Search results for: bayesian estimation‎

Authors: Saba Arif, Anam Nadeem, Roman Kalvin, Tanzeel Rashid, Burhan Ali, Juntakan Taweekun

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Currently, the energy crisis is taking serious attention. Globally, industries and building are major share takers of energy. 72% of total global energy is consumed by residential houses, markets, and commercial building. Additionally, in appliances air conditioners are major consumer of electricity; about 60% energy is used for cooling purpose in houses due to HVAC units. Energy demand will aid in determining what changes will be needed whether it is the estimation of the required energy for households or instituting conservation measures. Bottom-up model is one of the most famous methods for forecasting. In current research bottom-up model of air conditioners' energy consumption in all income classes in comparison with seasonal variation and hourly consumption is calculated. By comparison of energy consumption of all income classes by usage of air conditioners, total consumption of actual demand and current availability can be seen.

Keywords: air conditioning, bottom up model, income classes, energy demand

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Authors: Manoj Kumar, Rajesh Kumar

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With the favourable geographical conditions at Indian-subcontinent, it is suitable for flourishing renewable energy. Increasing amount of dependence on coal and other conventional sources is driving the world into pollution and depletion of resources. This paper presents the statistics of energy consumption and energy generation in Indian Sub-continent, which notifies us with the increasing energy demands surpassing energy generation. With the aggrandizement in demand for energy, usage of coal has increased, since the major portion of energy production in India is from thermal power plants. The increase in usage of thermal power plants causes pollution and depletion of reserves; hence, a paradigm shift to renewable sources is inevitable. In this work, the capacity and potential of renewable sources in India are analyzed. Based on the analysis of this work, future potential of these sources is estimated.

Keywords: depletion of reserves, energy consumption and generation, emmissions, global warming, renewable sources

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Authors: Alexander Norbach

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The script in this paper describes the use of advanced simulation environment using electronic systems (Microcontroller, Operational Amplifiers, and FPGA). The simulation may be used for all dynamic systems with the diffusion and the ionisation behaviour also. By additionally required observer structure, the system works with parallel real-time simulation based on diffusion model and the state-space representation for other dynamics. The proposed deposited model may be used for electrodynamic effects, including ionising effects and eddy current distribution also. With the script and proposed method, it is possible to calculate the spatial distribution of the electromagnetic fields in real-time. For further purpose, the spatial temperature distribution may be used also. With upon system, the uncertainties, unknown initial states and disturbances may be determined. This provides the estimation of the more precise system states for the required system, and additionally, the estimation of the ionising disturbances that occur due to radiation effects. The results have shown that a system can be also developed and adopted specifically for space systems with the real-time calculation of the radiation effects only. Electronic systems can take damage caused by impacts with charged particle flux in space or radiation environment. In order to be able to react to these processes, it must be calculated within a shorter time that ionising radiation and dose is present. All available sensors shall be used to observe the spatial distributions. By measured value of size and known location of the sensors, the entire distribution can be calculated retroactively or more accurately. With the formation, the type of ionisation and the direct effect to the systems and thus possible prevent processes can be activated up to the shutdown. The results show possibilities to perform more qualitative and faster simulations independent of kind of systems space-systems and radiation environment also. The paper gives additionally an overview of the diffusion effects and their mechanisms. For the modelling and derivation of equations, the extended current equation is used. The size K represents the proposed charge density drifting vector. The extended diffusion equation was derived and shows the quantising character and has similar law like the Klein-Gordon equation. These kinds of PDE's (Partial Differential Equations) are analytically solvable by giving initial distribution conditions (Cauchy problem) and boundary conditions (Dirichlet boundary condition). For a simpler structure, a transfer function for B- and E- fields was analytically calculated. With known discretised responses g₁(k·Ts) and g₂(k·Ts), the electric current or voltage may be calculated using a convolution; g₁ is the direct function and g₂ is a recursive function. The analytical results are good enough for calculation of fields with diffusion effects. Within the scope of this work, a proposed model of the consideration of the electromagnetic diffusion effects of arbitrary current 'waveforms' has been developed. The advantage of the proposed calculation of diffusion is the real-time capability, which is not really possible with the FEM programs available today. It makes sense in the further course of research to use these methods and to investigate them thoroughly.

Keywords: advanced observer, electrodynamics, systems, diffusion, partial differential equations, solver

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Authors: Amir Alirezaei, Shahram Vahdani

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This study estimates the seismic demands of tall buildings with central symmetric setbacks by using nonlinear time history analysis. Three setback structures, all 60-story high with setback in three levels, are used for evaluation. The effects of irregularities occurred by setback, are evaluated by determination of global-drift, story-displacement and story drift. Story-displacement is modified by roof displacement and first story displacement and story drift is modified by global drift. All results are calculated at the center of mass and in x and y direction. Also the absolute values of these quantities are determined. The results show that increasing of vertical irregularities increases the global drift of the structure and enlarges the deformations in the height of the structure. It is also observed that the effects of geometry irregularity in the seismic deformations of setback structures are higher than those of mass irregularity.

Keywords: deformation demand, drift, setback, tall building

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Authors: Salam Alrekabi, A. B. Cundy, Mohammed Haloob Al-Majidi

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Novel multiscale hybrid reinforced cementitious composites based on carbon nanotubes (MHRCC-CNT), and carbon nanofibers (MHRCC-CNF) are new types of cement-based material fabricated with micro steel fibers and nanofilaments, featuring superior strain hardening, ductility, and energy absorption. This study focused on established models to predict the compressive strength, and direct and splitting tensile strengths of the produced cementitious composites. The analysis was carried out based on the experimental data presented by the previous author’s study, regression analysis, and the established models that available in the literature. The obtained models showed small differences in the predictions and target values with experimental verification indicated that the estimation of the mechanical properties could be achieved with good accuracy.

Keywords: multiscale hybrid reinforced cementitious composites, carbon nanotubes, carbon nanofibers, mechanical strength prediction

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Authors: Ranajoy Bhattcharyya

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We estimate international product cycles as shifting product spaces by using 1976 to 2010 UN Comtrade data on all differentiated tradable products in all countries. We use a product space approach to identify the representative product baskets of high-, middle and low-income countries and then use these baskets to identify the patterns of change in comparative advantage of countries over time. We find evidence of a product cycle in two senses: First, high-, middle- and low-income countries differ in comparative advantage, and high-income products migrate to the middle-income basket. A similar pattern is observed for middle- and low-income countries. Our estimation of the lag shows that middle-income countries tend to quickly take up the products of high-income countries, but low-income countries take a longer time absorbing these products. Thus, the gap between low- and middle-income countries is considerably higher than that between middle- and high-income nations.

Keywords: product cycle, comparative advantage, representative product basket, ex-post data

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Authors: Koffi Sodokin

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Financing microstructures are increasingly seen as a means of financial inclusion and improving overall well-being in developing countries. In practice, digital transformation in finance can accelerate the optimal functioning of financing microstructures, such as access by households to microfinance and microinsurance. Large households' access to finance can lead to a reduction in income inequality and an overall improvement in well-being. This paper explores the impact of access to digital finance and financing microstructures on household well-being and the reduction of income inequality. To this end, we use the propensity score matching, the double difference, and the smooth instrumental quantile regression as estimation methods with two periods of survey data. The paper uses the FinScope consumer data (2016) and the Harmonized Living Standards Measurement Study (2018) from Togo in a comparative perspective. The results indicate that access to digital finance, as a cultural game changer, and to financing microstructures improves overall household well-being and contributes significantly to reducing income inequality.

Keywords: financing microstructure, microinsurance, microfinance, digital finance, well-being, income inequality

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Authors: Hamide Amani, Afshin FarahBakhsh, Iman Farahbakhsh

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In this paper, an amprometric biosensor based on surface modified polypyrrole (PPy) has been developed for the quantitative estimation of urea in aqueous solutions. The incorporation of urease (Urs) into a bipolymeric substrate consisting of PPy was performed by entrapment to the polymeric matrix, PPy acts as amperometric transducer in these biosensors. To increase the membrane conductivity, multi-walled carbon nanotubes (MWCNT) were added to the PPy solution. The entrapped MWCNT in PPy film and the bipolymer layers were prepared for construction of Pt/PPy/MWCNT/Urs. Two different configurations of working electrodes were evaluated to investigate the potential use of the modified membranes in biosensors. The evaluation of two different configurations of working electrodes suggested that the second configuration, which was composed of an electrode-mediator-(pyrrole and multi-walled carbon nanotube) structure and enzyme, is the best candidate for biosensor applications.

Keywords: urea biosensor, polypyrrole, multi-walled carbon nanotube, urease

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Authors: Yosep Chong, Yejin Kim, Jingyun Choi, Hwanjo Yu, Eun Jung Lee, Chang Suk Kang

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For the past decades, immunohistochemistry (IHC) has been playing an important role in the diagnosis of human neoplasms, by helping pathologists to make a clearer decision on differential diagnosis, subtyping, personalized treatment plan, and finally prognosis prediction. However, the IHC performed in various tumors of daily practice often shows conflicting and very challenging results to interpret. Even comprehensive diagnosis synthesizing clinical, histologic and immunohistochemical findings can be helpless in some twisted cases. Another important issue is that the IHC data is increasing exponentially and more and more information have to be taken into account. For this reason, we reached an idea to develop an expert supporting system to help pathologists to make a better decision in diagnosing human neoplasms with IHC results. We gave probabilistic decision tree algorithm and tested the algorithm with real case data of lymphoid neoplasms, in which the IHC profile is more important to make a proper diagnosis than other human neoplasms. We designed probabilistic decision tree based on Bayesian theorem, program computational process using MATLAB (The MathWorks, Inc., USA) and prepared IHC profile database (about 104 disease category and 88 IHC antibodies) based on WHO classification by reviewing the literature. The initial probability of each neoplasm was set with the epidemiologic data of lymphoid neoplasm in Korea. With the IHC results of 131 patients sequentially selected, top three presumptive diagnoses for each case were made and compared with the original diagnoses. After the review of the data, 124 out of 131 were used for final analysis. As a result, the presumptive diagnoses were concordant with the original diagnoses in 118 cases (93.7%). The major reason of discordant cases was that the similarity of the IHC profile between two or three different neoplasms. The expert supporting system algorithm presented in this study is in its elementary stage and need more optimization using more advanced technology such as deep-learning with data of real cases, especially in differentiating T-cell lymphomas. Although it needs more refinement, it may be used to aid pathological decision making in future. A further application to determine IHC antibodies for a certain subset of differential diagnoses might be possible in near future.

Keywords: database, expert supporting system, immunohistochemistry, probabilistic decision tree

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Authors: Rhoda Afriyie Mensah, Lin Jiang, Solomon Asante-Okyere, Xu Qiang, Cong Jin

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Flammability analysis of extruded polystyrene (XPS) has become crucial due to its utilization as insulation material for energy efficient buildings. Using the Kissinger-Akahira-Sunose and Flynn-Wall-Ozawa methods, the degradation kinetics of two pure XPS from the local market, red and grey ones, were obtained from the results of thermogravity analysis (TG) and microscale combustion calorimetry (MCC) experiments performed under the same heating rates. From the experiments, it was discovered that red XPS released more heat than grey XPS and both materials showed two mass loss stages. Consequently, the kinetic parameters for red XPS were higher than grey XPS. A comparative evaluation of activation energies from MCC and TG showed an insignificant degree of deviation signifying an equivalent apparent activation energy from both methods. However, different activation energy profiles as a result of the different chemical pathways were presented when the dependencies of the activation energies on extent of conversion for TG and MCC were compared.

Keywords: flammability, microscale combustion calorimetry, thermogravity analysis, thermal degradation, kinetic analysis

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Authors: Fanqiang Kong, Chending Bian

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In this work, we exploit two assumed properties of the abundances of the observed signatures (endmembers) in order to reconstruct the abundances from hyperspectral data. Joint-sparsity is the first property of the abundances, which assumes the adjacent pixels can be expressed as different linear combinations of same materials. The second property is rank-deficiency where the number of endmembers participating in hyperspectral data is very small compared with the dimensionality of spectral library, which means that the abundances matrix of the endmembers is a low-rank matrix. These assumptions lead to an optimization problem for the sparse unmixing model that requires minimizing a combined l_2,p-norm and nuclear norm. We propose a variable splitting and augmented Lagrangian algorithm to solve the optimization problem. Experimental evaluation carried out on synthetic and real hyperspectral data shows that the proposed method outperforms the state-of-the-art algorithms with a better spectral unmixing accuracy.

Keywords: hyperspectral unmixing, joint-sparse, low-rank representation, abundance estimation

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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: Susmita Ghosh

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Catchment area of Damodar River, India experiences seasonal rains due to the south-west monsoon every year and depending upon the intensity of the storms, floods occur. During the monsoon season, the rainfall in the area is mainly due to active monsoon conditions. The upstream reach of Damodar river system has five dams store the water for utilization for various purposes viz, irrigation, hydro-power generation, municipal supplies and last but not the least flood moderation. But, in the downstream reach of Damodar River, known as Lower Damodar region, is severely and frequently suffering from flood due to heavy monsoon rainfall and also release from upstream reservoirs. Therefore, an effective flood management study is required to know in depth the nature and extent of flood, water logging, and erosion related problems, affected area, and damages in the Lower Damodar region, by conducting mathematical model study. The design flood or discharge is needed to decide to assign the respective model for getting several scenarios from the simulation runs. The ultimate aim is to achieve a sustainable flood management scheme from the several alternatives. there are various methods for estimating flood discharges to be carried through the rivers and their tributaries for quick drainage from inundated areas due to drainage congestion and excess rainfall. In the present study, the flood frequency analysis is performed to decide the design flood discharge of the study area. This, on the other hand, has limitations in respect of availability of long peak flood data record for determining long type of probability density function correctly. If sufficient past records are available, the maximum flood on a river with a given frequency can safely be determined. The floods of different frequency for the Damodar has been calculated by five candidate distributions i.e., generalized extreme value, extreme value-I, Pearson type III, Log Pearson and normal. Annual peak discharge series are available at Durgapur barrage for the period of 1979 to 2013 (35 years). The available series are subjected to frequency analysis. The primary objective of the flood frequency analysis is to relate the magnitude of extreme events to their frequencies of occurrence through the use of probability distributions. The design flood for return periods of 10, 15 and 25 years return period at Durgapur barrage are estimated by flood frequency method. It is necessary to develop flood hydrographs for the above floods to facilitate the mathematical model studies to find the depth and extent of inundation etc. Null hypothesis that the distributions fit the data at 95% confidence is checked with goodness of fit test, i.e., Chi Square Test. It is revealed from the goodness of fit test that the all five distributions do show a good fit on the sample population and is therefore accepted. However, it is seen that there is considerable variation in the estimation of frequency flood. It is therefore considered prudent to average out the results of these five distributions for required frequencies. The inundated area from past data is well matched using this flood.

Keywords: design discharge, flood frequency, goodness of fit, sustainable flood management

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Authors: Cristobal García

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The visual inspection of bolted joints in wind turbines is dangerous, expensive, and impractical due to the non-possibility to access the platform by workboat in certain sea state conditions, as well as the high costs derived from the transportation of maintenance technicians to offshore platforms located far away from the coast, especially if helicopters are involved. Consequently, the wind turbine operators have the need for simpler and less demanding techniques for the analysis of the bolts tightening. Vibration-based structural health monitoring is one of the oldest and most widely-used means for monitoring the health of onshore and offshore wind turbines. The core of this work is to find out if the modal parameters can be efficiently used as a key performance indicator (KPIs) for the assessment of joint bolts in a 1:50 scale tower of a floating offshore wind turbine (12 MW). A non-destructive vibration test is used to extract the vibration signals of the towers with different damage statuses. The procedure can be summarized in three consecutive steps. First, an artificial excitation is introduced by means of a commercial shaker mounted on the top of the tower. Second, the vibration signals of the towers are recorded for 8 s at a sampling rate of 20 kHz using an array of commercial accelerometers (Endevco, 44A16-1032). Third, the natural frequencies, damping, and overall vibration mode shapes are calculated using the software Siemens LMS 16A. Experiments show that the natural frequencies, damping, and mode shapes of the tower are directly dependent on the fixing conditions of the towers, and therefore, the variations of both parameters are a good indicator for the estimation of the static axial force acting in the bolt. Thus, this vibration-based structural method proposed can be potentially used as a diagnostic tool to evaluate the tightening torques of the bolted joints with the advantages of being an economical, straightforward, and multidisciplinary approach that can be applied for different typologies of connections by operation and maintenance technicians. In conclusion, TSI, in collaboration with the consortium of the FIBREGY project, is conducting innovative research where vibrations are utilized for the estimation of the tightening torque of a 1:50 scale steel-based tower prototype. The findings of this research carried out in the context of FIBREGY possess multiple implications for the assessment of the bolted joint integrity in multiple types of connections such as tower-to-nacelle, modular, tower-to-column, tube-to-tube, etc. This research is contextualized in the framework of the FIBREGY project. The EU-funded FIBREGY project (H2020, grant number 952966) will evaluate the feasibility of the design and construction of a new generation of marine renewable energy platforms using lightweight FRP materials in certain structural elements (e.g., tower, floating platform). The FIBREGY consortium is composed of 11 partners specialized in the offshore renewable energy sector and funded partially by the H2020 program of the European Commission with an overall budget of 8 million Euros.

Keywords: SHM, vibrations, connections, floating offshore platform

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Authors: K. B. Rajasekarababu, J. Karthik, G. Vinayagamurthy

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This paper is intended to explain the influence of major axis on aerodynamic characteristics of elliptical section. Many engineering applications such as off shore structures, bridge piers, civil structures and pipelines can be modelled as a circular cylinder but flow over complex bodies like, submarines, Elliptical wing, fuselage, missiles, and rotor blades, in which the parameters such as axis ratio can influence the flow characteristics of the wake and nature of separation. Influence of Major axis in Flow characteristics of elliptical sections are examined both experimentally and computationally in this study. For this research, four elliptical models with varying major axis [*AR=1, 4, 6, 10] are analysed. Experimental works have been conducted in a subsonic wind tunnel. Furthermore, flow characteristics on elliptical model are predicted from k-ε turbulence model using the commercial CFD packages by pressure based transient solver with Standard wall conditions.The analysis can be extended to estimation and comparison of Drag coefficient and Fatigue analysis of elliptical sections.

Keywords: elliptical section, major axis, aerodynamic characteristics, k-ε turbulence model

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Authors: Fuad M. Alkoot

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We aim at highlighting the benefits of classifier systems especially in supporting educational management decisions. The paper aims at using classifiers in an educational application where an outcome is predicted based on given input parameters that represent various conditions at the institute. We present a classifier system that is designed using a limited training set with data for only one semester. The achieved system is able to reach at previously known outcomes accurately. It is also tested on new input parameters representing variations of input conditions to see its prediction on the possible outcome value. Given the supervised expectation of the outcome for the new input we find the system is able to predict the correct outcome. Experiments were conducted on one semester data from two departments only, Switching and Mathematics. Future work on other departments with larger training sets and wider input variations will show additional benefits of classifier systems in supporting the management decisions at an educational institute.

Keywords: machine learning, pattern recognition, classifier design, educational management, outcome estimation

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Authors: Honggang Qu, Yong Xu, Rongmei Liu, Zhenji Gao, Bin Wang

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Today's mining industry is advancing gradually toward digital and visual direction. The three-dimensional visualization geological modeling of mine is the digital characterization of mineral deposits and is one of the key technology of digital mining. Three-dimensional geological modeling is a technology that combines geological spatial information management, geological interpretation, geological spatial analysis and prediction, geostatistical analysis, entity content analysis and graphic visualization in a three-dimensional environment with computer technology and is used in geological analysis. In this paper, the three-dimensional geological modeling of an iron mine through the use of Surpac is constructed, and the weight difference of the estimation methods between the distance power inverse ratio method and ordinary kriging is studied, and the ore body volume and reserves are simulated and calculated by using these two methods. Compared with the actual mine reserves, its result is relatively accurate, so it provides scientific bases for mine resource assessment, reserve calculation, mining design and so on.

Keywords: three-dimensional geological modeling, geological database, geostatistics, block model

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Authors: Jungyeol Hong, Dongjoo Park

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The urban transit system is a critical part of a solution to the economic, energy, and environmental challenges. Furthermore, it ultimately contributes the improvement of people’s quality of lives. For taking these kinds of advantages, the city of Seoul has tried to construct an integrated transit system including both subway and buses. The effort led to the fact that approximately 6.9 million citizens use the integrated transit system every day for their trips. Diagnosing the current transit network is a significant task to provide more convenient and pleasant transit environment. Therefore, the critical objective of this study is to establish a methodological framework for the analysis of an integrated bus-subway network and to examine the relationship between subway ridership and parameters such as network topology measures, bus demand, and a variety of commercial business facilities. Regarding a statistical approach to estimate subway ridership at a station level, many previous studies relied on Ordinary Least Square regression, but there was lack of studies considering the endogeneity issues which might show in the subway ridership prediction model. This study focused on both discovering the impacts of integrated transit network topology measures and endogenous effect of bus demand on subway ridership. It could ultimately contribute to developing more accurate subway ridership estimation accounting for its statistical bias. The spatial scope of the study covers Seoul city in South Korea, and it includes 243 subway stations and 10,120 bus stops with the temporal scope set during twenty-four hours with one-hour interval time panels each. The subway and bus ridership information in detail was collected from the Seoul Smart Card data in 2015 and 2016. First, integrated subway-bus network topology measures which have characteristics regarding connectivity, centrality, transitivity, and reciprocity were estimated based on the complex network theory. The results of integrated transit network topology analysis were compared to subway-only network topology. Also, the non-recursive approach which is Three-Stage Least Square was applied to develop the daily subway ridership model as capturing the endogeneity between bus and subway demands. Independent variables included roadway geometry, commercial business characteristics, social-economic characteristics, safety index, transit facility attributes, and dummies for seasons and time zone. Consequently, it was found that network topology measures were significant size effect. Especially, centrality measures showed that the elasticity was a change of 4.88% for closeness centrality, 24.48% for betweenness centrality while the elasticity of bus ridership was 8.85%. Moreover, it was proved that bus demand and subway ridership were endogenous in a non-recursive manner as showing that predicted bus ridership and predicted subway ridership is statistically significant in OLS regression models. Therefore, it shows that three-stage least square model appears to be a plausible model for efficient subway ridership estimation. It is expected that the proposed approach provides a reliable guideline that can be used as part of the spectrum of tools for evaluating a city-wide integrated transit network.

Keywords: integrated transit system, network topology measures, three-stage least squared, endogeneity, subway ridership

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Authors: Samba Raju, Chiluveru, Manoj Tripathy

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Intelligibility is an essential characteristic of a speech signal, which is used to help in the understanding of information in speech signal. Background noise in the environment can deteriorate the intelligibility of a recorded speech. In this paper, we presented a simple variance subtracted - variable level discrete wavelet transform, which improve the intelligibility of speech. The proposed algorithm does not require an explicit estimation of noise, i.e., prior knowledge of the noise; hence, it is easy to implement, and it reduces the computational burden. The proposed algorithm decides a separate decomposition level for each frame based on signal dominant and dominant noise criteria. The performance of the proposed algorithm is evaluated with speech intelligibility measure (STOI), and results obtained are compared with Universal Discrete Wavelet Transform (DWT) thresholding and Minimum Mean Square Error (MMSE) methods. The experimental results revealed that the proposed scheme outperformed competing methods

Keywords: discrete wavelet transform, speech intelligibility, STOI, standard deviation

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Authors: Mourad Zmami Oussema BenSalha

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The current research aims to assess empirically the reaction of private investment to exchange rate fluctuations in Tunisia using a sample of 548 firms operating in manufacturing industries between 1997 and 2002. The micro-econometric model we estimate is based on an accelerator-profit specification investment model increased by two variables that measure the variation and the volatility of exchange rates. Estimates using the system the GMM method reveal that the effects of the exchange rate depreciation on investment are negative since it increases the cost of imported capital goods. Turning to the exchange rate volatility, as measured by the GARCH (1,1) model, our findings assign a significant role to the exchange rate uncertainty in explaining the sluggishness of private investment in Tunisia in the full sample of firms. Other estimation attempts based on various sub samples indicate that the elasticities of investment relative to the exchange rate volatility depend upon many firms’ specific characteristics such as the size and the ownership structure.

Keywords: investment, exchange rate volatility, manufacturing firms, system GMM, Tunisia

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Authors: Shama Urooj

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The present work investigates the relationship among financial inclusion, modernization, and energy performance in SCO member countries during the years 2011–2021. PCA is used to create composite indexes of financial inclusion, modernization, and energy performance. We used panel regression models that are both reliable and heteroscedasticity-consistent to look at the relationship among variables. The findings indicate that financial inclusion (FI) and modernization, along with the increased FDI, all appear to contribute to the energy performance in the SCO member countries. However, per capita GDP has a negative impact on energy performance. These results are unbiased and consistent with the robust results obtained by applying different econometric models. Feasible Generalized Least Square (FGLS) estimation is also used for checking the uniformity of the main model results. This research work concludes that there has been no policy coherence in SCO member countries regarding the coordination of growing financial inclusion and modernization for energy sustainability in recent years. In order to improve energy performance with modern development, policies regarding financial inclusion and modernization need be integrated both at national as well as international levels.

Keywords: financial inclusion, energy performance, modernization, technological development, SCO.

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Authors: Eun Kyung Kim, Kyehan Rhee

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Viscoelastic wall properties of the arterial plaques change as the disease progresses, and estimation of wall viscoelasticity can provide a valuable assessment tool for plaque rupture prediction. Cross section of the stenotic coronary artery was modeled based on the IVUS image, and the finite element analysis was performed to get wall deformation under pulsatile pressure. The effects of viscoelastic parameters of the plaque on luminal diameter variations were explored. The result showed that decrease of viscous effect reduced the phase angle between the pressure and displacement waveforms, and phase angle was dependent on the viscoelastic properties of the wall. Because viscous effect of tissue components could be identified using the phase angle difference, wall deformation waveform analysis may be applied to predict plaque wall composition change and vascular wall disease progression.

Keywords: atherosclerotic plaque, diameter variation, finite element method, viscoelasticity

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Authors: Kayode Balogun, Femi Ayoola

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Crime is at alarming rate in this part of world and there are many factors that are contributing to this antisocietal behaviour both among the youths and old. In this work, principal component analysis (PCA) was used as a tool to reduce the dimensionality and to really know those variables that were crime prone in the study region. Data were collected on twenty-eight crime variables from National Bureau of Statistics (NBS) databank for a period of fifteen years, while retaining as much of the information as possible. We use PCA in this study to know the number of major variables and contributors to the crime in the Southwest Nigeria. The results of our analysis revealed that there were eight principal variables have been retained using the Scree plot and Loading plot which implies an eight-equation solution will be appropriate for the data. The eight components explained 93.81% of the total variation in the data set. We also found that the highest and commonly committed crimes in the Southwestern Nigeria were: Assault, Grievous Harm and Wounding, theft/stealing, burglary, house breaking, false pretence, unlawful arms possession and breach of public peace.

Keywords: crime rates, data, Southwest Nigeria, principal component analysis, variables

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Authors: Haniye Dehestani, Yadollah Ordokhani

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In this work, we present an efficient approach for solving variable-order time-fractional partial differential equations, which are based on Legendre and Laguerre polynomials. First, we introduced the pseudo-operational matrices of integer and variable fractional order of integration by use of some properties of Riemann-Liouville fractional integral. Then, applied together with collocation method and Legendre-Laguerre functions for solving variable-order time-fractional partial differential equations. Also, an estimation of the error is presented. At last, we investigate numerical examples which arise in physics to demonstrate the accuracy of the present method. In comparison results obtained by the present method with the exact solution and the other methods reveals that the method is very effective.

Keywords: collocation method, fractional partial differential equations, legendre-laguerre functions, pseudo-operational matrix of integration

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Authors: H. Barati, M. Wu, A. Kharicha, A. Ludwig

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A transient model for nozzle clogging has been developed and successfully validated against a laboratory experiment. Key steps of clogging are considered: transport of particles by turbulent flow towards the nozzle wall; interactions between fluid flow and nozzle wall, and the adhesion of the particle on the wall; the growth of the clog layer and its interaction with the flow. The current paper is to investigate the mesh (size and type) sensitivity of the model in both two and three dimensions. It is found that the algorithm for clog growth alone excluding the flow effect is insensitive to the mesh type and size, but the calculation including flow becomes sensitive to the mesh quality. The use of 2D meshes leads to overestimation of the clog growth because the 3D nature of flow in the boundary layer cannot be properly solved by 2D calculation. 3D simulation with tetrahedron mesh can also lead to an error estimation of the clog growth. A mesh-independent result can be achieved with hexahedral mesh, or at least with triangular prism (inflation layer) for near-wall regions.

Keywords: clogging, continuous casting, inclusion, simulation, submerged entry nozzle

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Authors: Ben Nwokenkwo, Michael M. Eze, Felix Ike

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The need to study trends in land values around institutions of higher learning cannot be overemphasized. Numerous studies in Nigeria have investigated the economic, and social influence of the sitting of institutions of higher learning at the micro, meso and macro levels. However, very few studies have evaluated the temporal extent at which such institution influences local land values. Since institutions greatly influence both the physical and environmental aspects of their immediate vicinity, attention must be taken to understand the influence of such changes on land values. This study examines the trend in land values using the Mann-Kendall analysis in order to determine if, between its beginning and end, a monotonic increase, decrease or stability exist in the land values across six institutions of higher learning for the period between 2004 and 2014. Specifically, The analysis was applied to the time series of the price(or value) of the land .The results of this study revealed that land values has either been increasing or remained stabled across all the institution sampled. The study finally recommends measures that can be put in place as counter magnets for land values estimation across institutions of higher learning.

Keywords: influence, land, trend, value

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Authors: Mario Belseran

Abstract:

The issue of climate change become world attention where one of them increase in air temperature due to greenhouse gas emissions. This climate change is caused by gases in the atmosphere, one of which is CO2. DKI Jakarta as the capital has a dense population with a variety of existing land use. Land use that is dominated by settlements resulting in fewer green space, which functions to absorb atmospheric CO2. Image interpretation SPOT-7 is used to determine the greenness level of vegetation on a green space using the vegetation index NDVI, EVI, GNDVI and OSAVI. Measuring the diameter and height of trees were also performed to obtain the value of biomass that will be used as the CO2 absorption value. The CO2 absorption value that spread in Jakarta are classified into three classes: high, medium, and low. The distribution pattern of CO2 absorption value at green space in Jakarta dominance in the medium class with the distribution pattern is located in South Jakarta, East Jakarta, North Jakarta and West Jakarta. The distribution pattern of green space in Jakarta scattered randomly and more dominate in East Jakarta and South Jakarta

Keywords: carbon dioxide, DKI Jakarta, green space, SPOT-7, vegetation index

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Authors: Muluegziabher Semagne Mekonnen

Abstract:

This study was intended to show the irrigation water requirements and evaluation of canal hydraulics steady state conditions to improve on scheme performance of the Meki-Ziway irrigation project. The methodology used was the CROPWAT 8.0 model to estimate the irrigation water requirements of five major crops irrigated in the study area. The results showed that for the whole existing and potential irrigation development area of 2000 ha and 2599 ha, crop water requirements were 3,339,200 and 4,339,090.4 m³, respectively. Hydraulic simulation models are fundamental tools for understanding the hydraulic flow characteristics of irrigation systems. Hydraulic simulation models are fundamental tools for understanding the hydraulic flow characteristics of irrigation systems. In this study Hydraulic Analysis of Irrigation Canals Using HEC-RAS Model was conducted in Meki-Ziway Irrigation Scheme. The HEC-RAS model was tested in terms of error estimation and used to determine canal capacity potential.

Keywords: HEC-RAS, irrigation, hydraulic. canal reach, capacity

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Authors: Hafida Bouarfa, Mohamed Abed

Abstract:

The main object of our work is the development and the validation of a system indicated Fuzzy Vulnerability. Fuzzy Vulnerability uses a fuzzy representation in order to tolerate the imprecision during the description of construction. At the the second phase, we evaluated the similarity between the vulnerability of a new construction and those of the whole of the historical cases. This similarity is evaluated on two levels: 1) individual similarity: bases on the fuzzy techniques of aggregation; 2) Global similarity: uses the increasing monotonous linguistic quantifiers (RIM) to combine the various individual similarities between two constructions. The third phase of the process of Fuzzy Vulnerability consists in using vulnerabilities of historical constructions narrowly similar to current construction to deduce its estimate vulnerability. We validated our system by using 50 cases. We evaluated the performances of Fuzzy Vulnerability on the basis of two basic criteria, the precision of the estimates and the tolerance of the imprecision along the process of estimation. The comparison was done with estimates made by tiresome and long models. The results are satisfactory.

Keywords: case based reasoning, fuzzy logic, fuzzy case based reasoning, seismic vulnerability

Procedia PDF Downloads 292

Authors: Katleho Daniel Makatjane, Diteboho Lawrence Xaba, Ntebogang Dinah Moroke

Abstract:

The current study investigates the behaviour of time-varying parameters that are based on the score function of the predictive model density at time t. The mechanism to update the parameters over time is the scaled score of the likelihood function. The results revealed that there is high persistence of time-varying, as the location parameter is higher and the skewness parameter implied the departure of scale parameter from the normality with the unconditional parameter as 1.5. The results also revealed that there is a perseverance of the leptokurtic behaviour in stock returns which implies the returns are heavily tailed. Prior to model estimation, the White Neural Network test exposed that the stock price can be modelled by a GAS model. Finally, we proposed further researches specifically to model the existence of time-varying parameters with a more detailed model that encounters the heavy tail distribution of the series and computes the risk measure associated with the returns.

Keywords: generalized autoregressive score model, South Africa, stock returns, time-varying

Procedia PDF Downloads 500