Search results for: predicted mean vote

Authors: Wesal A. Maash

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The purpose of this study was to investigate Saudi students' knowledge of CT and their attitudes to it. The sample consisted of 121 students from 23 cities who are studying currently in UK universities with a mix of background variables (age, gender, and university level). A questionnaire was developed by the researcher to be used as the tool of the study. Its validity and reliability were established. The results revealed a negative correlation between knowledge of CT and the attitudes to it. It was also indicated that there exist statistically significant differences between the means of knowledge according to the university level, in favour of postgraduates. Moreover, no significant differences in the level of attitudes to CT were found according to age. Similarly, no significant differences in the knowledge of CT were found according to gender. Further, the attitudes to CT of Saudi students can be predicted based upon their university level. The findings suggest conducting further interpretive or mixed methods research with Saudi international students in order to understand the context in more depth.

Keywords: critical thinking, Saudi international students, knowledge of critical thinking, attitudes towards critical thinking

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Authors: Yu-Jen Shih, Yao-Hui Hunag

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Electrocoagulation (EC) using metallic nickel foam as anode and cathode for the removal of boron from solution was studied. The electrolytic parameters included pH, current density, and initial boron concentration for optimizing the EC process. Experimental results showed that removal efficiency was increased by elevating pH from 4.0 to 8.0, and then decreased at higher pH. The electrolytic efficacy was not affected by current density. In respect of energy consumption, 1.25 mA/cm2 of current density was acceptable for an effective EC of boron, while increasing boric acid from 10 to 100 ppm-B did not impair removal efficiency too much. Cyclic voltammetry indicated that the oxide film, Ni(OH)2 and NiOOH, at specific overpotentials would result in less weight loss of anode than that predicted by the Faraday’s law. The optimal conditions under which 99.2% of boron was removed and less than 1 ppm-B remained in the electrolyte would be pH 8, four pairs of electrodes, and 1.25 mA/cm2 in 120 min as treating wastewaters containing 10 ppm-B. XRD and SEM characterization suggested that the granular crystallites of hydroxide precipitates was composed of theophrastite.

Keywords: borohydrides, hydrogen generation, NiOOH, electrocoagulation, cyclic voltammetry, boron removal

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Authors: Doseong Eom, Jeongmin Kim, Kwang Ryel Ryu

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Large exhibition halls require a lot of energy to maintain comfortable atmosphere for the visitors viewing inside. One way of reducing the energy cost is to have thermal energy storage systems installed so that the thermal energy can be stored in the middle of night when the energy price is low and then used later when the price is high. To minimize the overall energy cost, however, we should be able to decide how much energy to save during which time period exactly. If we can foresee future energy load and the corresponding cost, we will be able to make such decisions reasonably. In this paper, we use machine learning technique to obtain models for predicting weather conditions and the number of visitors on hourly basis for the next day. Based on the energy load thus predicted, we build a cost-optimal daily operation plan for the thermal energy storage systems and cooling and heating facilities through simulation-based optimization.

Keywords: building energy management, machine learning, operation planning, simulation-based optimization

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Authors: Hajar Mohafezatkar Abadi

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The family foundation is formed by marriage, and each couple, with their unique attitudes and personalities, takes a step into marriage. The more efficient and flexible these variables are, the more stable the marriage will be predicted. This group of couples sees their conflicts as an opportunity for growth, not as a threat to their shared life. Regarding family issue importance, a lot of research has been done around this topic which can be an effective step toward improving couples' life quality. The aim of the present study was to determine the role of personality and attitude on marital conflict. 306 couples (153 females, 153 males) were selected using multistage cluster sampling. The participants completed the personality Questionnaire (16PF, Cattell, 1975), marital conflict Questionnaire (MCQ-R, Sanaee Zaker, 1387), and dysfunctional attitude Questionnaire (DAS-26, Weissman & beck. 1987). The regression analysis results indicated that some personality traits and dysfunctional attitudes had a significant positive correlation with marital conflict.

Keywords: marital conflict, dysfunctional attitude, personality, personality questionnaire (16PF)

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Authors: Deepika Bhalla, Raj Kumar Bansal, Hari Om Gupta

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Dissolved Gas Analysis (DGA) has been widely used for fault diagnosis in a transformer. Artificial neural networks (ANN) have high accuracy but are regarded as black boxes that are difficult to interpret. For many problems it is desired to extract knowledge from trained neural networks (NN) so that the user can gain a better understanding of the solution arrived by the NN. This paper applies a pedagogical approach for rule extraction from function approximating neural networks (REFANN) with application to incipient fault diagnosis using the concentrations of the dissolved gases within the transformer oil, as the input to the NN. The input space is split into subregions and for each subregion there is a linear equation that is used to predict the type of fault developing within a transformer. The experiments on real data indicate that the approach used can extract simple and useful rules and give fault predictions that match the actual fault and are at times also better than those predicted by the IEC method.

Keywords: artificial neural networks, dissolved gas analysis, rules extraction, transformer

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Authors: Rola El-Nimri, Mu’Tasime Abdel-Jaber, Yasser Hunaiti

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The flexural behavior of light-gauge steel box sections filled with recycled concrete was assessed through an experimental program involving 15 composite beams. Recycled concrete was obtained by replacing natural aggregates (NA) with recycled concrete aggregate (RCA) and recycled asphalt pavement (RAP) with replacement levels of 20%, 40%, 60%, 80%, and 100% by the total weight of NA. In addition, RCA and RAP were incorporated in the same mixes with replacement levels of (1) 20% RCA and 80% RAP; (2) 40% RCA and 60% RAP; (3) 60% RCA and 40% RAP; and (4) 80% RCA and 20% RAP. A comparison between the experimental capacities and the theoretically predicted values according to Eurocode 4 (EC4) was made as well. Results proved that the ultimate capacity of composite beams decreased with the increase of recycled aggregate (RA) percentage and EC4 was conservative in predicting the ultimate capacity of composite beams.

Keywords: flexure, light gauge, recycled asphalt pavement, recycled concrete aggregate, steel tube

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Authors: Gang Liu, Huimin Song, Can Wang, Runnan Zhang, Lu Fang

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Currently, resource sharing and system security are critical issues. This paper proposes a POL module composed of PRIV ILEGE attribute (PA), obligation and log which improves attribute based access control (ABAC) model in dynamically granting authorizations and revoking authorizations. The following describes the new model termed PABAC in terms of the POL module structure, attribute definitions, policy formulation and authorization architecture, which demonstrate the advantages of it. The POL module addresses the problems which are not predicted before and not described by access control policy. It can be one of the subject attributes or resource attributes according to the practical application, which enhances the flexibility of the model compared with ABAC. A scenario that illustrates how this model is applied to the real world is provided.

Keywords: access control, attribute based access control, granting authorizations, privilege, revoking authorizations, system security

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Authors: Tamilmani Thiruvengadam, Ramasthanan Arulampalam

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This project comprises laying approximately 1.8km of 400mm, 1200mm and 2400mm diameter sewer pipes using pipe jacking machines along Mugliston Park, Buangkok Drive, and Buangkok Link. The works include an estimated 14 circular shafts with depth ranging from 10.0 meters to 29.0 meters. Cast in-situ circular shaft will be used for the temporary shaft excavation. The geology is predominantly Backfill and old alluvium with weak material encountered in between. Where there is a very soft clay, F1 material or weak soil is expected, ground improvement will be carried out outside of the shaft followed by cast in-situ concrete ring wall within the improved soil zone. This paper presents the design methodology, analysis and results of temporary shafts for micro TBM launching and constructing permanent manholes. There is also a comparison of instrumentation readings with the analysis predicted values.

Keywords: circular shaft, ground improvement, old alluvium, temporary shaft

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Authors: Mahdi Asghari

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The cavitation phenomenon is the formation and production of micro-bubbles and eventually the bursting of the micro-bubbles inside the liquid fluid, which results in localized high pressure and temperature, causing physical and chemical fluid changes. This pressure and temperature are predicted to be 2000 atmospheres and 5000 °C, respectively. As a result of small bubbles bursting from this process, temperature and pressure increase momentarily and locally, so that the intensity and magnitude of these temperatures and pressures provide the energy needed to break the molecular bonds of heavy compounds such as fuel oil. In this paper, we study the theory of cavitation and the methods of cavitation production by acoustic and hydrodynamic methods and the necessary mechanical equipment and reactors for industrial application of the hydrodynamic cavitation method to break down the molecular bonds of the fuel oil and convert it into useful and economical products.

Keywords: Cavitation, Hydrodynamic Cavitation, Cavitation Reactor, Fuel Oil

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Authors: Mihail Simion Beldean-Galea, Virginia Coman, Florina Copaciu, Mihaela Vlassa, Radu Mihaiescu, Adina Croitoru, Viorel Arghius, Modest Gertsiuk, Mikola Gertsiuk

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Taking into consideration the huge number of chemicals released into environment compartments a proper environmental risk assessment is difficult to predict due to the gap of legislation and improper toxicological assessment of chemicals compounds. In Romania as well as in many other countries from Europe, the chemical status of the water body is characterized taking into consideration the Water Framework Directive (WFD) and the substances listed in Annex X. This Annex includes 45 substances from different classes of organic compounds and heavy metals for which AA-EQS and MAC-EQS have been established. For other compounds which are not included in Annex X, different methodologies to prioritize chemicals for risk assessment and monitoring has been proposed. These methodologies take into account Predicted No-Effect Concentrations (PNECs) of different classes of chemicals compounds available from existing risk assessments or from read-across models for acute toxicity to the standard test organisms such as Daphnia magna and Selenastrum capricornutum. Our work presents the monitoring results of 30 priority substances including polyaromatic hydrocarbons, pesticides, halogenated compounds, plasticizers and heavy metals and other 34 substances from different classes of pesticides and pharmaceuticals which are not included on the list of priority substances, performed in the Upper Tisza River Watershed from Romania and Ukraine. The obtained monitoring data were used for the establishment of the list of more relevant pollutants in the studied area and to establish the potential river basin specific pollutants. For this purpose, two indicators such as the Frequency of exceedance and Extent of exceedance of Predicted no-Effect Concentration (PNEC) were evaluated. These two indicators are based on maximum environmental concentrations (MECs) of priority substances and for other pollutants is use statistically based averages of obtained measured concentration compared to the lowest PNEC thresholds. From the obtained results it can be concluded that polyaromatic hydrocarbon such as Fluoranthene, Benzo[a]pyrene, Benzo[b]fluorathene, benzo[k]fluoranthene, Benzo(g.h.i)perylene, Indeno(1.2.3-cd)-pyrene, heavy metals such as Cadmium, Lead and Nickel can be considered as river basin specific pollutants, their concentration exceeding the Annual Average EQS concentration. Other compounds such as estrone, estriol, 174-β estradiol, naproxen or some antibiotics (Penicillin G, Tetracycline or Ceftazidime) should be taken into account for a long monitoring, in some cases their concentration exceeding PNEC. Acknowledgements: This work is performed in the frame of NATO SfP Programme, Project no. 984440.

Keywords: prioritization, river basin specific pollutants, Tisza River, water framework directive

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Authors: Marlene Perez Villalpando, Kelly Joel Gurubel Tun

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In this paper, we propose an optimal control strategy for a hydroelectric power plant subject to input disturbances like meteorological phenomena. The engineering characteristics of the system are described by a nonlinear model. The random availability of renewable sources is predicted by a high-order neural network trained with an extended Kalman filter, whereas the power generation is regulated by the optimal control law. The main advantage of the system is the stabilization of the amount of power generated in the plant. A control supervisor maintains stability and availability in hydropower reservoirs water levels for power generation. The proposed approach demonstrated a good performance to stabilize the reservoir level and the power generation along their desired trajectories in the presence of disturbances.

Keywords: hydropower, high order neural network, Kalman filter, optimal control

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Authors: E. L. Elghazy, A. M. Sanad, M. G. Ghoneim

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Over the past two decades research has shown that fiber reinforced polymers can be efficiently, economically and safely used for strengthening and rehabilitation of reinforced concrete (RC) structures. Designing FRP confined concrete columns requires reliable analytical tools that predict the level of performance and ductility enhancement. A numerical procedure is developed aiming at determining the type and thickness of FRP jacket needed to achieve a certain level of ductility enhancement. The procedure starts with defining the stress strain curve, which is used to obtain moment curvature relationship then displacement ductility ratio of reinforced concrete cross-sections subjected to bending moment and axial force. Three sets of published experimental tests were used to validate the numerical procedure. Comparisons between predicted results obtained by using the proposed procedure and actual results of experimental tests proved the reliability of the proposed procedure.

Keywords: columns, confinement, ductility, FRP, numerical

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Authors: Laidi Maamar, Hanini Salah

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The present work investigates the potential of artificial neural network (ANN) model to predict the horizontal global solar radiation (HGSR). The ANN is developed and optimized using three years meteorological database from 2011 to 2013 available at the meteorological station of Blida (Blida 1 university, Algeria, Latitude 36.5°, Longitude 2.81° and 163 m above mean sea level). Optimal configuration of the ANN model has been determined by minimizing the Root Means Square Error (RMSE) and maximizing the correlation coefficient (R2) between observed and predicted data with the ANN model. To select the best ANN architecture, we have conducted several tests by using different combinations of parameters. A two-layer ANN model with six hidden neurons has been found as an optimal topology with (RMSE=4.036 W/m²) and (R²=0.999). A graphical user interface (GUI), was designed based on the best network structure and training algorithm, to enhance the users’ friendliness application of the model.

Keywords: artificial neural network, global solar radiation, solar energy, prediction, Algeria

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Authors: V. D. Thi, M. Li, M. Khelifa, M. El Ganaoui, Y. Rogaume

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This paper presents a two-dimensional model to study the heat and moisture transfer through porous building materials. Dynamic and static coupled models of heat and moisture transfer in porous material under low temperature are presented and the coupled models together with variable initial and boundary conditions have been considered in an analytical way and using the finite element method. The resulting coupled model is converted to two nonlinear partial differential equations, which is then numerically solved by an implicit iterative scheme. The numerical results of temperature and moisture potential changes are compared with the experimental measurements available in the literature. Predicted results demonstrate validation of the theoretical model and effectiveness of the developed numerical algorithms. It is expected to provide useful information for the porous building material design based on heat and moisture transfer model.

Keywords: finite element method, heat transfer, moisture transfer, porous materials, wood

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Authors: Abiodun Musbau Lawal, Sunday Samson Babalola, Uzor Friday Ordu

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Issue of employees counterproductive work behavior in government owned organization in emerging economies has continued to be a major concern. This study investigated the factors of pay satisfaction, intent to leave and age as predictors of counterproductive work behavior among non-academic employee in a Nigerian federal government owned university. A sample of 200 non-academic employees completed questionnaires. Hierarchical multiple regression was conducted to determine the contribution of each of the predictor variables on the criterion variable on counterproductive work behavior. Results indicate that age of participants (β = -.18; p < .05) significantly independently predicted CWB by accounting for 3% of the explained variance. Addition of pay satisfaction (β = -.14; p < .05) significantly accounted for 5% of the explained variance, while intent to leave (β = -.17; p < .05) further resulted in 8% of the explained variance in counterproductive work behavior. The importance of these findings with regards to reduction in counterproductive work behavior is highlighted.

Keywords: counterproductive, work behaviour, pay satisfaction, intent to leave

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Authors: S. A. Naeini, A. Khalili

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Nowadays, tunnels with different applications are developed, and most of them are related to subway tunnels. The excavation of shallow tunnels that pass under municipal utilities is very important, and the surface settlement control is an important factor in the design. The study sought to analyze the settlement and also to find an appropriate model in order to predict the behavior of the tunnel in Tehran subway line-3. The displacement in these sections is also determined by using numerical analyses and numerical modeling. In addition, the Adaptive Neuro-Fuzzy Inference System (ANFIS) method is utilized by Hybrid training algorithm. The database pertinent to the optimum network was obtained from 46 subway tunnels in Iran and Turkey which have been constructed by the new Austrian tunneling method (NATM) with similar parameters based on type of their soil. The surface settlement was measured, and the acquired results were compared to the predicted values. The results disclosed that computing intelligence is a good substitute for numerical modeling.

Keywords: settlement, Subway Line, FLAC3D, ANFIS Method

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Authors: Karim Hamidi Machekposhti, Hossein Sedghi, Abdolrasoul Telvari, Hossein Babazadeh

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Rainfall and runoff phenomenon is a chaotic and complex outcome of nature which requires sophisticated modelling and simulation methods for explanation and use. Time Series modelling allows runoff data analysis and can be used as forecasting tool. In the paper attempt is made to model river runoff data and predict the future behavioural pattern of river based on annual past observations of annual river runoff. The river runoff analysis and predict are done using ARIMA model. For evaluating the efficiency of prediction to hydrological events such as rainfall, runoff and etc., we use the statistical formulae applicable. The good agreement between predicted and observation river runoff coefficient of determination (R²) display that the ARIMA (4,1,1) is the suitable model for predicting Karkheh River runoff at Iran.

Keywords: time series modelling, ARIMA model, river runoff, Karkheh River, CLS method

Procedia PDF Downloads 341

Authors: Sondos M. Hammad, Sherin M. ElGokhy, Mahmoud M. Fahmy, Elsayed A. Sallam

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In this paper, an ensemble-based Support Vector Machine (SVM) classification approach is proposed. It is used for miRNA prediction. Three problems, commonly associated with previous approaches, are alleviated. These problems arise due to impose assumptions on the secondary structural of premiRNA, imbalance between the numbers of the laboratory checked miRNAs and the pseudo-hairpins, and finally using a training data set that does not consider all the varieties of samples in different species. We aggregate the predicted outputs of three well-known SVM classifiers; namely, Triplet-SVM, Virgo and Mirident, weighted by their variant features without any structural assumptions. An additional SVM layer is used in aggregating the final output. The proposed approach is trained and then tested with balanced data sets. The results of the proposed approach outperform the three base classifiers. Improved values for the metrics of 88.88% f-score, 92.73% accuracy, 90.64% precision, 96.64% specificity, 87.2% sensitivity, and the area under the ROC curve is 0.91 are achieved.

Keywords: MiRNAs, SVM classification, ensemble algorithm, assumption problem, imbalance data

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Authors: N. Alhazmi

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Knowing the thermodynamics properties of hydrocarbons is vital when it comes to analyzing the related chemical reaction outcomes and understanding the reaction process, especially in terms of petrochemical industrial applications, combustions, and catalytic reactions. However, measuring the thermodynamics properties experimentally is time-consuming and costly. In this paper, Gaussian process regression (GPR) has been used to directly predict the main thermodynamic properties - standard enthalpy of formation, standard entropy, and heat capacity -for more than 360 cyclic and non-cyclic alkanes, alkenes, and alkynes. A simple workflow has been proposed that can be applied to directly predict the main properties of any hydrocarbon by knowing its descriptors and chemical structure and can be generalized to predict the main properties of any material. The model was evaluated by calculating the statistical error R², which was more than 0.9794 for all the predicted properties.

Keywords: thermodynamic, Gaussian process regression, hydrocarbons, regression, supervised learning, entropy, enthalpy, heat capacity

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Authors: Heri Kuswanto, Brina Miftahurrohmah, Fatkhurokhman Fauzi

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Southeast Asia has experienced rising temperatures and is predicted to reach a 1.5°C increase by 2030, which is earlier than the Paris Agreement target. Solar Radiation Management (SRM) has been proposed as an alternative to combat global warming. This research investigates changes in the annual maximum temperature (TXx) with and without SRM over southeast Asia. We examined outputs from three ensemble members of the Geoengineering Large Ensemble Project (GLENS) experiment for the period 2051 to 2080. One ensemble member generated outputs that significantly deviated from the others, leading to the removal of ensemble 3 from the impact analysis. Our observations indicate that the magnitude of TXx changes with SRM is heterogeneous across countries. We found that SRM significantly reduces TXx levels compared to historical periods. Furthermore, SRM can reduce temperatures by up to 5°C compared to scenarios without SRM, with even more pronounced effects in Thailand, Cambodia, Laos, and Myanmar. This indicates that SRM can mitigate climate change by lowering future TXx levels.

Keywords: solar radiation management, GLENS, extreme, temperature, ensemble

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Authors: Marlon Gallo, Eduardo Miguel, Laura Oca, Eneko Gonzalez, Unai Iraola

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The heat generation of an energy storage system is an essential topic when designing a battery pack and its cooling system. Heat generation estimation is used together with thermal models to predict battery temperature in operation and adapt the design of the battery pack and the cooling system to these thermal needs guaranteeing its safety and correct operation. In the present work, a comparison between the use of a heat flux sensor (HFS) for indirect measurement of heat losses in a cell and the widely used and simplified version of Bernardi’s equation for estimation is presented. First, a Li-ion cell is thermally characterized with an HFS to measure the thermal parameters that are used in a first-order lumped thermal model. These parameters are the equivalent thermal capacity and the thermal equivalent resistance of a single Li-ion cell. Static (when no current is flowing through the cell) and dynamic (making current flow through the cell) tests are conducted in which HFS is used to measure heat between the cell and the ambient, so thermal capacity and resistances respectively can be calculated. An experimental platform records current, voltage, ambient temperature, surface temperature, and HFS output voltage. Second, an equivalent circuit model is built in a Matlab-Simulink environment. This allows the comparison between the generated heat predicted by Bernardi’s equation and the HFS measurements. Data post-processing is required to extrapolate the heat generation from the HFS measurements, as the sensor records the heat released to the ambient and not the one generated within the cell. Finally, the cell temperature evolution is estimated with the lumped thermal model (using both HFS and Bernardi’s equation total heat generation) and compared towards experimental temperature data (measured with a T-type thermocouple). At the end of this work, a critical review of the results obtained and the possible mismatch reasons are reported. The results show that indirectly measuring the heat generation with HFS gives a more precise estimation than Bernardi’s simplified equation. On the one hand, when using Bernardi’s simplified equation, estimated heat generation differs from cell temperature measurements during charges at high current rates. Additionally, for low capacity cells where a small change in capacity has a great influence on the terminal voltage, the estimated heat generation shows high dependency on the State of Charge (SoC) estimation, and therefore open circuit voltage calculation (as it is SoC dependent). On the other hand, with indirect measuring the heat generation with HFS, the resulting error is a maximum of 0.28ºC in the temperature prediction, in contrast with 1.38ºC with Bernardi’s simplified equation. This illustrates the limitations of Bernardi’s simplified equation for applications where precise heat monitoring is required. For higher current rates, Bernardi’s equation estimates more heat generation and consequently, a higher predicted temperature. Bernardi´s equation accounts for no losses after cutting the charging or discharging current. However, HFS measurement shows that after cutting the current the cell continues generating heat for some time, increasing the error of Bernardi´s equation.

Keywords: lithium-ion battery, heat flux sensor, heat generation, thermal characterization

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Authors: N. Agon, T. Kavka, J. Vierendeels, M. Hrabovský, G. Van Oost

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A plasma jet model was developed with a rigorous method for calculating the thermophysical properties of the gas mixture without mixing rules. A simplified model approach to account for the anode effects was incorporated in this model to allow the valorization of the simulations with experimental results. The radial heat transfer was under-predicted by the model because of the limitations of the radiation model, but the calculated evolution of centerline temperature, velocity and gas composition downstream of the torch exit corresponded well with the measured values. The CFD modeling of thermal plasmas is either focused on development of the plasma arc or the flow of the plasma jet outside of the plasma torch. In the former case, the Maxwell equations are coupled with the Navier-Stokes equations to account for electromagnetic effects which control the movements of the anode arc attachment. In plasma jet simulations, however, the computational domain starts from the exit nozzle of the plasma torch and the influence of the arc attachment fluctuations on the plasma jet flow field is not included in the calculations. In that case, the thermal plasma flow is described by temperature, velocity and concentration profiles at the torch exit nozzle and no electromagnetic effects are taken into account. This simplified approach is widely used in literature and generally acceptable for plasma torches with a circular anode inside the torch chamber. The unique DC hybrid water/gas-stabilized plasma torch developed at the Institute of Plasma Physics of the Czech Academy of Sciences on the other hand, consists of a rotating anode disk, located outside of the torch chamber. Neglecting the effects of the anode arc attachment downstream of the torch exit nozzle leads to erroneous predictions of the flow field. With the simplified approach introduced in this model, the Joule heating between the exit nozzle and the anode attachment position of the plasma arc is modeled by a volume heat source and the jet deflection caused by the anode processes by a momentum source at the anode surface. Furthermore, radiation effects are included by the net emission coefficient (NEC) method and diffusion is modeled with the combined diffusion coefficient method. The time-averaged simulation results are compared with numerous experimental measurements. The radial temperature profiles were obtained by spectroscopic measurements at different axial positions downstream of the exit nozzle. The velocity profiles were evaluated from the time-dependent evolution of flow structures, recorded by photodiode arrays. The shape of the plasma jet was compared with charge-coupled device (CCD) camera pictures. In the cooler regions, the temperature was measured by enthalpy probe downstream of the exit nozzle and by thermocouples in radial direction around the torch nozzle. The model results correspond well with the experimental measurements. The decrease in centerline temperature and velocity is predicted within an acceptable range and the shape of the jet closely resembles the jet structure in the recorded images. The temperatures at the edge of the jet are underestimated due to the absence of radial radiative heat transfer in the model.

Keywords: anode arc attachment, CFD modeling, experimental comparison, thermal plasma jet

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Authors: N. Jinesh, K. Shankar

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This article presents a method of using the one dimensional piezo-electric patch on beam model for structural identification. A hybrid element constituted of one dimensional beam element and a PZT sensor is used with reduced material properties. This model is convenient and simple for identification of beams. Accuracy of this element is first verified against a corresponding 3D finite element model (FEM). The structural identification is carried out as an inverse problem whereby parameters are identified by minimizing the deviation between the predicted and measured voltage response of the patch, when subjected to excitation. A non-classical optimization algorithm Particle Swarm Optimization is used to minimize this objective function. The signals are polluted with 5% Gaussian noise to simulate experimental noise. The proposed method is applied on beam structure and identified parameters are stiffness and damping. The model is also validated experimentally.

Keywords: inverse problem, particle swarm optimization, PZT patches, structural identification

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Authors: Zahide Tepeli Temiz, Itir Tari Comert

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Attachment patterns based on early emotional interactions between infant and primary caregiver continue to be influential in adult life, in terms of mental health and behaviors of individuals. Several studies reveal that infant-caregiver relationships have impressed the affect regulation, coping with stressful and negative situations, general satisfaction of life, and self image in adulthood, besides the attachment styles. The present study aims to examine the relationships between university students’ attachment style and their self-esteem, alexithymic features, satisfaction of life, and level of resilience. In line with this aim, the hypothesis of the prediction of attachment styles (anxious and avoidant) over life satisfaction, self-esteem, alexithymia, and psychological resilience was tested. Additionally, in this study Structural Equational Modeling was conducted to investigate the mediational role of self-esteem in the relationship between attachment styles and alexithymia, life satisfaction, and resilience. This model was examined with path analysis. The sample of the research consists of 425 university students who take education from several region of Turkey. The participants who sign the informed consent completed the Demographic Information Form, Experiences in Close Relationships-Revised, Rosenberg Self-Esteem Scale, The Satisfaction with Life Scale, Toronto Alexithymia Scale, and Resilience Scale for Adults. According to results, anxious, and avoidant dimensions of insecure attachment predicted the self-esteem score and alexithymia in positive direction. On the other hand, these dimensions of attachment predicted life satisfaction in negative direction. The results of linear regression analysis indicated that anxious and avoidant attachment styles didn’t predict the resilience. This result doesn’t support the theory and research indicating the relationship between attachment style and psychological resilience. The results of path analysis revealed the mediational role self esteem in the relation between anxious, and avoidant attachment styles and life satisfaction. In addition, SEM analysis indicated the indirect effect of attachment styles over alexithymia and resilience besides their direct effect. These findings support the hypothesis of this research relation to mediating role of self-esteem. Attachment theorists suggest that early attachment experiences, including supportive and responsive family interactions, have an effect on resilience to harmful situations in adult life, ability to identify, describe, and regulate emotions and also general satisfaction with life. Several studies examining the relationship between attachment styles and life satisfaction, alexithymia, and psychological resilience draw attention to mediational role of self-esteem. Results of this study support the theory of attachment patterns with the mediation of self-image influence the emotional, cognitive, and behavioral regulation of person throughout the adulthood. Therefore, it is thought that any intervention intended for recovery in attachment relationship will increase the self-esteem, life satisfaction, and resilience level, on the one side, decrease the alexithymic features, on the other side.

Keywords: alexithymia, anxious attachment, avoidant attachment, life satisfaction, path analysis, resilience, self-esteem, structural equation

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Authors: Megan E. Davies

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With the intention of identifying cognitive processes uniquely involved in the dark triad personality traits of psychopathy, Machiavellianism, and narcissism, this study aimed to determine further potential differences and parameters of individual traits by explaining a statistically significant amount of variance between the constructs of manipulativeness, impulsiveness, grit, and need for cognition within the dark triad. Applying a cross-sectional design, N = 96 participants self-reported using the MACH-IV, SRP-III, NFC-S, and Grit Scale for Perseverance and Passion for Long-Term Goals. Hierarchical regression analyses showed that only manipulativeness predicted Machiavellianism, whereas manipulativeness and impulsiveness were found to have predictive qualities for psychopathy. Overall, these results found areas of discrepancy and overlap between manipulation and impulsivity regarding psychopathy and Machiavellianism. Additionally, this study serves to preliminarily eliminate the Need for Cognition and grit as predictive variables for Machiavellianism and psychopathy.

Keywords: Machiavellianism, psychopathy, manipulation, impulsiveness, need for cognition, grit, dark triad

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Authors: Nur Köprülü

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One of the main questions that have arisen after the Arab uprisings has centered on whether they will lead to democratic transition and what the roles of Islamist actors will be. It has become apparent today that one of the key outcomes has been the partial, if not total, overthrow of authoritarian regimes in some cases. So, this article aims to analyse three synchronous upshots brought about by the uprisings, referring to patterns of state formation in the Maghreb and Mashreq. One of the main outcomes has been the persistence of authoritarianism in various forms, and the fragility of the Arab republics coping with the protests as compared to the more resilient character of the monarchies. In addition, none of the uprisings has brought an Islamist organization to incontestable power, as some predicted. However, ‘old’ Islamist actors have since re-emerged as key players, namely the Muslim Brotherhood in Tunisia, Egypt, Jordan and elsewhere. Thus, to understand the synthesis of change and continuity in the Middle East in the aftermath of the Arab Spring, analysing the changing faces of authoritarianism in the region and the impact on Islamists in both the Maghreb and the Mashreq is imperative.

Keywords: authoritarianism, democratization, Arab spring, Islamists

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Authors: S. Naveen, V. Sivasubramanian

Abstract:

A modeling theory is proposed to consider the vaporization of LNG during its contact with water following its release from an underwater source. The spillage of LNG underwater can lead to a decrease in the surface temperature of water and subsequent freezing. This can in turn affect the heat flux distribution from the released LNG onto the water surrounding it. The available models predict the rate of vaporization considering the surface of contact as a solid wall, and considering the entire phenomena as a solid-liquid operation. This assumption greatly under-predicted the overall heat transfer on LNG water interface. The vaporization flux would first decrease during the film boiling, followed by an increase during the transition boiling and a steady decrease during the nucleate boiling. A superheat theory is introduced to enhance the accuracy in the prediction of the heat transfer between LNG and water. The work suggests that considering the superheat theory can greatly enhance the prediction of LNG vaporization on underwater releases and also help improve the study of overall thermodynamics.

Keywords: evaporation rate, heat transfer, LNG vaporization, underwater LNG release

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Authors: Beulah Rani Inbanathan

Abstract:

In the present era, it is vivid from the numerous outcomes that data privacy is being compromised in various ways. Machine learning is one technology that uses the centralized server, and then data is given as input which is being analyzed by the algorithms present on this mentioned server, and hence outputs are predicted. However, each time the data must be sent by the user as the algorithm will analyze the input data in order to predict the output, which is prone to threats. The solution to overcome this issue is federated learning, where the models alone get updated while the data resides on the local machine and does not get exchanged with the other local models. Nevertheless, even on these local models, there are chances of data poisoning, and it is crystal clear from various experiments done by many people. This paper delves into many ways where data poisoning occurs and the many methods through which it is prevalent that data poisoning still exists. It includes the poisoning attacks on IoT devices, Edge devices, Autoregressive model, and also, on Industrial IoT systems and also, few points on how these could be evadible in order to protect our data which is personal, or sensitive, or harmful when exposed.

Keywords: data poisoning, federated learning, Internet of Things, edge computing

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Authors: Subrato Saha, Yun-Hyun Cho

Abstract:

In electric power steering (EPS), spoke type brushless ac (BLAC) motors offer distinct advantages over other electric motor types in terms torque smoothness, reliability and efficiency. This paper deals with the shape optimization of spoke type BLAC motor, in order to reduce cogging torque. This paper examines 3 steps skewing rotor angle, optimizing rotor core edge and rotor overlap length for reducing cogging torque in spoke type BLAC motor. The methods were applied to existing machine designs and their performance was calculated using finite- element analysis (FEA). Prototypes of the machine designs were constructed and experimental results obtained. It is shown that the FEA predicted the cogging torque to be nearly reduce using those methods.

Keywords: EPS, 3-Step skewing, spoke type BLAC, cogging torque, FEA, optimization

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Authors: Muhammed Jamiu Mustapha, Jamiu Folarin, Stephen Obiri Agyei, Rasheed Ademola Adebiyi, Mutiu Iyanda Lasisi

Abstract:

The role of the media in political discourse cannot be overemphasized as they form an important part of societal development. The media institution is considered the fourth estate of the realm because it serves as a check and balance to the arms of government (Executive, Legislature and Judiciary) especially in a democratic setup, and makes public office holders accountable to the people. They scrutinize the political candidates and conduct a holistic analysis of the achievement of the government in order to make the people’s representative accountable to the electorates. The media in Nigeria play a seminal role in shaping how people vote during elections. Newspaper headlines are catchy phrases that easily capture the attention of the audience and call them (audience) to action. Research conducted on newspaper headlines looks at the linguistic aspect and how the tenses used has a resultant effect on peoples’ attitude and behaviour. Communication scholars have also conducted studies that interrogate whether newspaper headlines influence peoples' voting patterns and decisions. Propaganda and negative stories about political opponents are stapling features in electioneering campaigns. Nigerian newspaper readers have the characteristic of scanning newspaper headlines. And the question is whether politicians effectively have played into this tendency to brand opponents negatively, based on half-truths and inadequate information. This study illustrates major trends in the Nigerian political landscape looking at the past four presidential elections and frames the progress of the research in the extant body of political propaganda research in Africa. The study will use the quantitative content analysis of newspaper headlines from 2007 to 2019 to be able to ascertain whether newspaper headlines had any effect on the election results of the presidential elections during these years. This will be supplemented by Key Informant Interviews of political scientists or experts to draw further inferences from the quantitative data. Drawing on newspaper headlines of selected newspapers in Nigeria that have a political propaganda angle for the presidential elections, the analysis will correspond to and complements extant descriptions of how the field of political propaganda has been developed in Nigeria, providing evidence of four presidential elections that have shaped Nigerian politics. Understanding the development of the behavioural change of the electorates provide useful context for trend analysis in political propaganda communication. The findings will contribute to how newspaper headlines are used partly or wholly to decide the outcome of presidential elections in Nigeria.

Keywords: newspaper headlines, political propaganda, presidential elections, trend analysis

Procedia PDF Downloads 235