Search results for: performance prism model

Authors: Farhan Aljuaidi

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The rapid expansion of Alkarj city, Saudi Arabia, towards the outlet of Wadi AlAin is critical for the planners and decision makers. Nowadays, two major projects such as Salman bin Abdulaziz University compound and new industrial area are developed in this flood prone area where no channels are clear and identified. The main contribution of this study is to divert the flow away from these vital projects by reconstructing new channels. To do so, Lidar data were used to generate contour lines for the actual elevation of the highways and local roads. These data were analyzed and compared to the contour lines derived from the topographical maps 1:50.000. The magnitude of the expected flow was estimated using Snyder's Model based on the morphometric data acquired by DEM of the catchment area. The results indicate that maximum discharge peak reaches 2694,3 m3/sec, the mean is 303,7 m3/sec and the minimum is 74,3 m3/sec. The runoff was estimated at 252,2. 610 m3/s, the mean is 41,5. 610 m3/s and the minimum is 12,4. 610 m3/s.

Keywords: Desert flood, Saudi Arabia, Snyder's Model, flow estimation

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Authors: Marcello De Falco, Gianluca Natrella, Mauro Capocelli

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CO₂ capture and utilization (CCU) is a promising approach to reduce GHG(greenhouse gas) emissions. Many technologies in this field are recently attracting attention. However, since CO₂ is a very stable compound, its utilization as a reagent is energetic intensive. As a consequence, it is unclear whether CCU processes allow for a net reduction of environmental impacts from a life cycle perspective and whether these solutions are sustainable. Among the tools to apply for the quantification of the real environmental benefits of CCU technologies, exergy analysis is the most rigorous from a scientific point of view. The exergy of a system is the maximum obtainable work during a process that brings the system into equilibrium with its reference environment through a series of reversible processes in which the system can only interact with such an environment. In other words, exergy is an “opportunity for doing work” and, in real processes, it is destroyed by entropy generation. The exergy-based analysis is useful to evaluate the thermodynamic inefficiencies of processes, to understand and locate the main consumption of fuels or primary energy, to provide an instrument for comparison among different process configurations and to detect solutions to reduce the energy penalties of a process. In this work, the exergy analysis of a process for the production of Dimethyl Ether (DME) from green hydrogen generated through an electrolysis unit and pure CO₂ captured from flue gas is performed. The model simulates the behavior of all units composing the plant (electrolyzer, carbon capture section, DME synthesis reactor, purification step), with the scope to quantify the performance indices based on the II Law of Thermodynamics and to identify the entropy generation points. Then, a plant optimization strategy is proposed to maximize the exergy efficiency.

Keywords: green DME production, exergy analysis, energy penalties, exergy efficiency

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Authors: Preeti Gacche

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A considerable part of undergraduate level English Examination papers is devoted to grammar. Hence the grammar questions in the question papers are evaluated and the opinions of both students and teachers about them are obtained and analyzed. A grammar test of 100 marks is administered to 43 students to check their performance. The question papers have been evaluated by 10 different teachers and their scores compared. The analysis of 38 University question papers reveals that on an average 20 percent marks are allotted to grammar. Almost all the grammar topics are tested. Abundant use of grammatical terminology is observed in the questions. Decontextualization, repetition, possibility of multiple correct answers and grammatical errors in framing the questions have been observed. Opinions of teachers and students about grammar questions vary in many respects. The students responses are analyzed medium-wise and sex-wise. The Medium at the School level and the sex of the students are found to play no role as far as interest in the study of grammar is concerned. English medium students solve grammar questions intuitively whereas non-English medium students are required to recollect the rules of grammar. Prepositions, Verbs, Articles and Model auxiliaries are found to be easy topics for most students whereas the use of conjunctions is the most difficult topic. Out of context items of grammar are difficult to answer in comparison with contextualized items of grammar. Hence contextualized texts to test grammar items are desirable. No formal training in setting questions is imparted to teachers by the competent authorities like the University. They need to be trained in testing. Statistically there is no significant change of score with the change in the rater in testing of grammar items. There is scope of future improvement. The question papers need to be evaluated and feedback needs to be obtained from students and teachers for future improvement.

Keywords: context, evaluation, grammar, tests

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Authors: Yung-Jin Weng, Chia-Chi Chang, Chun-Yu Tsai

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This paper is focused on the research of imprinting and replica molding of quasi-grey scale soft mold curved surface microstructure mold. In this paper, a magnetic photocuring forming system is first developed and built independently, then the magnetic curved surface microstructure soft mode is created; moreover, the magnetic performance of the magnetic curved surface at different heights is tested and recorded, and through experimentation and simulation, the magnetic curved surface microstructure soft mold is used in the research of quasi-grey scale soft mold curved surface microstructure imprinting and replica molding. The experimental results show that, under different surface curvatures and voltage control conditions, different quasi-grey scale array microstructures take shape. In addition, this paper conducts research on the imprinting and replica molding of photoresist composite magnetic powder in order to discuss the forming performance of magnetic photoresist, and finally, the experimental result is compared with the simulation to obtain more accurate prediction and results. This research is predicted to provide microstructure component preparation technology with heterogeneity and controllability, and is a kind of valid shaping quasi-grey scale microstructure manufacturing technology method.

Keywords: soft mold, magnetic, microstructure, curved surface

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Authors: Indu Saini, Ashu Khanna, S. K. Peddoju

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Cloud computing is the new buzz word today attracting high interest among various domains like business enterprises, Particularly in Small and Medium Enterprises. As it is a pay-per-use model, SMEs have high expectations that adapting this model will not only make them flexible, hassle-free but also economic. In view of such expectations, this paper analyses the possibility of adapting cloud computing technologies in SMEs in light of economic concerns. In this paper, two hypotheses are developed to compare the average annual per-user costs of using Enterprise Resource Planning systems in two ways, The traditional approach and the cloud approach. A web based survey is conducted apart from the Interviews with the peers to collect the data across the selected SMEs and t-test is performed to compare both the technologies on the proposed hypothesis. Results achieved are produced and discussed.

Keywords: cloud computing, small and medium enterprises, enterprise resource solutions, interviews

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Authors: Bawadi M. A., Abbad J. A., Baras E. A.

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This study was conducted to assess wind energy resources in the area of Al-Adwas Ras-Huwirah Hadhramout Governorate, Yemen, through using statistical calculations, the Weibull model and SPSS program were used in the monthly and the annual to analyze the wind energy resource; the convergence of wind energy; turbine efficiency in the selected area. Wind speed data was obtained from NASA over a period of ten years (2010-2019) and at heights of 50 m above ground level. Probability distributions derived from wind data and their distribution parameters are determined. The density probability function is fitted to the measured probability distributions on an annual basis. This study also involves locating preliminary sites for wind farms using Geographic Information System (GIS) technology. This further leads to maximizing the output energy from the most suitable wind turbines in the proposed site.

Keywords: wind speed analysis, Yemen wind energy, wind power density, Weibull distribution model

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Authors: Min Wei

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Objectives: Experience tourism represents an advanced stage of tourism compared with sightseeing tourism and relaxation tourism. Experience tourism reflects the full respect of experience economy to the human natures. This paper chose one of the most popular ocean tourism products in Zhoushan, as a subject and investigated the constructive elements in tourist experience based on the needs of tourists. Methods: This paper started with the influences of tourism product innovation on tourist experience, then proposed a model of the relationship between tourist experience, tourist satisfaction, and the following behavior of tourists, and concluded that tourist experience improves tourist satisfaction and thereby enhances tourist loyalty based on the developmental pathway of experience tourism. To ensure the accuracy of the collected data of the research results, the sample of this questionnaire survey is chosen by the method of occasional sampling, combined with the judgment of the investigators and the convenience of the questionnaire survey, the survey objects are selected from the scenic spots of Putuo Mountain, Zhujiajian, Taohua Island, waiting room of passenger terminal, etc. Before filling in the questionnaire, the author and the respondents have a short communication. On the premise that the respondents can fully understand the purpose and content of the questionnaire, tourists fill in the questionnaire independently and collect it on the spot. Results: The research results of this paper are mainly embodied in the following aspects: it is concluded that there are many constructive factors of tourists' experience in Zhoushan tourism products. Based on Zhoushan tourism products, this paper explores the constructive factors of tourists' experience in Zhoushan tourism products from three aspects: attracting object experience, facility experience and service experience. At present, there are still big differences between Zhoushan tourism products, tourists’ expectations and tourists' experience, mainly in the aspects of transportation, publicity and tour guide service. Corresponding measures should be taken to improve tourists' experience quality and satisfaction. Conclusions: The influence factors of island tourism products are discriminated, and established a structural model of tourist experience, which includes three basic elements: attractions, facilities, and services. This model was further verified by questionnaires and analyses in Putuo Shan, Zhujia Jian, and Taohua Island. Finally, we combined this model and made some suggestions on boost the satisfaction of Zhoushan islands.

Keywords: experience tourism, tourists’ expectations, tourists' experience, tourism products

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Authors: Anny Zambrano, German Gonzalez, Yair Quintero

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The continuum damage concept is used to study the interaction between hydraulic fractures and natural fractures, the objective is representing the path and relation among this two fractures types and predict its complex behavior without the need to pre-define their direction as occurs in other finite element applications, providing results more consistent with the physical behavior of the phenomenon. The approach uses finite element simulations through Abaqus software to model damage fracturing, the fracturing process by damage propagation in a rock. The modeling the phenomenon develops in two dimensional (2D) so that the fracture will be represented by a line and the crack front by a point. It considers nonlinear constitutive behavior, finite strain, time-dependent deformation, complex boundary conditions, strain hardening and softening, and strain based damage evolution in compression and tension. The complete governing equations are provided and the method is described in detail to permit readers to replicate all results. The model is compared to models that are published and available. Comparisons are focused in five interactions between natural fractures (NF) and hydraulic fractures: Fractured arrested at NF, crossing NF with or without offset, branching at intersecting NFs, branching at end of NF and NF dilation due to shear slippage. The most significant new finding is, that is not necessary to use pre-defined addresses propagation and stress condition can be evaluated as a dominant factor in the process. This is important because it can model in a more real way the generated complex hydraulic fractures, and be a valuable tool to predict potential problems and different geometries of the fracture network in the process of fracturing due to fluid injection.

Keywords: continuum damage, hydraulic fractures, natural fractures, complex fracture network, stiffness

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Authors: Kveta Olsanova, Gina Cook, Marija Zlatic

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This paper discusses the theoretical framework suggesting the dependencies between luxury brands’ CSR (Corporate Social Responsibility) variables and the purchase intention of luxury shoppers. The framework is based on a literature review and in-depth individual interviews with a sample of luxury users and buyers. The measures of the model are based on existing research and the authors' qualitative research results. The model suggests that purchase intention in the luxury segment is dependent on the luxury values (symbolic, experiential, functional and social), individual sustainable dimension (composed of societal, environmental and economic variables) and awareness of the brand’s CSR, the last two relationships being potentially moderated by certain conditions such as demographics and general attitudes towards CSR and sustainability. The model’s output is in the formulation of several hypotheses, to be tested in an upcoming quantitative study. The qualitative phase indicated that the perceived symbolic, functional and experiential value dimensions of luxury brands were stronger drivers of purchase intention compared to the sustainable dimension. The contribution of the research consists of highlighting CSR’s impact on customer purchase intent as a potential implication for luxury brand management due to two aspects: (i) consumer awareness of the existing CSR activities of luxury brands is low, and this might be challenged by the demands of Gen Z entrants into the lux industry as they are known for their positive approach to CSR; (ii) the UN’s SDGs will bring CSR to the attention of all industries, including currently 'CSR silent' segments represented by luxury. Our research should contribute to incorporation of strategic CSR into the policies and strategies of the luxury segment by providing evidence that luxury customers do care.

Keywords: CSR, luxury shoppers, purchase intention, sustainability

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Authors: Jinesh Kumar Jain, Faishal Pathan

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The concept of sustainable development and effective environmental regulation has led to the emergence of a new field of study and practise that is the Green Supply Chain Management. GSCM has become a subject of great importance for both the developed and developing countries to achieve the desired and much-awaited goals of the firm within the environmental and sustainable framework. Its merits are comprised of good financial pay off and competitiveness to the firms in a long lasting and sustainable manner. The purpose of the paper is to briefly review the recent literature of the GSCM and also determines the new direction area of this emerging field. A detailed study has helped to enlighten the minute details and develop the research direction of the study. The GSCM has gained popularity with both academic and practitioners. The items for the study were developed based on the extent literature. Here we found that the state of adoption of GSCM practices by Indian Firms was still in its infancy, the awareness of environmental sustainability was quite low among consumers and the regulatory frameworks were also lacking in terms promoting environmental sustainability. The present paper is an attempt to emphasize much attention on the above-mentioned issues and present a conclusive summary to make its use widespread and for reaching.

Keywords: environmental management, environmental performance, financial performance, green supply chain management

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Authors: Linjie Zhang, Baifen Ren, Xi Zhang, Genwang Liu

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Ship detection is of great significance for both military and civilian applications. Synthetic aperture radar (SAR) with all-day, all-weather, ultra-long-range characteristics, has been used widely. In view of the low time resolution of low orbit SAR and the needs for high time resolution SAR data, GEO (Geosynchronous orbit) SAR is getting more and more attention. Since GEO SAR has short revisiting period and large coverage area, it is expected to be well utilized in marine ship targets monitoring. However, the height of the orbit increases the time of integration by almost two orders of magnitude. For moving marine vessels, the utility and efficacy of GEO SAR are still not sure. This paper attempts to find the feasibility of GEO SAR by giving a GEO SAR simulator of moving ships. This presented GEO SAR simulator is a kind of geometrical-based radar imaging simulator, which focus on geometrical quality rather than high radiometric. Inputs of this simulator are 3D ship model (.obj format, produced by most 3D design software, such as 3D Max), ship's velocity, and the parameters of satellite orbit and SAR platform. Its outputs are simulated GEO SAR raw signal data and SAR image. This simulating process is accomplished by the following four steps. (1) Reading 3D model, including the ship rotations (pitch, yaw, and roll) and velocity (speed and direction) parameters, extract information of those little primitives (triangles) which is visible from the SAR platform. (2) Computing the radar scattering from the ship with physical optics (PO) method. In this step, the vessel is sliced into many little rectangles primitives along the azimuth. The radiometric calculation of each primitive is carried out separately. Since this simulator only focuses on the complex structure of ships, only single-bounce reflection and double-bounce reflection are considered. (3) Generating the raw data with GEO SAR signal modeling. Since the normal ‘stop and go’ model is not available for GEO SAR, the range model should be reconsidered. (4) At last, generating GEO SAR image with improved Range Doppler method. Numerical simulation of fishing boat and cargo ship will be given. GEO SAR images of different posture, velocity, satellite orbit, and SAR platform will be simulated. By analyzing these simulated results, the effectiveness of GEO SAR for the detection of marine moving vessels is evaluated.

Keywords: GEO SAR, radar, simulation, ship

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Authors: Adriana Postal, Silvio C. Sampaio, Marcio A. Villas Boas, Josué P. Castro

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This study deals with the estimation of reference evapotranspiration (ET₀) in an agricultural context, focusing on efficient irrigation management to meet the growing interest in the sustainable management of water resources. Given the importance of water in agriculture and its scarcity in many regions, efficient use of this resource is essential to ensure food security and environmental sustainability. The methodology used involved the application of artificial intelligence techniques, specifically Multilayer Perceptron (MLP) Artificial Neural Networks (ANNs), to predict ET₀ in the state of Paraná, Brazil. The models were trained and validated with meteorological data from the Brazilian National Institute of Meteorology (INMET), together with data obtained from a producer's weather station in the western region of Paraná. Two optimizers (SGD and Adam) and different meteorological variables, such as temperature, humidity, solar radiation, and wind speed, were explored as inputs to the models. Nineteen configurations with different input variables were tested; amidst them, configuration 9, with 8 input variables, was identified as the most efficient of all. Configuration 10, with 4 input variables, was considered the most effective, considering the smallest number of variables. The main conclusions of this study show that MLP ANNs are capable of accurately estimating ET₀, providing a valuable tool for irrigation management in agriculture. Both configurations (9 and 10) showed promising performance in predicting ET₀. The validation of the models with cultivator data underlined the practical relevance of these tools and confirmed their generalization ability for different field conditions. The results of the statistical metrics, including Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Coefficient of Determination (R²), showed excellent agreement between the model predictions and the observed data, with MAE as low as 0.01 mm/day and 0.03 mm/day, respectively. In addition, the models achieved an R² between 0.99 and 1, indicating a satisfactory fit to the real data. This agreement was also confirmed by the Kolmogorov-Smirnov test, which evaluates the agreement of the predictions with the statistical behavior of the real data and yields values between 0.02 and 0.04 for the producer data. In addition, the results of this study suggest that the developed technique can be applied to other locations by using specific data from these sites to further improve ET₀ predictions and thus contribute to sustainable irrigation management in different agricultural regions. The study has some limitations, such as the use of a single ANN architecture and two optimizers, the validation with data from only one producer, and the possible underestimation of the influence of seasonality and local climate variability. An irrigation management application using the most efficient models from this study is already under development. Future research can explore different ANN architectures and optimization techniques, validate models with data from multiple producers and regions, and investigate the model's response to different seasonal and climatic conditions.

Keywords: agricultural technology, neural networks in agriculture, water efficiency, water use optimization

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Authors: Zahid Ullah, Atlas Khan

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This abstract focuses on the advancements in mathematical modeling and optimization techniques that play a crucial role in enhancing the efficiency, reliability, and performance of these systems. In this era of rapidly evolving technology, mathematical modeling and optimization offer powerful tools to tackle the complex challenges faced by control, signal processing, and energy systems. This abstract presents the latest research and developments in mathematical methodologies, encompassing areas such as control theory, system identification, signal processing algorithms, and energy optimization. The abstract highlights the interdisciplinary nature of mathematical modeling and optimization, showcasing their applications in a wide range of domains, including power systems, communication networks, industrial automation, and renewable energy. It explores key mathematical techniques, such as linear and nonlinear programming, convex optimization, stochastic modeling, and numerical algorithms, that enable the design, analysis, and optimization of complex control and signal processing systems. Furthermore, the abstract emphasizes the importance of addressing real-world challenges in control, signal processing, and energy systems through innovative mathematical approaches. It discusses the integration of mathematical models with data-driven approaches, machine learning, and artificial intelligence to enhance system performance, adaptability, and decision-making capabilities. The abstract also underscores the significance of bridging the gap between theoretical advancements and practical applications. It recognizes the need for practical implementation of mathematical models and optimization algorithms in real-world systems, considering factors such as scalability, computational efficiency, and robustness. In summary, this abstract showcases the advancements in mathematical modeling and optimization techniques for control, signal processing, and energy systems. It highlights the interdisciplinary nature of these techniques, their applications across various domains, and their potential to address real-world challenges. The abstract emphasizes the importance of practical implementation and integration with emerging technologies to drive innovation and improve the performance of control, signal processing, and energy.

Keywords: mathematical modeling, optimization, control systems, signal processing, energy systems, interdisciplinary applications, system identification, numerical algorithms

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Authors: Hussin K. Ragb, Vijayan K. Asari

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In this paper, we present a pedestrian detection descriptor called Fused Structure and Texture (FST) features based on the combination of the local phase information with the texture features. Since the phase of the signal conveys more structural information than the magnitude, the phase congruency concept is used to capture the structural features. On the other hand, the Center-Symmetric Local Binary Pattern (CSLBP) approach is used to capture the texture information of the image. The dimension less quantity of the phase congruency and the robustness of the CSLBP operator on the flat images, as well as the blur and illumination changes, lead the proposed descriptor to be more robust and less sensitive to the light variations. The proposed descriptor can be formed by extracting the phase congruency and the CSLBP values of each pixel of the image with respect to its neighborhood. The histogram of the oriented phase and the histogram of the CSLBP values for the local regions in the image are computed and concatenated to construct the FST descriptor. Several experiments were conducted on INRIA and the low resolution DaimlerChrysler datasets to evaluate the detection performance of the pedestrian detection system that is based on the FST descriptor. A linear Support Vector Machine (SVM) is used to train the pedestrian classifier. These experiments showed that the proposed FST descriptor has better detection performance over a set of state of the art feature extraction methodologies.

Keywords: pedestrian detection, phase congruency, local phase, LBP features, CSLBP features, FST descriptor

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Authors: Vinayambika S. Bhat, S. Shanmuga Priya, I. Thirunavukkarasu, Shreeranga Bhat

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An attempt has been made to design a decoupling controller for systems with more inputs more outputs with dead time in it. The de-coupler is designed for the chemical process industry 3×3 plant transfer function with dead time. The Quantitative Feedback Theory (QFT) based controller has also been designed here for the 2×2 distillation column transfer function. The developed control techniques were simulated using the MATLAB/Simulink. Also, the stability of the process was analyzed, together with the presence of various perturbations in it. Time domain specifications like setting time along with overshoot and oscillations were analyzed to prove the efficiency of the de-coupler method. The load disturbance rejection was tested along with its performance. The QFT control technique was synthesized based on the stability and performance specifications in the presence of uncertainty in time constant of the plant transfer function through sequential loop shaping technique. Further, the energy efficiency of the distillation column was improved by proper tuning of the controller. A distillation column consumes 3% of the total energy consumption of the world. A suitable control technique is very important from an economic point of view. The real time implementation of the process is under process in our laboratory.

Keywords: distillation, energy, MIMO process, time delay, robust stability

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Authors: Rong Yuan, Zhao Tao

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Only a handful of literature have used to non-linear model to investigate the influencing factors of greenhouse gas (GHG) emissions in China’s manufacturing sectors. And there is a limit in investigating quantitatively and systematically the mechanism of correlation between economic development and GHG emissions considering inherent differences among manufacturing sub-sectors. Considering the sectorial characteristics, the manufacturing sub-sectors with various impacts of output on GHG emissions may be explained by different development modes in each manufacturing sub-sector, such as investment scale, technology level and the level of international competition. In order to assess the environmental impact associated with any specific level of economic development and explore the factors that affect GHG emissions in China’s manufacturing industry during the process of economic growth, using the threshold Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model, this paper investigated the influence impacts of GHG emissions for China’s manufacturing sectors of different stages of economic development. A data set from 28 manufacturing sectors covering an 18-year period was used. Results demonstrate that output per capita and investment scale contribute to increasing GHG emissions while energy efficiency, R&D intensity and FDI mitigate GHG emissions. Results also verify the nonlinear effect of output per capita on emissions as: (1) the Environmental Kuznets Curve (EKC) hypothesis is supported when threshold point RMB 31.19 million is surpassed; (2) the driving strength of output per capita on GHG emissions becomes stronger as increasing investment scale; (3) the threshold exists for energy efficiency with the positive coefficient first and negative coefficient later; (4) the coefficient of output per capita on GHG emissions decreases as R&D intensity increases. (5) FDI shows a reduction in elasticity when the threshold is compassed.

Keywords: China, GHG emissions, manufacturing industry, threshold STIRPAT model

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Authors: Hammad Majeed, Hanna Knuutila, Magne Hillestad, Hallvard F. Svendsen

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Formation of aerosols can cause serious complications in industrial exhaust gas CO2 capture processes. SO3 present in the flue gas can cause aerosol formation in an absorption based capture process. Small mist droplets and fog formed can normally not be removed in conventional demisting equipment because their submicron size allows the particles or droplets to follow the gas flow. As a consequence of this aerosol based emissions in the order of grams per Nm3 have been identified from PCCC plants. In absorption processes aerosols are generated by spontaneous condensation or desublimation processes in supersaturated gas phases. Undesired aerosol development may lead to amine emissions many times larger than what would be encountered in a mist free gas phase in PCCC development. It is thus of crucial importance to understand the formation and build-up of these aerosols in order to mitigate the problem. Rigorous modelling of aerosol dynamics leads to a system of partial differential equations. In order to understand mechanics of a particle entering an absorber an implementation of the model is created in Matlab. The model predicts the droplet size, the droplet internal variable profiles and the mass transfer fluxes as function of position in the absorber. The Matlab model is based on a subclass method of weighted residuals for boundary value problems named, orthogonal collocation method. The model comprises a set of mass transfer equations for transferring components and the essential diffusion reaction equations to describe the droplet internal profiles for all relevant constituents. Also included is heat transfer across the interface and inside the droplet. This paper presents results describing the basic simulation tool for the characterization of aerosols formed in CO2 absorption columns and gives examples as to how various entering droplets grow or shrink through an absorber and how their composition changes with respect to time. Below are given some preliminary simulation results for an aerosol droplet composition and temperature profiles.

Keywords: absorption columns, aerosol formation, amine emissions, internal droplet profiles, monoethanolamine (MEA), post combustion CO2 capture, simulation

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Authors: M. Ashaque Meah, Md. Fazlul Karim, M. Shah Noor, Nazmun Nahar Papri, M. Khalid Hossen, M. Ismoen

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Tsunami and inundation modelling due to far field tsunami propagation in a limited area is a very challenging numerical task because it involves many aspects such as the formation of various types of waves and the irregularities of coastal boundaries. To compute the effect of far field tsunami and extent of inland inundation due to far field tsunami along the coastal belts of west coast of Malaysia and Southern Thailand, a formulated boundary condition and a moving boundary condition are simultaneously used. In this study, a boundary fitted curvilinear grid system is used in order to incorporate the coastal and island boundaries accurately as the boundaries of the model domain are curvilinear in nature and the bending is high. The tsunami response of the event 26 December 2004 along the west open boundary of the model domain is computed to simulate the effect of far field tsunami. Based on the data of the tsunami source at the west open boundary of the model domain, a boundary condition is formulated and applied to simulate the tsunami response along the coastal and island boundaries. During the simulation process, a moving boundary condition is initiated instead of fixed vertical seaside wall. The extent of inland inundation and tsunami propagation pattern are computed. Some comparisons are carried out to test the validation of the simultaneous use of the two boundary conditions. All simulations show excellent agreement with the data of observation.

Keywords: open boundary condition, moving boundary condition, boundary-fitted curvilinear grids, far-field tsunami, shallow water equations, tsunami source, Indonesian tsunami of 2004

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Authors: Kazushige Wada, Mayuko Ueda

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In the present study, we reanalyzed lapse errors in the last phase of a job, by re-counting near lapse errors and increasing the number of participants. We also examined the results of this study from the perspective of prospective memory (PM), which concerns future actions. This study was designed to investigate whether perceiving the importance of PM tasks caused lapse errors in the last phase of a job and to determine if such errors could be explained from the perspective of PM processing. Participants (N = 34) conducted a computerized clicking task, in which they clicked on 10 figures that they had learned in advance in 8 blocks of 10 trials. Participants were requested to click the check box in the start display of a block and to click the checking off box in the finishing display. This task was a PM task. As a measure of PM performance, we counted the number of omission errors caused by forgetting to check off in the finishing display, which was defined as a lapse error. The perceived importance was manipulated by different instructions. Half the participants in the highly important task condition were instructed that checking off was very important, because equipment would be overloaded if it were not done. The other half in the not important task condition was instructed only about the location and procedure for checking off. Furthermore, we controlled workload and the emotion of surprise to confirm the effect of demand capacity and attention. To manipulate emotions during the clicking task, we suddenly presented a photo of a traffic accident and the sound of a skidding car followed by an explosion. Workload was manipulated by requesting participants to press the 0 key in response to a beep. Results indicated too few forgetting induced lapse errors to be analyzed. However, there was a weak main effect of the perceived importance of the check task, in which the mouse moved to the “END” button before moving to the check box in the finishing display. Especially, the highly important task group showed more such near lapse errors, than the not important task group. Neither surprise, nor workload affected the occurrence of near lapse errors. These results imply that high perceived importance of PM tasks impair task performance. On the basis of the multiprocess framework of PM theory, we have suggested that PM task performance in this experiment relied not on monitoring PM tasks, but on spontaneous retrieving.

Keywords: prospective memory, perceived importance, lapse errors, multi process framework of prospective memory.

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Authors: Yumeng Ma, Fang Wang, Jinxia Huang

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Researchers put forward higher requirements for efficient acquisition and utilization of domain knowledge in the big data era. As literature is an effective way for researchers to quickly and accurately understand the research situation in their field, the knowledge discovery based on literature has become a new research method. As a tool to organize and manage knowledge in a specific domain, the subject knowledge base can be used to mine and present the knowledge behind the literature to meet the users' personalized needs. This study designs the construction route of the subject knowledge base for specific research problems. Information extraction method based on knowledge engineering is adopted. Firstly, the subject knowledge model is built through the abstraction of the research elements. Then under the guidance of the knowledge model, extraction rules of knowledge points are compiled to analyze, extract and correlate entities, relations, and attributes in literature. Finally, a database platform based on this structured knowledge is developed that can provide a variety of services such as knowledge retrieval, knowledge browsing, knowledge q&a, and visualization correlation. Taking the construction practices in the field of activating blood circulation and removing stasis as an example, this study analyzes how to construct subject knowledge base based on literature knowledge extraction. As the system functional test shows, this subject knowledge base can realize the expected service scenarios such as a quick query of knowledge, related discovery of knowledge and literature, knowledge organization. As this study enables subject knowledge base to help researchers locate and acquire deep domain knowledge quickly and accurately, it provides a transformation mode of knowledge resource construction and personalized precision knowledge services in the data-intensive research environment.

Keywords: knowledge model, literature knowledge extraction, precision knowledge services, subject knowledge base

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Authors: Seyed Hossein Iranmanesh, Hassan Nouri, Seyed Reza Iranmanesh

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In the dynamic and complex landscape of today’s business, organizations often face challenges in impactful decision-making across multi-project settings. To efficiently allocate resources, coordinate tasks, and optimize project outcomes, establishing robust decision-making processes is essential. Furthermore, the increasing importance of information systems and their integration within organizational workflows introduces an additional layer of complexity. This research proposes the use of blockchain technology as a suitable solution to enhance decision-making in multi-project environments, particularly within the realm of information systems. The conceptual framework in this study comprises four independent variables and one dependent variable. The identified independent variables for the targeted research include: Blockchain Layer in Integrated Systems, Quality of Generated Information ,User Satisfaction with Integrated Systems and Utilization of Integrated Systems. The project’s performance, considered as the dependent variable and moderated by organizational policies and procedures, reflects the impact of blockchain technology adoption on organizational effectiveness1. The results highlight the significant influence of blockchain implementation on organizational performance.

Keywords: multi-project environments, decision support systems, information systems, blockchain technology, decentralized systems.

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Authors: Kari Huhtala, Iiro Jussila

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The supervisory board is assumed to use power in the governance of a firm, but the actual use of power has been scantly investigated. The research question of the paper is “How does the supervisory board use power in the selection of the board of directors”. The data stem from 11 large Finnish agricultural cooperatives. The research approach was qualitative including semi-structured interviews of the board of directors and supervisory board chairpersons. The results were analyzed and interpreted against theories of social power. As a result, the use of power is approached from two perspectives: (1) formal position-based authority and (2) informal power. Central elements of power were the mandate of the supervisory board, the role of the supervisory board, the supervisory board chair, the nomination committee, collaboration between the supervisory board and the board of directors, the role of regions and the role of the board of directors. The study contributes to the academic discussion on corporate governance in cooperatives and on the supervisory board in the context of the two-tier model. Additional research of the model in other countries and of other types of cooperatives would further academic understanding of supervisory boards.

Keywords: board, co-operative, supervisory board, selection, director

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Authors: Pablo Lopez Hurtado, Antroine Rouilly, Virginie Vandenbossche

Abstract:

Cellulose fibre insulation is an eco-friendly building material made from recycled paper fibres, treated with borates for fungal and fire resistance. It is comparable in terms of thermal and acoustic performance to mineral wool insulation and other insulation materials based on non-renewable resources. The main method of application consists in separating and blowing the fibres in attics or closed wall cavities. Another method, known as the “wet spray method” is gaining interest. With this method the fibres are projected with pulverized water, which stick to the wall cavities. The issue with the wet spray technique is that the water dosage could be difficult to control. A high water dosage implies not only a longer drying time, depending on ambient conditions, but also a change in the performance of the material itself. In our work we studied the thermal and mechanical properties of wet spray-cellulose insulation in order to understand how water dosage could affect these properties. The material was first characterized to study the chemical and physical properties of the fibres. Then representative samples of wet sprayed cellulose with varying applied water dosage were subject to thermal conductivity and compression testing in order to better understand how changes in the fibres induced by drying can affect these properties.

Keywords: cellulose fibre, recycled paper, moisture sorption, thermal insulation

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Authors: Ming-Yeh Lu, Shiao-Shing Chen, Saikat Sinha Ray, Hung-Te Hsu

Abstract:

The submerged anaerobic osmotic membrane bioreactor (AnOMBR) integrated with periodic microfiltration (MF) extraction for simultaneous phosphorus and clean water recovery from wastewater was evaluated. A laboratory-scale AnOMBR used cellulose triacetate (CTA) membranes with effective membrane area of 130 cm² was fully submerged into a 5 L bioreactor at 30-35 ℃. Active layer was orientated to feed stream for minimizing membrane fouling and scaling. Additionally, a peristaltic pump was used to circulate magnesium sulphate (MgSO₄) solution applied as draw solution (DS). Microfiltration membrane periodically extracted about 1 L solution when the TDS reaches to 5 g/L to recover phosphorus and simultaneously control the salt accumulation in the bioreactor. During experiment progress, the average water flux was around 1.6 LMH. The AnOMBR process showed greater than 95% removal of soluble chemical oxygen demand (sCOD), nearly 100% of total phosphorous whereas only partial of ammonia was removed. On the other hand, the average methane production of 0.22 L/g sCOD was obtained. Subsequently, the overall performance demonstrates that a novel submerged AnOMBR system is potential for simultaneous wastewater treatment and resource recovery from wastewater. Therefore, the new concept of this system can be used to replace for the conventional AnMBR in the future.

Keywords: anaerobic treatment, forward osmosis, phosphorus recovery, membrane bioreactor

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Authors: Saad M. Alshehri, Tansir Ahamad

Abstract:

Thiourea-Formaldehyde Pre-Polymer (TUF) was prepared by the reaction thiourea and formaldehyde in basic medium and used as a coating materials for magnetite Fe3O4. The synthesized polymer coated microspheres (TUF@Fe3O4) was characterized using FTIR, TGA SEM and TEM. Its BET surface area was up to 1680 m2 g_1. The adsorption capacity of this ACF product was evaluated in its adsorption of Methylene Blue (MB) in water under different pH values and different temperature. We found that the adsorption process was well described both by the Langmuir and Freundlich isotherm model. The kinetic processes of MB adsorption onto TUF@Fe3O4 were described in order to provide a more clear interpretation of the adsorption rate and uptake mechanism. The overall kinetic data was acceptably explained by a pseudo second-order rate model. Evaluated ∆Go and ∆Ho specify the spontaneous and exothermic nature of the reaction. The adsorption takes place with a decrease in entropy (∆So is negative). The monolayer capacity for MB was up to 450 mg g_1 and was one of the highest among similar polymeric products. It was due to its large BET surface area.

Keywords: TGA, FTIR, magentite, thiourea formaldehyde resin, methylene blue, adsorption

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Authors: Redouane Lombarkia

Abstract:

To apply a new material model developed and validated for plain weave fabric CFRP composites usually used in stanchions in sub-cargo section in aircrafts. This work deals with the development of a numerical model of the fuselage section of commercial aircraft based on the pure explicit finite element method FEM within Abaqus/Explicit commercial code. The aim of this work is the evaluation of the energy absorption capabilities of a full-scale composite fuselage section, including sub-cargo stanchions, Drop tests were carried out from a free fall height of about 5 m and impact velocity of about 6 m∕s. To asses, the prediction efficiency of the proposed numerical modeling procedure, a comparison with literature existed experimental results was performed. We demonstrate the efficiency of the proposed methodology to well capture crash damage mechanisms compared to experimental results

Keywords: crashworthiness, fuselage section, finite elements method (FEM), stanchions, specific energy absorption SEA

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Authors: Qingsong Xiong, Cheng Yuan, Qingzhao Kong, Haibei Xiong

Abstract:

Deep-learning-driven approaches based on vibration responses have attracted larger attention in rapid structural condition assessment while obtaining sufficient measured training data with corresponding labels is relevantly costly and even inaccessible in practical engineering. This study proposes an integrated label propagation network for structural condition assessment, which is able to diffuse the labels from continuously-generating measurements by intact structure to those of missing labels of damage scenarios. The integrated network is embedded with damage-sensitive features extraction by deep autoencoder and pseudo-labels propagation by optimized fuzzy clustering, the architecture and mechanism which are elaborated. With a sophisticated network design and specified strategies for improving performance, the present network achieves to extends the superiority of self-supervised representation learning, unsupervised fuzzy clustering and supervised classification algorithms into an integration aiming at assessing damage conditions. Both numerical simulations and full-scale laboratory shaking table tests of a two-story building structure were conducted to validate its capability of detecting post-earthquake damage. The identifying accuracy of a present network was 0.95 in numerical validations and an average 0.86 in laboratory case studies, respectively. It should be noted that the whole training procedure of all involved models in the network stringently doesn’t rely upon any labeled data of damage scenarios but only several samples of intact structure, which indicates a significant superiority in model adaptability and feasible applicability in practice.

Keywords: autoencoder, condition assessment, fuzzy clustering, label propagation

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Authors: Wenlong Feng, Zhenchun Du, Jianguo Yang

Abstract:

To decrease the grating scale thermal expansion error, a novel method which based on multiple temperature detections is proposed. Several temperature sensors are installed on the grating scale and the temperatures of these sensors are recorded. The temperatures of every point on the grating scale are calculated by interpolating between adjacent sensors. According to the thermal expansion principle, the grating scale thermal expansion error model can be established by doing the integral for the variations of position and temperature. A novel compensation method is proposed in this paper. By applying the established error model, the grating scale thermal expansion error is decreased by 90% compared with no compensation. The residual positioning error of the grating scale is less than 15um/10m and the accuracy of the machine tool is significant improved.

Keywords: thermal expansion error of grating scale, error compensation, machine tools, integral method

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Authors: Salman Hameed

Abstract:

In this paper, a self-tuning fuzzy PI controller (STFPIC) is proposed for thyristor controlled series capacitor (TCSC) to improve power system dynamic performance. In a STFPIC controller, the output scaling factor is adjusted on-line by an updating factor (α). The value of α is determined from a fuzzy rule-base defined on error (e) and change of error (Δe) of the controlled variable. The proposed self-tuning controller is designed using a very simple control rule-base and the most natural and unbiased membership functions (MFs) (symmetric triangles with equal base and 50% overlap with neighboring MFs). The comparative performances of the proposed STFPIC and the standard fuzzy PI controller (FPIC) have been investigated on a multi-machine power system (namely, 4 machine two area system) through detailed non-linear simulation studies using MATLAB/SIMULINK. From the simulation studies it has been found out that for damping oscillations, the performance of the proposed STFPIC is better than that obtained by the standard FPIC. Moreover, the proposed STFPIC as well as the FPIC have been found to be quite effective in damping oscillations over a wide range of operating conditions and are quite effective in enhancing the power carrying capability of the power system significantly.

Keywords: genetic algorithm, power system stability, self-tuning fuzzy controller, thyristor controlled series capacitor

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Authors: Romulo D. C. Santos, Silvio M. A. Gama, Ramiro G. R. Camacho

Abstract:

In this present paper, the thermos-fluid dynamics considering the mixed convection (natural and forced convections) and the principles of turbulence flow around complex geometries have been studied. In these applications, it was necessary to analyze the influence between the flow field and the heated immersed body with constant temperature on its surface. This paper presents a study about the Newtonian incompressible two-dimensional fluid around isothermal geometry using the immersed boundary method (IBM) with the virtual physical model (VPM). The numerical code proposed for all simulations satisfy the calculation of temperature considering Dirichlet boundary conditions. Important dimensionless numbers such as Strouhal number is calculated using the Fast Fourier Transform (FFT), Nusselt number, drag and lift coefficients, velocity and pressure. Streamlines and isothermal lines are presented for each simulation showing the flow dynamics and patterns. The Navier-Stokes and energy equations for mixed convection were discretized using the finite difference method for space and a second order Adams-Bashforth and Runge-Kuta 4th order methods for time considering the fractional step method to couple the calculation of pressure, velocity, and temperature. This work used for simulation of turbulence, the Smagorinsky, and Spalart-Allmaras models. The first model is based on the local equilibrium hypothesis for small scales and hypothesis of Boussinesq, such that the energy is injected into spectrum of the turbulence, being equal to the energy dissipated by the convective effects. The Spalart-Allmaras model, use only one transport equation for turbulent viscosity. The results were compared with numerical data, validating the effect of heat-transfer together with turbulence models. The IBM/VPM is a powerful tool to simulate flow around complex geometries. The results showed a good numerical convergence in relation the references adopted.

Keywords: immersed boundary method, mixed convection, turbulence methods, virtual physical model

Procedia PDF Downloads 104