Search results for: blue color detection

Authors: G. Disciglio, F. Lops, A. Carlucci, G. Gatta, A. Tarantino, L. Frabboni, F. Carriero, F. Cibelli, M. L. Raimondo, E. Tarantino

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The Phelipanche ramosa is is an important crop whose cultivation in the Mediterranean basin is severely contained the phitoparasitic weed Phelipanche ramose. The semiarid regions of the world are considered the main center of this parasitic weed, where heavy infestation is due to the ability to produce high numbers of seeds (up to 500,000 per plant), that remain viable for extended period (more than 19 years). In this paper 12 treatments of parasitic weed control including chemical, agronomic, biological and biotechnological methods have been carried out. In 2014 a trial was performed at Foggia (southern Italy). on processing tomato (cv Docet), grown in field infested by Phelipanche ramosa, Tomato seedlings were transplant on May 5, 2014 on a clay-loam soil (USDA) fertilized by 100 kg ha-1 of N; 60 kg ha-1 of P2O5 and 20 kg ha-1 of S. Afterwards, top dressing was performed with 70 kg ha-1 of N. The randomized block design with 3 replicates was adopted. During the growing cycle of the tomato, at 56-78 and 92 days after transplantation, the number of parasitic shoots emerged in each pot was detected. At harvesting, on August 18, the major quantity-quality yield parameters were determined (marketable yield, mean weight, dry matter, pH, soluble solids and color of fruits). All data were subjected to analysis of variance (ANOVA), using the JMP software (SAS Institute Inc., Cary, NC, USA), and for comparison of means was used Tukey's test. Each treatment studied did not provide complete control against Phelipanche ramosa. However among the 12 tested methods, Fusarium, gliphosate, radicon biostimulant and Red Setter tomato cv (improved genotypes obtained by Tilling technology) proved to mitigate the virulence of the attacks of Phelipanche ramose. It is assumed that these effects can be improved by combining some of these treatments each other, especially for a gradual and continuing reduction of the “seed bank” of the parasite in the soil.

Keywords: control methods, Phelipanche ramosa, tomato crop, mediterranean basin

Procedia PDF Downloads 563

Authors: Ramona-Niculina Jurcau, Ioana-Marieta Jurcau, Dong Hun Kwak, Nicolae-Alexandru Colceriu

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Background: Stress management (SM) is a topic of great academic interest and equally a task to accomplish. In addition, it is recognized the beneficial role of unconventional therapies (UCT) in stress modulation. Aims: The aim was to evaluate medical (MS) versus non-medical students’ (NMS) opinions about academic stress management (ASM) using UCT. Methods: MS (n=103, third year males and females) and NMS (n=112, males and females, from humanities faculties, different years of study), out of their academic program, voluntarily answered to a questionnaire concerning: a) Classification of the four most important academic stress factors; b) The extent to which their daily life influences academic stress; c) The most important SM methods they know; d) Which of these methods they are applying; e) the UCT they know or about which they have heard; f) Which of these they know to have stress modulation effects; g) Which of these UCT, participants are using or would like to use for modulating stress; and if participants use UTC for their own choose or following a specialist consultation in those therapies (SCT); h) If they heard about the following UCT and what opinion they have (using visual analogue scale) about their use (following CST) for the ASM: Phytotherapy (PT), apitherapy (AT), homeopathy (H), ayurvedic medicine (AM), traditional Chinese medicine (TCM), music therapy (MT), color therapy (CT), forest therapy (FT). Results: Among the four most important academic stress factors, for MS more than for NMS, are: busy schedule, large amount of information taught; high level of performance required, reduced time for relaxing. The most important methods for SM that MS and NMS know, hierarchically are: listen to music, meeting friends, playing sport, hiking, sleep, regularly breaks, seeing positive side, faith; of which, NMS more than MS, are partially applying to themselves. UCT about which MS and less NMS have heard, are phytotherapy, apitherapy, acupuncture, reiki. Of these UTC, participants know to have stress modulation effects: some plants, bee’s products and music; they use or would like to use for ASM (the majority without SCT) certain teas, honey and music. Most of MS and only some NMS heard about PT, AT, TCM, MT and much less about H, AM, CT, TT. NMS more than MS, would use these UCT, following CST. Conclusions: 1) Academic stress is similarly reflected in MS and NMS opinions. 2) MS and NMS apply similar but very few UCT for stress modulation. 3) Information that MS and NMS have about UCT and their ASM application is reduced. 4) It is remarkable that MS and especially NMS, are open to UCT use for ASM, following an SCT.

Keywords: academic stress, stress management, stress modulation, medical students, non-medical students, unconventional therapies

Procedia PDF Downloads 357

Authors: M. D. D. Chathurangi, M. G. K. Nayanathara, K. M. H. M. M. Gunapala, G. M. R. G. Dayananda, Kavinga Yapa Abeywardena, Deemantha Siriwardana

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Due to the growing popularity of social media platforms at present, there are various concerns, mostly cyberbullying, spam, bot accounts, and the spread of incorrect information. To develop a risk score calculation system as a thorough method for deciphering and exposing unethical social media profiles, this research explores the most suitable algorithms to our best knowledge in detecting the mentioned concerns. Various multiple models, such as Naïve Bayes, CNN, KNN, Stochastic Gradient Descent, Gradient Boosting Classifier, etc., were examined, and the best results were taken into the development of the risk score system. For cyberbullying, the Logistic Regression algorithm achieved an accuracy of 84.9%, while the spam-detecting MLP model gained 98.02% accuracy. The bot accounts identifying the Random Forest algorithm obtained 91.06% accuracy, and 84% accuracy was acquired for fake news detection using SVM.

Keywords: cyberbullying, spam behavior, bot accounts, fake news, machine learning

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Authors: Xavier Ruiz Del Portal

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This paper incorporates mobility between the legal and black economies into a model of tax evasion with endogenous labor supply in which underreporting is possible in one sector but impossible in the other. We have found that the results of the effects along the extensive margin (number of evaders) become more robust and conclusive than those along the intensive margin (hours of illegal work) usually considered by the literature. In particular, it is shown that the following policies reduce the number of evaders: (a) larger and more progressive evasion penalties; (b) higher detection probabilities; (c) an increase in the legal sector wage rate; (d) a decrease in the moonlighting wage rate; (e) higher costs for creating opportunities to evade; (f) lower opportunities to evade, and (g) greater psychological costs of tax evasion. When tax concealment and illegal work also are taken into account, the effects do not vary significantly under the assumptions in Cowell (1985), except for the fact that policies (a) and (b) only hold as regards low- and middle-income groups and policies (e) and (f) as regards high-income groups.

Keywords: income taxation, tax evasion, extensive margin responses, the penalty system

Procedia PDF Downloads 155

Authors: Magdalena Bury-Kaminska, Aneta Szudy-Szczyrek, Aleksandra Nowaczynska, Olga Jankowska-Lecka, Marek Hus, Klaudia Kot

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Introduction: The aim of the research was to determine the changes in cognitive functioning in patients with plasma cell myeloma by comparing patients’ state before the treatment and during chemotherapy as well as to determine the biological factors that can be used to predict patients’ cognitive state. Methods: The patients underwent the research procedure twice: before chemotherapy and after 4-6 treatment cycles. A psychological test and measurement of the following biological variables were carried out: TNF-α (tumor necrosis factor), IL-6 (interleukin 6), IL-10 (interleukin 10), BDNF (brain-derived neurotrophic factor). The following research methods were implemented: the Montreal Cognitive Assessment (MoCA), Battery of Tests for Assessing Cognitive Functions PU1, experimental and clinical trials based on the Choynowski’s Memory Scale, Stroop Color-Word Interference Test (SCWT), depression measurement questionnaire. Results: The analysis of the research showed better cognitive functions of patients during chemotherapy in comparison to the phase before it. Moreover, neurotrophin BDNF allows to predict the level of selected cognitive functions (semantic fluency and execution control) already at the diagnosis stage. After 4-6 cycles, it is also possible to draw conclusions concerning the extent of working memory based on the level of BDNF. Cytokine TNF-α allows us to predict the level of letter fluency during anti-cancer treatment. Conclusions: It is possible to presume that BDNF has a protective influence on patients’ cognitive functions and working memory and that cytokine TNF-α co-occurs with a diminished execution control and better material grouping in terms of phonological fluency. Acknowledgment: This work was funded by the National Science Center in Poland [grant no. 2017/27/N/HS6/02057.

Keywords: chemobrain, cognitive impairment, non−central nervous system cancers, hematologic diseases

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Authors: Wenlong Feng, Zhenchun Du, Jianguo Yang

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To decrease the grating scale thermal expansion error, a novel method which based on multiple temperature detections is proposed. Several temperature sensors are installed on the grating scale and the temperatures of these sensors are recorded. The temperatures of every point on the grating scale are calculated by interpolating between adjacent sensors. According to the thermal expansion principle, the grating scale thermal expansion error model can be established by doing the integral for the variations of position and temperature. A novel compensation method is proposed in this paper. By applying the established error model, the grating scale thermal expansion error is decreased by 90% compared with no compensation. The residual positioning error of the grating scale is less than 15um/10m and the accuracy of the machine tool is significant improved.

Keywords: thermal expansion error of grating scale, error compensation, machine tools, integral method

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Authors: Huy Q. Tran, Jungwon Huh, Kiseok Kwak, Choonghyun Kang

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Infrared thermography (IRT) technique has been proven to be a good method for nondestructive evaluation of concrete material. In the building, a broad range of applications has been used such as subsurface defect inspection, energy loss, and moisture detection. The purpose of this research is to consider the qualitative and quantitative performance of reinforced concrete deteriorations using active infrared thermography technique. An experiment of three different heating regimes was conducted on a concrete slab in the laboratory. The thermal characteristics of the IRT method, i.e., absolute contrast and observation time, are investigated. A linear relationship between the observation time and the real depth was established with a well linear regression R-squared of 0.931. The results showed that the absolute contrast above defective area increases with the rise of the size of delamination and the heating time. In addition, the depth of delamination can be predicted by using the proposal relationship of this study.

Keywords: concrete building, infrared thermography, nondestructive evaluation, subsurface delamination

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Authors: Gemma García López

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The goal of this study is to analyze if search queries carried out in search engines such as Google, can offer emotional information about the user that performs them. Knowing the emotional state in which the Internet user is located can be a key to achieve the maximum personalization of content and the detection of worrying behaviors. For this, two studies were carried out using tools with advanced natural language processing techniques. The first study determines if a query can be classified as positive, negative or neutral, while the second study extracts emotional content from words and applies the categorical and dimensional models for the representation of emotions. In addition, we use search queries in Spanish and English to establish similarities and differences between two languages. The results revealed that text search queries performed by users on the Internet can be classified emotionally. This allows us to better understand the emotional state of the user at the time of the search, which could involve adapting the technology and personalizing the responses to different emotional states.

Keywords: emotion classification, text search queries, emotional analysis, sentiment analysis in text, natural language processing

Procedia PDF Downloads 141

Authors: Lars Laußat, Manfred Helmus, Kamil Szczesny, Markus König

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As one result of the project “Reactive Construction Project Scheduling using Real Time Construction Logistic Data and Simulation”, a procedure for using data about uncertain resource availability assumptions in reactive scheduling processes has been developed. Prediction data about resource availability is generated in a formalized way using real-time monitoring data e.g. from auto-ID systems on the construction site and in the supply chains. The paper focuses on the formalization of the procedure for monitoring construction logistic processes, for the detection of disturbance and for generating of new and uncertain scheduling assumptions for the reactive resource constrained simulation procedure that is and will be further described in other papers.

Keywords: auto-ID, construction logistic, fuzzy, monitoring, RFID, scheduling

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Authors: Hyun-Woo Cho

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Detection of incipient abnormal events in production processes is important to improve safety and reliability of manufacturing operations and reduce losses caused by failures. The construction of calibration models for predicting faulty conditions is quite essential in making decisions on when to perform preventive maintenance. This paper presents a multivariate calibration monitoring approach based on the statistical analysis of process measurement data. The calibration model is used to predict faulty conditions from historical reference data. This approach utilizes variable selection techniques, and the predictive performance of several prediction methods are evaluated using real data. The results shows that the calibration model based on supervised probabilistic model yielded best performance in this work. By adopting a proper variable selection scheme in calibration models, the prediction performance can be improved by excluding non-informative variables from their model building steps.

Keywords: calibration model, monitoring, quality improvement, feature selection

Procedia PDF Downloads 356

Authors: Jijun Shi, Lichen Sun, Jianchao Zhao, Lizhi Sun, Enjun Liu, Chongwu Guo

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Because of the consistency of pressure direction, more short cycle, and high sensitivity, Charging-Vacuum helium mass spectrometer leak testing technology is the most popular leak testing technology for the seal testing of the spacecraft parts, especially the small and medium size ones. Usually, auxiliary pump was used, and the minimum detectable leak rate could reach 5E-9Pa•m3/s, even better on certain occasions. Relative error is more important when evaluating the results. How to choose the reference leak, the background level of helium, and record formats would affect the leak rate tested. In the linearity range of leak testing system, it would reduce 10% relative error if the reference leak with larger leak rate was used, and the relative error would reduce obviously if the background of helium was low efficiently, the record format of decimal was used, and the more stable data were recorded.

Keywords: leak testing, spacecraft parts, relative error, error control

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Authors: Bothinah Altaf, Gary Montague, Elaine B. Martin

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This study involves the modeling and monitoring of an ammonia synthesis fixed-bed reactor using partial least squares (PLS) and its variants. The process exhibits complex dynamic behavior due to the presence of heat recycling and feed quench. One limitation of static PLS model in this situation is that it does not take account of the process dynamics and hence dynamic PLS was used. Although it showed, superior performance to static PLS in terms of prediction, the monitoring scheme was inappropriate hence adaptive PLS was considered. A limitation of adaptive PLS is that non-conforming observations also contribute to the model, therefore, a new adaptive approach was developed, robust adaptive dynamic PLS. This approach updates a dynamic PLS model and is robust to non-representative data. The developed methodology showed a clear improvement over existing approaches in terms of the modeling of the reactor and the detection of faults.

Keywords: ammonia synthesis fixed-bed reactor, dynamic partial least squares modeling, recursive partial least squares, robust modeling

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Authors: Umberto Cerasani, Luca Cerasani

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Methods for earthquakes forecasting have been intensively investigated in the last decades, but there is still no universal solution agreed by seismologists. Rock failure is most often preceded by a tiny elastic movement in the failure area and by the appearance of micro-cracks. These micro-cracks could be detected at the soil surface and represent useful earth-quakes precursors. The aim of this study was to verify whether tiny raw acceleration signals (in the 10⁻¹ to 10⁻⁴ cm/s² range) prior to the arrival of main primary-waves could be exploitable and related to earthquakes magnitude. Mathematical tools such as Fast Fourier Transform (FFT), moving average and wavelets have been applied on raw acceleration data available on the ITACA web site, and the study focused on one of the most unpredictable earth-quakes, i.e., the August 24th, 2016 at 01H36 one that occurred in the central Italy area. It appeared that these tiny acceleration signals preceding main P-waves have different patterns both on frequency and time domains for high magnitude earthquakes compared to lower ones.

Keywords: earthquake, accelerometer, earthquake forecasting, seism

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Authors: Jia-Chao Wang

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A model of the universe without invoking space expansion is proposed to explain the observed redshift-distance relation and the cosmic microwave background radiation (CMB). The main hypothesized feature of the model is that photons traveling in space interact with the CMB photon gas. This interaction causes the photons to gradually lose energy through dissipation and, therefore, experience redshift. The interaction also causes some of the photons to be scattered off their track toward an observer and, therefore, results in beam intensity attenuation. As observed, the CMB exists everywhere in space and its photon density is relatively high (about 410 per cm³). The small average energy of the CMB photons (about 6.3×10⁻⁴ eV) can reduce the energies of traveling photons gradually and will not alter their momenta drastically as in, for example, Compton scattering, to totally blur the images of distant objects. An object moving through a thermalized photon gas, such as the CMB, experiences a drag. The cause is that the object sees a blue shifted photon gas along the direction of motion and a redshifted one in the opposite direction. An example of this effect can be the observed CMB dipole: The earth travels at about 368 km/s (600 km/s) relative to the CMB. In the all-sky map from the COBE satellite, radiation in the Earth's direction of motion appears 0.35 mK hotter than the average temperature, 2.725 K, while radiation on the opposite side of the sky is 0.35 mK colder. The pressure of a thermalized photon gas is given by Pγ = Eγ/3 = αT⁴/3, where Eγ is the energy density of the photon gas and α is the Stefan-Boltzmann constant. The observed CMB dipole, therefore, implies a pressure difference between the two sides of the earth and results in a CMB drag on the earth. By plugging in suitable estimates of quantities involved, such as the cross section of the earth and the temperatures on the two sides, this drag can be estimated to be tiny. But for a photon traveling at the speed of light, 300,000 km/s, the drag can be significant. In the present model, for the dissipation part, it is assumed that a photon traveling from a distant object toward an observer has an effective interaction cross section pushing against the pressure of the CMB photon gas. For the attenuation part, the coefficient of the typical attenuation equation is used as a parameter. The values of these two parameters are determined by fitting the 748 µ vs. z data points compiled from 643 supernova and 105 γ-ray burst observations with z values up to 8.1. The fit is as good as that obtained from the lambda cold dark matter (ΛCDM) model using online cosmological calculators and Planck 2015 results. The model can be used to interpret Hubble's constant, Olbers' paradox, the origin and blackbody nature of the CMB radiation, the broadening of supernova light curves, and the size of the observable universe.

Keywords: CMB as the lowest energy state, model of the universe, origin of CMB in a static universe, photon-CMB photon gas interaction

Procedia PDF Downloads 134

Authors: Surita Maini, Sanjay Dhanka

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Machine learning (ML) involves developing algorithms and statistical models that enable computers to learn and make predictions or decisions based on data without being explicitly programmed. Because of its unlimited abilities ML is gaining popularity in medical sectors; Medical Imaging, Electronic Health Records, Genomic Data Analysis, Wearable Devices, Disease Outbreak Prediction, Disease Diagnosis, etc. In the last few decades, many researchers have tried to diagnose Breast Cancer (BC) using ML, because early detection of any disease can save millions of lives. Working in this direction, the authors have proposed a hybrid ML technique RBF SVM, to predict the BC in earlier the stage. The proposed method is implemented on the Breast Cancer UCI ML dataset with 569 instances and 32 attributes. The authors recorded performance metrics of the proposed model i.e., Accuracy 98.24%, Sensitivity 98.67%, Specificity 97.43%, F1 Score 98.67%, Precision 98.67%, and run time 0.044769 seconds. The proposed method is validated by K-Fold cross-validation.

Keywords: breast cancer, support vector classifier, machine learning, hyper parameter tunning

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Authors: Masood Ahmad, Ataul Aziz Ikram, Ishtiaq Wahid

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Wireless sensor network (WSN) is the interconnection of mobile wireless nodes with limited energy and memory. These networks can be deployed formany critical applications like military operations, rescue management, fire detection and so on. In flat routing structure, every node plays an equal role of sensor and router. The topology may change very frequently due to the mobile nature of nodes in WSNs. The topology maintenance may produce more overhead messages. To avoid topology maintenance overhead messages, an optimized cluster based mobile wireless sensor network using memetic algorithm is proposed in this paper. The nodes in this network are first divided into clusters. The cluster leaders then transmit data to that base station. The network is validated through extensive simulation study. The results show that the proposed technique has superior results compared to existing techniques.

Keywords: WSN, routing, cluster based, meme, memetic algorithm

Procedia PDF Downloads 481

Authors: Ali N. Siyal, Saima Q. Memon, Latif Elçi, Aydan Elçi

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Polystyrene (PS) was extracted from Styrofoam (expanded polystyrene foam) waste, so called white pollutant. The PS was functionalized with N, N- Bis(2-aminobenzylidene)benzene-1,2-diamine (ABA) ligand through an azo spacer. The resin was characterized by FT-IR spectroscopy and elemental analysis. The PS-N=N-ABA resin was used for the enrichment and speciation of Cr(III)/Cr(VI) ions and total Cr determination in aqueous samples by Flame Atomic Absorption Spectrometry (FAAS). The separation of Cr(III)/Cr(VI) ions was achieved at pH 2. The recovery of Cr(VI) ions was achieved ≥ 95.0% at optimum parameters: pH 2; resin amount 300 mg; flow rates 2.0 mL min-1 of solution and 2.0 mL min-1 of eluent (2.0 mol L-1 HNO3). Total Cr was determined by oxidation of Cr(III) to Cr(VI) ions using H2O2. The limit of detection (LOD) and quantification (LOQ) of Cr(VI) were found to be 0.40 and 1.20 μg L-1, respectively with preconcentration factor of 250. Total saturation and breakthrough capacitates of the resin for Cr(IV) ions were found to be 0.181 and 0.531 mmol g-1, respectively. The proposed method was successfully applied for the preconcentration/speciation of Cr(III)/Cr(VI) ions and determination of total Cr in industrial effluents.

Keywords: styrofoam waste, polymeric resin, preconcentration, speciation, Cr(III)/Cr(VI) ions, FAAS

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Authors: Taru Singh, Shukla Das, V. G. Ramachandran

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Objectives: To develop SYBR green based real-time PCR assay to detect carbapenemases (NDM, IMP) genes in E. coli. Methods: A total of 40 E. coli from stool samples were tested. Six were previously characterized as resistant to carbapenems and documented by PCR. The remaining 34 isolates previously tested susceptible to carbapenems and were negative for these genes. Bacterial RNA was extracted using manual method. The real-time PCR was performed using the Light Cycler III 480 instrument (Roche) and specific primers for each carbapenemase target were used. Results: Each one of the two carbapenemase gene tested presented a different melting curve after PCR amplification. The melting temperature (Tm) analysis of the amplicons identified was as follows: blaIMP type (Tm 82.18°C), blaNDM-1 (Tm 78.8°C). No amplification was detected among the negative samples. The results showed 100% concordance with the genotypes previously identified. Conclusions: The new assay was able to detect the presence of two different carbapenemase gene type by real-time PCR.

Keywords: resistance, b-lactamases, E. coli, real-time PCR

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Authors: A. Ejah Umraeni Salam, M. Tola, M. Selintung, F. Maricar

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Clean water is an essential and fundamental human need. Therefore, its supply must be assured by maintaining the quality, quantity and water pressure. However the fact is, on its distribution system, leakage happens and becomes a common world issue. One of the technical causes of the leakage is a leaking pipe. The purpose of the research is how to use the Radial Basis Function Neural (RBFNN) model to detect the location and the magnitude of the pipeline leakage rapidly and efficiently. In this study the RBFNN are trained and tested on data from EPANET hydraulic modeling system. Method of Radial Basis Function Neural Network is proved capable to detect location and magnitude of pipeline leakage with of the accuracy of the prediction results based on the value of RMSE (Root Meant Square Error), comparison prediction and actual measurement approaches 0.000049 for the whole pipeline system.

Keywords: radial basis function neural network, leakage pipeline, EPANET, RMSE

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Authors: Milenko Košutić, Jelena Filipović, Zvonko Nježić

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Extrusion technology is thermal processing that is applied to improve the nutritional, hygienic, and physical-chemical characteristics of the raw material. Overall, the extrusion process is an efficient method for the production of a wide range of food products. It combines heat, pressure, and shear to transform raw materials into finished goods with desired textures, shapes, and nutritional profiles. The extruded products’ quality is remarkably dependent upon feed material composition, barrel temperature profile, feed moisture content, screw speed, and other extrusion system parameters. Given consumer expectations for snack foods, a high expansion index and low bulk density, in addition to crunchy texture and uniform microstructure, are desired. This paper investigates the effects of simultaneous different types of corn (white corn, yellow corn, red corn, and black corn) addition and different screw speed (350, 500, 650 rpm) on the physical, technological, and functional properties of flakes products. Black corn flour and screw speed at 350 rpm positively influenced physical, technological characteristics, mineral composition, and antioxidant properties of flake products with the best total score analysis of 0,59. Overall, the combination of Tukey's HSD test and PCA enables a comprehensive analysis of the observed corn products, allowing researchers to identify them. This research aims to analyze the influence of different types of corn flour (white corn, yellow corn, red corn, and black corn) on the nutritive and sensory properties of the product (quality, texture, and color), as well as the acceptance of the new product by consumers on the territory of Novi Sad. The presented data point that investigated corn flakes from black corn flour at 350 rpm is a product with good physical-technological and functional properties due to a higher level of antioxidant activity.

Keywords: corn types, flakes product, nutritive quality, acceptability

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Authors: Ghazi Abdul Rehman Qasmi

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Islam is the preacher and torch-bearer of unity and solidarity. All the followers of Islam are advised to be united. Islam strongly condemns those elements which disunite the unity of Muslim Ummah. Like pearls in a rosary, Islam has united the Muslims from all over the world in the wreath of unity and forbade the Muslims to avoid separation and to be disintegrated. The aspect of unity is prominent in all divine injunctions and about worship. By offering five times obligatory congregational prayers, passion of mutual love and affection is increased and on the auspicious days like Friday, Eid-ul-fiter and Eid-ul-azha, majority of the Muslims come together at central places to offer these congregational prayers. Thus unity and harmony among the Muslims can be seen. Similarly the Muslim pilgrims from all over the world eliminate all kind of worldly discrimination to perform many rituals of pilgrimage while wearing white color cloth as a dress. Pilgrimage is a demonstration of Islamic strength. When the Muslims from all over the world perform the same activities together and they offer their prayers under the leadership of one leader (IMAM). Muslims come together on the occasion of pilgrimage to perform Tawaf (seven circuits,first three circuits at a hurried pace(Rammal) and followed by four times, more closely, at a leisurely pace, round the Holy Kaabah to perform circumambulation known as Tawaf in religious terminology,Saee(running or walking briskly seven times between two small hills Safa&Marwa), Ramy-al-jamarat (throwing pebbles at the stone pillars, symbolizing the devil). In this way dignity and sublimity of Islam is increased and unity and integrity of Muslim Ummah is promoted also. By studying the life history of Hazrat Muhammad (P.B.U.H) we come to know that our Holy Prophet (P.B.U.H) has put emphasis on unity and integrity. We have to follow the Islamic teachings to create awareness among the members of Muslim Ummah. In the light of the Holy Quran and Sunnah, we have to utilize all the sources and potential for this noble cause.

Keywords: unity, Ummah, sources, Islamic teaching

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Authors: Raghad A. Altowairgi

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With the wide spread of social media platforms, young people tend to use them extensively as the first means of communication due to their ease and modernity. But these platforms often create a fertile ground for bullies to practice their aggressive behavior against their victims. Platform usage cannot be reduced, but intelligent mechanisms can be implemented to reduce the abuse. This is where machine learning comes in. Understanding and classifying text can be helpful in order to minimize the act of cyberbullying. Artificial intelligence techniques have expanded to formulate an applied tool to address the phenomenon of cyberbullying. In this research, machine learning models are built to classify text into two classes; cyberbullying and non-cyberbullying. After preprocessing the data in 4 stages; removing characters that do not provide meaningful information to the models, tokenization, removing stop words, and lowering text. BoW and TF-IDF are used as the main features for the five classifiers, which are; logistic regression, Naïve Bayes, Random Forest, XGboost, and Catboost classifiers. Each of them scores 92%, 90%, 92%, 91%, 86% respectively.

Keywords: cyberbullying, machine learning, Bag-of-Words, term frequency-inverse document frequency, natural language processing, Catboost

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Authors: Hemant Kumar, R. N. K. Sharma, A. P. Krishna

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The study has been carried out on the Saranda in Jharkhand and a part of Odisha state. Geospatial data of Hyperion, a remote sensing satellite, have been used. This study has used a wide variety of patterns related to image processing to enhance and extract the mining class of Fe and Mn ores.Landsat-8, OLI sensor data have also been used to correctly explore related minerals. In this way, various processes have been applied to increase the mineralogy class and comparative evaluation with related frequency done. The Hyperion dataset for hyperspectral remote sensing has been specifically verified as an effective tool for mineral or rock information extraction within the band range of shortwave infrared used. The abundant spatial and spectral information contained in hyperspectral images enables the differentiation of different objects of any object into targeted applications for exploration such as exploration detection, mining.

Keywords: Hyperion, hyperspectral, sensor, Landsat-8

Procedia PDF Downloads 124

Authors: Maximo Cozzetti

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The aim is to evaluate the capability of the 'Siberian Husky' (FCI-Standard Nº 270) breed of the common dog (Canis lupus familiaris) to detect terminally-ill human patients undergoing palliative care. A total of 49 such patients that fulfill the 'National Scientific and Technical Research Council–Ethical Principles for the Behavior of the Scientific and Technical Investigator' policy, (mainly affected with Stage IV Hodgkin lymphoma or Stage IV Carcinoma, though various other terminal diseases were present) and 49 controls were enrolled. A total of 13 specimens of Siberian Huskies (Canis lupus familiaris FCI – Standard Nº 270) were selected. After a conditioning training regime in which the canines were rewarded when identifying terminally ill patients and excluding the control subjects, a double-blind experiment was conducted in which the canines were presented with a previously unknown patient through an olfactory-proof plexiglass window for 2-minute intervals. The test subjects correctly identified 89.80% of the humans as either ‘ill’ or ‘healthy’. It is important to note that both groups of humans were selected considering and preventing confounding and self-identifying factors such as age, ethnicity, clothing, posture, skin color, alopecia (chemotherapy-induced or otherwise), etc. The olfactory-proofing of the test area rules out the use of the sense of smell to detect distinctive drugs or bodily odors that may be associated with terminal diseases. Thus, the Siberian Husky breed of the common dog shows the visual capability to detect and identify terminally ill patients undergoing palliative care regardless of age, posture, and quantity of hair. Though the capability of the breed of dog to detect terminally-ill patients was observed thoroughly during the course of the experiments, the exact process by which the canines identify the test subjects remains unknown and further research is encouraged.

Keywords: Canis lupus familiaris, Siberian Husky, visual identification of terminall illness, FCI-Standard Nº270

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Authors: Anuja Singh, Avik K. Pati, Ashok K. Mishra

Abstract:

Organic fluorophores with π-conjugated scaffolds are important because of their interesting optoelectronic properties. In recent years, our lab has been engaged in understanding the photophysics of small diacetylene bridged fluorophores and found the diynes as a promising class of π-conjugated fluorophores. Building on this understanding, recently we have focused on the photophysics of a less explored class of cross-conjugated Y-shaped enediynes (one double and two triple bonds). Here we present the photophysical properties of such enediynes which show interesting photophysical properties that include dual emissions from locally excited (LE) and intramolecular charge transfer (ICT) states and ring size dependent aggregate fluorescence in non-aqueous media. The dyes also show prominent aggregate fluorescence in mixed-aqueous solvents and solid powder form. We further show that the solid state fluorescence can be reversibly switched multiple of cycles by external stimuli, highlighting their potential applications in solid states. The enediynes with push-pull electronic substituents/moieties exhibit high contrast fluorescence color switching upon continuous photon illumination. The intriguing photophysical outcomes of the enediynyl fluorophores are judiciously exploited to generate single-component white light emission in binary solvent mixtures and sense polar aprotic vapor in polymer film matrices. The photophysical behavior of the dyes is further successfully utilized to monitor the microenvironment changes of biologically relevant anisotropic media such as bile salts. In summary, the newly introduced cross-conjugated enediynes enrich the toolbox of organic fluorophores and vouch to display versatile applications.

Keywords: aggregation in solution and solid state, enediynes, physical photochemistry and photophysics, vapor sensing and white light emission

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Authors: Neelamshobha Nirala, R. Periyasamy, Awanish Kumar

Abstract:

Diabetes is a metabolic disorder and with the increase of global prevalence of diabetes, cardiovascular diseases and mortality related to diabetes has also increased. Diabetes causes the increase of arterial stiffness by elusive hormonal and metabolic abnormalities. We used photoplethysmograph (PPG), a simple non-invasive method to study the change in arterial stiffness due to diabetes. Toe PPG signals were taken from 29 diabetic subjects with mean age of (65±8.4) years and 21 non-diabetic subjects of mean age of (49±14) years. Mean duration of diabetes is 12±8 years for diabetic group. Rise-time (RT) and area under rise time (AUR) were calculated from the PPG signal of each subject and Welch’s t-test is used to find the significant difference between two groups. We obtained a significant difference of (p-value) 0.0005 and 0.03 for RT and AUR respectively between diabetic and non-diabetic subjects. Average value of RT and AUR is 0.298±0.003 msec and 14.4±4.2 arbitrary units respectively for diabetic subject compared to 0.277±0.0005 msec and 13.66±2.3 a.u respectively for non-diabetic subjects. In conclusion, this study support that arterial stiffness is increased in diabetes and can be detected early using PPG.

Keywords: area under rise-time, AUR, arterial stiffness, diabetes, photoplethysmograph, PPG, rise-time (RT)

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Authors: P. S. Surya Meghana, K. Lingeshwaran, C. Kannan, V. Raghavendran, C. Priya

Abstract:

One of the most basic and powerful tools in all of science and medicine is the light microscope, the fundamental device for laboratory as well as research purposes. With the improving technology, the need for portable, economic and user-friendly instruments is in high demand. The conventional microscope fails to live up to the emerging trend. Also, adequate access to healthcare is not widely available, especially in developing countries. The most basic step towards the curing of a malady is the diagnosis of the disease itself. The main aim of this paper is to diagnose Malaria with the most common device, cell phones, which prove to be the immediate solution for most of the modern day needs with the development of wireless infrastructure allowing to compute and communicate on the move. This opened up the opportunity to develop novel imaging, sensing, and diagnostics platforms using mobile phones as an underlying platform to address the global demand for accurate, sensitive, cost-effective, and field-portable measurement devices for use in remote and resource-limited settings around the world.

Keywords: cellular, hand-held, health care, image processing, malarial parasites, microscope

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Authors: Morello Sara, Pederiva Sabina, Bianchi Manila, Martucci Francesca, Marchis Daniela, Decastelli Lucia

Abstract:

Vegetables represent an integral part of a healthy diet due to their valuable nutritional properties and the growth in consumer demand in recent years is particularly remarkable for a diet rich in vitamins and micronutrients. However, plant-based products are involved in several food outbreaks connected to various sources of contamination and quite often, bacteria responsible for side effects showed high resistance to antibiotics. The abuse of antibiotics can be one of the main mechanisms responsible for increasing antibiotic resistance (AR). Plants grown for food use can be contaminated directly by spraying antibiotics on crops or indirectly by treatments with antibiotics due to the use of manure, which may contain both antibiotics and genes of antibiotic resistance (ARG). Antibiotic residues could represent a potential way of human health risk due to exposure through the consumption of plant-based foods. The presence of antibiotic-resistant bacteria might pose a particular risk to consumers. The present work aims to investigate through a multidisciplinary approach the occurrence of ARG by means of a biomolecular approach (PCR) and the prevalence of antibiotic residues using a multi residues LC-MS/MS method, both in different plant-based products. During the period from July 2020 to October 2021, a total of 74 plant samples (33 lettuces and 41 tomatoes) were collected from 57 farms located throughout the Piedmont area, and18 out of 74 samples (11 lettuces and 7 tomatoes) were selected to LC-MS/MS analyses. DNA extracted (ExtractME, Blirt, Poland) from plants used on crops and isolated bacteria were analyzed with 6 sets of end-point multiplex PCR (Qiagen, Germany) to detect the presence of resistance genes of the main antibiotic families, such as tet genes (tetracyclines), bla (β-lactams) and mcr (colistin). Simultaneous detection of 43 molecules of antibiotics belonging to 10 different classes (tetracyclines, sulphonamides, quinolones, penicillins, amphenicols, macrolides, pleuromotilines, lincosamides, diaminopyrimidines) was performed using Exion LC system AB SCIEX coupled to a triple quadrupole mass spectrometer QTRAP 5500 from AB SCIEX. The PCR assays showed the presence of ARG in 57% (n=42): tetB (4.8%; n=2), tetA (9.5%; n=4), tetE (2.4%; n=1), tetL (12%; n=5), tetM (26%; n=11), blaSHV (21.5%; n=9), blaTEM (4.8%; n =2) and blaCTX-M (19%; n=8). In none of the analyzed samples was the mcr gene responsible for colistin resistance detected. Results obtained from LC-MS/MS analyses showed that none of the tested antibiotics appear to exceed the LOQ (100 ppb). Data obtained confirmed the presence of bacterial populations containing antibiotic resistance determinants such as tet gene (tetracycline) and bla genes (beta-lactams), widely used in human medicine, which can join the food chain and represent a risk for consumers, especially with raw products. The presence of traces of antibiotic residues in vegetables, in concentration below the LOQ of the LC-MS/MS method applied, cannot be excluded. In conclusion, traces of antibiotic residues could be a health risk to the consumer due to potential involvement in the spread of AR. PCR represents a useful and effective approach to characterize and monitor AR carried by bacteria from the entire food chain.

Keywords: plant-based products, ARG, PCR, antibiotic residues

Procedia PDF Downloads 90

Authors: Raghuveer Kaur, Kartikay Sharma, Ashu Khanna

Abstract:

Earnings management has been present from times immemorial. The recent downfall of giant enterprises like Enron, Satyam and WorldCom has brought a lot of focus on the study and detection of earnings management. The present study is an attempt to study earnings management in one of the fastest emerging economy - India. The study makes an attempt to understand earnings management in different sectors of the economy. The paper first tests a hypothesis to check whether different sectors of India are engaged in earnings management or not. In the later section the paper aims to study the level of earnings management in 6 popular sectors of India: IT&BPO, Retail, Telecom, Biotech, Hotels and coffee. To measure earnings management two popular techniques of detecting earnings management has been employed: Modified Jones Model and Beniesh M Score. A total of 332 companies were studied. Publicly available data from Capitaline database has been used. The paper also classifies the top and bottom five performers on the basis of sales turnover in each sector and identifies whether they manage their earnings or not.

Keywords: earnings management, India, modified Jones model, Beneish M score

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Authors: Norah Mohammed Alshahrani, Abdulaziz Almaleh

Abstract:

Autism Spectrum Disorder (ASD) is a condition related to issues with brain development that affects how a person recognises and communicates with others which results in difficulties with interaction and communication socially and it is constantly growing. Early recognition of ASD allows children to lead safe and healthy lives and helps doctors with accurate diagnoses and management of conditions. Therefore, it is crucial to develop a method that will achieve good results and with high accuracy for the measurement of ASD in children. In this paper, ASD datasets of toddlers and children have been analyzed. We employed the following machine learning techniques to attempt to explore ASD and they are Random Forest (RF), Decision Tree (DT), Na¨ıve Bayes (NB) and Support Vector Machine (SVM). Then Feature selection was used to provide fewer attributes from ASD datasets while preserving model performance. As a result, we found that the best result has been provided by the Support Vector Machine (SVM), achieving 0.98% in the toddler dataset and 0.99% in the children dataset.

Keywords: autism spectrum disorder, machine learning, feature selection, support vector machine

Procedia PDF Downloads 152