Search results for: band selection

Authors: Devansh Desai, Rahul Nigam

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Crop water stress (W) at a given growth stage starts to set in as moisture availability (M) to roots falls below 75% of maximum. It has been found that ratio of crop evapotranspiration (ET) and reference evapotranspiration (ET0) is an indicator of moisture adequacy and is strongly correlated with ‘M’ and ‘W’. The spatial variability of ET0 is generally less over an agricultural farm of 1-5 ha than ET, which depends on both surface and atmospheric conditions, while the former depends only on atmospheric conditions. Solutions from surface energy balance (SEB) and thermal infrared (TIR) remote sensing are now known to estimate latent heat flux of ET. In the present study, ET and moisture adequacy index (MAI) (=ET/ET0) have been estimated over two contrasting western India agricultural farms having rice-wheat system in semi-arid climate and arid grassland system, limited by moisture availability. High-resolution multi-band TIR sensing observations at 65m from ECOSTRESS (ECOsystemSpaceborne Thermal Radiometer Experiment on Space Station) instrument on-board International Space Station (ISS) were used in an analytical SEB model, STIC (Surface Temperature Initiated Closure) to estimate ET and MAI. The ancillary variables used in the ET modeling and MAI estimation were land surface albedo, NDVI from close-by LANDSAT data at 30m spatial resolution, ET0 product at 4km spatial resolution from INSAT 3D, meteorological forcing variables from short-range weather forecast on air temperature and relative humidity from NWP model. Farm-scale ET estimates at 65m spatial resolution were found to show low RMSE of 16.6% to 17.5% with R2 >0.8 from 18 datasets as compared to reported errors (25 – 30%) from coarser-scale ET at 1 to 8 km spatial resolution when compared to in situ measurements from eddy covariance systems. The MAI was found to show lower (<0.25) and higher (>0.5) magnitudes in the contrasting agricultural farms. The study showed the potential need of high-resolution high-repeat spaceborne multi-band TIR payloads alongwith optical payload in estimating farm-scale ET and MAI for estimating consumptive water use and water stress. A set of future high-resolution multi-band TIR sensors are planned on-board Indo-French TRISHNA, ESA’s LSTM, NASA’s SBG space-borne missions to address sustainable irrigation water management at farm-scale to improve crop water productivity. These will provide precise and fundamental variables of surface energy balance such as LST (Land Surface Temperature), surface emissivity, albedo and NDVI. A synchronization among these missions is needed in terms of observations, algorithms, product definitions, calibration-validation experiments and downstream applications to maximize the potential benefits.

Keywords: thermal remote sensing, land surface temperature, crop water stress, evapotranspiration

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Authors: H. Ali, A. Whitehead

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Providing a panoramic view of famous landmarks around the world offers artistic and historic value for historians, tourists, and researchers. Exploring the history of famous landmarks by presenting a comprehensive view of a temporal panorama merged with geographical and historical information presents a unique challenge of dealing with images that span a long period, from the 1800’s up to the present. This work presents the concept of temporal panorama through a timeline display of aligned historic and modern images for many famous landmarks. Utilization of this panorama requires a collection of hundreds of thousands of landmark images from the Internet comprised of historic images and modern images of the digital age. These images have to be classified for subset selection to keep the more suitable images that chronologically document a landmark’s history. Processing of historic images captured using older analog technology under various different capturing conditions represents a big challenge when they have to be used with modern digital images. Successful processing of historic images to prepare them for next steps of temporal panorama creation represents an active contribution in cultural heritage preservation through the fulfillment of one of UNESCO goals in preservation and displaying famous worldwide landmarks.

Keywords: cultural heritage, image registration, image subset selection, registered image similarity, temporal panorama, timescapes

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Authors: Aticha Kwaengsopha

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The purpose of this research was to study the behaviour and related factors that tourists utilized for making decisions to choose their accommodations at a tourist destination, Bangkontee district, Samut Songkhran Province, Thailand. The independent variables included gender, age, income, occupation, and region, while the three important dependent variables included selection behaviour, factors related selection process, and satisfaction of the accommodation service. A total of 400 Thai and international tourists were interviewed at tourist destination of Bangkontee. A questionnaire was used as the tool for collecting data. Descriptive statistics in this research included percentage, mean, and standard deviation. The findings revealed that the majority of respondents were single, female, and with the age between 23-30 years old. Most of the international tourists were from Asia and planned to stay in Thailand about 1-6 days. In addition, the majority of tourists preferred to travel in small groups of 3 persons. The majority of respondents used internet and word of mouth as the main tool to search for information. The majority of respondents spent most of their budget on food & drink, accommodation, and travelling. Even though the majority of tourists were satisfied with the quality of accommodation, the price range of accommodation, and the image of accommodation and the facilities of the accommodation, they indicated that they were not likely to re-visit Thailand in the near future.

Keywords: behaviour, decision factors, tourists, media engineering

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Authors: Sospeter P. Maganga, Alphonce Wikedzi, Mussa D. Budeba, Samwel V. Manyele

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This study characterizes complex gold ores (elemental and mineralogical composition, gold distribution, ore grindability, and mineral liberation) for preliminary process selection. About 200 kg of ore samples were collected from each location using systematic sampling by mass interval. Ores were dried, crushed, milled, and split into representative sub-samples (about 1 kg) for elemental and mineralogical composition analyses using X-ray fluorescence (XRF), fire assay finished with Atomic Absorption Spectrometer (AAS), and X-ray Diffraction (XRD) methods, respectively. The gold distribution was studied on size-by-size fractions, while ore grindability was determined using the standard Bond test. The mineral liberation analysis was conducted using ThermoFisher Scientific Mineral Liberation Analyzer (MLA) 650, where unsieved polished grain mounts (80% passing 700 µm) were used as MLA feed. Two MLA measurement modes, X-ray modal analysis (XMOD) and sparse phase liberation-grain X-ray mapping analysis (SPL-GXMAP), were employed. At least two cyanide consumers (Cu, Fe, Pb, and Zn) and kinetics impeders (Mn, S, As, and Bi) were present in all locations investigated. Copper content at Kapanda (0.77% Cu) and Ibindi (7.48% Cu) exceeded the recommended threshold of 0.5% Cu for direct cyanidation. The gold ore at Ibindi indicated a higher rate of grinding compared to other locations. This could be explained by the highest grindability (2.119 g/rev.) and lowest Bond work index (10.213 kWh/t) values. The pyrite-marcasite, chalcopyrite, galena, and siderite were identified as major gold, copper, lead, and iron-bearing minerals, respectively, with potential for economic extraction. However, only gold and copper can be recovered under conventional milling because of grain size issues (galena is exposed by 10%) and process complexity (difficult to concentrate and smelt iron from siderite). Therefore, the preliminary process selection is copper flotation followed by gold cyanidation for Kapanda and Ibindi ores, whereas gold cyanidation with additives such as glycine or ammonia is selected for Mawemeru and Itumbi ores because of low concentrations of Cu, Pb, Fe, and Zn minerals.

Keywords: complex gold ores, mineral liberation, ore characterization, ore grindability

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Authors: Phutthiwat Waiyawuththanapoom

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This study has only one objective which is to identify the different in factors of choosing the distributor for food and non-food OTOP entrepreneur in Thailand. In this research, the types of OTOP product will be divided into two groups which are food and non-food. The sample for the food type OTOP product was the processed fruit and vegetable from Nakorn Pathom province and the sample for the non-food type OTOP product was the court doll from Ang Thong province. The research was divided into 3 parts which were a study of the distribution pattern and how to choose the distributor of the food type OTOP product, a study of the distribution pattern and how to choose the distributor of the non-food type OTOP product and a comparison between 2 types of products to find the differentiation in the factor of choosing distributor. The data and information was collected by using the interview. The populations in the research were 5 producers of the processed fruit and vegetable from Nakorn Pathom province and 5 producers of the court doll from Ang Thong province. The significant factor in choosing the distributor of the food type OTOP product is the material handling efficiency and on-time delivery but for the non-food type OTOP product is focused on the channel of distribution and cost of the distributor.

Keywords: distributor, OTOP, food and non-food, selection

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Authors: Farhad Alizadeh, Alireza Faregh Gharamaleki, Mojtaba Jalilzadeh, Houshang Gholami, Ali Akhoundzadeh

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This study presented hybrid pre-processing approach along with a conceptual model to enhance the accuracy of river discharge prediction. In order to achieve this goal, Ensemble Empirical Mode Decomposition algorithm (EEMD), Discrete Wavelet Transform (DWT) and Mutual Information (MI) were employed as a hybrid pre-processing approach conjugated to Least Square Support Vector Machine (LSSVM). A conceptual strategy namely multi-station model was developed to forecast the Souris River discharge more accurately. The strategy used herein was capable of covering uncertainties and complexities of river discharge modeling. DWT and EEMD was coupled, and the feature selection was performed for decomposed sub-series using MI to be employed in multi-station model. In the proposed feature selection method, some useless sub-series were omitted to achieve better performance. Results approved efficiency of the proposed DWT-EEMD-MI approach to improve accuracy of multi-station modeling strategies.

Keywords: river stage-discharge process, LSSVM, discrete wavelet transform, Ensemble Empirical Decomposition Mode, multi-station modeling

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Authors: Katarina Rogulj, Ivana Racetin, Jelena Kilic

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In this study, the fuzzy logic approach (FLA) was developed for construction project management (CPM) under uncertainty and duality. The focus was on decision making in selecting the type of the glass facade for a residential-commercial building in the main design. The adoption of fuzzy sets was capable of reflecting construction managers’ reliability level over subjective judgments, and thus the robustness of the system can be achieved. An α-cuts method was utilized for discretizing the fuzzy sets in FLA. This method can communicate all uncertain information in the optimization process, taking into account the values of this information. Furthermore, FLA provides in-depth analyses of diverse policy scenarios that are related to various levels of economic aspects when it comes to the construction projects' valid decision making. The developed approach is applied to CPM to demonstrate its applicability. Analyzing the materials of glass facades, variants were defined. The development of the FLA for the CPM included relevant construction projec'ts stakeholders that were involved in the criteria definition to evaluate each variant. Using fuzzy Decision-Making Trial and Evaluation Laboratory Method (DEMATEL) comparison of the glass facade was conducted. This way, a rank, according to the priorities for inclusion into the main design, of variants is obtained. The concept was tested on a residential-commercial building in the city of Rijeka, Croatia. The newly developed methodology was then compared with the existing one. The aim of the research was to define an approach that will improve current judgments and decisions when it comes to the material selection of buildings facade as one of the most important architectural and engineering tasks in the main design. The advantage of the new methodology compared to the old one is that it includes the subjective side of the managers’ decisions, as an inevitable factor in each decision making. The proposed approach can help construction projects managers to identify the desired type of glass facade according to their preference and practical conditions, as well as facilitate in-depth analyses of tradeoffs between economic efficiency and architectural design.

Keywords: construction projects management, DEMATEL, fuzzy logic approach, glass façade selection

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Authors: Nino Abesadze, Marine Mindorashvili, Nino Paresashvili

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At present actual tourism indicators cannot be calculated in Georgia, making it impossible to perform their quantitative analysis. Therefore, the study conducted by us is highly important from a theoretical as well as practical standpoint. The main purpose of the article is to make complex statistical analysis of tourist expenses of foreign visitors and to calculate statistical attractiveness indices of the tourism potential of Georgia. During the research, the method involving random and proportional selection has been applied. Computer software SPSS was used to compute statistical data for corresponding analysis. Corresponding methodology of tourism statistics was implemented according to international standards. Important information was collected and grouped from major Georgian airports, and a representative population of foreign visitors and a rule of selection of respondents were determined. The results show a trend of growth in tourist numbers and the share of tourists from post-soviet countries are constantly increasing. The level of satisfaction with tourist facilities and quality of service has improved, but still we have a problem of disparity between the service quality and the prices. The design of tourist expenses of foreign visitors is diverse; competitiveness of tourist products of Georgian tourist companies is higher. Attractiveness of popular cities of Georgia has increased by 43%.

Keywords: tourist, expenses, indexes, statistics, analysis

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Authors: Kemka C. Ihemelandu, Chukwuemeka U. Ihemelandu

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The incidence of melanoma has been increasing rapidly over the past two decades, making melanoma a current public health crisis. Unfortunately, even as screening efforts continue to expand in an effort to ameliorate the death rate from melanoma, there is a need to improve diagnostic accuracy to decrease misdiagnosis. Artificial intelligence (AI) a new frontier in patient care has the ability to improve the accuracy of melanoma diagnosis. Convolutional neural network (CNN) a form of deep neural network, most commonly applied to analyze visual imagery, has been shown to outperform the human brain in pattern recognition. However, there are noted limitations with the accuracy of the CNN models. Our aim in this study was the optimization of convolutional neural network algorithms for the automated diagnosis of melanoma. We hypothesized that Optimal selection of the momentum and batch hyperparameter increases model accuracy. Our most successful model developed during this study, showed that optimal selection of momentum of 0.25, batch size of 2, led to a superior performance and a faster model training time, with an accuracy of ~ 83% after nine hours of training. We did notice a lack of diversity in the dataset used, with a noted class imbalance favoring lighter vs. darker skin tone. Training set image transformations did not result in a superior model performance in our study.

Keywords: melanoma, convolutional neural network, momentum, batch hyperparameter

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Authors: A. Khan, H. Mahmood

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In Underwater Wireless Sensor Networks (UWSNs), sensor nodes close to water surface (final destination) are often preferred for selection as forwarders. However, their frequent selection makes them depleted of their limited battery power. In consequence, these nodes die during early stage of network operation and create energy holes where forwarders are not available for packets forwarding. These holes severely affect network throughput. As a result, system performance significantly degrades. In this paper, a routing protocol is proposed to avoid energy holes during packets forwarding. The proposed protocol does not require the conventional position information (localization) of holes to avoid them. Localization is cumbersome; energy is inefficient and difficult to achieve in underwater environment where sensor nodes change their positions with water currents. Forwarders with the lowest water pressure level and the maximum number of neighbors are preferred to forward packets. These two parameters together minimize packet drop by following the paths where maximum forwarders are available. To avoid interference along the paths with the maximum forwarders, a packet holding time is defined for each forwarder. Simulation results reveal superior performance of the proposed scheme than the counterpart technique.

Keywords: energy holes, interference, routing, underwater

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Authors: Maria C. Proença, Marco Aniceto, Pedro N. Santos, José C. Freitas

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A methodology based on wavelets is proposed for the automatic location and delimitation of defects in limestone plates. Natural defects include dark colored spots, crystal zones trapped in the stone, areas of abnormal contrast colors, cracks or fracture lines, and fossil patterns. Although some of these may or may not be considered as defects according to the intended use of the plate, the goal is to pair each stone with a map of defects that can be overlaid on a computer display. These layers of defects constitute a database that will allow the preliminary selection of matching tiles of a particular variety, with specific dimensions, for a requirement of N square meters, to be done on a desktop computer rather than by a two-hour search in the storage park, with human operators manipulating stone plates as large as 3 m x 2 m, weighing about one ton. Accident risks and work times are reduced, with a consequent increase in productivity. The base for the algorithm is wavelet decomposition executed in two instances of the original image, to detect both hypotheses – dark and clear defects. The existence and/or size of these defects are the gauge to classify the quality grade of the stone products. The tuning of parameters that are possible in the framework of the wavelets corresponds to different levels of accuracy in the drawing of the contours and selection of the defects size, which allows for the use of the map of defects to cut a selected stone into tiles with minimum waste, according the dimension of defects allowed.

Keywords: automatic detection, defects, fracture lines, wavelets

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Authors: Rafay Ahmed, Condon Lau

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Bone healing is a complex and sequential process involving changes at the molecular level. Raman spectroscopy is a promising technique to study bone mineral and matrix environments simultaneously. In this study, subcritical calvarial defects are used to study bone composition during healing without discomposing the fracture. The model allowed to monitor the natural healing of bone avoiding mechanical harm to the callus. Calvarial defects were created using 1mm burr drill in the parietal bones of Sprague-Dawley rats (n=8) that served in vivo defects. After 7 days, their skulls were harvested after euthanizing. One additional defect per sample was created on the opposite parietal bone using same calvarial defect procedure to serve as control defect. Raman spectroscopy (785 nm) was established to investigate bone parameters of three different skull surfaces; in vivo defects, control defects and normal surface. Principal component analysis (PCA) was utilized for the data analysis and interpretation of Raman spectra and helped in the classification of groups. PCA was able to distinguish in vivo defects from normal surface and control defects. PC1 shows that the major variation at 958 cm⁻¹, which corresponds to ʋ1 phosphate mineral band. PC2 shows the major variation at 1448 cm⁻¹ which is the characteristic band of CH2 deformation and corresponds to collagens. Raman parameters, namely, mineral to matrix ratio and crystallinity was found significantly decreased in the in vivo defects compared to surface and controls. Scanning electron microscope and optical microscope images show the formation of newly generated matrix by means of bony bridges of collagens. Optical profiler shows that surface roughness increased by 30% from controls to in vivo defects after 7 days. These results agree with Raman assessment parameters and confirm the new collagen formation during healing.

Keywords: Raman spectroscopy, principal component analysis, calvarial defects, tissue characterization

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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Manufacturing companies are facing global competition and enormous cost pressure. The use of machine learning applications can help reduce production costs and create added value. Predictive quality enables the securing of product quality through data-supported predictions using machine learning models as a basis for decisions on test results. Furthermore, machine learning methods are able to process large amounts of data, deal with unfavourable row-column ratios and detect dependencies between the covariates and the given target as well as assess the multidimensional influence of all input variables on the target. Real production data are often subject to highly fluctuating boundary conditions and unbalanced data sets. Changes in production data manifest themselves in trends, systematic shifts, and seasonal effects. Thus, Machine learning applications require intensive pre-processing and feature selection. Data preprocessing includes rule-based data cleaning, the application of dimensionality reduction techniques, and the identification of comparable data subsets. Within the used real data set of Bosch hydraulic valves, the comparability of the same production conditions in the production of hydraulic valves within certain time periods can be identified by applying the concept drift method. Furthermore, a classification model is developed to evaluate the feature importance in different subsets within the identified time periods. By selecting comparable and stable features, the number of features used can be significantly reduced without a strong decrease in predictive power. The use of cross-process production data along the value chain of hydraulic valves is a promising approach to predict the quality characteristics of workpieces. In this research, the ada boosting classifier is used to predict the leakage of hydraulic valves based on geometric gauge blocks from machining, mating data from the assembly, and hydraulic measurement data from end-of-line testing. In addition, the most suitable methods are selected and accurate quality predictions are achieved.

Keywords: classification, achine learning, predictive quality, feature selection

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Authors: Lucja Rodzik, Joanna Lewandowska-Lancucka, Michal Szuwarzynski, Krzysztof Szczubialka, Maria Nowakowska

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The analysis of nucleobases is of great importance for bioscience since their abnormal concentration in body fluids suggests the deficiency and mutation of the immune system, and it is considered to be an important parameter for diagnosis of various diseases. The presented conjugate meets the need for development of the effective, selective and highly sensitive sensor for nucleobase/nucleoside detection. The novel, highly fluorescent cadmium telluride quantum dots (CdTe QDs) functionalized with thymine and stabilized with thioglycolic acid (TGA) conjugates has been developed and thoroughly characterized. Successful formation of the material was confirmed by elemental analysis, and UV–Vis fluorescence and FTIR spectroscopies. The crystalline structure of the obtained product was characterized with X-ray diffraction (XRD) method. The composition of CdTe QDs and their thymine conjugate was also examined using X-ray photoelectron spectroscopy (XPS). The size of the CdTe-thymine was 3-6 nm as demonstrated using atomic force microscopy (AFM) and high resolution transmission electron microscopy (HRTEM) imaging. The plasmon resonance fluorescence band at 540 nm on excitation at 351 nm was observed for these nanoparticles. The intensity of this band increased with the increase in the amount of conjugated thymine with no shift in its position. Based on the fluorescence measurements, it was found that the CdTe-thymine conjugate interacted efficiently and selectively not only with adenine, a nucleobase complementary to thymine, but also with nucleosides and adenine-containing modified nucleosides, i.e., 5′-deoxy-5′-(methylthio)adenosine (MTA) and 2’-O-methyladenosine, the urinary tumor markers which allow monitoring of the disease progression. The applicability of the CdTe-thymine sensor for the real sample analysis was also investigated in simulated urine conditions. High sensitivity and selectivity of CdTe-thymine fluorescence towards adenine, adenosine and modified adenosine suggest that obtained conjugate can be potentially useful for development of the biosensor for complementary nucleobase/nucleoside detection.

Keywords: CdTe quantum dots, conjugate, sensor, thymine

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Authors: Nour Hassan Ismail, Abdelmonem Nassar, Khaled Baz

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Semiconductor crystals smaller than about 10 nm, known as quantum dots, have properties that differ from large samples, including a band gap that becomes larger for smaller particles. These properties create several applications for quantum dots. In this paper, new shapes of quantum dot arrays are used to enhance the photo physical properties of gold nano-particles. This paper presents a study of the effect of nano-particles shape, array, and size on their absorption characteristics.

Keywords: quantum dots, nano-particles, LSPR

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Authors: Javed Iqbal

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The growing need for energy by the human society and depletion of conventional energy sources demands a renewable, safe, infinite, low-cost and omnipresent energy source. One of the most suitable ways to solve the foreseeable world’s energy crisis is to use the power of the sun. Photovoltaic devices are especially of wide interest as they can convert solar energy to electricity. Recently the best performing solar cells are silicon-based cells. However, silicon cells are expensive, rigid in structure and have a large timeline for the payback of cost and electricity. Organic photovoltaic cells are cheap, flexible and can be manufactured in a continuous process. Therefore, organic photovoltaic cells are an extremely favorable replacement. Organic photovoltaic cells utilize sunlight as energy and convert it into electricity through the use of conductive polymers/ small molecules to separate electrons and electron holes. A major challenge for these new organic photovoltaic cells is the efficiency, which is low compared with the traditional silicon solar cells. To overcome this challenge, usually two straightforward strategies have been considered: (1) reducing the band-gap of molecular donors to broaden the absorption range, which results in higher short circuit current density (JSC) of devices, and (2) lowering the highest occupied molecular orbital (HOMO) energy of molecular donors so as to increase the open-circuit voltage (VOC) of applications devices.8 Keeping in mind the cost of chemicals it is hard to try many materials on test basis. The best way is to find the suitable material in the bulk. For this purpose, we use computational approach to design molecules based on our organic chemistry knowledge and determine their physical and electronic properties. In this study, we did DFT calculations with different options to get high open circuit voltage and after getting suitable data from calculation we finally did synthesis of a novel D–π–A–π–D type low band-gap small molecular donor material (ZOPTAN-TPA). The Aarylene vinylene based bis(arylhalide) unit containing a cyanostilbene unit acts as a low-band- gap electron-accepting block, and is coupled with triphenylamine as electron-donating blocks groups. The motivation for choosing triphenylamine (TPA) as capped donor was attributed to its important role in stabilizing the separated hole from an exciton and thus improving the hole-transporting properties of the hole carrier.3 A π-bridge (thiophene) is inserted between the donor and acceptor unit to reduce the steric hindrance between the donor and acceptor units and to improve the planarity of the molecule. The ZOPTAN-TPA molecule features a low HOMO level of 5.2 eV and an optical energy gap of 2.1 eV. Champion OSCs based on a solution-processed and non-annealed active-material blend of [6,6]-phenyl-C61-butyric acid methyl ester (PCBM) and ZOPTAN-TPA in a mass ratio of 2:1 exhibits a power conversion efficiency of 1.9 % and a high open-circuit voltage of over 1.0 V.

Keywords: high open circuit voltage, donor, triphenylamine, organic solar cells

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Authors: Regina Chua

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To reduce the costs of re-fielding a large survey, a Random Forest classifier was applied to measure the accuracy of classifying individuals into their assigned segments with the fewest possible questions. Given a long survey, one needed to determine the most predictive ten or fewer questions that would accurately assign new individuals to custom segments. Furthermore, the solution needed to be quick in its classification and usable in non-Python environments. In this paper, a supervised Random Forest classifier was modeled on a dataset with 7,000 individuals, 60 questions, and 254 features. The Random Forest consisted of an iterative collection of individual decision trees that result in a predicted segment with robust precision and recall scores compared to a single tree. A random 70-30 stratified sampling for training the algorithm was used, and accuracy trade-offs at different depths for each segment were identified. Ultimately, the Random Forest classifier performed at 87% accuracy at a depth of 10 with 20 instead of 254 features and 10 instead of 60 questions. With an acceptable accuracy in prioritizing feature selection, new tools were developed for non-Python environments: a worksheet with a formulaic version of the algorithm and an embedded function to predict the segment of an individual in real-time. Random Forest was determined to be an optimal classification model by its feature selection, performance, processing speed, and flexible application in other environments.

Keywords: machine learning, supervised learning, data science, random forest, classification, prediction, predictive modeling

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Authors: D. Rama Krishna, Y. Pandu Rangaiah

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This paper presents the design of multiband reconfigurable antenna using PIN diodes for four iterations and all the four iterations have been validated by measuring return loss and pattern measurements of developed prototype antenna. The simulated and experimental data have demonstrated the concepts of a multiband reconfigurable antenna by switching OFF and ON of PIN diodes for multiple band frequencies. The technique has taken the advantage of a different number of radiating lengths with the use of PIN diode switches, each configuration resonating at multiband frequencies.

Keywords: frequency reconfigurable, meandered line multiband antenna, PIN diode, multiband frequencies

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Authors: Shahrokh Barati, Reza Ramezani

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Due to the countries growing attention to the renewable energy producing, the demand for energy from renewable energy has gone up among the renewable energy sources; wind energy is the fastest growth in recent years. In this regard, in order to increase the availability of wind turbines, using of Fault Detection and Isolation (FDI) system is necessary. Wind turbines include of various faults such as sensors fault, actuator faults, network connection fault, mechanical faults and faults in the generator subsystem. Although, sensors and actuators have a large number of faults in wind turbine but have discussed fewer in the literature. Therefore, in this work, we focus our attention to design a sensor and actuator fault detection and isolation algorithm and Fault-tolerant control systems (FTCS) for Wind Turbine. The aim of this research is to propose a comprehensive fault detection and isolation system for sensors and actuators of wind turbine based on data-driven approaches. To achieve this goal, the features of measurable signals in real wind turbine extract in any condition. The next step is the feature selection among the extract in any condition. The next step is the feature selection among the extracted features. Features are selected that led to maximum separation networks that implemented in parallel and results of classifiers fused together. In order to maximize the reliability of decision on fault, the property of fault repeatability is used.

Keywords: FDI, wind turbines, sensors and actuators faults, renewable energy

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Authors: Hafawa Messaoudi, Taoufik Aguili

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Due to the rapid growth in the use of wireless communication systems, there has been a recent increase in public concern regarding the exposure of humans to Radio Frequency (RF) electromagnetic radiation. This is particularly evident in the case of mobile telephone handsets. Previously, the insertion of a ferrite sheet between the antenna and the human head, the use of conductive materials (such as aluminum), the use of metamaterials (SRR), frequency selective surface (FSS), and electromagnetic band gap (EBG) structures to design high performance devices were proposed as methods of reducing the SAR value. This paper aims to provide an investigation of the effectiveness of various available Specific Absorption Rate (SAR) reduction solutions.

Keywords: EBG, HIS, metamaterials, SAR reduction

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Authors: N. Mansouri, A. Asadi

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Data Grid is a geographically distributed environment that deals with data intensive application in scientific and enterprise computing. Data replication is a common method used to achieve efficient and fault-tolerant data access in Grids. In this paper, a dynamic data replication strategy, called Enhanced Latest Access Largest Weight (ELALW) is proposed. This strategy is an enhanced version of Latest Access Largest Weight strategy. However, replication should be used wisely because the storage capacity of each Grid site is limited. Thus, it is important to design an effective strategy for the replication replacement task. ELALW replaces replicas based on the number of requests in future, the size of the replica, and the number of copies of the file. It also improves access latency by selecting the best replica when various sites hold replicas. The proposed replica selection selects the best replica location from among the many replicas based on response time that can be determined by considering the data transfer time, the storage access latency, the replica requests that waiting in the storage queue and the distance between nodes. Simulation results utilizing the OptorSim show our replication strategy achieve better performance overall than other strategies in terms of job execution time, effective network usage and storage resource usage.

Keywords: data grid, data replication, simulation, replica selection, replica placement

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Authors: Adijat Olubukola Olateju

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Women empowerment is an essential developmental tool in every economy especially in less developed countries; as it helps to enhance women's socio-economic well-being. Some empirical evidence has shown that microcredit has been an effective tool in enhancing women empowerment, especially in developing countries. This paper therefore, investigates the impact of microcredit programme on women empowerment in Lagos State, Nigeria. The study used Cowries Microfinance Bank (CMB) as a case study bank, and a total of 359 women entrepreneurs were selected by simple random sampling technique from the list of Cowries Microfinance Bank. Selection bias which could arise from non-random selection of participants or non-random placement of programme, was adjusted for by dividing the data into participant women entrepreneurs and non-participant women entrepreneurs. The data were analyzed with a Propensity Score Matching (PSM) technique. The result of the Average Treatment Effect on the Treated (ATT) obtained from the PSM indicates that the credit programme has a significant effect on the empowerment of women in the study area. It is therefore, recommended that microfinance banks should be encouraged to give loan to women and for more impact of the loan to be felt by the beneficiaries the loan programme should be complemented with other programmes such as training, grant, and periodic monitoring of programme should be encouraged.

Keywords: empowerment, microcredit, socio-economic wellbeing, development

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Authors: Yi Hu, Chun-Chi Lin, Shau-En Yeh, Shin Lee

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In this study, p–n heterojunctions with La0.5Sr0.5CoO3 (LSCO) and W-doped VO2 thin films were fabricated by the radio frequency (r.f.) magnetron sputtering technique and sol-gel process, respectively. The thickness of VO2 and LSCO thin films are about 40 nm and 400 nm, respectively. Good crystalline match between LSCO and VO2 films was observed from the SEM. The built-in voltages for the junction are about 1.1 V and 2.3 V for the sample in the metallic and insulating state, respectively. The sample can undergo the current induced MIT during applying field when the sample was heated at 40 and 50ºC. This is in agreement with the value obtained from the difference in the work functions of LSCO and VO2. The band structure of the heterojunction was proposed based on the results of analysis.

Keywords: hetrojection, Mott transition, switching , VO2

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Authors: M. Taghavi Zavareh, H. Saremi

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Railway transportation is one of the types of transportation systems which, due to the advantages such as the ability to transport a large number of passengers, environmental protection, low energy consumption, and contribution to tourism, has importance. The existence of suitable and accessible stations is one of the requirements that leads to better performance and plays a significant role in the economic, social, political, and cultural development of urban areas. This paper aims to propose a framework for locating railway passenger stations. This research used descriptive-analytical methods and library tools to answer which definitions and theoretical approaches are suitable for the location of railway passenger stations. The results showed that theoretical approaches such as Transit-Oriented Development and Urban Regeneration are of the utmost importance theoretical bases in the field of research. Moreover, we studied three stations in Iran to find out about real trends and criteria in this research. This study also proposed four major criteria including accessibility, development, rail related and economics, and environmental harmony. Ultimately with an emphasis on the proposed criteria, the study concludes that the combination of Transit-Oriented Development and Urban Regeneration is the most suitable framework to locate railway passenger stations.

Keywords: railway passenger station, railway station, site selection, transit-oriented development, urban regeneration

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Authors: Iman Farasat, Howard M. Salis

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The CRISPR/Cas9 system has revolutionized genome engineering by enabling site-directed and high-throughput genome editing, genome insertion, and gene knockdowns in several species, including bacteria, yeast, flies, worms, and human cell lines. This technology has the potential to enable human gene therapy to treat genetic diseases and cancer at the molecular level; however, the current CRISPR/Cas9 system suffers from seemingly sporadic off-target genome mutagenesis that prevents its use in gene therapy. A comprehensive mechanistic model that explains how the CRISPR/Cas9 functions would enable the rational design of the guide-RNAs responsible for target site selection while minimizing unexpected genome mutagenesis. Here, we present the first quantitative model of the CRISPR/Cas9 genome mutagenesis system that predicts how guide-RNA sequences (crRNAs) control target site selection and cleavage activity. We used statistical thermodynamics and law of mass action to develop a five-step biophysical model of cas9 cleavage, and examined it in vivo and in vitro. To predict a crRNA's binding specificities and cleavage rates, we then compiled a nearest neighbor (NN) energy model that accounts for all possible base pairings and mismatches between the crRNA and the possible genomic DNA sites. These calculations correctly predicted crRNA specificity across 5518 sites. Our analysis reveals that cas9 activity and specificity are anti-correlated, and, the trade-off between them is the determining factor in performing an RNA-mediated cleavage with minimal off-targets. To find an optimal solution, we first created a scheme of safe-design criteria for Cas9 target selection by systematic analysis of available high throughput measurements. We then used our biophysical model to determine the optimal Cas9 expression levels and timing that maximizes on-target cleavage and minimizes off-target activity. We successfully applied this approach in bacterial and mammalian cell lines to reduce off-target activity to near background mutagenesis level while maintaining high on-target cleavage rate.

Keywords: biophysical model, CRISPR, Cas9, genome editing

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Authors: Seungmin Shin, Jin-Baek Kim

Abstract:

Hematite (α-Fe2O3) has very good semiconducting properties with a band gap of 2.1 eV and is antiferromagnetic. Due to its electrochemical stability, low toxicity, wide abundance, and low-cost, hematite, it is a particularly attractive material for photoelectrochemical cells. Additionally, hematite has also found applications in gas sensing, field emission, heterogeneous catalysis, and lithium-ion battery electrodes. Here, we discovered a new universal top-down method for the synthesis of one-dimensional hematite nanowire arrays. Various shapes and lengths of hematite nanowire have been easily fabricated over large areas by sequential processes. The obtained hematite nanowire arrays are promising candidates as photoanodes in photoelectrochemical solar cells.

Keywords: hematite, lithography, nanowire, top-down process

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Authors: M. Golzade Gangraj, A. Abdi, N. ganji

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Aim: The aim of this study was to evaluate the Effect of aerobic training with Coriandrum sativum extract on selection of oxidative stress markers in diabetic rats. Methods: The population of male Wistar rats is the Pasteur Institute. Forty rats were randomly selected as subjects. After moving the mouse in vitro and stay for a week in a cage for sustainability, were diabetic. Diabetes induced by injection STZ (55 mg per kg of body weight of mice) was performed. According blood glucose was randomly divided into four experimental groups (control, training, extract and training-extract). Extract group consumed 150 mg per kg of body weight per day coriander juice. Training group performed aerobic training (50-55% VO2max). Result: The results showed that aerobic exercise training and coriander seed extract caused a significant increase in total antioxidant; superoxide dismutase and catalase were significantly decreased malondialdehyde. Conclusion: the research findings can be stated that the exercise with coriander seed extract has the ability to inhibit free radicals and can have beneficial effects on the body's antioxidant defense system and reduce oxidative stress in diabetic rats with STZ. Because it improves the body's antioxidant defense by increasing serum levels of antioxidant enzymes.

Keywords: aerobic training, coriandrum sativum, antioxidant, diabetes

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Authors: S. Varnagiris, M. Urbonavicius, S. Tuckute, M. Lelis, K. Bockute

Abstract:

Amongst many water purification techniques, TiO₂ photocatalysis is recognized as one of the most promising sustainable methods. It is known that for photocatalytical applications anatase is the most suitable TiO₂ phase, however heterojunction of anatase/rutile phases could improve the photocatalytical activity of TiO₂ even further. Despite the relative simplicity of TiO₂ different synthesis methods lead to the highly dispersed crystal phases and photocatalytic activity of the corresponding samples. Accordingly, suggestions and investigations of various innovative methods of TiO₂ synthesis are still needed. In this work structural and photocatalytical properties of TiO₂ films deposited by the unconventional method of simultaneous co-sputtering from two magnetrons powered by pulsed-Direct Current (pDC) and Radio Frequency (RF) power sources with negative bias voltage have been studied. More specifically, TiO₂ film thickness, microstructure, surface roughness, crystal structure, optical transmittance and photocatalytical properties were investigated by profilometer, scanning electron microscope, atomic force microscope, X-ray diffractometer and UV-Vis spectrophotometer respectively. The proposed unconventional two magnetron co-sputtering based TiO₂ film formation method showed very promising results for crystalline TiO₂ film formation while keeping process temperatures below 100 °C. XRD analysis revealed that by using proper combination of power source type and bias voltage various TiO₂ phases (amorphous, anatase, rutile or their mixture) can be synthesized selectively. Moreover, strong dependency between power source type and surface roughness, as well as between the bias voltage and band gap value of TiO₂ films was observed. Interestingly, TiO₂ films deposited by two magnetron co-sputtering without bias voltage had one of the highest band gap values between the investigated films but its photocatalytic activity was superior compared to all other samples. It is suggested that this is due to the dominating nanocrystalline anatase phase with various exposed surfaces including photocatalytically the most active {001}.

Keywords: films, magnetron co-sputtering, photocatalysis, TiO₂

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Authors: Rabab M. Ramadan, Elaraby A. Elgallad

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With extensive application, the performance of unimodal biometrics systems has to face a diversity of problems such as signal and background noise, distortion, and environment differences. Therefore, multimodal biometric systems are proposed to solve the above stated problems. This paper introduces a bimodal biometric recognition system based on the extracted features of the human palm print and iris. Palm print biometric is fairly a new evolving technology that is used to identify people by their palm features. The iris is a strong competitor together with face and fingerprints for presence in multimodal recognition systems. In this research, we introduced an algorithm to the combination of the palm and iris-extracted features using a texture-based descriptor, the Scale Invariant Feature Transform (SIFT). Since the feature sets are non-homogeneous as features of different biometric modalities are used, these features will be concatenated to form a single feature vector. Particle swarm optimization (PSO) is used as a feature selection technique to reduce the dimensionality of the feature. The proposed algorithm will be applied to the Institute of Technology of Delhi (IITD) database and its performance will be compared with various iris recognition algorithms found in the literature.

Keywords: iris recognition, particle swarm optimization, feature extraction, feature selection, palm print, the Scale Invariant Feature Transform (SIFT)

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Authors: Hoora Dehghani, Meisam Shahbazi, Reza Zare

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During the previous decade, a significant evolution has occurred in the number of private educational centers and, accordingly, the increase in the number of providers and students of these centers around the world. The number of language teaching institutes in Iran that are considered private educational sectors is also growing exponentially as the request for learning foreign languages has extremely increased in recent years. This fact caused competition among the institutions in improving better services tailored to the students’ demands to win the competition. Along with the growth in the industry of education, higher education institutes should apply the marketing-related concepts and view students as customers because students’ outlooks are similar to consumers with education. Studying the influential factors in the selection of an institute has multiple benefits. Firstly, it acknowledges the institutions of the students’ choice factors. Secondly, the institutions use the obtained information to improve their marketing methods. It also helps institutions know students’ outlooks that can be applied to expand the student know-how. Moreover, it provides practical evidence for educational centers to plan useful amenities and programs, and use efficient policies to cater to the market, and also helps them execute the methods that increase students’ feeling of contentment and assurance. Thus, this study explored the influencing factors in the selection of a language learning institute by language learners and examined and compared the importance among the varying age groups and genders. In the first phase of the study, the researchers selected 15 language learners as representative cases within the specified age ranges and genders purposefully and interviewed them to explore the comprising elements in their language institute selection process and analyzed the results qualitatively. In the second phase, the researchers identified elements as specified items of a questionnaire, and 1000 English learners across varying educational contexts rated them. The TOPSIS method was used to analyze the data quantitatively by representing the level of importance of the items for the participants generally and specifically in each subcategory; genders and age groups. The results indicated that the educational quality, teaching method, duration of training course, establishing need-oriented courses, and easy access were the most important elements. On the other hand, offering training in different languages, the specialized education of only one language, the uniform and appropriate appearance of office staff, having native professors to the language of instruction, applying Computer or online tests instead of the usual paper tests respectively as the least important choice factors in selecting a language institute. Besides, some comparisons among different groups’ ratings of choice factors were made, which revealed the differences among different groups' priorities in choosing a language institute.

Keywords: choice factors, EFL institute selection, english learning, need analysis, TOPSIS

Procedia PDF Downloads 164