Search results for: refractive index sensing

Authors: Kai Liu

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Remote sensing-derived land surface temperature (LST) can provide an indication of the temporal and spatial patterns of surface evapotranspiration (ET). However, the spatial resolution achieved by existing commonly satellite products is ~1 km, which remains too coarse for ET estimations. This paper proposed a model that can disaggregate coarse resolution MODIS LST at 1 km scale to fine spatial resolutions at the scale of 250 m. Our approach attempted to weaken the impacts of soil moisture and growing statues on LST variations. The proposed model spatially disaggregates the coarse thermal data by using a non-linear model involving Bowen ratio, normalized difference vegetation index (NDVI) and photochemical reflectance index (PRI). This LST disaggregation model was tested on two heterogeneous landscapes in central Iowa, USA and Heihe River, China, during the growing seasons. Statistical results demonstrated that our model achieved better than the two classical methods (DisTrad and TsHARP). Furthermore, using the surface energy balance model, it was observed that the estimated ETs using the disaggregated LST from our model were more accurate than those using the disaggregated LST from DisTrad and TsHARP.

Keywords: Bowen ration, downscaling, evapotranspiration, land surface temperature

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Authors: Monojit Manna, Arpan Adhikary

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In Mobile cloud sensing across the globe, an emerging paradigm is selected by the user to compute sensing tasks. In urban cities current days, Mobile vehicles are adapted to perform the task of data sensing and data collection for universality and mobility. In this work, we focused on the optimality and mobile nodes that can be selected in order to collect the maximum amount of data from urban areas and fulfill the required data in the future period within a couple of minutes. We map out the requirement of the vehicle to configure the maximum data optimization problem and budget. The Application implementation is basically set up to generalize a realistic online platform in which real-time vehicles are moving apparently in a continuous manner. The data center has the authority to select a set of vehicles immediately. A deep learning-based scheme with the help of mobile vehicles (DLMV) will be proposed to collect sensing data from the urban environment. From the future time perspective, this work proposed a deep learning-based offline algorithm to predict mobility. Therefore, we proposed a greedy approach applying an online algorithm step into a subset of vehicles for an NP-complete problem with a limited budget. Real dataset experimental extensive evaluations are conducted for the real mobility dataset in Rome. The result of the experiment not only fulfills the efficiency of our proposed solution but also proves the validity of DLMV and improves the quantity of collecting the sensing data compared with other algorithms.

Keywords: mobile crowdsensing, deep learning, vehicle recruitment, sensing coverage, data collection

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Authors: Rana Tabassum, Ravi Kant, Banshi D. Gupta

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Malic acid is an extensively distributed organic acid in numerous horticultural products in minute amounts which significantly contributes towards taste determination by balancing sugar and acid fractions. An enhanced concentration of malic acid is utilized as an indicator of fruit maturity. In addition, malic acid is also a crucial constituent of several cosmetics and pharmaceutical products. An efficient detection and quantification protocol for malic acid is thus highly demanded. In this study, we report a novel detection scheme for malic acid by synergistically collaborating fiber optic surface plasmon resonance (FOSPR) and distinctive features of nanomaterials favorable for sensing applications. The design blueprint involves the deposition of an assembly of malate dehydrogenase enzyme entrapped in ZnO nanowires forming the sensing route over silver coated central unclad core region of an optical fiber. The formation and subsequent decomposition of the enzyme-analyte complex on exposure of the sensing layer to malic acid solutions of diverse concentration results in modification of the dielectric function of the sensing layer which is manifested in terms of shift in resonance wavelength. Optimization of experimental variables such as enzyme concentration entrapped in ZnO nanowires, dip time of probe for deposition of sensing layer and working pH range of the sensing probe have been accomplished through SPR measurements. The optimized sensing probe displays high sensitivity, broad working range and a minimum limit of detection value and has been successfully tested for malic acid determination in real samples of fruit juices. The current work presents a novel perspective towards malic acid determination as the unique and cooperative combination of FOSPR and nanomaterials provides myriad advantages such as enhanced sensitivity, specificity, compactness together with the possibility of online monitoring and remote sensing.

Keywords: surface plasmon resonance, optical fiber, sensor, malic acid

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Authors: Hamed Movahedizadeh, Annuar Md Nassir, Mehdi Karimimalayer, Navid Samimi Sedeh, Ehsan Bagherpour

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The aim of this paper is to evaluate Tehran’s Stock Exchange (TSE) performance regarding with impact of four macroeconomic factors including world crude Oil Price (OP), World Gold Price (GP), Consumer Price Index (CPI) and total Supplied Oil by Iran (SO) from January 2006 to December 2012 that Iran faced with economic and oil sanctions. Iran's exports of crude oil and lease condensate reduced to roughly 1.5 million barrels per day (bbl/d) in 2012, compared to 2.5 million bbl/d in 2011 due to hard sanctions. Monthly data are collected and subjected to a battery of tests through ordinary least square by EViews7. This study found that gold price and oil price are positively correlated with stock returns while total oil supplied and consumer price index have negative relationship with stock index, however, consumer price index tends to become insignificant in stock index. While gold price and consumer price index have short run relationship with TSE index at 10% of significance level this amount for oil price is significant at 5% and there is no significant short run relationship between supplied oil and Tehran stock returns. Moreover, this study found that all macroeconomic factors have long-run relationship with Tehran Stock Exchange Index.

Keywords: consumer price index, gold price, macroeconomic, oil price, sanction, stock market, supplied oil

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Authors: U. F. Mammadova

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Natural resources is the main self-supplying way which is being studied in the paper. Ecologically clean and independent clean energy stock is wind one. This potential is first studied by applying remote sensing way. In any coordinate of the district, wind energy potential has been determined by measuring the potential by applying radar technique which gives a possibility to reveal 2 D view. At several heights, including 10,50,100,150,200 ms, the measurements have been realized. The achievable power generation for m2 in the district was calculated. Daily, hourly, and monthly wind energy potential data were graphed and schemed in the paper. The energy, environmental, and economic advantages of wind energy for the Agsu district were investigated by analyzing radar spectral measurements after the remote sensing process.

Keywords: wind potential, spectral radar analysis, ecological clean energy, ecological safety

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Authors: Chun-Ming Huang, Yi-Jun Liu, Yi-Jie Hsieh, Jin-Ju Chue, Wei-Lin Lai, Chun-Yu Chen, Chih-Chyau Yang, Chien-Ming Wu

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The market of wearable devices has been growing rapidly in two years. The integration of sensors and wearable devices has become the trend of the next technology products. Thus, the academics and industries are eager to cultivate talented persons in sensing technology. Currently, academic and industries have more and more demands on the integrations of versatile sensors and applications, especially for the teams who focus on the development of sensor circuit architectures. These teams tape-out many MEMs sensors chips through the chip fabrication service from National Chip Implementation Center (CIC). However, most of these teams are only able to focus on the circuit design of MEMs sensors; they lack the key support of further system demonstration. This paper follows the CIC’s main mission of promoting the chip/system advanced design technology and aims to establish the environments of the modularized sensing system platform and the system design flow with the measurement and calibration technology. These developed environments are used to support these research teams and help academically advanced sensor designs to perform the system demonstration. Thus, the research groups can promote and transfer their advanced sensor designs to industrial and further derive the industrial economic values. In this paper, the modularized sensing platform is proposed to enable the system demonstration for advanced sensor chip design. The environment of sensor measurement and calibration is established for academic to achieve an accurate sensor result. Two reference sensor designs cooperated with the modularized sensing platform are given to show the sensing system integration and demonstration. These developed environments and platforms are currently provided to academics in Taiwan, and so that the academics can obtain a better environment to perform the system demonstration and improve the research and teaching quality.

Keywords: modularized sensing platform, sensor design and calibration, sensor system, sensor system design flow

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Authors: Siavash Eftekharifar, Tohid Yousefi Rezaii, Mahdi Shamsi

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The purpose of this paper is to exploit compressed sensing (CS) method in order to model and compress the electrocardiogram (ECG) signals at a high compression ratio. In order to obtain a sparse representation of the ECG signals, first a suitable basis matrix with Gaussian kernels, which are shown to nicely fit the ECG signals, is constructed. Then the sparse model is extracted by applying some optimization technique. Finally, the CS theory is utilized to obtain a compressed version of the sparse signal. Reconstruction of the ECG signal from the compressed version is also done to prove the reliability of the algorithm. At this stage, a greedy optimization technique is used to reconstruct the ECG signal and the Mean Square Error (MSE) is calculated to evaluate the precision of the proposed compression method.

Keywords: compressed sensing, ECG compression, Gaussian kernel, sparse representation

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Authors: B. Bouadjemia, M. Houaria, S. Haida, Y. B. Idriss, A, Akham, M. Matouguia, A. Gasmia, T. Lantria, S. Bentataa

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It have investigated the structural, optoelectronic, elastic and thermodynamic properties of KGeX₃ (X = F, Cl and Br) using the density functional theory (DFT) with generalized gradient approximation (GGA) for potential exchange correlation. The modified Becke-Johnson (mBJ-GGA) potential approximation is also used for calculating the optoelectronic properties of the material.The results show that the band structure of the metalloid halide perovskites KGeX₃ (X = F, Cl and Br) have a semiconductor behavior with direct band gap at R-R direction, the gap energy values for each compound as following: 2.83, 1.27 and 0.79eV respectively. The optical properties, such as real and imaginary parts of the dielectric functions, refractive index, reflectivity and absorption coefficient, are investigated. As results, these compounds are competent candidates for optoelectronic and photovoltaic devices in this range of the energy spectrum.

Keywords: density functional theory (DFT), semiconductor behavior, metalloid halide perovskites, optical propertie and photovoltaic devices

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Authors: Rabah Bensaha, Badreddine Toubal

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We investigate the structural, optical and magnetic properties of TiO2, Co-doped TiO2, Ni-doped TiO2 and Co-Ni co-doped TiO2 thin films prepared by the sol-gel dip coating method. Fully anatase phase was obtained by adding metal ions without any detectable impurity phase or oxide formed. AFM and SEM micrographs clearly confirm that the addition of Co-Ni affects the shape of anatase nanoparticles. The crystallite sizes and surface roughness of TiO2 films increase with Co-doping, Ni-doping and Co–Ni co-doping, respectively. The refractive index, thickness and optical band gap values of the films were obtained by means of optical transmittance spectra measurements. The band gap of TiO2 sample was decreased by Co-doping, Ni-doping and Co–Ni co-doping TiO2 films. Both undoped and Co-Ni co-doped films were found to be ferromagnetic at room temperature may due to the presence of oxygen vacancy defect and the probable formation of metal clusters Co-Ni.

Keywords: Co-Ni co-doped, anatase TiO2, ferromagnetic, sol-gel method, thin films

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Authors: Teja Sai Puligadda

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Satellite images in detail can serve an important role in the geographic study. Quantitative and qualitative information provided by the satellite and remote sensing images minimizes the complexity of work and time. Data/images are captured at regular intervals by satellite remote sensing systems, and the amount of data collected is often enormous, and it expands rapidly as technology develops. Interpreting remote sensing images, geographic data mining, and researching distinct vegetation types such as agricultural and forests are all part of satellite image categorization. One of the biggest challenge data scientists faces while classifying satellite images is finding the best suitable classification algorithms based on the available that could able to classify images with utmost accuracy. In order to categorize satellite images, which is difficult due to the sheer volume of data, many academics are turning to deep learning machine algorithms. As, the CNN algorithm gives high accuracy in image recognition problems and automatically detects the important features without any human supervision and the ANN algorithm stores information on the entire network (Abhishek Gupta., 2020), these two deep learning algorithms have been used for satellite image classification. This project focuses on remote sensing through Deep Neural Networks i.e., ANN and CNN with Deep Sat (SAT-4) Airborne dataset for classifying images. Thus, in this project of classifying satellite images, the algorithms ANN and CNN are implemented, evaluated & compared and the performance is analyzed through evaluation metrics such as Accuracy and Loss. Additionally, the Neural Network algorithm which gives the lowest bias and lowest variance in solving multi-class satellite image classification is analyzed.

Keywords: artificial neural network, convolutional neural network, remote sensing, accuracy, loss

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Authors: Omid Azimaraghi, Noushin Khazaei

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Background: Fluid therapy is an important aspect of the perioperative period and a major challenge for anesthesiologists. To authors best knowledge, there is a lack of strong guidance and evidence regarding the optimal approach to fluid therapy. Therefore a variety of medical devices have been introduced to help physicians. In this study, we aimed to evaluate the effectiveness of pleth variability index in guiding fluid therapy in different patient positions. Materials and Methods: Inclusion criteria consisted of patients aged 18-50 years old and classified as American Society of Anesthesiologists physical status I and II, who were candidates for elective thyroidectomy surgery. In total, 36 patients meeting the inclusion criteria were enrolled in the study. After induction of anesthesia and start of mechanical ventilation Pleth variability index was measured in the supine position, then patients were placed in Trendelenburg and reverse Trendelenburg position (30 degrees, 5 minutes); Pleth Variability Index has measured again in the mentioned positions. Results: Mean PVI (Pleth Variability Index) in the supine position was 14.3 ± 3.7 in comparison to 21.5 ± 4.3 in the reverse Trendelenburg position. The mean PVI in Trendelenburg position was 9.1 ± 2.0 in Trendelenburg position (p < 0.05). Conclusion: In conclusion, we found that Pleth Variability Index varies with patient position and this should be taken into account when using this index during fluid therapy.

Keywords: fluid therapy, Pleth Variability Index, position, surgery

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Authors: Sapan Bhatnagar, Danish Akhtar, Salman Ahmed, Asif Ekbal, Gufran Beig

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Particulates are the solid and liquid droplets present in the atmosphere, they have serious negative effects on human health and environment. PM10 and PM2.5 are so small that they can penetrate deep into our lungs through the respiratory system. Determination of the amount of particulates present in the atmosphere per cubic meter is necessary to monitor, regulate and model atmospheric particulate levels. Air Quality Index is an index tells us how clean or polluted our air is, and what associated health effects might be a concern for us. The AQI focuses on health affects you may experience within a few hours or days after breathing polluted air. The quality rating for each pollutant was calculated. The geometric mean of these quality ratings gives the Air Quality Index. The existing concentrations of pollutants were compared with ambient air quality standards.

Keywords: air quality index, particulate, respirable dust sampler, dust sampler

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Authors: Tatsuya Yamazaki, Kazuya Miyakawa, Tomohiko Sugiyama, Toshitaka Iwatani

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The introduction of sensor technologies into agriculture is a necessary step to realize Precision Agriculture. Although sensing methodologies themselves have been prevailing owing to miniaturization and reduction in costs of sensors, there are some difficulties to analyze and understand the sensing data. Targeting at pears ’Le Lectier’, which is particular to Niigata in Japan, cultivation environmental data have been collected at pear fields by eight sorts of sensors: field temperature, field humidity, rain gauge, soil water potential, soil temperature, soil moisture, inner-bag temperature, and inner-bag humidity sensors. With regard to the inner-bag temperature and humidity sensors, they are used to measure the environment inside the fruit bag used for pre-harvest bagging of pears. In this experiment, three kinds of fruit bags were used for the pre-harvest bagging. After over 100 days continuous measurement, volumes of sensing data have been collected. Firstly, correlation analysis among sensing data measured by respective sensors reveals that one sensor can replace another sensor so that more efficient and cost-saving sensing systems can be proposed to pear farmers. Secondly, differences in characteristic and performance of the three kinds of fruit bags are clarified by the measurement results by the inner-bag environmental sensing. It is found that characteristic and performance of the inner-bags significantly differ from each other by statistical analysis. Lastly, a relational model between the sensing data and the pear outlook quality is established by use of Structural Equation Model (SEM). Here, the pear outlook quality is related with existence of stain, blob, scratch, and so on caused by physiological impair or diseases. Conceptually SEM is a combination of exploratory factor analysis and multiple regression. By using SEM, a model is constructed to connect independent and dependent variables. The proposed SEM model relates the measured sensing data and the pear outlook quality determined on the basis of farmer judgement. In particularly, it is found that the inner-bag humidity variable relatively affects the pear outlook quality. Therefore, inner-bag humidity sensing might help the farmers to control the pear outlook quality. These results are supported by a large quantity of inner-bag humidity data measured over the years 2014, 2015, and 2016. The experimental and analytical results in this research contribute to spreading Precision Agriculture technologies among the farmers growing ’Le Lectier’.

Keywords: precision agriculture, pre-harvest bagging, sensor fusion, structural equation model

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Authors: Salako Rotimi, Oshungade Stephen, Ojewoye Opeyemi

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The maintenance of price stability is one of the macroeconomic challenges facing Nigeria as a nation. This paper attempts to build a co-integration multivariate time series model for inflation movement in Nigeria using data extracted from the abstract of statistics of the Central Bank of Nigeria (CBN) from 2008 to 2017. The Johansen cointegration test suggests at least one co-integration vector describing the long run relationship between Consumer Price Index (CPI), Food Price Index (FPI) and Non-Food Price Index (NFPI). All three series show increasing pattern, which indicates a sign of non-stationary in each of the series. Furthermore, model predictability was established with root-mean-square-error, mean absolute error, mean average percentage error, and Theil’s unbiased statistics for n-step forecasting. The result depicts that the long run coefficient of a consumer price index (CPI) has a positive long-run relationship with the food price index (FPI) and non-food price index (NFPI).

Keywords: economic, inflation, model, series

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Authors: Smriti Bhatnagar

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This study aims to find if the Transit-oriented planning and development approach benefit the quality of air in neighborhoods of New Delhi. Two methodologies, namely the land use regression analysis and the Transit-oriented development index analysis, are being used to explore this relationship. Land Use Regression Analysis makes use of urban form characteristics as obtained for 33 neighborhoods in Delhi. These comprise road lengths, land use areas, population and household densities, number of amenities and distance between amenities. Regressions are run to establish the relationship between urban form variables and air quality parameters (dependent variables). For the Transit-oriented development index analysis, the Transit-oriented Development index is developed as a composite index comprising 29 urban form indicators. This index is developed by assigning weights to each of the 29 urban form data points. Regressions are run to establish the relationship between the Transit-oriented development index and air quality parameters. The thesis finds that elements of Transit-oriented development if incorporated in planning approach, have a positive effect on air quality. Roads suited for non-motorized transport, well connected civic amenities in neighbourhoods, for instance, have a directly proportional relationship with air quality. Transit-oriented development index, however, is not found to have a consistent relationship with air quality parameters. The reason could this, however, be in the way that the index has been constructed.

Keywords: air quality, land use regression, mixed-use planning, transit-oriented development index, New Delhi

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Authors: Feng Yue, Fei Dai

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With the rapid development of urbanization process in China, its environmental protection pressure is severely tested. So, analyzing and optimizing the landscape pattern is an important measure to ease the pressure on the ecological environment. This paper takes Wuhan Urban Development Zone as the research object, and studies its landscape pattern evolution and quantitative optimization strategy. First, remote sensing image data from 1990 to 2015 were interpreted by using Erdas software. Next, the landscape pattern index of landscape level, class level, and patch level was studied based on Fragstats. Then five indicators of ecological environment based on National Environmental Protection Standard of China were selected to evaluate the impact of landscape pattern evolution on the ecological environment. Besides, the cost distance analysis of ArcGIS was applied to simulate wildlife migration thus indirectly measuring the improvement of ecological environment quality. The result shows that the area of land for construction increased 491%. But the bare land, sparse grassland, forest, farmland, water decreased 82%, 47%, 36%, 25% and 11% respectively. They were mainly converted into construction land. On landscape level, the change of landscape index all showed a downward trend. Number of patches (NP), Landscape shape index (LSI), Connection index (CONNECT), Shannon's diversity index (SHDI), Aggregation index (AI) separately decreased by 2778, 25.7, 0.042, 0.6, 29.2%, all of which indicated that the NP, the degree of aggregation and the landscape connectivity declined. On class level, the construction land and forest, CPLAND, TCA, AI and LSI ascended, but the Distribution Statistics Core Area (CORE_AM) decreased. As for farmland, water, sparse grassland, bare land, CPLAND, TCA and DIVISION, the Patch Density (PD) and LSI descended, yet the patch fragmentation and CORE_AM increased. On patch level, patch area, Patch perimeter, Shape index of water, farmland and bare land continued to decline. The three indexes of forest patches increased overall, sparse grassland decreased as a whole, and construction land increased. It is obvious that the urbanization greatly influenced the landscape evolution. Ecological diversity and landscape heterogeneity of ecological patches clearly dropped. The Habitat Quality Index continuously declined by 14%. Therefore, optimization strategy based on greenway network planning is raised for discussion. This paper contributes to the study of landscape pattern evolution in planning and design and to the research on spatial layout of urbanization.

Keywords: landscape pattern, optimization strategy, ArcGIS, Erdas, landscape metrics, landscape architecture

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Authors: Zulkiflee Abd Latif, Sitinor Atikah Nordin, Alawi Sulaiman

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Different tree species possess different and various benefits. Arenga Pinnata tree species own several potential uses that is valuable for the economy and the country. Mapping vegetation using remote sensing technique involves various process, techniques and consideration. Using satellite imagery, this method enables the access of inaccessible area and with the availability of near infra-red band; it is useful in vegetation analysis, especially in identifying tree species. Pixel-based and object-based classification technique is used as a method in this study. Pixel-based classification technique used in this study divided into unsupervised and supervised classification. Object based classification technique becomes more popular another alternative method in classification process. Using spectral, texture, color and other information, to classify the target make object-based classification is a promising technique for classification. Classification of Arenga Pinnata trees is overlaid with elevation, slope and aspect, soil and river data and several other data to give information regarding the tree character and living environment. This paper will present the utilization of remote sensing technique in order to map Arenga Pinnata tree species

Keywords: Arenga Pinnata, pixel-based classification, object-based classification, remote sensing

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Authors: Changju Lee, Seungmo Ku, Sondo Kim, Woojin Chang

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How to detecting financial bubble? Addressing this simple question has been the focus of a vast amount of empirical research spanning almost half a century. However, financial bubble is hard to observe and varying over the time; there needs to be more research on this area. In this paper, we used abnormal difference between common stocks price and those preferred stocks price to explain financial bubble. First, we proposed the ‘W-index’ which indicates spread between common stocks and those preferred stocks in stock market. Second, to prove that this ‘W-index’ is valid for measuring financial bubble, we showed that there is an inverse relationship between this ‘W-index’ and S&P500 rate of return. Specifically, our hypothesis is that when ‘W-index’ is comparably higher than other periods, financial bubbles are added up in stock market and vice versa; according to our hypothesis, if investors made long term investments when ‘W-index’ is high, they would have negative rate of return; however, if investors made long term investments when ‘W-index’ is low, they would have positive rate of return. By comparing correlation values and adjusted R-squared values of between W-index and S&P500 return, VIX index and S&P500 return, and TED index and S&P500 return, we showed only W-index has significant relationship between S&P500 rate of return. In addition, we figured out how long investors should hold their investment position regard the effect of financial bubble. Using this W-index, investors could measure financial bubble in the market and invest with low risk.

Keywords: financial bubble detection, future return, forecasting, pairs trading, preferred stocks

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Authors: Maryam Kiani, Xiaoqin Tian, Yu Du, Abdul Basit Kiani

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Zn-doped MgFe₂O₄ nanoparticles (ZMFO) (Zn=0.0, 0.2, 0.35, 0.5,) were prepared by Co-precipitation synthesis route. Structural and morphological analysis confirmed the formation of spinel cubic nanostructure by X-Ray diffraction (XRD) data shows high reactive surface area owing to a small average particle size of about 14 nm, which greatly influences the gas sensing mechanism. The gas sensing property of ZMFO for several gases was obtained by measuring the resistance as a function of different factors, like composition and response time in air and in the presence of gas. The sensitivity of spinel ferrite to gases CO₂, O₂, and O₂ at room temperature has been compared. The nanostructured ZMFO exhibited high sensitivity in the order of CO₂>O₂ and showed a good response time of (~1min) to CO₂, demonstrating that this expanse of research can be used in the field of gas sensors devising high sensitivity and good selectivity at 25°C.

Keywords: MgFe₂O₄ nanoparticles, hydrothermal synthesis, gas sensing properties, XRD

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Authors: Ariadne C. Catto, Luis F. da Silva, Khalifa Aguir, Valmor Roberto Mastelaro

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Zinc oxide (ZnO) pure or doped are one of the most promising metal oxide semiconductors for gas sensing applications due to the well-known high surface-to-volume area and surface conductivity. It was shown that ZnO is an excellent gas-sensing material for different gases such as CO, O2, NO2 and ethanol. In this context, pure and doped ZnO exhibiting different morphologies and a high surface/volume ratio can be a good option regarding the limitations of the current commercial sensors. Different studies showed that the sensitivity of metal-doped ZnO (e.g. Co, Fe, Mn,) enhanced its gas sensing properties. Motivated by these considerations, the aim of this study consisted on the investigation of the role of Co ions on structural, morphological and the gas sensing properties of nanostructured ZnO samples. ZnO and Zn1-xCoxO (0 < x < 5 wt%) thin films were obtained via the polymeric precursor method. The sensitivity, selectivity, response time and long-term stability gas sensing properties were investigated when the sample was exposed to a different concentration range of ozone (O3) at different working temperatures. The gas sensing property was probed by electrical resistance measurements. The long and short-range order structure around Zn and Co atoms were investigated by X-ray diffraction and X-ray absorption spectroscopy. X-ray photoelectron spectroscopy measurement was performed in order to identify the elements present on the film surface as well as to determine the sample composition. Microstructural characteristics of the films were analyzed by a field-emission scanning electron microscope (FE-SEM). Zn1-xCoxO XRD patterns were indexed to the wurtzite ZnO structure and any second phase was observed even at a higher cobalt content. Co-K edge XANES spectra revealed the predominance of Co2+ ions. XPS characterization revealed that Co-doped ZnO samples possessed a higher percentage of oxygen vacancies than the ZnO samples, which also contributed to their excellent gas sensing performance. Gas sensor measurements pointed out that ZnO and Co-doped ZnO samples exhibit a good gas sensing performance concerning the reproducibility and a fast response time (around 10 s). Furthermore, the Co addition contributed to reduce the working temperature for ozone detection and improve the selective sensing properties.

Keywords: cobalt-doped ZnO, nanostructured, ozone gas sensor, polymeric precursor method

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Authors: Ali J. Ghandour, Houssam A. Krayem, Abedelkarim A. Jezzini

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High-resolution satellite images and remote sensing can provide global information in a fast way compared to traditional methods of data collection. Under such high resolution, a road is not a thin line anymore. Objects such as cars and trees are easily identifiable. Automatic vehicles enumeration can be considered one of the most important applications in traffic management. In this paper, autonomous vehicle detection and classification approach in highway environment is proposed. This approach consists mainly of three stages: (i) first, a set of preprocessing operations are applied including soil, vegetation, water suppression. (ii) Then, road networks detection and delineation is implemented using built-up area index, followed by several morphological operations. This step plays an important role in increasing the overall detection accuracy since vehicles candidates are objects contained within the road networks only. (iii) Multi-level Otsu segmentation is implemented in the last stage, resulting in vehicle detection and classification, where detected vehicles are classified into cars and trucks. Accuracy assessment analysis is conducted over different study areas to show the great efficiency of the proposed method, especially in highway environment.

Keywords: remote sensing, object identification, vehicle and road extraction, vehicle and road features-based classification

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Authors: Amir Bahrami

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In the fields of chemical graph theory, molecular topology, and mathematical chemistry, a topological index or a descriptor index also known as a connectivity index is a type of a molecular descriptor that is calculated based on the molecular graph of a chemical compound. Topological indices are numerical parameters of a graph which characterize its topology and are usually graph invariant. Topological indices are used for example in the development of quantitative structure-activity relationships (QSARs) in which the biological activity or other properties of molecules are correlated with their chemical structure. In this paper some descriptor index (descriptor index) of single-walled carbon nanotubes, is determined.

Keywords: chemical graph theory, molecular topology, molecular descriptor, single-walled carbon nanotubes

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Authors: Ibraheem K. Ibraheem

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The aim of this research is to design and implement line-tracking mobile robot. The robot must follow a line drawn on the floor with different color, avoids hitting moving object like another moving robot or walking people and achieves color sensing. The control system reacts by controlling each of the motors to keep the tracking sensor over the middle of the line. Proximity sensors used to avoid hitting moving objects that may pass in front of the robot. The programs have been written using micro c instructions, then converted into PIC16F887 ATmega48/88/168 microcontrollers counterparts. Practical simulations show that the walking robot accurately achieves line following action and exactly recognizes the colors and avoids any obstacle in front of it.

Keywords: color sensing, H-bridge, line following, mobile robot, PIC microcontroller, obstacle avoidance, phototransistor

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Authors: L. Foudia, K. Haddadi, M. Reffas

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First principles study of structural, elastic, electronic and optical properties of the monoclinic perovskite type ScRhO₃ has been reported using the pseudo-potential plane wave method within the local density approximation. The calculated lattice parameters, including the lattice constants and angle β, are in excellent agreement with the available experimental data, which proving the reliability of the chosen theoretical approach. Pressure dependence up to 20 GPa of the single crystal and polycrystalline elastic constants has been investigated in details using the strain-stress approach. The mechanical stability, ductility, average elastic wave velocity, Debye temperature and elastic anisotropy were also assessed. Electronic band structure and density of states (DOS) demonstrated its semiconducting nature showing a direct band gap of 1.38 eV. Furthermore, several optical properties, such as absorption coefficient, reflectivity, refractive index, dielectric function, optical conductivity and electron energy loss function, have been calculated for radiation up to 40 eV.

Keywords: ab-initio, perovskite, DFT, band gap

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Authors: Shamil Mardi Al Islam, Zaima Ahmed

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The aim of this article is to explore whether certain macroeconomic variables such as industrial index, inflation, broad money, exchange rate and deposit rate as a proxy for interest rate are interlinked with Dhaka stock price index (DSEX index) precisely after the introduction of new index by Dhaka Stock Exchange (DSE) since January 2013. Bangladesh stock market has experienced rapid growth since its inception. It might not be a very well-developed capital market as compared to its neighboring counterparts but has been a strong avenue for investment and resource mobilization. The data set considered consists of monthly observations, for a period of four years from January 2013 to June 2018. Findings from cointegration analysis suggest that DSEX and macroeconomic variables have a significant long-run relationship. VAR decomposition based on VAR estimated indicates that money supply explains a significant portion of variation of stock index whereas, inflation is found to have the least impact. Impact of industrial index is found to have a low impact compared to the exchange rate and deposit rate. Policies should there aim to increase industrial production in order to enhance stock market performance. Further reasonable money supply should be ensured by authorities to stimulate stock market performance.

Keywords: deposit rate, DSEX, industrial index, VAR

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Authors: Faten Adel Ismael Chaqmaqchee

Abstract:

Optical, electrical and optical-electrical characterisations of surface light emitting VCSOAs devices are reported. The hot electron light emitting and lasing in semiconductor hetero-structure vertical cavity semiconductor optical amplifier (HELLISH VCSOA) device is a surface emitter based on longitudinal injection of electron and hole pairs in their respective channels. Ga0.35In0.65N0.02As0.08/GaAs was used as an active material for operation in the 1.3 μm window of the optical communications. The device has undoped Distributed Bragg Reflectors (DBRs) and the current is injected longitudinally, directly into the active layers and does not involve DBRs. Therefore, problems associated with refractive index contrast and current injection through the DBR layers, which are common with the doped DBRs in conventional VCSOAs, are avoided. The highest gain of around 4 dB is obtained for the 1300 nm wavelength operation.

Keywords: HELLISH, VCSOA, GaInNAs, luminescence, gain

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Authors: Hamid Rostami Jaz, Kamran Ameri Siahooei

Abstract:

Up to now different methods have been used to forecast the index returns and the index rate. Artificial intelligence and artificial neural networks have been one of the methods of index returns forecasting. This study attempts to carry out a comparative study on the performance of different Radial Base Neural Network and Feed-Forward Perceptron Neural Network to forecast investment returns on the index. To achieve this goal, the return on investment in Tehran Stock Exchange index is evaluated and the performance of Radial Base Neural Network and Feed-Forward Perceptron Neural Network are compared. Neural networks performance test is applied based on the least square error in two approaches of in-sample and out-of-sample. The research results show the superiority of the radial base neural network in the in-sample approach and the superiority of perceptron neural network in the out-of-sample approach.

Keywords: exchange index, forecasting, perceptron neural network, Tehran stock exchange

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Authors: İsmail İnce

Abstract:

The aim of this study is to determine index and mechanical properties of pyroclastic rock in a practical way by means of electrical resistivity method. For this purpose, electrical resistivity, uniaxial compressive strength, point load strength, P-wave velocity, density and porosity values of 10 different pyroclastic rocks were measured in the laboratory. A simple regression analysis was made among the index-mechanical properties of the samples compatible with electrical resistivity values. A strong exponentially relation was found between index-mechanical properties and electrical resistivity values. The electrical resistivity method can be used to assess the engineering properties of the rock from which it is difficult to obtain regular shaped samples as a non-destructive method.

Keywords: electrical resistivity, index-mechanical properties, pyroclastic rocks, regression analysis

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Authors: Aafaf El Jazouli, Ahmed Barakat, Rida Khellouk

Abstract:

Mapping of soil degradation is derived from field observations, laboratory measurements, and remote sensing data, integrated quantitative methods to map the spatial characteristics of soil properties at different spatial and temporal scales to provide up-to-date information on the field. Since soil salinity, texture and organic matter play a vital role in assessing topsoil characteristics and soil quality, remote sensing can be considered an effective method for studying these properties. The main objective of this research is to asses soil degradation by combining remote sensing data and laboratory analysis. In order to achieve this goal, the required study of soil samples was taken at 50 locations in the upper basin of Oum Er Rbia in the Middle Atlas in Morocco. These samples were dried, sieved to 2 mm and analyzed in the laboratory. Landsat 8 OLI imagery was analyzed using physical or empirical methods to derive soil properties. In addition, remote sensing can serve as a supporting data source. Deterministic potential (Spline and Inverse Distance weighting) and probabilistic interpolation methods (ordinary kriging and universal kriging) were used to produce maps of each grain size class and soil properties using GIS software. As a result, a correlation was found between soil texture and soil organic matter content. This approach developed in ongoing research will improve the prospects for the use of remote sensing data for mapping soil degradation in arid and semi-arid environments.

Keywords: Soil degradation, GIS, interpolation methods (spline, IDW, kriging), Landsat 8 OLI, Oum Er Rbia high basin

Procedia PDF Downloads 138

Authors: G. Punithavathy

Abstract:

The research proposes a statistical model for the distributed acoustic sensor interrogation units that broadcast a laser pulse into the fiber optics, where interactions within the fiber determine the localized acoustic energy that causes light reflections known as backscatter. The backscattered signal's amplitude and phase can be calculated using explicit equations. The created model makes amplitude signal spectrum and autocorrelation predictions that are confirmed by experimental findings. Phase signal characteristics that are useful for researching optical time domain reflectometry (OTDR) system sensing applications are provided and examined, showing good agreement with the experiment. The experiment was successfully done with the use of Python coding. In this research, we can analyze the entire distributed acoustic sensing (DAS) component parts separately. This model assumes that the fiber is in a static condition, meaning that there is no external force or vibration applied to the cable, that means no external acoustic disturbances present. The backscattered signal consists of a random noise component, which is caused by the intrinsic imperfections of the fiber, and a coherent component, which is due to the laser pulse interacting with the fiber.

Keywords: distributed acoustic sensing, optical fiber devices, optical time domain reflectometry, Rayleigh scattering

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