Search results for: peak estimation

Authors: Asmamaw Yehun, Tsegaye Kassa, Addisu Hunegnaw, Martin Vermeer

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There are various models to estimate the neutral atmospheric parameter values, such as in-suite and reanalysis datasets from numerical models. Accurate estimated values of the atmospheric parameters are useful for weather forecasting and, climate modeling and monitoring of climate change. Recently, Global Navigation Satellite System (GNSS) measurements have been applied for atmospheric sounding due to its robust data quality and wide horizontal and vertical coverage. The Global Positioning System (GPS) solutions that includes tropospheric parameters constitute a reliable set of data to be assimilated into climate models. The objective of this paper is, to estimate the neutral atmospheric parameters such as Wet Zenith Delay (WZD), Precipitable Water Vapour (PWV) and Total Zenith Delay (TZD) using six selected GPS stations in the equatorial regions, more precisely, the Ethiopian GPS stations from 2012 to 2015 observational data. Based on historic estimated GPS-derived values of PWV, we forecasted the PWV from 2015 to 2030. During data processing and analysis, we applied GAMIT-GLOBK software packages to estimate the atmospheric parameters. In the result, we found that the annual averaged minimum values of PWV are 9.72 mm for IISC and maximum 50.37 mm for BJCO stations. The annual averaged minimum values of WZD are 6 cm for IISC and maximum 31 cm for BDMT stations. In the long series of observations (from 2012 to 2015), we also found that there is a trend and cyclic patterns of WZD, PWV and TZD for all stations.

Keywords: atmosphere, GNSS, neutral atmosphere, precipitable water vapour

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Authors: Gizem Eser Erdek

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This study is research on predicting the remaining life of industrial cutting tools used in the industrial production process with deep learning methods. When the life of cutting tools decreases, they cause destruction to the raw material they are processing. This study it is aimed to predict the remaining life of the cutting tool based on the damage caused by the cutting tools to the raw material. For this, hole photos were collected from the hole-drilling machine for 8 months. Photos were labeled in 5 classes according to hole quality. In this way, the problem was transformed into a classification problem. Using the prepared data set, a model was created with convolutional neural networks, which is a deep learning method. In addition, VGGNet and ResNet architectures, which have been successful in the literature, have been tested on the data set. A hybrid model using convolutional neural networks and support vector machines is also used for comparison. When all models are compared, it has been determined that the model in which convolutional neural networks are used gives successful results of a %74 accuracy rate. In the preliminary studies, the data set was arranged to include only the best and worst classes, and the study gave ~93% accuracy when the binary classification model was applied. The results of this study showed that the remaining life of the cutting tools could be predicted by deep learning methods based on the damage to the raw material. Experiments have proven that deep learning methods can be used as an alternative for cutting tool life estimation.

Keywords: classification, convolutional neural network, deep learning, remaining life of industrial cutting tools, ResNet, support vector machine, VggNet

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Authors: Ahmad Rabby

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The demographic trend analyses of Bombay-duck from time series catch data using CMSY and BSM for the first time in Bangladesh. During 2000-2018, CMSY indicates average lowest production in 2000 and highest in 2018. This has been used in the estimation of prior biomass by the default rules. Possible 31030 viable trajectories for 3422 r-k pairs were found by the CMSY analysis and the final estimates for intrinsic rate of population increase (r) was 1.19 year-1 with 95% CL= 0.957-1.48 year-1. The carrying capacity(k) of Bombay-duck was 283×103 tons with 95% CL=173×103 - 464×103 tons and MSY was 84.3×103tons year-1, 95% CL=49.1×103-145×103 tons year-1. Results from Bayesian state-space implementation of the Schaefer production model (BSM) using catch & CPUE data, found catchabilitiy coefficient(q) was 1.63 ×10-6 from lcl=1.27×10-6 to ucl=2.10×10-6 and r= 1.06 year-1 with 95% CL= 0.727 - 1.55 year-1, k was 226×103 tons with 95% CL=170×103-301×103 tons and MSY was 60×103 tons year-1 with 95% CL=49.9 ×103- 72.2 ×103 tons year-1. Results for Bombay-duck fishery management based on BSM assessment from time series catch data illustrated that, Fmsy=0.531 with 95% CL =0.364 - 0.775 (if B > 1/2 Bmsy then Fmsy =0.5r); Fmsy=0.531 with 95% CL =0.364-0.775 (r and Fmsy are linearly reduced if B < 1/2Bmsy). Biomass in 2018 was 110×103 tons with 2.5th to 97.5th percentile=82.3-155×103 tons. Relative biomass (B/Bmsy) in last year was 0.972 from 2.5th percentile to 97.5th percentile=0.728 -1.37. Fishing mortality in last year was 0.738 with 2.5th-97.5th percentile=0.525-1.37. Exploitation F/Fmsy was 1.39, from 2.5th to 97.5th percentile it was 0.988 -1.86. The biological reference points of B/BMSY was smaller than 1.0, while F/FMSY was higher than 1.0 revealed an over-exploitation of the fishery, indicating that more conservative management strategies are required for Bombay-duck fishery.

Keywords: biological reference points, catchability coefficient, carrying capacity, intrinsic rate of population increase

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Authors: Eyup Dogan

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One criticism of the energy-growth-environment literature, to the best of our knowledge, is that only a few studies analyze the influence of tourism on CO₂ emissions even though tourism sector is closely related to the environment. The other criticism is the selection of methodology. Panel estimation techniques that fail to consider both heterogeneity and cross-sectional dependence across countries can cause forecasting errors. To fulfill the mentioned gaps in the literature, this study analyzes the impacts of real GDP, renewable energy and tourism on the levels of carbon dioxide (CO₂) emissions for the top 10 most-visited countries around the world. This study focuses on the top 10 touristic (most-visited) countries because they receive about the half of the worldwide tourist arrivals in late years and are among the top ones in 'Renewables Energy Country Attractiveness Index (RECAI)'. By looking at Pesaran’s CD test and average growth rates of variables for each country, we detect the presence of cross-sectional dependence and heterogeneity. Hence, this study uses second generation econometric techniques (cross-sectionally augmented Dickey-Fuller (CADF), and cross-sectionally augmented IPS (CIPS) unit root test, the LM bootstrap cointegration test, and the DOLS and the FMOLS estimators) which are robust to the mentioned issues. Therefore, the reported results become accurate and reliable. It is found that renewable energy mitigates the pollution whereas real GDP and tourism contribute to carbon emissions. Thus, regulatory policies are necessary to increase the awareness of sustainable tourism. In addition, the use of renewable energy and the adoption of clean technologies in tourism sector as well as in producing goods and services play significant roles in reducing the levels of emissions.

Keywords: air pollution, tourism, renewable energy, income, panel data

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Authors: Mourad Morsli, Mohamed Tahiri, Azzedine Samdi

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The Cities are the urbanized territories most favorable to the consumption of resources (materials, energy). In Morocco, the economic capital Casablanca is one of them, with its 4M inhabitants and its 60% share in the economic and industrial activity of the kingdom. In the absence of legal status in force, urban development has favored the generation of millions of tons of demolition and construction waste scattered in open spaces causing a significant nuisance to the environment and citizens. Hence the main objective of our work is to valorize concrete waste. The representative wastes are mainly concrete, concrete, and fired clay bricks, ceramic tiles, marble panels, gypsum, and scrap metal. The work carried out includes: geolocation with a combination of artificial intelligence, GIS, and Google Earth, which allowed the estimation of the quantity of these wastes per site; then the sorting, crushing, grinding, and physicochemical characterization of the collected samples allowed the definition of the exploitation ways for each extracted fraction for integrated management of the said wastes. In the present work, we proceeded to the exploitation of the fractions obtained after sieving the representative samples to incorporate them in the manufacture of new ecological materials for construction. These formulations prepared studies have been tested and characterized: physical criteria (specific surface, resistance to flexion and compression) and appearance (cracks, deformation). We will present in detail the main results of our research work and also describe the specific properties of each material developed.

Keywords: demolition and construction waste, GIS combination software, inert waste recovery, ecological materials, Casablanca, Morocco

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Authors: Andreina Giustiniani, Massimiliano Oliveri

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Rhythmic activity in different frequencies could subserve distinct functional roles during visual perception and visual mental imagery. In particular, alpha band activity is thought to play a role in active inhibition of both task-irrelevant regions and processing of non-relevant information. In the present blind placebo-controlled study we applied alpha transcranial alternating current stimulation (tACS) in the occipital cortex both during a basic visual perception and a visual working memory task. To understand if the role of alpha is more related to a general inhibition of distractors or to an inhibition of task-irrelevant regions, we added a non visual distraction to both the tasks.Sixteen adult volunteers performed both a simple perception and a working memory task during 10 Hz tACS. The electrodes were placed over the left and right occipital cortex, the current intensity was 1 mA peak-to-baseline. Sham stimulation was chosen as control condition and in order to elicit the skin sensation similar to the real stimulation, electrical stimulation was applied for short periods (30 s) at the beginning of the session and then turned off. The tasks were split in two sets, in one set distracters were included and in the other set, there were no distracters. Motor interference was added by changing the answer key after subjects completed the first set of trials.The results show that alpha tACS improves working memory only when no motor distracters are added, suggesting a role of alpha tACS in inhibiting non-relevant regions rather than in a general inhibition of distractors. Additionally, we found that alpha tACS does not affect accuracy and hit rates during the visual perception task. These results suggest that alpha activity in the occipital cortex plays a different role in perception and working memory and it could optimize performance in tasks in which attention is internally directed, as in this working memory paradigm, but only when there is not motor distraction. Moreover, alpha tACS improves working memory performance by means of inhibition of task-irrelevant regions while it does not affect perception.

Keywords: alpha activity, interference, perception, working memory

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Authors: Khanh To Duc, Monica Chiogna, Gianfranco Adimari

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With three diagnostic categories, assessment of the performance of diagnostic tests is achieved by the analysis of the receiver operating characteristic (ROC) surface, which generalizes the ROC curve for binary diagnostic outcomes. The volume under the ROC surface (VUS) is a summary index usually employed for measuring the overall diagnostic accuracy. When the true disease status can be exactly assessed by means of a gold standard (GS) test, unbiased nonparametric estimators of the ROC surface and VUS are easily obtained. In practice, unfortunately, disease status verification via the GS test could be unavailable for all study subjects, due to the expensiveness or invasiveness of the GS test. Thus, often only a subset of patients undergoes disease verification. Statistical evaluations of diagnostic accuracy based only on data from subjects with verified disease status are typically biased. This bias is known as verification bias. Here, we consider the problem of correcting for verification bias when continuous diagnostic tests for three-class disease status are considered. We assume that selection for disease verification does not depend on disease status, given test results and other observed covariates, i.e., we assume that the true disease status, when missing, is missing at random. Under this assumption, we discuss several solutions for ROC surface analysis based on imputation and re-weighting methods. In particular, verification bias-corrected estimators of the ROC surface and of VUS are proposed, namely, full imputation, mean score imputation, inverse probability weighting and semiparametric efficient estimators. Consistency and asymptotic normality of the proposed estimators are established, and their finite sample behavior is investigated by means of Monte Carlo simulation studies. Two illustrations using real datasets are also given.

Keywords: imputation, missing at random, inverse probability weighting, ROC surface analysis

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Authors: R. Hocine, A. Boudjemai, A. Amrani, K. Belkacemi

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Temperature rising is a negative factor in almost all systems. It could cause by self heating or ambient temperature. In solar photovoltaic cells this temperature rising affects on the behavior of cells. The ability of a PV module to withstand the effects of periodic hot-spot heating that occurs when cells are operated under reverse biased conditions is closely related to the properties of the cell semi-conductor material. In addition, the thermal effect also influences the estimation of the maximum power point (MPP) and electrical parameters for the PV modules, such as maximum output power, maximum conversion efficiency, internal efficiency, reliability, and lifetime. The cells junction temperature is a critical parameter that significantly affects the electrical characteristics of PV modules. For practical applications of PV modules, it is very important to accurately estimate the junction temperature of PV modules and analyze the thermal characteristics of the PV modules. Once the temperature variation is taken into account, we can then acquire a more accurate MPP for the PV modules, and the maximum utilization efficiency of the PV modules can also be further achieved. In this paper, the three-Dimensional Transmission Line Matrix (3D-TLM) method was used to map the surface temperature distribution of solar cells while in the reverse bias mode. It was observed that some cells exhibited an inhomogeneity of the surface temperature resulting in localized heating (hot-spot). This hot-spot heating causes irreversible destruction of the solar cell structure. Hot spots can have a deleterious impact on the total solar modules if individual solar cells are heated. So, the results show clearly that the solar cells are capable of self-generating considerable amounts of heat that should be dissipated very quickly to increase PV module's lifetime.

Keywords: thermal effect, conduction, heat dissipation, thermal conductivity, solar cell, PV module, nodes, 3D-TLM

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Authors: Amanina Iymia Jeffree, Reena Thriumani, Mohammad Iqbal Omar, Ammar Zakaria, Yumi Zuhanis Has-Yun Hashim, Ali Yeon Md Shakaff

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Metabolite profiling is a strategy to be approached in the pattern recognition method focused on three types of cancer cell line that driving the most to death specifically lung, breast, and colon cancer. The purpose of this study was to discriminate the VOCs pattern among cancerous and control group based on metabolite profiling. The sampling was executed utilizing the cell culture technique. All culture flasks were incubated till 72 hours and data collection started after 24 hours. Every running sample took 24 minutes to be completed accordingly. The comparative metabolite patterns were identified by the implementation of headspace-solid phase micro-extraction (HS-SPME) sampling coupled with gas chromatography-mass spectrometry (GCMS). The optimizations of the main experimental variables such as oven temperature and time were evaluated by response surface methodology (RSM) to get the optimal condition. Volatiles were acknowledged through the National Institute of Standards and Technology (NIST) mass spectral database and retention time libraries. To improve the reliability of significance, it is of crucial importance to eliminate background noise which data from 3rd minutes to 17th minutes were selected for statistical analysis. Targeted metabolites, of which were annotated as known compounds with the peak area greater than 0.5 percent were highlighted and subsequently treated statistically. Volatiles produced contain hundreds to thousands of compounds; therefore, it will be optimized by chemometric analysis, such as principal component analysis (PCA) as a preliminary analysis before subjected to a pattern classifier for identification of VOC samples. The volatile organic compound profiling has shown to be significantly distinguished among cancerous and control group based on metabolite profiling.

Keywords: in vitro cancer cell line, metabolite profiling, pattern recognition, volatile organic compounds

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Authors: Tiao Chang, Ivan Caballero, Hong Zhou

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Streams carry water and sediment naturally by maintaining channel dimensions, pattern, and profile over time. Watershed erosion as a natural process has occurred to contribute sediment to streams over time. The formation of channel dimensions is complex. This study is to relate quantifiable and consistent channel dimensions at the bankfull stage to the corresponding watershed erosion estimation by the Revised Universal Soil Loss Equation (RUSLE). Twelve sites of which drainage areas range from 7 to 100 square miles in the Hocking River Basin of Ohio were selected for the bankfull geometry determinations including width, depth, cross-section area, bed slope, and drainage area. The twelve sub-watersheds were chosen to obtain a good overall representation of the Hocking River Basin. It is of interest to determine how these bankfull channel dimensions are related to the soil erosion of corresponding sub-watersheds. Soil erosion is a natural process that has occurred in a watershed over time. The RUSLE was applied to estimate erosions of the twelve selected sub-watersheds where the bankfull geometry measurements were conducted. These quantified erosions of sub-watersheds are used to investigate correlations with bankfull channel dimensions including discharge, channel width, channel depth, cross-sectional area, and pebble distribution. It is found that drainage area, bankfull discharge and cross-sectional area correlates strongly with watershed erosion well. Furthermore, bankfull width and depth are moderately correlated with watershed erosion while the particle size, D50, of channel bed sediment is not well correlated with watershed erosion.

Keywords: watershed, stream, sediment, channel

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Authors: Malik Abid Hussain Khokhar, Muhammad Adnan Tahir, Hisham Bin Hafeez Awan

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Continuous environmental determinism and climatic change in the entire globe due to increasing land surface temperature (LST) has become a vital phenomenon nowadays. LST is accelerating because of increasing greenhouse gases in the environment which results of melting down ice caps, ice sheets and glaciers. It has not only worse effects on vegetation and water bodies of the region but has also severe impacts on monsoon areas in the form of capricious rainfall and monsoon failure extensive precipitation. Environment can be monitored with the help of various geographic information systems (GIS) based algorithms i.e. SC (Single), DA (Dual Angle), Mao, Sobrino and SW (Split Window). Estimation of LST is very much possible from digital image processing of satellite imagery. This paper will encompass extraction of LST of Abbottabad using SW technique of GIS and Remote Sensing over last ten years by means of Landsat 7 ETM+ (Environmental Thematic Mapper) and Landsat 8 vide their Thermal Infrared (TIR Sensor) and Optical Land Imager (OLI sensor less Landsat 7 ETM+) having 100 m TIR resolution and 30 m Spectral Resolutions. These sensors have two TIR bands each; their emissivity and spectral radiance will be used as input statistics in SW algorithm for LST extraction. Emissivity will be derived from Normalized Difference Vegetation Index (NDVI) threshold methods using 2-5 bands of OLI with the help of e-cognition software, and spectral radiance will be extracted TIR Bands (Band 10-11 and Band 6 of Landsat 7 ETM+). Accuracy of results will be evaluated by weather data as well. The successive research will have a significant role for all tires of governing bodies related to climate change departments.

Keywords: environment, Landsat 8, SW Algorithm, TIR

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Authors: Medhanie Gebremedhin Gebru, Alex Schechter

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Dimethyl ether (DME) possesses several advantages over other small organic molecules such as methanol, ethanol, and ammonia in terms of providing higher energy density, being less toxic, and having lower Nafion membrane crossover. However, the absence of an active and stable catalyst has been the bottleneck that hindered the commercialization of direct DME fuel cells. A Vulcan XC72 carbon-supported ternary metal catalyst, Pt₃Pd₃Sn₂/C is reported to have yielded the highest specific power density (90 mW mg-¹PGM) as compared to other catalysts tested fordirect DME fuel cell (DDMEFC). However, the micropores and sulfur groups present in Vulcan XC72 hinder the fuel utilization by causing Pt agglomeration and sulfur poisoning. Vulcan XC72 having a high carbon sp³ hybridization content, is also prone to corrosion. Therefore, carbon supports such as multi-walled carbon nanotube (MWCNT), black pearl 2000 (BP2000), and their cold N2 plasma-treated counterpartswere tested to further enhance the activity of the catalyst, and the outputs with these carbons were compared with the originally used support. Detailed characterization of the pristine and carbon supports was conducted. Electrochemical measurements in three-electrode cells and laboratory prototype fuel cells were conducted.Pt₃Pd₃Sn₂/BP2000 exhibited excellent performance in terms of electrochemical active surface area (ECSA), peak current density (jp), and DME oxidation charge (Qoxi). The effect of the plasma activation on the activity improvement was observed only in the case of MWCNT while having little or no effect on the other carbons. A Pt₃Pd₃Sn₂ supported on the optimized mixture of carbons containing 75% plasma-activated MWCNT and 25% BP2000 (Pt₃Pd₃Sn₂/75M25B) provided the highest reported power density of 117 mW mg-1PGM using an anode loading of1.55 mgPGMcm⁻².

Keywords: DME, DDMEFC, ternary metal catalyst, carbon support, plasma activation

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Authors: Ehsan Pegah, Huabei Liu

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Determination of the internal friction angle (φ) in natural soil deposits is an important issue in geotechnical engineering. The main objective of this study was to examine the evaluation of this parameter in overconsolidated granular soil deposits by using the P-wave velocity and the anisotropic components of S-wave velocity (i.e., both the vertical component (SV) and the horizontal component (SH) of S-wave). To this end, seventeen pairs of P-wave and S-wave seismic refraction profiles were carried out at three different granular sites in Iran using non-invasive seismic wave methods. The acquired shot gathers were processed, from which the P-wave, SV-wave and SH-wave velocities were derived. The reference values of φ and overconsolidation ratio (OCR) in the soil deposits were measured through laboratory tests. By assuming cross-anisotropy of the soils, the P-wave and S-wave velocities were utilized to develop an equation for calculating the coefficient of lateral earth pressure at-rest (K₀) based on the theory of elasticity for a cross-anisotropic medium. In addition, to develop an equation for OCR estimation in granular geomaterials in terms of SH/SV velocity ratios, a general regression analysis was performed on the resulting information from this research incorporated with the respective data published in the literature. The calculated K₀ values coupled with the estimated OCR values were finally employed in the Mayne and Kulhawy formula to evaluate φ in granular soil deposits. The results showed that reliable values of φ could be estimated based on the seismic wave velocities. The findings of this study may be used as the appropriate approaches for economic and non-invasive determination of in-situ φ in granular soil deposits using the surface seismic surveys.

Keywords: angle of internal friction, overconsolidation ratio, granular soils, P-wave velocity, SV-wave velocity, SH-wave velocity

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Authors: Thakur Pushpawati, Singh Vinita, Agrawal Sarita, Mohapatra Eli

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Polycystic ovary syndrome (PCOS) is a disease of endocrine and frequently encountered in women in their reproductive period, and it is characterized by clinical features of anovulation, clinical and biochemical features of hyperandrogenism, and PCOS morphology on ultrasonographic examination. In Indian scenario, only a few studies are available on the correlation of serum 25-dihydroxy vitamin D3 level and insulin level. The present study is a prospective case-control study and aims to estimate the concentration of serum 25-dihydroxy vitamin D3 and insulin resistance and determine the association of serum 25-dihydroxy vitamin D3 with insulin resistance in PCOS women of 18-40 years age group. In this study, the primary objective is to estimate the concentration of 25-dihydroxy vitamin D3, insulin, glycaemic status, calcium and phosphorus levels in 18-40 year age women with polycystic ovary syndrome and to compare these parameters with age and BMI matched healthy control of same age group women. The secondary objective is to determine the association between 25-dihydroxy vitamin D3 concentration and insulin resistance among PCOS cases in 18-40 years age group women. This study was carried on at outpatient Department of Obstetrics & Gynaecology, Aiims Raipur. It took one year from the date of approval. In case, 32 women were diagnosed (Diagnosed PCOS cases as per Rotterdoms criteria among women of 18-40 years of age), as control group 32 women of 18-40 years of age were diagnosed As a result, serum insulin level was elevated among PCOS women along with 25-dihydroxy vitamin D3 deficiency.Conclude up, PCOS is more common in the age group of 20-40 years. There is a strong correlation between vitamin D deficiency and insulin resistance among PCOS patients.

Keywords: vitamin D, insulin resistance, PCOS, reproductive age group

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Authors: Xiaohua Zhu, Lingling Ma, Yongguang Zhao

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Leaf Area Index (LAI) is a key structural characteristic of crops and plays a significant role in precision agricultural management and farmland ecosystem modeling. However, LAI retrieved from different resolution data contain a scaling bias due to the spatial heterogeneity and model non-linearity, that is, there is scale effect during multi-scale LAI estimate. In this article, a typical farmland in semi-arid regions of Chinese Inner Mongolia is taken as the study area, based on the combination of PROSPECT model and SAIL model, a multiple dimensional Look-Up-Table (LUT) is generated for multiple crops LAI estimation from unmanned aerial vehicle (UAV) hyperspectral data. Based on Taylor expansion method and computational geometry model, a scale transfer model considering both difference between inter- and intra-class is constructed for scale effect analysis of LAI inversion over inhomogeneous surface. The results indicate that, (1) the LUT method based on classification and parameter sensitive analysis is useful for LAI retrieval of corn, potato, sunflower and melon on the typical farmland, with correlation coefficient R2 of 0.82 and root mean square error RMSE of 0.43m2/m-2. (2) The scale effect of LAI is becoming obvious with the decrease of image resolution, and maximum scale bias is more than 45%. (3) The scale effect of inter-classes is higher than that of intra-class, which can be corrected efficiently by the scale transfer model established based Taylor expansion and Computational geometry. After corrected, the maximum scale bias can be reduced to 1.2%.

Keywords: leaf area index (LAI), scale effect, UAV-based hyperspectral data, look-up-table (LUT), remote sensing

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Authors: Sara Seddiki, Maazouzi Abdelhak

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The main objective of this modest work is to follow the physicochemical and bacteriological evolution of the wastewater from the town of Bechar subjected to purification by filtration according to various local supports, namely Sable and Terrill by reducing nuisances that undergo the receiving environment (Oued Bechar) and therefore make this water source reusable in different areas. The study first made it possible to characterize the urban wastewater of the Bechar wadi, which presents an environmental threat, thus allowing an estimation of the pollutant load, the chemical oxygen demand COD (145 mg / l) and the biological oxygen demand BOD5 (72 mg / l) revealed that these waters are less biodegradable (COD / BOD5 ratio = 0.62), have a fairly high conductivity (2.76 mS/cm), and high levels of mineral matter presented by chlorides and sulphates 390 and 596.1 mg / l respectively, with a pH of 8.1. The characterization of the sand dune (Beni Abbes) shows that quartz (97%) is the most present mineral. The granular analysis allowed us to determine certain parameters like the uniformity coefficient (CU) and the equivalent diameter, and scanning electron microscope (SEM) observations and X-ray analysis were performed. The study of filtered wastewater shows satisfactory and very encouraging treatment results, with complete elimination of total coliforms and streptococci and a good reduction of total aerobic germs in the sand and clay-sand filter. A good yield has been reported in the sand Terrill filter for the reduction of turbidity. The rates of reduction of organic matter in terms of the biological oxygen demand, in chemical oxygen demand recorded, are of the order of 60%. The elimination of sulphates is 40% for the sand filter.

Keywords: urban wastewater, filtration, bacteriological and physicochemical parameters, sand, Terrill, Oued Bechar

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Authors: G. Balaji, R. Balasundaraprabhu, S. Prasanna, M. D. Kannan, K. Sivakumaran, David Mcilroy

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Copper Zin tin sulphide (Cu2ZnSnS4 or CZTS) is found to be better alternative to Copper Indium gallium diselenide as absorber layers in thin film based solar cells due to the utilisation of earth-abundant materials in the midst of lower toxicity. In the present study, Cu2ZnSnS4 thin films were prepared on soda lime glass using (CuS, ZnS, SnS) targets and were deposited by three different stacking orders, using RF Magnetron sputtering. The substrate temperature was fixed at 300 °C during the depositions. CZTS thin films were characterized using X-ray diffraction, X-ray photoelectron spectroscopy, Raman spectroscopy and UV-Vis-NIR spectroscopy. All the samples exhibited X-ray peaks pertaining to (112) kesterite phase of CZTS, along with the presence of a predominant wurtzite CZTS phase. X-ray photoelectron spectroscopy revealed the presence of all the elements in all the samples. The change in stacking order clearly shows that it affects the structural and phase properties of the films. Relative atomic concentrations of Zn, Cu, Sn and S, which are determined by high-resolution XPS core level spectra integrated peak areas revealed that the CZTS films exhibit inhomogeneity in both stoichiometry and elemental composition. Raman spectroscopy studies on the film showed the presence of CZTS phase. The energy band gap of the CZTS thin films was found to be in the range of 1.5 eV to 1.6 eV. The films were then annealed at 450 °C for 5 hrs and it was found that the predominant nature of the X-ray peaks has transformed from Wurtzite to Kesterite phase which is highly desirable for absorber layers in thin film solar cells. The optimized CZTS layer was used as an absorber layer in thin film solar cells. ZnS and CdS were used as buffer layers which in turn prepared by Hot wall epitaxy technique. Gallium doped Zinc oxide was used as a transparent conducting oxide. The solar cell structure Glass/Mo/CZTS/CdS or ZnS/GZO has been fabricated, and solar cell parameters were measured.

Keywords: earth-abundant, Kesterite, RF sputtering, thin film solar cells

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Authors: Navneet Singh Deora, Aastha Deswal, H. N. Mishra

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Pasta is one of the most widely consumed food products around the world. Rapid determination of the moisture content in pasta will assist food processors to provide online quality control of pasta during large scale production. Rapid Fourier transform near-infrared method (FT-NIR) was developed for determining moisture content in pasta. A calibration set of 150 samples, a validation set of 30 samples and a prediction set of 25 samples of pasta were used. The diffuse reflection spectra of different types of pastas were measured by FT-NIR analyzer in the 4,000-12,000 cm-1 spectral range. Calibration and validation sets were designed for the conception and evaluation of the method adequacy in the range of moisture content 10 to 15 percent (w.b) of the pasta. The prediction models based on partial least squares (PLS) regression, were developed in the near-infrared. Conventional criteria such as the R2, the root mean square errors of cross validation (RMSECV), root mean square errors of estimation (RMSEE) as well as the number of PLS factors were considered for the selection of three pre-processing (vector normalization, minimum-maximum normalization and multiplicative scatter correction) methods. Spectra of pasta sample were treated with different mathematic pre-treatments before being used to build models between the spectral information and moisture content. The moisture content in pasta predicted by FT-NIR methods had very good correlation with their values determined via traditional methods (R2 = 0.983), which clearly indicated that FT-NIR methods could be used as an effective tool for rapid determination of moisture content in pasta. The best calibration model was developed with min-max normalization (MMN) spectral pre-processing (R2 = 0.9775). The MMN pre-processing method was found most suitable and the maximum coefficient of determination (R2) value of 0.9875 was obtained for the calibration model developed.

Keywords: FT-NIR, pasta, moisture determination, food engineering

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Authors: Sylvie Studente

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Despite the increase in international students migrating to the UK, the transition from home environment to a host institution abroad can be overwhelming for many students due to acculturative stressors. These stressors are reported to peak within the first six months of transitioning into study abroad which has determinantal impacts for Higher Education Institutions. These impacts include; increased drop-out rates and overall decreases in academic performance. Research suggests that belongingness can negate acculturative stressors through providing opportunities for students to form necessary social connections. In response to this universities have focussed on utilising technology to create learning communities with the most commonly deployed being social media, blogs, and discussion forums. Despite these attempts, the application of technology in supporting international students is still ambiguous. With the reported growing popularity of mobile devices among students and accelerations in learning technology owing to the COVID-19 pandemic, the potential is recognised to address this challenge via the use of chatbot technology. Whilst traditionally, chatbots were deployed as conversational agents in business domains, they have since been applied to the field of education. Within this emerging area of research, a gap exists in addressing the educational value of chatbots over and above the traditional service orientation categorisation. The proposed study seeks to extend upon current understandings by investigating the challenges faced by international students in studying abroad and exploring the potential of chatbots as a solution to assist students’ acculturation. There has been growing interest in the application of chatbot technology to education accelerated by the shift to online learning during the COVID-19 pandemic. Although interest in educational chatbots has surged, there is a lack of consistency in the research area in terms of guidance on the design to support international students in HE. This gap is widened when considering the additional challenge of supporting multicultural international students with diverse. Diversification in education is rising due to increases in migration trends for international study. As global opportunities for education increase, so does the need for multiculturally inclusive learning support.

Keywords: chatbots, education, international students, acculturation

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Authors: Zain Ul Hassan, Muhammad Zain Ul Abadin, Muhammad Zubair Khan

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Unmanned aerial vehicles (UAVs) have now become of predominant importance for various operations, and an immense amount of work is going on in this specific category. The structural stability and life of these UAVs is key factor that should be considered while deploying them to different intelligent operations as their failure leads to loss of sensitive real-time data and cost. This paper presents an applied research on the development of a structural health monitoring system for a UAV designed and fabricated by deploying modular approach. Firstly, a modular UAV has been designed which allows to dismantle and to reassemble the components of the UAV without effecting the whole assembly of UAV. This novel approach makes the vehicle very sustainable and decreases its maintenance cost to a significant value by making possible to replace only the part leading to failure. Then the SHM for the designed architecture of the UAV had been specified as a combination of wings integrated with strain gauges, on-board data logger, bridge circuitry and the ground station. For the research purpose sensors have only been attached to the wings being the most load bearing part and as per analysis was done on ANSYS. On the basis of analysis of the load time spectrum obtained by the data logger during flight, fatigue life of the respective component has been predicted using fracture mechanics techniques of Rain Flow Method and Miner’s Rule. Thus allowing us to monitor the health of a specified component time to time aiding to avoid any failure.

Keywords: fracture mechanics, rain flow method, structural health monitoring system, unmanned aerial vehicle

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Authors: Hayriye Anıl, Görkem Kar

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In addition to being rich in renewable energy resources, Turkey is one of the countries that promise potential in geothermal energy production with its high installed power, cheapness, and sustainability. Increasing imbalance penalties become an economic burden for organizations since geothermal generation plants cannot maintain the balance of supply and demand due to the inadequacy of the production forecasts given in the day-ahead market. A better production forecast reduces the imbalance penalties of market participants and provides a better imbalance in the day ahead market. In this study, using machine learning, deep learning, and, time series methods, the total generation of the power plants belonging to Zorlu Natural Electricity Generation, which has a high installed capacity in terms of geothermal, was estimated for the first one and two weeks of March, then the imbalance penalties were calculated with these estimates and compared with the real values. These modeling operations were carried out on two datasets, the basic dataset and the dataset created by extracting new features from this dataset with the feature engineering method. According to the results, Support Vector Regression from traditional machine learning models outperformed other models and exhibited the best performance. In addition, the estimation results in the feature engineering dataset showed lower error rates than the basic dataset. It has been concluded that the estimated imbalance penalty calculated for the selected organization is lower than the actual imbalance penalty, optimum and profitable accounts.

Keywords: machine learning, deep learning, time series models, feature engineering, geothermal energy production forecasting

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Authors: Heeba A. Gurku

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Introduction: Cone Beam CT(CBCT) images play an integral part in proper patient positioning in cancer patients undergoing radiation therapy treatment. But these images are low in quality. The purpose of this study is to generate high-quality synthetic CT images from CBCT using generative models. Material and Methods: This study utilized two datasets from The Cancer Imaging Archive (TCIA) 1) Lung cancer dataset of 20 patients (with full view CBCT images) and 2) Pancreatic cancer dataset of 40 patients (only 27 patients having limited view images were included in the study). Cycle Generative Adversarial Networks (GAN) and its variant Attention Guided Generative Adversarial Networks (AGGAN) models were used to generate the synthetic CTs. Models were evaluated by visual evaluation and on four metrics, Structural Similarity Index Measure (SSIM), Peak Signal Noise Ratio (PSNR) Mean Absolute Error (MAE) and Root Mean Square Error (RMSE), to compare the synthetic CT and original CT images. Results: For pancreatic dataset with limited view CBCT images, our study showed that in Cycle GAN model, MAE, RMSE, PSNR improved from 12.57to 8.49, 20.94 to 15.29 and 21.85 to 24.63, respectively but structural similarity only marginally increased from 0.78 to 0.79. Similar, results were achieved with AGGAN with no improvement over Cycle GAN. However, for lung dataset with full view CBCT images Cycle GAN was able to reduce MAE significantly from 89.44 to 15.11 and AGGAN was able to reduce it to 19.77. Similarly, RMSE was also decreased from 92.68 to 23.50 in Cycle GAN and to 29.02 in AGGAN. SSIM and PSNR also improved significantly from 0.17 to 0.59 and from 8.81 to 21.06 in Cycle GAN respectively while in AGGAN SSIM increased to 0.52 and PSNR increased to 19.31. In both datasets, GAN models were able to reduce artifacts, reduce noise, have better resolution, and better contrast enhancement. Conclusion and Recommendation: Both Cycle GAN and AGGAN were significantly able to reduce MAE, RMSE and PSNR in both datasets. However, full view lung dataset showed more improvement in SSIM and image quality than limited view pancreatic dataset.

Keywords: CT images, CBCT images, cycle GAN, AGGAN

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Authors: Mai. M. Toughan, Ahmed A. A. Sallam, Ashraf O. Abd El-Latif

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Termites are eusocial insects that are found on all continents except Antarctica. Termites have serious destructive impact, damaging local huts and crops of poor subsistence. The annual cost of termite damage and its control is determined in the billions globally. In Egypt, most of these damages are due to the subterranean termite species especially the sand termite, P. hypostoma. Pyrethroids became the primary weapon for subterranean termite control, after the use of chlorpyrifos as a soil termiticide was banned. Despite the important role of pyrethroids in termite control, its extensive use in pest control led to the eventual rise of insecticide resistance which may make many of the pyrethroids ineffective. The ability to diagnose the precise mechanism of pyrethroid resistance in any insect species would be the key component of its management at specified location for a specific population. In the present study, detailed toxicological and biochemical studies was conducted on the mechanism of pyrethroid resistance in P. hypostoma. The susceptibility of field populations of P. hypostoma against deltamethrin, α-cypermethrin and ƛ-cyhalothrin was evaluated. The obtained results revealed that the workers of P. hypostoma have developed high resistance level against the tested pyrethroids. Studies carried out through estimation of detoxification enzyme activity indicated that enhanced esterase and cytochrome P450 activities were probably important mechanisms for pyrethroid resistance in field populations. Elevated esterase activity and also additional esterase isozyme were observed in the pyrethroid-resistant populations compared to the susceptible populations. Strong positive correlation between cytochrome P450 activity and pyrethroid resistance was also reported. |Deltamethrin could be recommended as a resistance-breaking pyrethroid that is active against resistant populations of P. hypostoma.

Keywords: Psammotermes hypostoma, pyrethroid resistance, esterase, cytochrome P450

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Authors: Samy A. Khalil, U. Ali Rahoma

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The measurements of solar radiation, satellite data has been routinely utilize to estimate solar energy. However, the temporal coverage of satellite data has some limits. The reanalysis, also known as "retrospective analysis" of the atmosphere's parameters, is produce by fusing the output of NWP (Numerical Weather Prediction) models with observation data from a variety of sources, including ground, and satellite, ship, and aircraft observation. The result is a comprehensive record of the parameters affecting weather and climate. The effectiveness of reanalysis datasets (ERA-5) for North Africa was evaluate against high-quality surfaces measured using statistical analysis. Estimating the distribution of global solar radiation (GSR) over five chosen areas in North Africa through ten-years during the period time from 2011 to 2020. To investigate seasonal change in dataset performance, a seasonal statistical analysis was conduct, which showed a considerable difference in mistakes throughout the year. By altering the temporal resolution of the data used for comparison, the performance of the dataset is alter. Better performance is indicate by the data's monthly mean values, but data accuracy is degraded. Solar resource assessment and power estimation are discuses using the ERA-5 solar radiation data. The average values of mean bias error (MBE), root mean square error (RMSE) and mean absolute error (MAE) of the reanalysis data of solar radiation vary from 0.079 to 0.222, 0.055 to 0.178, and 0.0145 to 0.198 respectively during the period time in the present research. The correlation coefficient (R2) varies from 0.93 to 99% during the period time in the present research. This research's objective is to provide a reliable representation of the world's solar radiation to aid in the use of solar energy in all sectors.

Keywords: solar energy, ERA-5 analysis data, global solar radiation, North Africa

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Authors: Percy Galvez, Anatoly Petukhin, Paul Somerville, Ken Miyakoshi, Kojiro Irikura, Daniel Peter

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Physics-based dynamic rupture modelling is necessary for estimating parameters such as rupture velocity and slip rate function that are important for ground motion simulation, but poorly resolved by observations, e.g. by seismic source inversion. In order to generate a large number of physically self-consistent rupture models, whose rupture process is consistent with the spatio-temporal heterogeneity of past earthquakes, we use multicycle simulations under the heterogeneous rate-and-state (RS) friction law for a 45deg dip-slip fault. We performed a parametrization study by fully dynamic rupture modeling, and then, a set of spontaneous source models was generated in a large magnitude range (Mw > 7.0). In order to validate rupture models, we compare the source scaling relations vs. seismic moment Mo for the modeled rupture area S, as well as average slip Dave and the slip asperity area Sa, with similar scaling relations from the source inversions. Ground motions were also computed from our models. Their peak ground velocities (PGV) agree well with the GMPE values. We obtained good agreement of the permanent surface offset values with empirical relations. From the heterogeneous rupture models, we analyzed parameters, which are critical for ground motion simulations, i.e. distributions of slip, slip rate, rupture initiation points, rupture velocities, and source time functions. We studied cross-correlations between them and with the friction weakening distance Dc value, the only initial heterogeneity parameter in our modeling. The main findings are: (1) high slip-rate areas coincide with or are located on an outer edge of the large slip areas, (2) ruptures have a tendency to initiate in small Dc areas, and (3) high slip-rate areas correlate with areas of small Dc, large rupture velocity and short rise-time.

Keywords: earthquake dynamics, strong ground motion prediction, seismic engineering, source characterization

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Authors: Mehmet Akif Bütüner, İlhan Koşalay

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Hydroelectric power plants (HEPPs) are renewable energy power plants with the highest installed power in the world. While the control systems operating in these power plants ensure that the system operates at the desired operating point, it is also responsible for stopping the relevant unit safely in case of any malfunction. While these control systems are expected not to miss signals that require stopping, on the other hand, it is desired not to cause unnecessary stops. In traditional control systems including modern systems with SCADA infrastructure, alarm conditions to create warnings or trip conditions to put relevant unit out of service automatically are usually generated with predefined limits regardless of different operating conditions. This approach results in alarm/trip conditions to be less likely to detect minimal changes which may result in serious malfunction scenarios in near future. With the methods proposed in this research, routine behavior of the oil circulation of hydraulic governor of a HEPP will be modeled with machine learning methods using historical data obtained from SCADA system. Using the created model and recently gathered data from control system, oil pressure of hydraulic accumulators will be estimated. Comparison of this estimation with the measurements made and recorded instantly by the SCADA system will help to foresee failure before becoming worse and determine remaining useful life. By using model outputs, maintenance works will be made more planned, so that undesired stops are prevented, and in case of any malfunction, the system will be stopped or several alarms are triggered before the problem grows.

Keywords: hydroelectric, governor, anomaly detection, machine learning, regression

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Authors: Aqsa Kanwal, Min Zhang, Faisal Sharaf, Li Chengtao

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The globe is facing increasing challenges of plastic pollution due to single-use of plastic-based packaging material. The plastic material is continuously being dumped into the natural environment, which causes serious harm to the entire ecosystem. Polymer degradation in nature is very difficult, so the use of biodegradable polymers instead of conventional polymers can mitigate this issue. Due to the good mechanical properties and biodegradability, aliphatic-aromatic polymers are being widely commercialized. Due to the advancement in molecular biology, many studies have reported specific microbes that can effectively degrade PBAT. Aliphatic polyesters undergo hydrolytic cleavage of ester groups, so they can be easily degraded by microorganisms. In this study, we investigated the enzymatic degradation of poly (butylene adipate terephthalate) (PBAT) copolymer using lipase B from Candida Antarctica (CALB). Results of the study displayed approximately 5.16 % loss in PBAT mass after 2 days which significantly increased to approximately 15.7 % at the end of the experiment (12 days) as compared to blank. The pH of the degradation solution also displayed significant reduction and reached the minimum value of 6.85 at the end of the experiment. The structure and morphology of PBAT after degradation were characterized by FTIR, XRD, SEM, and TGA. FTIR analysis showed that after degradation many peaks become weaker and the peak at 2950 cm-1 almost disappeared after 12 days. The XRD results indicated that as the degradation time increases the intensity of diffraction peaks slightly increases as compared to the blank PBAT. TGA analysis also confirmed the successful degradation of PBAT with time. SEM micrographs further confirmed that degradation has occurred. Hence, biodegradable polymers can widely be used. The effect of PBAT biodegradation on plant growth was also studied and it was found that PBAT has no toxic effect on the growth of plants. Hence PBAT can be employed in a wide range of applications.

Keywords: aliphatic-aromatic co-polyesters, polybutylene adipate terephthalate, lipase (CALB), biodegradation, plant growth

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Authors: Mohamed Ali Ben Halima, Malik Koubi, Joseph Lanfranchi, Yohan Wloczysiak

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This article assesses the consequences on the frequency and duration of ordinary sick leave of the January 2012 and 2018 reforms modifying the scope of sick leave reimbursement in the French civil service. These reforms introduce a one-day waiting period which removes the compensation for the first day of ordinary sick leave. In order to evaluate these reforms, we use an administrative database from the National Pension Fund for local public employees (FPT). The first important result of our data analysis is that the one-day waiting period was not introduced at the same time in the French Local Public Service establishments, or even never in some. This peculiarity allows for an identification strategy using a difference-in-differences method based on the definition at each date of groups of employees treated and not treated by the reform, since establishments that apply the one-day waiting period coexist with establishments that do not apply it. Two types of estimators are used for this evaluation: individual and time fixed effects estimators and DIDM estimators which correct for the biases of the Two Way Fixed Effects one. The results confirm that the change in the sick pay system decreases the probability of having at least one ordinary sick leave as well as the number and duration of these episodes. On the other hand, the estimates show that longer leave episodes are not less affected than shorter ones. Finally, the validity tests of the estimators support the results obtained for the second period of 2018-2019, but suggest estimation biases for the period 2012-2013. The extent to which the endogeneity of the choices of implementation of the reform at the local level impact these estimates needs to be further tested.

Keywords: sick leave, one-day waiting period, territorial civil service, public policy evaluation

Procedia PDF Downloads 76

Authors: Stefano Barone

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Seismic retrofit of buildings through base isolation represents a consolidated protection strategy against earthquakes. It consists in decoupling the ground motion from that of the structure and introducing anti-seismic devices at the base of the building, characterized by high horizontal flexibility and medium/high dissipative capacity. This allows to protect structural elements and to limit damages to non-structural ones. For these reasons, full functionality is guaranteed after an earthquake event. Base isolation is applied extensively to both new and existing buildings. For the latter, it usually does not require any interruption of the structure use and occupants evacuation, a special advantage for strategic buildings such as schools, hospitals, and military buildings. This paper describes the application of seismic isolation to three existing masonry buildings in Italy: Villa “La Maddalena” in Macerata (Marche region), “Giacomo Matteotti” and “Plinio Il Giovane” school buildings in Perugia (Umbria region). The seismic hazard of the sites is characterized by a Peak Ground Acceleration (PGA) of 0.213g-0.287g for the Life Safety Limit State and between 0.271g-0.359g for the Collapse Limit State. All the buildings are isolated with a combination of free sliders type TETRON® CD with confined elastomeric disk and anti-seismic rubber isolators type ISOSISM® HDRB to reduce the eccentricity between the center of mass and stiffness, thus limiting torsional effects during a seismic event. The isolation systems are designed to lengthen the original period of vibration (i.e., without isolators) by at least three times and to guarantee medium/high levels of energy dissipation capacity (equivalent viscous damping between 12.5% and 16%). This allows the structures to resist 100% of the seismic design action. This article shows the performances of the supplied anti-seismic devices with particular attention to the experimental dynamic response. Finally, a special focus is given to the main site activities required to isolate a masonry building.

Keywords: retrofit, masonry buildings, seismic isolation, energy dissipation, anti-seismic devices

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Authors: Marko Batic, Nikola Tomasevic, Sanja Vranes

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One of the strongholds in the ubiquitous efforts related to the energy conservation and energy efficiency improvement is represented by the retrofit of high energy consumers in buildings. In general, HVAC systems represent the highest energy consumers in buildings. However they usually suffer from mal-operation and/or malfunction, causing even higher energy consumption than necessary. Various Fault Detection and Diagnosis (FDD) systems can be successfully employed for this purpose, especially when it comes to the application at a single device/unit level. In the case of more complex systems, where multiple devices are operating in the context of the same building, significant energy efficiency improvements can only be achieved through application of comprehensive FDD systems relying on additional higher level knowledge, such as their geographical location, served area, their intra- and inter- system dependencies etc. This paper presents a comprehensive FDD system that relies on the utilization of common knowledge repository that stores all critical information. The discussed system is deployed as a test-bed platform at the two at Fiumicino and Malpensa airports in Italy. This paper aims at presenting advantages of implementation of the knowledge base through the utilization of ontology and offers improved functionalities of such system through examples of typical queries and reasoning that enable derivation of high level energy conservation measures (ECM). Therefore, key SPARQL queries and SWRL rules, based on the two instantiated airport ontologies, are elaborated. The detection of high level irregularities in the operation of airport heating/cooling plants is discussed and estimation of energy savings is reported.

Keywords: airport ontology, knowledge management, ontology modeling, reasoning

Procedia PDF Downloads 528