimation error. The main idea is that a dissemblance index (DI) is carefully identified and defined for precisely measuring the actual estimation error. Moreover, the graded mean integration (GMI) representation is adopted for determining more representative numeric regression coefficients. Notably, to comprehensively compare the performance of the proposed model with other ones, three different criteria are adopted. The results from commonly used test numerical examples and an application to Taiwan's business monitoring indicator illustrate that the proposed dissemblance index method not only produces valid fuzzy regression models for fuzzy input-output data, but also has satisfactory and stable performance in terms of the total estimation error based on these three criteria.

Keywords: dissemblance index, forecasting, fuzzy sets, linear regression

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Authors: Mahadehe Hassan

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Transport system and industries which are the main basis of industrial and socio-economic development of any country. It is mainly dependent on fossil fuels. Bangladesh has fossil fuel reserves of 9.51 TCF as of July 2023, and if no new gas fields are discovered in the next 7-9 years and if the existing gas consumption rate continues, the fossil fuel reserves will be exhausted. The demand for petroleum products in Bangladesh is increasing steadily, with 63% imported by BPC and 37% imported by private companies. 61.61% of BPC imported products are used in the transport sector and 5.49% in the industrial sector, which is expensive and harmful to the environment. Liquefied Petroleum Gas (LPG) should be considered as an alternative energy for Bangladesh based on Sustainable Development Goals (SDGs) criteria for sustainable, clean and affordable energy. This will not only lead to the much desired mitigation of energy famine in the country but also contribute favorably to the macroeconomic indicators. Considering the environmental and economic issues, the government has referred to CNG (compressed natural gas) as the fuel carrier since 2000, but currently due to the decline mode of gas reserves, the government of Bangladesh is thinking of new energy sources for transport and industrial sectors which will be sustainable, environmentally friendly and economically viable. Liquefied Petroleum Gas (LPG) is the best choice for fueling transport and industrial sectors in Bangladesh. At present, a total of 1.54 million metric tons of liquefied petroleum gas (LPG) is marketed in Bangladesh by the public and private sectors. 83% of it is used by households, 12% by industry and commerce and 5% by transportation. Industrial and transport sector consumption is negligible compared to household consumption. So the purpose of the research is to find out the challenges of LPG market development in transport and industrial sectors in Bangladesh and make recommendations to reduce the challenges. Secure supply chain, inadequate infrastructure, insufficient investment, lack of government monitoring and consumer awareness in the transport sector and industrial sector are major challenges for LPG market development in Bangladesh. Bangladesh government as well as private owners should come forward in the development of liquefied petroleum gas (LPG) industry to reduce the challenges of secure energy sector for sustainable development. Furthermore, ensuring adequate Liquefied Petroleum Gas (LPG) supply in Bangladesh requires government regulations, infrastructure improvements in port areas, awareness raising and most importantly proper pricing of Liquefied Petroleum Gas (LPG) to address the energy crisis in Bangladesh.

Keywords: transportand industries fuel, LPG consumption, challenges, economical sustainability

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Authors: Ferzat Anka

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Many types of problems can be solved using traditional analytical methods. However, these methods take a long time and cause inefficient use of resources. In particular, different approaches may be required in solving complex and global engineering problems that we frequently encounter in real life. The bigger and more complex a problem, the harder it is to solve. Such problems are called Nondeterministic Polynomial time (NP-hard) in the literature. The main reasons for recommending different metaheuristic algorithms for various problems are the use of simple concepts, the use of simple mathematical equations and structures, the use of non-derivative mechanisms, the avoidance of local optima, and their fast convergence. They are also flexible, as they can be applied to different problems without very specific modifications. Thanks to these features, it can be easily embedded even in many hardware devices. Accordingly, this approach can also be used in trend application areas such as IoT, big data, and parallel structures. Indeed, the metaheuristic approaches are algorithms that return near-optimal results for solving large-scale optimization problems. This study is focused on the new metaheuristic method that has been merged with the chaotic approach. It is based on the chaos theorem and helps relevant algorithms to improve the diversity of the population and fast convergence. This approach is based on Chimp Optimization Algorithm (ChOA), that is a recently introduced metaheuristic algorithm inspired by nature. This algorithm identified four types of chimpanzee groups: attacker, barrier, chaser, and driver, and proposed a suitable mathematical model for them based on the various intelligence and sexual motivations of chimpanzees. However, this algorithm is not more successful in the convergence rate and escaping of the local optimum trap in solving high-dimensional problems. Although it and some of its variants use some strategies to overcome these problems, it is observed that it is not sufficient. Therefore, in this study, a newly expanded variant is described. In the algorithm called Ex-ChOA, hybrid models are proposed for position updates of search agents, and a dynamic switching mechanism is provided for transition phases. This flexible structure solves the slow convergence problem of ChOA and improves its accuracy in multidimensional problems. Therefore, it tries to achieve success in solving global, complex, and constrained problems. The main contribution of this study is 1) It improves the accuracy and solves the slow convergence problem of the ChOA. 2) It proposes new hybrid movement strategy models for position updates of search agents. 3) It provides success in solving global, complex, and constrained problems. 4) It provides a dynamic switching mechanism between phases. The performance of the Ex-ChOA algorithm is analyzed on a total of 8 benchmark functions, as well as a total of 2 classical and constrained engineering problems. The proposed algorithm is compared with the ChoA, and several well-known variants (Weighted-ChoA, Enhanced-ChoA) are used. In addition, an Improved algorithm from the Grey Wolf Optimizer (I-GWO) method is chosen for comparison since the working model is similar. The obtained results depict that the proposed algorithm performs better or equivalently to the compared algorithms.

Keywords: optimization, metaheuristic, chimp optimization algorithm, engineering constrained problems

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Authors: Salami Akeem Olanrewaju

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The transportation models or problems are primarily concerned with the optimal (best possible) way in which a product produced at different factories or plants (called supply origins) can be transported to a number of warehouses or customers (called demand destinations). The objective in a transportation problem is to fully satisfy the destination requirements within the operating production capacity constraints at the minimum possible cost. The objective of this study is to determine ways of minimizing transport cost in order to maximum profit. Data were gathered from the records of the Distribution Department of 7-Up Bottling Company Plc. Ilorin, Kwara State, Nigeria. The data were analyzed using SPSS (Statistical Package for Social Sciences) while applying the three methods of solving a transportation problem. The three methods produced the same results; therefore, any of the method can be adopted by the company in transporting its final products to the wholesale dealers in order to minimize total production cost.

Keywords: cost minimization, resources utilization, distribution system, allocation problem

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Authors: Opeyemi A. Oyewo, Seshibe Makgato

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This paper presents the synthesis, characterization, and application of pelletized chitosan immobilized sawdust cellulose nanocrystals (PCCN) in a fixed-bed column for the continuous adsorption of methyl blue (MB) from water. The product was characterized using FT-IR, XRD, and SEM analysis. Microstructural examination revealed that the pellets are porous and spherical. XRD examination revealed phases that can be attributed to the presence of chitosan in PCCN. The effects of starting concentration, bed depth, and flow rate on synthetic water were explored. To identify MB breakthrough behaviour, performance indices such as bed volume, adsorbent exhaustion rate, and service time were investigated. Furthermore, the breakthrough data were incorporated into both the Thomas and Bohart-Adams models. The Thomas model was suitable for describing MB breakthrough curves. However, more research with diverse water matrices may be required to assess the resilience of PCCN.

Keywords: adsorption, dynamic, methyl blue, pelletization

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Authors: Mohamed M. El Gendy, Ibrahim A. El Arabi, Rafeek W. Abdel-Missih, Omar A. Kandil

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Nonlinear analysis is one of the most important design and safety tools in structural engineering. Based on the finite-element method, a geometrical and material nonlinear analysis of large span reinforced concrete arches is carried out considering soil-structure interaction. The concrete section details and reinforcement distribution are taken into account. The behavior of soil is considered via Winkler's and continuum models. A computer program (NARC II) is specially developed in order to follow the structural behavior of large span reinforced concrete arches up to failure. The results obtained by the proposed model are compared with available literature for verification. This work confirmed that the geometrical and material nonlinearities, as well as soil structure interaction, have considerable influence on the structural response of reinforced concrete arches.

Keywords: nonlinear analysis, reinforced concrete arched structure, soil-structure interaction, geotechnical engineering

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Authors: Francis C. Emejeamara, Alison S. Tomlin, James Gooding

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Due to the highly turbulent nature of urban air flows, and by virtue of the fact that turbines are likely to be located within the roughness sublayer of the urban boundary layer, proposed urban wind installations are faced with major challenges compared to rural installations. The challenge of operating within turbulent winds can however, be counteracted by the development of suitable gust tracking solutions. In order to assess the cost effectiveness of such controls, a detailed understanding of the urban wind resource, including its turbulent characteristics, is required. Estimating the ambient turbulence and total kinetic energy available at different control response times is essential in evaluating the potential performance of wind systems within the urban environment should effective control solutions be employed. However, high resolution wind measurements within the urban roughness sub-layer are uncommon, and detailed CFD modelling approaches are too computationally expensive to apply routinely on a city wide scale. This paper therefore presents an alternative semi-empirical methodology for estimating the excess energy content (EEC) present in the complex and gusty urban wind. An analytical methodology for predicting the total wind energy available at a potential turbine site is proposed by assessing the relationship between turbulence intensities and EEC, for different control response times. The semi-empirical model is then incorporated with an analytical methodology that was initially developed to predict mean wind speeds at various heights within the built environment based on detailed mapping of its aerodynamic characteristics. Based on the current methodology, additional estimates of turbulence intensities and EEC allow a more complete assessment of the available wind resource. The methodology is applied to 4 UK cities with results showing the potential of mapping turbulence intensities and the total wind energy available at different heights within each city. Considering the effect of ambient turbulence and choice of wind system, the wind resource over neighbourhood regions (of 250 m uniform resolution) and building rooftops within the 4 cities were assessed with results highlighting the promise of mapping potential turbine sites within each city.

Keywords: excess energy content, small-scale wind, turbulence intensity, urban wind energy, wind resource assessment

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Authors: Arezou Javadi

Abstract:

The use of algorithmic models dependent on software calculations and simulation of new government management assays with the help of specialized software had increased the productivity and efficiency of the government management system recently. This has caused the management approach to change from the old bitch & fix model, which has low efficiency and less usefulness, to the capable management model with higher efficiency called the partnership with resident model. By using Govpilot TM software, the relationship between people in a system and the government was examined. The method of two tailed interaction was the outsourcing of a goal in a system, which is formed in the order of goals, qualified executive people, optimal executive model, and finally, summarizing additional activities at the different statistical levels. The results showed that the participation of people in a financial implementation system with a statistical potential of P≥5% caused a significant increase in investment and initial capital in the government system with maximum implement project in a smart government.

Keywords: machine learning, financial income, statistical potential, govpilot

Procedia PDF Downloads 88

Authors: Arezou Javadi

Abstract:

The use of algorithmic models dependent on software calculations and simulation of new government management assays with the help of specialized software had increased the productivity and efficiency of the government management system recently. This has caused the management approach to change from the old bitch & fix model, which has low efficiency and less usefulness, to the capable management model with higher efficiency called the partnership with resident model. By using Govpilot TM software, the relationship between people in a system and the government was examined. The method of two tailed interaction was the outsourcing of a goal in a system, which is formed in the order of goals, qualified executive people, optimal executive model, and finally, summarizing additional activities at the different statistical levels. The results showed that the participation of people in a financial implementation system with a statistical potential of P≥5% caused a significant increase in investment and initial capital in the government system with maximum implement project in a smart government.

Keywords: machine learning, financial income, statistical potential, govpilot

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Authors: Weng Jiantao, Wu Yiqun

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The efficiency of natural ventilation, wind pressure distribution on building surface, wind comfort for pedestrians and buildings’ wind tolerance in traditional settlements are closely related to the pattern of terrain. On the basis of field research on the typical island terrain in China, the physical and mathematical models are established by using CFD software, and then the simulation results of the wind field are exported. We discuss the relationship between wind direction and wind field results. Furthermore simulation results are imported into ArcGIS platform. The evaluation model of island site selection is established with considering slope factor. We realize the visual model of site selection on complex island terrain. The multi-plans of certain residential are discussed based on wind simulation; at last the optimal project is selected. Results can provide the theory guidance for settlement planning and construction in China's traditional island.

Keywords: CFD, island terrain, site selection, construction mechanism

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Authors: Changqiao Wu, Guoqing Ding, Xin Chen

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In this paper, ways of modeling dynamic measurement systems are discussed. Specially, for linear system with single-input single-output, it could be modeled with shallow neural network. Then, gradient based optimization algorithms are used for searching the proper coefficients. Besides, method with normal equation and second order gradient descent are proposed to accelerate the modeling process, and ways of better gradient estimation are discussed. It shows that the mathematical essence of the learning objective is maximum likelihood with noises under Gaussian distribution. For conventional gradient descent, the mini-batch learning and gradient with momentum contribute to faster convergence and enhance model ability. Lastly, experimental results proved the effectiveness of second order gradient descent algorithm, and indicated that optimization with normal equation was the most suitable for linear dynamic models.

Keywords: dynamic system modeling, neural network, normal equation, second order gradient descent

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Authors: Khaoula Hidouri, Ali Benhmidene, Bechir Chouachi, Dhananjay R. Mishra, Ammar Houas

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Activated carbon DSAC36-24 iy is adsorbent materials, characterized by a specific surface area of 548.13 m²g⁻¹. Their manufacture uses the natural raw materials like the nucleus of dates. In this study the treatment is done in two stages: A chemical treatment by H₃PO₄ followed by a physical treatment under nitrogen for 1 hour then under stream of CO₂ for 24 hours. A characterization of the various parameters was determined such as the measurement of the specific surface area, determination of pHPZC, bulk density, iodine value. The study of the adsorption of organic molecules (hydroquinone, paranitrophenol, 2,4-dinitrophenol, 2,4,6-trinitrophenol) indicates that the adsorption phenomena are essentially due to the van der Waals interaction. In the case of organic molecules carrying the polar substituents, the existence of hydrogen bonds is also proved by the donor-acceptor forces. The study of the pH effect was done with modeling by different models (Langmuir, Freundlich, Langmuir-Freundlich, Redlich-Peterson), a kinetic treatment is also followed by the application of Lagergren, Weber, Macky.

Keywords: adsoprtion ishoterms, adsorption kinetics, DSAC36-24, organic molecule

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Authors: Saba Rahimi, Ozan Oktay, Javier Alvarez-Valle, Sujeeth Bharadwaj

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Successful application of deep learning in medical image analysis necessitates unprecedented amounts of labeled training data. Unlike conventional 2D applications, radiological images can be three-dimensional (e.g., CT, MRI), consisting of many instances within each image. The problem is exacerbated when expert annotations are required for effective pixel-wise labeling, which incurs exorbitant labeling effort and cost. Active learning is an established research domain that aims to reduce labeling workload by prioritizing a subset of informative unlabeled examples to annotate. Our contribution is a cost-effective approach for U-Net 3D models that uses Monte Carlo sampling to analyze pixel-wise uncertainty. Experiments on the AAPM 2017 lung CT segmentation challenge dataset show that our proposed framework can achieve promising segmentation results by using only 42% of the training data.

Keywords: image segmentation, active learning, convolutional neural network, 3D U-Net

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Authors: R. Monteiro, A. Abarca

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Large scale seismic risk assessment has become increasingly popular to evaluate the physical vulnerability of a given region to seismic events, by putting together hazard, exposure and vulnerability components. This study, developed within the scope of the EU-funded project ITERATE (Improved Tools for Disaster Risk Mitigation in Algeria), explains the steps and expected results for the development of an integrated seismic risk model for assessment of the vulnerability of residential buildings in Northern Algeria. For this purpose, the model foresees the consideration of an updated seismic hazard model, as well as ad-hoc exposure and physical vulnerability models for local residential buildings. The first results of this endeavor, such as the hazard model and a specific taxonomy to be used for the exposure and fragility components of the model are presented, using as starting point the province of Blida, in Algeria. Specific remarks and conclusions regarding the characteristics of the Northern Algerian in-built are then made based on these results.

Keywords: Northern Algeria, risk, seismic hazard, vulnerability

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Authors: M. Kharazmi, M. Zakeri, M. Packirisamy, J. Faraji

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Micro/Nanorobotics or manipulation of nanoparticles by Atomic Force Microscopic (AFM) is one of the most important solutions for controlling the movement of atoms, particles and micro/nano metrics components and assembling of them to design micro/nano-meter tools. Accurate modelling of manipulation requires identification of forces and mechanical knowledge in the Nanoscale which are different from macro world. Due to the importance of the adhesion forces and the interaction of surfaces at the nanoscale several friction models were presented. In this research, friction and normal forces that are applied on the AFM by using of the dynamic bending-torsion model of AFM are obtained based on Hurtado-Kim friction model (HK), Johnson-Kendall-Robert contact model (JKR) and Greenwood-Williamson roughness model (GW). Finally, the effect of standard deviation of asperities height on the normal load, friction force and friction coefficient are studied.

Keywords: atomic force microscopy, contact model, friction coefficient, Greenwood-Williamson model

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Authors: Mohammad Sadegh Narges, Zahra Ghadampour

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Due to the specific condition, offshore pipelines are given careful consideration and care in both design and operation. Most of the offshore pipeline flows are multi-phase. Multi-phase flows construct different pattern or flow regimes (in simultaneous gas-liquid flow, flow regimes like slug flow, wave and …) under different circumstances. One of the influencing factors on the flow regime is the pipeline roughness value. So far, roughness value influences and the sensitivity of the present models to this parameter have not been taken into consideration. Therefore, roughness value influences on the flow regimes in offshore pipelines are discussed in this paper. Results showed that geometry, absolute pipeline roughness value (materials that the pipeline is made of) and flow phases prevailing the system are of the influential parameters on the flow regimes prevailing multi-phase pipelines in a way that a change in any of these parameters results in a change in flow regimes in all or part of the pipeline system.

Keywords: absolute roughness, flow regime, multi-phase flow, offshore pipelines

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Authors: Ying Yuken, Pengfei Wang, Zhang Qilin, Xiao Ben

Abstract:

Based on the main entrance and garden area (ME&G) project of Shanghai Disneyland, this paper introduces the application of BIM technology in this kind of low-rise comprehensive building with complex facade system, electromechanical system and decoration system. BIM technology is applied to the whole process of design, construction and completion of the whole project. With the construction of BIM application framework of the whole project, the key points of BIM modeling methods of different systems and the integration and coordination of BIM models are elaborated in detail. The specific application methods of BIM technology in similar complex low-rise building projects are sorted out. Finally, the paper summarizes the benefits of BIM technology application, and puts forward some suggestions for BIM management mode and practical application of similar projects in the future.

Keywords: BIM, complex low-rise building, BIM modeling, model integration and coordination, 3D scanning

Procedia PDF Downloads 172

Authors: Abigail Wiafe, Charles Nutrokpor, Adelaide Oduro-Asante

Abstract:

The advancement of technology is rapidly making people more receptive to music as computer-generated music requires minimal human interventions. Though algorithms are applied to generate music, the human experience of emotions is still explored. Thus, this study investigates the emotions humans experience listening to computer-generated music that possesses aesthetic qualities. Forty-two subjects participated in the survey. The selection process was purely arbitrary since it was based on convenience. Subjects listened and evaluated the emotions experienced from the computer-generated music through an online questionnaire. The Likert scale was used to rate the emotional levels after the music listening experience. The findings suggest that computer-generated music possesses aesthetic qualities that do not affect subjects' emotions as long as they are pleased with the music. Furthermore, computer-generated music has unique creativity, and expressioneven though the music produced is meaningless, the computational models developed are unable to present emotional contents in music as humans do.

Keywords: aesthetic, algorithms, emotions, computer-generated music

Procedia PDF Downloads 136

Authors: Dejan Tanikić, Miodrag Manić, Jelena Đoković, Saša Kalinović

Abstract:

This paper deals with the determination of the optimum machining parameters, according to the measured and modelled data of the cutting temperature and surface roughness, during the turning of the AISI 4140 steel. The high cutting temperatures are unwanted occurences in the metal cutting process. They impact negatively on the quality of the machined part. The machining experiments were performed using different cutting regimes (cutting speed, feed rate and depth of cut), with different values of the workpiece hardness, which causes different values of the measured cutting temperature as well as the measured surface roughness. The temperature and surface roughness data were modelled after that using Response Surface Methodology (RSM). The obtained RSM models are used in the process of optimization of the cutting regimes using the Genetic Algorithms (GA) tool, which enables the metal cutting process in the optimum conditions.

Keywords: genetic algorithms, machining parameters, response surface methodology, turning process

Procedia PDF Downloads 188

Authors: Md. Abdul Karim, Syed Imran Ahmed, Pandora T. Hardtman

Abstract:

Informed consent is one of the basic human and ethical rights for childbearing women. It plays a central role in promoting informed decision making between patients and service providers during the labor process. It gives mothers rights to accept or reject any examination and/or procedure, increases the respect and dignity of the mother during pregnancy, delivery and postpartum care. To assess the practices of this right during normal vaginal delivery and immediate postpartum care in tertiary level hospital setting in Bangladesh, a quantitative study with cross-sectional design was conducted in Dhaka Medical College & Hospital (DMCH) and Sir Salimullah Medical College & Mitford Hospital (SSMCH) in Dhaka in November 2015. A prevalence-based sample size of 190 was calculated where prevalence, confidence interval and level of significance were at 9.7%, 98% and 5% respectively. The respondents were the mothers who gave normal vaginal childbirth within past 24 hours and received postpartum care there. They were selected through systematic random sampling technique and their face-to-face interview of 190 mothers was done using a structured questionnaire. Data were entered into the spreadsheet (MS Excel 2013 version) and descriptive analysis of findings was done. The result shows the complete absence of informed consent practices and mostly absence of consented care such as right to information, respect for choices of preferences for examination and/or procedure of childbearing women. Although 95% of the mothers were informed that they were being proceeded with normal vaginal delivery, their choice of preference was absent during the process. Only consent (not informed consent) was taken from 50%-72% mothers for examination (except breast examination ‘0%’) and 8%-83% for any procedures during postpartum care. Only one-ninth (11%) of the mothers could ask service providers regarding the services they received. No consent was taken from 3% of the mothers- neither in the labor process nor in postpartum care. This current practice doesn’t comply with the Respectful Maternity Care (RMC) Charter 2011. The issue is not even clarified in the current Standard Clinical Management Protocols of the country. So, improvement of the existing protocol and increased awareness are essential to address this right of child-bearing women and to practice it during normal vaginal delivery and postpartum care.

Keywords: informed consent, normal vaginal delivery, respectful maternity care, tertiary level hospital

Procedia PDF Downloads 158