Search results for: noise estimation

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

Procedia PDF Downloads 128

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

Procedia PDF Downloads 87

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

Procedia PDF Downloads 254

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

Procedia PDF Downloads 103

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

Procedia PDF Downloads 169

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

Procedia PDF Downloads 93

Authors: Kemal Efe Eseller, Göktuğ Yazici

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Laser-induced breakdown spectroscopy (LIBS) is a rapid optical atomic emission spectroscopy which is used for material identification and analysis with the advantages of in-situ analysis, elimination of intensive sample preparation, and micro-destructive properties for the material to be tested. LIBS delivers short pulses of laser beams onto the material in order to create plasma by excitation of the material to a certain threshold. The plasma characteristics, which consist of wavelength value and intensity amplitude, depends on the material and the experiment’s environment. In the present work, medicine samples’ spectrum profiles were obtained via LIBS. Medicine samples’ datasets include two different concentrations for both paracetamol based medicines, namely Aferin and Parafon. The spectrum data of the samples were preprocessed via filling outliers based on quartiles, smoothing spectra to eliminate noise and normalizing both wavelength and intensity axis. Statistical information was obtained and principal component analysis (PCA) was incorporated to both the preprocessed and raw datasets. The machine learning models were set based on two different train-test splits, which were 70% training – 30% test and 80% training – 20% test. Cross-validation was preferred to protect the models against overfitting; thus the sample amount is small. The machine learning results of preprocessed and raw datasets were subjected to comparison for both splits. This is the first time that all supervised machine learning classification algorithms; consisting of Decision Trees, Discriminant, naïve Bayes, Support Vector Machines (SVM), k-NN(k-Nearest Neighbor) Ensemble Learning and Neural Network algorithms; were incorporated to LIBS data of paracetamol based pharmaceutical samples, and their different concentrations on preprocessed and raw dataset in order to observe the effect of preprocessing.

Keywords: machine learning, laser-induced breakdown spectroscopy, medicines, principal component analysis, preprocessing

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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

Procedia PDF Downloads 88

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 77

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 529

Authors: P. S. Thein, S. Pramumijoyo, K. S. Brotopuspito, J. Kiyono, W. Wilopo, A. Furukawa, A. Setianto

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In this study, we estimated the seismic ground motion parameters based on microtremor measurements at Palu City. Several earthquakes have struck along the Palu-Koro Fault during recent years. The USGS epicenter, magnitude Mw 6.3 event that occurred on January 23, 2005 caused several casualties. We conducted a microtremor survey to estimate the strong ground motion distribution during the earthquake. From this survey we produced a map of the peak ground acceleration, velocity, seismic vulnerability index and ground shear strain maps in Palu City. We performed single observations of microtremor at 151 sites in Palu City. We also conducted 8-site microtremors array investigation to gain a representative determination of the soil condition of subsurface structures in Palu City. From the array observations, Palu City corresponds to relatively soil condition with Vs ≤ 300 m/s, the predominant periods due to horizontal vertical ratios (HVSRs) are in the range of 0.4 to 1.8 s and the frequency are in the range of 0.7 to 3.3 Hz. Strong ground motions of the Palu area were predicted based on the empirical stochastic green’s function method. Peak ground acceleration and velocity becomes more than 400 gal and 30 kine in some areas, which causes severe damage for buildings in high probability. Microtremor survey results showed that in hilly areas had low seismic vulnerability index and ground shear strain, whereas in coastal alluvium was composed of material having a high seismic vulnerability and ground shear strain indication.

Keywords: Palu-Koro fault, microtremor, peak ground acceleration, peak ground velocity, seismic vulnerability index

Procedia PDF Downloads 403

Authors: Salem Alghamdi

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Genotypes collected from farmers at a different region of Saudi Arabia as well as from Egyptian cultivar and a new line from Yamen. Seeds of these genotypes were grown in Dirab Agriculture Research Station, (Middle Region) and Al-Ahsa Palms and Dates Research Center (East region), during summer of 2015. Field experiments were laid out in randomized complete block design on the first week of June with three replications. Each experiment plot contained 6 rows 3m in length. Inter- and intra-row spacing was 60 and 25cm, respectively. Seed yield and its components were estimated in addition to qualitative characters on cowpea plants grown only in Dirab using cowpea descriptor from IPGRI, 1982. Seeds for chemical composite and antioxidant contents were analyzed. Highly significant differences were detected between genotypes in both locations and the combined of two locations for seed yield and its components. Mean data clearly show exceeded determine genotypes in seed yield while indeterminate genotypes had higher biological yield that divided cowpea genotypes to two main groups 1- forage genotypes (KSU-CO98, KSU-CO99, KSU-CO100, and KSU-CO104) that were taller and produce higher branches, biological yield and these are suitable to feed on haulm 2- food genotypes (KSU-CO101, KSU-CO102, and KSU-CO103) that produce higher seed yield with lower haulm and also these genotypes characters by high seed index and light seed color. Highly significant differences were recorded for locations in all studied characters except the number of branches, seed index, and biological yield, however, the interaction of genotype x location was significant only for plant height, the number of pods and seed yield per plant.

Keywords: Cowpea, genotypes, antioxidant contents, yield

Procedia PDF Downloads 250

Authors: My Linh Hoang, Van Dung Hoang

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Environmental, Social, and Governance (ESG) factors have become a focus for companies globally, as businesses are now focusing on long-term sustainable goals rather than only operating for the goals of profit maximization. According to recent research, in several countries, companies have shown positive results in their financial performance by improving their ESG performance. The construction industry is one of the most crucial components of social and economic development; as a result, considerations for ESG factors are becoming more and more essential for companies in this sector. In Vietnam, the construction industry has been growing rapidly in recent years; however, it has yet to be discussed and studied extensively in Vietnam how ESG factors create impacts on corporate financial performance in general and construction corporations’ financial performance in particular. This research aims to examine the relationship between ESG factors and financial indicators in construction companies from 2011 to 2021 through panel data analysis of 75 listed construction companies in Vietnam and to provide insights into how these companies can better integrate ESG considerations into their operations to enhance their financial performance. The data was analyzed through 3 main methods: descriptive statistics, correlation coefficient analysis applied to all dependent, explanatory and control variables, and panel data analysis method. In panel data analysis, the study uses the fixed effects model (FEM) and random effects model (REM). The Hausman test will be used to select which model is suitable to be used. The findings indicate that maintaining a strong commitment to ESG principles can have a positive impact on financial performance. Finally, FGLS estimation will be performed when the problem of autocorrelation and variable variance appears in the model. This is significant for all parties involved, including investors, company managers, decision-makers, and industry regulators.

Keywords: ESG, financial performance, construction company, Vietnam

Procedia PDF Downloads 82

Authors: Ashirgul Kozhagulova, Ainash Shabdirova, Galym Tokazhanov, Minh Nguyen

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The synthetic rocks have been advantageous over the natural rocks in terms of availability and the consistent studying the impact of a particular parameter. The artificial rocks can be fabricated using variety of techniques such as mixing sand and Portland cement or gypsum, firing the mixture of sand and fine powder of borosilicate glass or by in-situ precipitation of calcite solution. In this study, sodium silicate solution has been used as the cementing agent for the quartz sand. The molded soft cylindrical sandstone samples are placed in the gas-tight pressure vessel, where the hardening of the material takes place as the chemical reaction between carbon dioxide and the silicate solution progresses. The vessel allows uniform disperse of carbon dioxide and control over the ambient gas pressure. Current paper shows how the bonding material is initially distributed in the intergranular space and the surface of the sand particles by the usage of Electron Microscopy and the Energy Dispersive Spectroscopy. During the study, the strength of the cement bond as a function of temperature is observed. The impact of cementing agent dosage on the micro and macro characteristics of the sandstone is investigated. The analysis of the cement bond at micro level helps to trace the changes to particles bonding damage after a potential yielding. Shearing behavior and compressional response have been examined resulting in the estimation of the shearing resistance and cohesion force of the sandstone. These are considered to be main input values to the mathematical prediction models of sand production from weak clastic oil reservoir formations.

Keywords: artificial sanstone, cement bond, microstructure, SEM, triaxial shearing

Procedia PDF Downloads 163

Authors: Sladjana Popovic

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The concept of vertical space urbanization, defined in English as "air rights development," can be considered a mechanism for the development of public spaces in urban areas of high density. A chronological overview of the transformation of space within the vertical projection of the existing traffic infrastructure that penetrates through the central areas of a city is given in this paper through the analysis of two illustrative case studies: more advanced and recent - "Plot 13" in Boston, and less well-known European example of structures erected above highways throughout Italy - the "Pavesi auto grill" chain. The backbone of this analysis is the examination of the possibility of yielding air rights within the vertical projection of public structures in the two examples by considering the factors that would enable its potential application in capitals in Southeastern Europe. The cession of air rights in the Southeastern Europe region, as a phenomenon, has not been a recognized practice in urban planning. In a formal sense, legal and physical feasibility can be seen to some extent in local models of structures built above protected historical heritage (i.e., archaeological sites); however, the mechanisms of the legal process of assigning the right to use and develop air rights above public structures is not a recognized concept. The goal of the analysis is to shed light on the influence of institutional participants in the implementation of innovative solutions for vertical urbanization, as well as strategic planning mechanisms in public-private partnership models that would enable the implementation of the concept in the region. The main question is whether the manipulation of the vertical projection of space could provide for innovative urban solutions that overcome the deficit and excessive use of the available construction land, particularly above the dominant public spaces and traffic infrastructure that penetrate central parts of a city. Conclusions reflect upon vertical urbanization that can bridge the spatial separation of the city, reduce noise pollution and contribute to more efficient urban planning along main transportation corridors.

Keywords: air rights development, innovative urbanism, public-private partnership, transport infrastructure, vertical urbanization

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Authors: Ashis Mallick, Rajeev Ranjan

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The closed form solution for thermal stresses in an annular fin with hyperbolic profile is derived using Adomian decomposition method (ADM). The conductive-convective fin with variable thermal conductivity is considered in the analysis. The nonlinear heat transfer equation is efficiently solved by ADM considering insulated convective boundary conditions at the tip of fin. The constant of integration in the solution is to be estimated using minimum decomposition error method. The solution of temperature field is represented in a polynomial form for convenience to use in thermo-elasticity equation. The non-dimensional thermal stress fields are obtained using the ADM solution of temperature field coupled with the thermo-elasticity solution. The influence of the various thermal parameters in temperature field and stress fields are presented. In order to show the accuracy of the ADM solution, the present results are compared with the results available in literature. The stress fields in fin with hyperbolic profile are compared with those of uniform thickness profile. Result shows that hyperbolic fin profile is better choice for enhancing heat transfer. Moreover, less thermal stresses are developed in hyperbolic profile as compared to rectangular profile. Next, Nelder-Mead based simplex search method is employed for the inverse estimation of unknown non-dimensional thermal parameters in a given stress fields. Owing to the correlated nature of the unknowns, the best combinations of the model parameters which are satisfying the predefined stress field are to be estimated. The stress fields calculated using the inverse parameters give a very good agreement with the stress fields obtained from the forward solution. The estimated parameters are suitable to use for efficient and cost effective fin designing.

Keywords: Adomian decomposition, inverse analysis, hyperbolic fin, variable thermal conductivity

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Authors: Yunbin Deng

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Most existing applications of automatic speech recognition relies on cooperative subjects at a short distance to a microphone. Standoff speech recognition using microphone arrays can extend the subject to sensor distance somewhat, but it is still limited to only a few feet. As such, most deployed applications of standoff speech recognitions are limited to indoor use at short range. Moreover, these applications require air passway between the subject and the sensor to achieve reasonable signal to noise ratio. This study reports long range (50 feet) automatic speech recognition experiments using a Laser Doppler Vibrometer (LDV) sensor. This study shows that the LDV sensor modality can extend the speech acquisition standoff distance far beyond microphone arrays to hundreds of feet. In addition, LDV enables 'listening' through the windows for uncooperative subjects. This enables new capabilities in automatic audio and speech intelligence, surveillance, and reconnaissance (ISR) for law enforcement, homeland security and counter terrorism applications. The Polytec LDV model OFV-505 is used in this study. To investigate the impact of different vibrating materials, five parallel LDV speech corpora, each consisting of 630 speakers, are collected from the vibrations of a glass window, a metal plate, a plastic box, a wood slate, and a concrete wall. These are the common materials the application could encounter in a daily life. These data were compared with the microphone counterpart to manifest the impact of various materials on the spectrum of the LDV speech signal. State of the art deep neural network modeling approaches is used to conduct continuous speaker independent speech recognition on these LDV speech datasets. Preliminary phoneme recognition results using time-delay neural network, bi-directional long short term memory, and model fusion shows great promise of using LDV for long range speech recognition. To author’s best knowledge, this is the first time an LDV is reported for long distance speech recognition application.

Keywords: covert speech acquisition, distant speech recognition, DSR, laser Doppler vibrometer, LDV, speech intelligence surveillance and reconnaissance, ISR

Procedia PDF Downloads 175

Authors: Omar Bouledroua, Djamel Zelmati, Zahreddine Hafsi, Milos B. Djukic

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Transporting hydrogen gas through the existing natural gas pipeline network offers an efficient solution for energy storage and conveyance. Hydrogen generated from excess renewable electricity can be conveyed through the API 5L steel-made pipelines that already exist. In recent years, there has been a growing demand for the transportation of hydrogen through existing gas pipelines. Therefore, numerical and experimental tests are required to verify and ensure the mechanical integrity of the API 5L steel pipelines that will be used for pressurized hydrogen transportation. Internal pressure loading is likely to accelerate hydrogen diffusion through the internal pipe wall and consequently accentuate the hydrogen embrittlement of steel pipelines. Furthermore, pre-cracked pipelines are susceptible to quick failure, mainly under a time-dependent cyclic pressure loading that drives fatigue crack propagation. Meanwhile, after several loading cycles, the initial cracks will propagate to a critical size. At this point, the remaining service life of the pipeline can be estimated, and inspection intervals can be determined. This paper focuses on the hydrogen embrittlement of API 5L steel-made pipeline under cyclic pressure loading. Pressurized hydrogen gas is transported through a network of pipelines where demands at consumption nodes vary periodically. The resulting pressure profile over time is considered a cyclic loading on the internal wall of a pre-cracked pipeline made of API 5L steel-grade material. Numerical modeling has allowed the prediction of fatigue crack evolution and estimation of the remaining service life of the pipeline. The developed methodology in this paper is based on the ASME B31.12 standard, which outlines the guidelines for hydrogen pipelines.

Keywords: hydrogen embrittlement, pipelines, transient flow, cyclic pressure, fatigue crack growth

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Authors: Deniz Guven, Wil Ward, Jinming Duan, Li Bai

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Over the past two decades or so, Optical Coherence Tomography (OCT) has been used to diagnose retina and optic nerve diseases. The retinal nerve fibre layer, for example, is a powerful diagnostic marker for detecting and staging glaucoma. With the advances in optical imaging hardware, the adoption of OCT is now commonplace in clinics. More and more OCT images are being generated, and for these OCT images to have clinical applicability, accurate automated OCT image segmentation software is needed. Oct image segmentation is still an active research area, as OCT images are inherently noisy, with the multiplicative speckling noise. Simple edge detection algorithms are unsuitable for detecting retinal layer boundaries in OCT images. Intensity fluctuation, motion artefact, and the presence of blood vessels also decrease further OCT image quality. In this paper, we introduce a new method for segmenting three-dimensional (3D) OCT images. This involves the use of a Kalman filter, which is commonly used in computer vision for object tracking. The Kalman filter is applied to the 3D OCT image volume to track the retinal layer boundaries through the slices within the volume and thus segmenting the 3D image. Specifically, after some pre-processing of the OCT images, points on the retinal layer boundaries in the first image are identified, and curve fitting is applied to them such that the layer boundaries can be represented by the coefficients of the curve equations. These coefficients then form the state space for the Kalman Filter. The filter then produces an optimal estimate of the current state of the system by updating its previous state using the measurements available in the form of a feedback control loop. The results show that the algorithm can be used to segment the retinal layers in OCT images. One of the limitations of the current algorithm is that the curve representation of the retinal layer boundary does not work well when the layer boundary is split into two, e.g., at the optic nerve, the layer boundary split into two. This maybe resolved by using a different approach to representing the boundaries, such as b-splines or level sets. The use of a Kalman filter shows promise to developing accurate and effective 3D OCT segmentation methods.

Keywords: optical coherence tomography, image segmentation, Kalman filter, object tracking

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Authors: Sachin, Shantanu Arya, Gunjan Mehta, Md. Shamim Ansari

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The cross-modal influence of visual information on speech perception can be illustrated by the McGurk effect which is an illusion of hearing of syllable /ta/ when a listener listens one syllable, e.g.: /pa/ while watching a synchronized video recording of syllable, /ka/. The McGurk effect is an excellent tool to investigate multisensory integration in speech perception in both normal hearing and hearing impaired populations. As the visual cue is unaffected by noise, individuals with hearing impairment rely more than normal listeners on the visual cues.However, when non congruent visual and auditory cues are processed together, audiovisual interaction seems to occur differently in normal and persons with hearing impairment. Therefore, this study aims to observe the audiovisual interaction in speech perception in Cochlear Implant users compares the same with normal hearing children. Auditory stimuli was routed through calibrated Clinical audiometer in sound field condition, and visual stimuli were presented on laptop screen placed at a distance of 1m at 0 degree azimuth. Out of 4 presentations, if 3 responses were a fusion, then McGurk effect was considered to be present. The congruent audiovisual stimuli /pa/ /pa/ and /ka/ /ka/ were perceived correctly as ‘‘pa’’ and ‘‘ka,’’ respectively by both the groups. For the non- congruent stimuli /da/ /pa/, 23 children out of 35 with normal hearing and 9 children out of 35 with cochlear implant had a fusion of sounds i.e. McGurk effect was present. For the non-congruent stimulus /pa/ /ka/, 25 children out of 35 with normal hearing and 8 children out of 35 with cochlear implant had fusion of sounds.The children who used cochlear implants for less than three years did not exhibit fusion of sound i.e. McGurk effect was absent in this group of children. To conclude, the results demonstrate that consistent fusion of visual with auditory information for speech perception is shaped by experience with bimodal spoken language during early life. When auditory experience with speech is mediated by cochlear implant, the likelihood of acquiring bimodal fusion is increased and it greatly depends on the age of implantation. All the above results strongly support the need for screening children for hearing capabilities and providing cochlear implants and aural rehabilitation as early as possible.

Keywords: cochlear implant, congruent stimuli, mcgurk effect, non-congruent stimuli

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Authors: Rahele Mesbah, Nic Van Der Wee, Manja Koenders, Erik Giltay, Albert Van Hemert, Max De Leeuw

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Introduction: Patients with bipolar disorder (BD), characterized by depressive and manic episodes, often suffer from cognitive dysfunction. An up-to-date meta-analysis of functional Magnetic Resonance Imaging (fMRI) studies examining cognitive function in BD is lacking. Objective: The aim of the current fMRI meta-analysis is to investigate brain functioning of bipolar patients compared with healthy subjects within three domains of emotion processing, reward processing, and working memory. Method: Differences in brain regions activation were tested within whole-brain analysis using the activation likelihood estimation (ALE) method. Separate analyses were performed for each cognitive domain. Results: A total of 50 fMRI studies were included: 20 studies used an emotion processing (316 BD and 369 HC) task, 9 studies a reward processing task (215 BD and 213 HC), and 21 studies used a working memory task (503 BD and 445 HC). During emotion processing, BD patients hyperactivated parts of the left amygdala and hippocampus as compared to HC’s, but showed hypoactivation in the inferior frontal gyrus (IFG). Regarding reward processing, BD patients showed hyperactivation in part of the orbitofrontal cortex (OFC). During working memory, BD patients showed increased activity in the prefrontal cortex (PFC) and anterior cingulate cortex (ACC). Conclusions: This meta-analysis revealed evidence for activity disturbances in several brain areas involved in the cognitive functioning of BD patients. Furthermore, most of the found regions are part of the so-called fronto-limbic network which is hypothesized to be affected as a result of BD candidate genes' expression.

Keywords: cognitive functioning, fMRI analysis, bipolar disorder, fronto-limbic network

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Authors: P. S. Dhananjaya Swamy, B. Chinnappa, G. B. Ramesh, Naveen P. Kumar

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Kodagu district is one of the most densely forested districts in the India as around sixty five per cent of geographical areas under tree cover. Nearly 53 per cent of the flora of Kodagu is endemic. The district is also a hotspot of endemic orchids found mainly in the Thadiandamol. Shade grown, eco-friendly coffee farms are perhaps a selected few places on this planet where nature runs wild. The Kodagu accounts for more than 8.8 per cent of floral diversity of Karnataka state. Estimation of unit cost of cultivation plays a vital role in determining the governmental program their market intervention policies. On an average, planters incurred around Rs. 17041 per acre. The extent of production risk was highest among small category of planters (66 %) compared to other two exhibiting production instability. The result shows that, the coffee productivity in medium plantations was 1051.2 kg per acre as against 758.5 and 789.2 kg in the case of small and large plantations. An annual net return per acre was highest in the case of medium planters (Rs. 26109.3) as against Rs. 20566.7 and Rs. 18572.7 in the case of small and large planters. Cost of production was lowest in the case of small planters (Rs. 18.9 per kg of output) followed by medium planters (Rs. 21.2 per kg of output) and large planters (Rs. 22.5 per kg of output). The productivity of coffee is less whenever it is grown under high shade and native tree cover; it is around 6 quintals per acre when compared with low shade conditions, which is around 8.9 quintals per acre, without a significant difference in the amount invested for growing coffee. Net gain was lower by Rs. 15.5 per kg for the planters growing under high shade and native trees cover when compared with low shade and exotic trees cover.

Keywords: coffee, cultivation, economics, Kodagu

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Authors: Pallavi Gajjar, Vinayak Malhotra

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Rockets have been known to have played a predominant role in spacecraft propulsion. The quintessential aspect of combustion-related requirements of a rocket engine is the minimization of the surrounding risks/hazards. Over time, it has become imperative to understand the combustion rate variation in presence of external energy source(s). Rocket propulsion represents a special domain of chemical propulsion assisted by high speed flows in presence of acoustics and thermal source(s). Jet noise leads to a significant loss of resources and every year a huge amount of financial aid is spent to prevent it. External heat source(s) induce high possibility of fire risk/hazards which can sufficiently endanger the operation of a space vehicle. Appreciable work had been done with justifiable simplification and emphasis on the linear variation of external energy source(s), which yields good physical insight but does not cater to accurate predictions. Present work experimentally attempts to understand the correlation between inter-energy conversions with the non-linear placement of external energy source(s). The work is motivated by the need to have better fire safety and enhanced combustion. The specific objectives of the work are a) To interpret the related energy transfer for combustion in presence of alternate external energy source(s) viz., thermal and acoustic, b) To fundamentally understand the role of key controlling parameters viz., separation distance, the number of the source(s), selected configurations and their non-linear variation to resemble real-life cases. An experimental setup was prepared using incense sticks as potential fuel and paraffin wax candles as the external energy source(s). The acoustics was generated using frequency generator, and source(s) were placed at selected locations. Non-equidistant parametric experimentation was carried out, and the effects were noted on regression rate changes. The results are expected to be very helpful in offering a new perspective into futuristic rocket designs and safety.

Keywords: combustion, acoustic energy, external energy sources, regression rate

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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: Kechnit Djamel, Ammarri Abdelhadi, Raphael Tshimang, Mark Trrig

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One of the most important aspects of monitoring rivers is navigation. The variation of discharge in the river generally produces a change in available draft for a vessel, particularly in the low flow season, which can impact the navigable water path, especially when the water depth is less than the normal one, which allows safe navigation for boats. The water depth is related to the bathymetry of the channel as well as the discharge. For a seasonal update of the navigation maps, a daily discharge value is required. Many novel approaches based on earth observation and remote sensing have been investigated for large rivers. However, it should be noted that most of these approaches are not currently able to directly estimate river discharge. This paper discusses the application of remote sensing tools using the analysis of the reflectance value of MODIS imagery and is combined with field measurements for the estimation of discharge. This approach is applied in the lower reach of the Congo River (Pool Malebo) for the period between 2019 and 2021. The correlation obtained between the observed discharge observed in the gauging station and the reflectance ratio time series is 0.81. In this context, a Discharge Reflectance Model (DRM) was developed to express discharge as a function of reflectance. This model introduces a non-contact method that allows discharge monitoring using earth observation. DRM was validated by field measurements using ADCP, in different sections on the Pool Malebo, over two different periods (dry and wet seasons), as well as by the observed discharge in the gauging station. The observed error between the estimated and measured discharge values ranges from 1 to 8% for the ADCP and from (1% to 11%) for the gauging station. The study of the uncertainties will give us the possibility to judge the robustness of the DRM.

Keywords: discharge monitoring, navigation, MODIS, empiric, ADCP, Congo River

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Authors: P. Chang, C. Lopez, C. Burbano

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Flood protection zones are riparian buffers that are formed to manage and mitigate the impact of flooding, and in turn, protect local populations. The purpose of this study was to evaluate the Guía Técnica de Criterios para el Acotamiento de las Rondas Hídricas in Colombia against international regulations in Canada and Spain, in order to determine its limitations and contribute to its improvement. The need to establish a specific corridor that allows for the dynamic development of a river is clear; however, limitations present in the Colombian Technical Guide are identified. The study shows that international regulations provide similar concepts as used in Colombia, but additionally integrate aspects such as regionalization that allows for a better characterization of the channel way, and incorporate the frequency of flooding and its probability of occurrence in the concept of risk when determining the protection zone. The case study analyzed in Dosquebradas - Risaralda aimed at comparing the application of the different standards through hydraulic modeling. It highlights that the current Colombian standard does not offer sufficient details in its implementation phase, which leads to a false sense of security related to inaccuracy and lack of data. Furthermore, the study demonstrates how the Colombian norm is ill-adapted to the conditions of Dosquebradas typical of the Andes region, both in the social and hydraulic aspects, and does not reduce the risk, nor does it improve the protection of the population. Our study considers it pertinent to include risk estimation as an integral part of the methodology when establishing protect flood zone, considering the particularity of water systems, as they are characterized by an heterogeneous natural dynamic behavior.

Keywords: environmental corridor, flood zone determination, hydraulic domain, legislation flood protection zone

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Authors: Rupa Jeena, Pankaj Chetry, Pradeep Sarin

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The study of fundamental particles and the forces governing them has always remained an attractive field of theoretical study to pursue. With the advancement and development of new technologies and instruments, it is possible now to perform particle physics experiments on a large scale for the validation of theoretical predictions. These experiments are generally carried out in a highly intense beam environment. This, in turn, requires the development of a detector prototype possessing properties like radiation tolerance, thermal stability, and fast timing response. Semiconductors like Silicon, Germanium, Diamond, and Gallium Nitride (GaN) have been widely used for particle detection applications. Silicon and germanium being narrow bandgap semiconductors, require pre-cooling to suppress the effect of noise by thermally generated intrinsic charge carriers. The application of diamond in large-scale experiments is rare owing to its high cost of fabrication, while GaN is one of the most extensively explored potential candidates. But we are aiming to introduce another wide bandgap semiconductor in this active area of research by considering all the requirements. We have made an attempt by utilizing the wide bandgap of rutile Titanium dioxide (TiO2) and other properties to use it for particle detection purposes. The thermal evaporation-oxidation (in PID furnace) technique is used for the deposition of the film, and the Metal Semiconductor Metal (MSM) electrical contacts are made using Titanium+Gold (Ti+Au) (20/80nm). The characterization comprising X-Ray Diffraction (XRD), Atomic Force Microscopy (AFM), Ultraviolet (UV)-Visible spectroscopy, and Laser Raman Spectroscopy (LRS) has been performed on the film to get detailed information about surface morphology. On the other hand, electrical characterizations like Current Voltage (IV) measurement in dark and light and test with laser are performed to have a better understanding of the working of the detector prototype. All these preliminary tests of the detector will be presented.

Keywords: particle detector, rutile titanium dioxide, thermal evaporation, wide bandgap semiconductors

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Authors: Jackson Niyongabo

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This study addresses a notable gap in the existing literature on the relationship between energy consumption, economic growth, and CO₂ emissions, particularly within the African context. While numerous studies have explored these dynamics globally and regionally across various development levels, few have delved into the nuances of regions and income levels specific to African countries. Furthermore, the evaluation of the interplay between green growth policies, green energy technologies, and their impact on environmental quality has been underexplored. This research aims to fill these gaps by conducting a comprehensive analysis of the transition from conventional economic growth and energy consumption to a paradigm of green growth coupled with green energy utilization across the African continent from 1980 to 2018. The study is structured into three main parts: an empirical examination of the long-term effects of energy intensity, renewable energy consumption, and economic growth on CO₂ emissions across diverse African regions and income levels; an estimation of the long-term impact of green growth and green energy use on CO₂ emissions for countries implementing green policies within Africa, as well as at regional and global levels; and a comparative analysis of the impact of green growth policies on environmental degradation before and after implementation. Employing advanced econometric methods and panel estimators, the study utilizes a testing framework, panel unit tests, and various estimators to derive meaningful insights. The anticipated results and conclusions will be elucidated through causality tests, impulse response, and variance decomposition analyses, contributing valuable knowledge to the discourse on sustainable development in the African context.

Keywords: economic growth, green growth, energy consumption, CO₂ emissions, econometric models, green energy

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