Search results for: computer processing of large databases

Authors: Oleg Reva, Ilya Korotetskiy, Marina Lankina, Murat Kulmanov, Aleksandr Ilin

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Molecular docking approaches are widely used for design of new antibiotics and modeling of antibacterial activities of numerous ligands which bind specifically to active centers of indispensable enzymes and/or key signaling proteins of pathogens. Widespread drug resistance among pathogenic microorganisms calls for development of new antibiotics specifically targeting important metabolic and information pathways. A generally recognized problem is that almost all molecular targets have been identified already and it is getting more and more difficult to design innovative antibacterial compounds to combat the drug resistance. A promising way to overcome the drug resistance problem is an induction of reversion of drug resistance by supplementary medicines to improve the efficacy of the conventional antibiotics. In contrast to well established computer-based drug design, modeling of drug resistance reversion still is in its infancy. In this work, we proposed an approach to identification of compensatory genetic variants reducing the fitness cost associated with the acquisition of drug resistance by pathogenic bacteria. The approach was based on an analysis of the population genetic of Mycobacterium tuberculosis and on results of experimental modeling of the drug resistance reversion induced by a new anti-tuberculosis drug FS-1. The latter drug is an iodine-containing nanomolecular complex that passed clinical trials and was admitted as a new medicine against MDR-TB in Kazakhstan. Isolates of M. tuberculosis obtained on different stages of the clinical trials and also from laboratory animals infected with MDR-TB strain were characterized by antibiotic resistance, and their genomes were sequenced by the paired-end Illumina HiSeq 2000 technology. A steady increase in sensitivity to conventional anti-tuberculosis antibiotics in series of isolated treated with FS-1 was registered despite the fact that the canonical drug resistance mutations identified in the genomes of these isolates remained intact. It was hypothesized that the drug resistance phenotype in M. tuberculosis requires an adjustment of activities of many genes to compensate the fitness cost of the drug resistance mutations. FS-1 cased an aggravation of the fitness cost and removal of the drug-resistant variants of M. tuberculosis from the population. This process caused a significant increase in genetic heterogeneity of the Mtb population that was not observed in the positive and negative controls (infected laboratory animals left untreated and treated solely with the antibiotics). A large-scale search for linkage disequilibrium associations between the drug resistance mutations and genetic variants in other genomic loci allowed identification of target proteins, which could be influenced by supplementary drugs to increase the fitness cost of the drug resistance and deprive the drug-resistant bacterial variants of their competitiveness in the population. The approach will be used to improve the efficacy of FS-1 and also for computer-based design of new drugs to combat drug-resistant infections.

Keywords: complete genome sequencing, computational modeling, drug resistance reversion, Mycobacterium tuberculosis

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Authors: Antoine F. Dedewanou, Eric N. Ekpinda

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We investigate whether and how deposit insurance program affects savings decisions in the Economic Community of Central African States (ECCAS). Specifically, using the World Bank’s 2014 and 2011 Global Financial Inclusion (Global Findex) databases, we apply special regressor approach. We find that the deposit insurance program increases significantly, everything else equal, the probability that people save their money at a financial institution by 11 percentage points in Gabon, by 22.2 percentage points in DR Congo and by 15.1 percentage points in Chad. These effects are matched with positive effects of age and education level. But in Cameroon, the effect of deposit insurance is not significant. The policies aimed at fostering financial inclusion will be more effective if there is a deposit insurance scheme in place, along with awareness among young people, and education programs. JEL Classification: G21, O12, O16

Keywords: deposit insurance, savings, special regressor, ECCAS countries

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Authors: Yuri S. Djikaev

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A large subset of aqueous aerosols can be initially (immediately upon formation) coated with various organic amphiphilic compounds whereof the hydrophilic moieties are attached to the aqueous aerosol core while the hydrophobic moieties are exposed to the air thus forming a hydrophobic coating thereupon. We study the thermodynamics of water condensation on such an aerosol whereof the hydrophobic organic coating is being concomitantly processed by chemical reactions with atmospheric reactive species. Such processing (chemical aging) enables the initially inert aerosol to serve as a nucleating center for water condensation. The most probable pathway of such aging involves atmospheric hydroxyl radicals that abstract hydrogen atoms from hydrophobic moieties of surface organics (first step), the resulting radicals being quickly oxidized by ubiquitous atmospheric oxygen molecules to produce surface-bound peroxyl radicals (second step). Taking these two reactions into account, we derive an expression for the free energy of formation of an aqueous droplet on an organic-coated aerosol. The model is illustrated by numerical calculations. The results suggest that the formation of aqueous cloud droplets on such aerosols is most likely to occur via Kohler activation rather than via nucleation. The model allows one to determine the threshold parameters necessary for their Kohler activation. Numerical results also corroborate previous suggestions that one can neglect some details of aerosol chemical composition in investigating aerosol effects on climate.

Keywords: aqueous aerosols, organic coating, chemical aging, cloud condensation nuclei, Kohler activation, cloud droplets

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Authors: Diwei Lin, Amanda Jh. Tan

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We present a very rare case of de novo large cell neuroendocrine carcinoma of the prostate (LCNEC) in an 84-year-old male on a background of high-grade, muscle-invasive transitional cell carcinoma of the bladder. While NE tumours account for 1% to 5% of all cases of prostate cancer and scattered NE cells can be found in 10% to 100% of prostate adenocarcinomas, pure LCNEC of the prostate is extremely rare. Most LCNEC of the prostate is thought to originate by clonal progression under the selection pressure of therapy and refractory to long-term hormonal treatment for adenocarcinoma of the prostate. De novo LCNEC is only described in case reports and is thought to develop via direct malignant transformation. Limited data in the English literature makes it difficult to accurately predict the prognosis of LCNEC of the prostate. However, current evidence suggesting that increasing NE differentiation in prostate adenocarcinoma is associated with a higher stage, high-grade disease, and a worse prognosis.

Keywords: large cell neuroendocrine cancer, prostate cancer, refractory cancer, medical and health sciences

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Authors: Nazneen Zehra

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Gir Protected Area (PA) is home to two sympatric large carnivores, the Asiatic lion and the common leopard, which share the same habitat. Understanding their interactions and coexistence is crucial for effective conservation management. From 2009 to 2012, we studied the availability and consumption of prey by these two carnivores to understand the dynamics of their interactions and coexistence. Ungulates provided approximately 3634.45 kg/km² of prey biomass, primarily composed of chital (ca. 2711.25 kg/km²), sambar (ca. 411.78 kg/km²), and nilgai (ca. 511.52 kg/km²). Other prey included peafowl (75.76 kg/km²) and langur (ca. 158.72 kg/km²). Both carnivores prioritized chital as their key prey species. The diet of Asiatic lions was predominantly composed of ungulates, with biomass contributions of chital (301.14 kg), sambar (378.75 kg), and nilgai (291.42 kg). Other prey species, such as peafowl and langur, contributed 1.36 kg and 2.40 kg, respectively, to the lions' diet. For leopards, the diet also heavily relied on chital (311.49 kg), followed by sambar (44.03 kg) and nilgai (172.78 kg). The biomass of other prey species in the leopards' diet included peafowl (2.08 kg) and langur (36.07 kg). Both species were found to primarily utilize teak-mixed forest, followed by riverine forest and teak-acacia-zizyphus habitats. The similarities in diet composition and habitat use indicate competition between these sympatric species. This competition may require one predator species to bear certain costs for the benefit of the other, which can influence conservation and management strategies. Effective conservation strategies are necessary to ensure the long-term survival of both the Asiatic lion and the common leopard equally and to maintain ecological balance in Gir PA.

Keywords: large carnivores, Gir PA, coexistence, resource utilization

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Authors: Catia Correia Caeiro, Kun Guo, Daniel Mills

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Despite its growing interest, emotions are still an understudied cognitive process and their origins are currently the focus of much debate among the scientific community. The use of facial expressions as traditional hallmarks of discrete and holistic emotions created a circular reasoning due to a priori assumptions of meaning and its associated appearance-biases. Ekman and colleagues solved this problem and laid the foundations for the quantitative and systematic study of facial expressions in humans by developing an anatomically-based system (independent from meaning) to measure facial behaviour, the Facial Action Coding System (FACS). One way of investigating emotion cognition processes is by applying comparative psychology methodologies and looking at either closely-related species (e.g. chimpanzees) or phylogenetically distant species sharing similar present adaptation problems (analogy). In this study, the domestic dog was used as a comparative animal model to look at facial expressions in social interactions in parallel with human facial expressions. The orofacial musculature seems to be relatively well conserved across mammal species and the same holds true for the domestic dog. Furthermore, the dog is unique in having shared the same social environment as humans for more than 10,000 years, facing similar challenges and acquiring a unique set of socio-cognitive skills in the process. In this study, the spontaneous facial movements of humans and dogs were compared when interacting with hetero- and conspecifics as well as in solitary contexts. In total, 200 participants were examined with FACS and DogFACS (The Dog Facial Action Coding System): coding tools across four different emotionally-driven contexts: a) Happiness (play and reunion), b) anticipation (of positive reward), c) fear (object or situation triggered), and d) frustration (negation of a resource). A neutral control was added for both species. All four contexts are commonly encountered by humans and dogs, are comparable between species and seem to give rise to emotions from homologous brain systems. The videos used in the study were extracted from public databases (e.g. Youtube) or published scientific databases (e.g. AM-FED). The results obtained allowed us to delineate clear similarities and differences on the flexibility of the facial musculature in the two species. More importantly, they shed light on what common facial movements are a product of the emotion linked contexts (the ones appearing in both species) and which are characteristic of the species, revealing an important clue for the debate on the origin of emotions. Additionally, we were able to examine movements that might have emerged for interspecific communication. Finally, our results are discussed from an evolutionary perspective adding to the recent line of work that supports an ancient shared origin of emotions in a mammal ancestor and defining emotions as mechanisms with a clear adaptive purpose essential on numerous situations, ranging from maintenance of social bonds to fitness and survival modulators.

Keywords: comparative and evolutionary psychology, emotion, facial expressions, FACS

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Authors: Yousif M. Yousif Abdallah, Mohamed E. Gar-Elnabi, Abdoelrahman H. A. Bakary, Alaa M. H. Eltoum, Abdelazeem K. M. Ali

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The study was established to measure the amount of radiation outside the treatment field in external beam radiation therapy using day method of dose calculation, the data was collected from 89 patients of cervical carcinoma in order to determine if the dose outside side the irradiation treatment field for spleen, liver, both kidneys, small bowel, large colon, skin within the acceptable limit or not. The cervical field included mainly 4 organs which are bladder, rectum part of small bowel and hip joint these organ received mean dose of (4781.987±281.321), (4736.91±331.8), (4647.64±387.1) and (4745.91±321.11) respectively. The mean dose received by outfield organs was (77.69±15.24cGy) to large colon, (93.079±12.31cGy) to right kidney (80.688±12.644cGy) to skin, (155.86±17.69cGy) to small bowel. This was more significant value noted.

Keywords: radiation dose, cervical carcinoma, day’s methods, radiation medicine

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Authors: F. Laatar, S. Ktifa, H. Ezzaouia

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Plasma Enhanced Chemical Vapor Deposition (PECVD) method is used to deposit hydrogenated nanocrystalline silicon films (nc-Si: H) on Porous Anodic Alumina Films (PAF) on glass substrate at different deposition duration. Influence of the deposition time on the physical properties of nc-Si: H grown on PAF was investigated through an extensive correlation between micro-structural and optical properties of these films. In this paper, we present an extensive study of the morphological, structural and optical properties of these films by Atomic Force Microscopy (AFM), X-Ray Diffraction (XRD) techniques and a UV-Vis-NIR spectrometer. It was found that the changes in DT can modify the films thickness, the surface roughness and eventually improve the optical properties of the composite. Optical properties (optical thicknesses, refractive indexes (n), absorption coefficients (α), extinction coefficients (k), and the values of the optical transitions EG) of this kind of samples were obtained using the data of the transmittance T and reflectance R spectra’s recorded by the UV–Vis–NIR spectrometer. We used Cauchy and Wemple–DiDomenico models for the analysis of the dispersion of the refractive index and the determination of the optical properties of these films.

Keywords: hydragenated nanocrystalline silicon, plasma processing chemical vapor deposition, X-ray diffraction, optical properties

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Authors: Jianjun Wu, Fanhui Guo, Yixin Zhang

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In this study, gasification-coke were produced by blending the middlings (MC), and coking coal (CC) and a large proportion of long flame coal (Shenfu coal, SC), the effects of blending ratio were investigated. Mineral evolution and crystalline order obtained by XRD methods were reproduced within reasonable accuracy. Structure characteristics of partially gasification-coke such as surface area and porosity were determined using the N₂ adsorption and mercury porosimetry. Experimental data of gasification-coke was dominated by the TGA results provided trend, reactivity differences between gasification-cokes are discussed in terms of structure characteristic, crystallinity, and alkali index (AI). The first-order reaction equation was suitable for the gasification reaction kinetics of CO₂ atmosphere which was represented by the volumetric reaction model with linear correlation coefficient above 0.985. The differences in the microporous structure of gasification-coke and catalysis caused by the minerals in parent coals were supposed to be the main factors which affect its reactivity. The addition of MC made the samples enriched with a large amount of ash causing a higher surface area and a lower crystalline order to gasification-coke which was beneficial to gasification reaction. The higher SiO₂ and Al₂O₃ contents, causing a decreasing AI value and increasing activation energy, which reduced the gasification reaction activity. It was found that the increasing amount of MC got a better performance on the coke gasification reactivity by blending > 30% SC with this coking process.

Keywords: low-rank coal, middlings, structure characteristic, mineral evolution, alkali index, gasification-coke, gasification kinetics

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Authors: A. A. Abaker Omer, H. B. Mohamed Balh, W. Liu, A. Abas, J. Yu, S. Li, W. Ma, W. El Kolaly, Y. Y. Ahmed Abuker

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We have discovered an important technical solution that could make new approaches in the processing of wet silicon etching, especially in the production of photovoltaic cells. During its inferior light-trapping and structural properties, the inverted pyramid structure outperforms the conventional pyramid textures and black silicone. The traditional pyramid textures and black silicon can only be accomplished with more advanced lithography, laser processing, etc. Importantly, our data demonstrate the feasibility of an inverted pyramidal structure of silicon via one-step Cu-catalyzed chemical etching (CCCE) in Cu (NO₃)₂/HF/H₂O₂/H₂O solutions. The effects of etching time and reaction temperature on surface geometry and light trapping were systematically investigated. The conclusion shows that the inverted pyramid structure has ultra-low reflectivity of ~4.2% in the wavelength of 300~1000 nm; introduce of Cu particles can significantly accelerate the dissolution of the silicon wafer. The etching and the inverted pyramid structure formation mechanism are discussed. Inverted pyramid structure with outstanding anti-reflectivity includes useful applications throughout the manufacture of semi-conductive industry-compatible solar cells, and can have significant impacts on industry colleagues and populations.

Keywords: Cu-catalyzed chemical etching, inverted pyramid nanostructured, reflection, solar cells

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Authors: Sandhya Baskaran, Hari Kumar Nagabushanam

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Sarcasm sentiment recognition is an area of natural language processing that is being probed into in the recent times. Even with the advancements in NLP, typical translations of words, sentences in its context fail to provide the exact information on a sentiment or emotion of a user. For example, if something bad happens, the statement ‘That's just what I need, great! Terrific!’ is expressed in a sarcastic tone which could be misread as a positive sign by any text-based analyzer. In this paper, we are presenting a unique real time ‘word with its tone’ spotting technique which would provide the sentiment analysis for a tone or pitch of a voice in combination with the words being expressed. This hybrid approach increases the probability for identification of special sentiment like sarcasm much closer to the real world than by mining text or speech individually. The system uses a tone analyzer such as YIN-FFT which extracts pitch segment-wise that would be used in parallel with a speech recognition system. The clustered data is classified for sentiments and sarcasm score for each of it determined. Our Simulations demonstrates the improvement in f-measure of around 12% compared to existing detection techniques with increased precision and recall.

Keywords: sarcasm recognition, tone-word spotting, natural language processing, pitch analyzer

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Authors: Arun Perumbilavil Anand

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In the recent years, Kerala is witnessing a large inflow of migrants from different parts of the country. Though initially, the migrants were largely from the districts of Tamil Nadu and mostly of seasonal nature, but at a later period, the state started getting migrants from the far-off states like UP, Assam, Bengal, etc. Higher wages for unskilled labour, large opportunities for employment, the reluctance on the part of Kerala workers to do menial and hard physical work, and the shortage of local labour, paradoxically despite the high unemployment rate in the state, led to the massive influx of migrant labourers. This study takes a multi-dimensional overview of migrant labour in Kerala by encompassing factors such as channels of migration, nature of employment contracts entered into and the corresponding wages and benefits obtained by them. The study also analysed the circumstances that led to the large influx of migrants from different states of India. It further makes an attempt to examine the varying dimensions of living and working environment, and also the health conditions of migrants. The study is based on the empirical findings obtained as a result of the primary interviews conducted with migrants in the districts of Palakkad, Malappuram, and Ernakulam. The study concludes by noting that Kerala will inevitably have to depend on migrant labour and is likely to experience heavy in-migration of labour in future, provided that if the existing socioeconomic and demographic situations persist. Since, this is inevitable, the best way before the state is to prepare well in advance to receive and accommodate such migrant labour to lead a comfortable life in a hassle free environment, so that it would definitely play a vital role in further strengthening and sustaining the growth trajectory of not only Kerala’s economy but also the states of origin.

Keywords: Kerala, labour, migration, migrant workers

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Authors: Yu Hung Chiang, Hei Chia Wang

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In the academic area, it is important for research to find proper research domain. Many researchers may refer to conference issues to find their interesting or new topics. Furthermore, conferences issues can help researchers realize current research trends in their field and learn about cutting-edge developments in their specialty. However, online published conference information may widely be distributed; it is not easy to be concluded. Many researchers use search engine of journals or conference issues to filter information in order to get what they want. However, this search engine has its limitation. There will still be some issues should be considered; i.e. researchers cannot find the associated topics which may be useful information for them. Hence, use Knowledge Management (KM) could be a way to resolve these issues. In KM, ontology is widely adopted; but most existed ontology construction methods do not consider social information between target users. To effective in academic KM, this study proposes a method of constructing research Topic Maps using Open Directory Project (ODP) and Social Information Processing (SIP). Through catching of social information in conference website: i.e. the information of co-authorship or collaborator, research topics can be associated among related researchers. Finally, the experiments show Topic Maps successfully help researchers to find the information they need more easily and quickly as well as construct associations between research topics.

Keywords: knowledge management, topic map, social information processing, ontology extraction

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Authors: M. Naveed Iqbal, Sheza Fatima, Noman Shabbir

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In the presence of energy crisis in Pakistan, off-grid remote areas are not on priority list. The use of new large scale coal fired power plants will also make this situation worst. Therefore, the greatest challenge in our society is to explore new ways to power off grid remote areas with renewable energy sources. It is time for a sustainable energy policy which puts consumers, the environment, human health, and peace first. The renewable energy is one of the biggest growing sectors of the energy industry. Therefore, the large scale use of micro grid is thus described here with modeling, simulation, planning and operating of the micro grid. The goal of this research paper is to go into detail of a library of major components of micro grid. The introduction will go through the detail view of micro grid definition. Then, the simulation of Micro Grid in MATLAB/ Simulink including the Photo Voltaic Cell will be described with the detailed modeling. The simulation with the design and modeling will be introduced too.

Keywords: micro grids, distribution generation, PV, off-grid operations

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Authors: Nathenal Thomas

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In the food chain and in many other agricultural products, corn, also known as maize, which goes by the scientific name Zea mays subsp, is a widely produced agricultural product. Corn has the highest adaptability. It comes in many different types, is employed in many different industrial processes, and is more adaptable to different agro-climatic situations. In Ethiopia, maize is among the most widely grown crop. Small-scale corn farming may be a household's only source of food in developing nations like Ethiopia. The aforementioned data demonstrates that the country's requirement for this crop is excessively high, and conversely, the crop's productivity is very low for a variety of reasons. The most damaging disease that greatly contributes to this imbalance between the crop's supply and demand is the corn disease. The failure to diagnose diseases in maize plant until they are too late is one of the most important factors influencing crop output in Ethiopia. This study will aid in the early detection of such diseases and support farmers during the cultivation process, directly affecting the amount of maize produced. The diseases in maize plants, such as northern leaf blight and cercospora leaf spot, have distinct symptoms that are visible. This study aims to detect the most frequent and degrading maize diseases using the most efficiently used subset of machine learning technology, deep learning so, called Image Processing. Deep learning uses networks that can be trained from unlabeled data without supervision (unsupervised). It is a feature that simulates the exercises the human brain goes through when digesting data. Its applications include speech recognition, language translation, object classification, and decision-making. Convolutional Neural Network (CNN) for Image Processing, also known as convent, is a deep learning class that is widely used for image classification, image detection, face recognition, and other problems. it will also use this algorithm as the state-of-the-art for my research to detect maize diseases by photographing maize leaves using a mobile phone.

Keywords: CNN, zea mays subsp, leaf blight, cercospora leaf spot

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Authors: K. S. Vedasingha, K. K. M. T. Perera, K. I. Hathurusinghe, H. W. I. Akalanka, Nelum Chathuranga Amarasena, Nalaka R. Dissanayake

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Railways provide the most convenient and economically beneficial mode of transportation, and it has been the most popular transportation method among all. According to the past analyzed data, it reveals a considerable number of accidents which occurred at railways and caused damages to not only precious lives but also to the economy of the countries. There are some major issues which need to be addressed in railways of South Asian countries since they fall under the developing category. The goal of this research is to minimize the influencing aspect of railway level crossing accidents by developing the “railway process automation system”, as there are high-risk areas that are prone to accidents, and safety at these places is of utmost significance. This paper describes the implementation methodology and the success of the study. The main purpose of the system is to ensure human safety by using the Internet of Things (IoT) and image processing techniques. The system can detect the current location of the train and close the railway gate automatically. And it is possible to do the above-mentioned process through a decision-making system by using past data. The specialty is both processes working parallel. As usual, if the system fails to close the railway gate due to technical or a network failure, the proposed system can identify the current location and close the railway gate through a decision-making system, which is a revolutionary feature. The proposed system introduces further two features to reduce the causes of railway accidents. Railway track crack detection and motion detection are those features which play a significant role in reducing the risk of railway accidents. Moreover, the system is capable of detecting rule violations at a level crossing by using sensors. The proposed system is implemented through a prototype, and it is tested with real-world scenarios to gain the above 90% of accuracy.

Keywords: crack detection, decision-making, image processing, Internet of Things, motion detection, prototype, sensors

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Authors: Adrienne Kline, Jaydip Desai

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Electroencephalogram (EEG) is a noninvasive technique that registers signals originating from the firing of neurons in the brain. The Emotiv EEG Neuroheadset is a consumer product comprised of 14 EEG channels and was used to record the reactions of the neurons within the brain to two forms of stimuli in 10 participants. These stimuli consisted of auditory and visual formats that provided directions of ‘right’ or ‘left.’ Participants were instructed to raise their right or left arm in accordance with the instruction given. A scenario in OpenViBE was generated to both stimulate the participants while recording their data. In OpenViBE, the Graz Motor BCI Stimulator algorithm was configured to govern the duration and number of visual stimuli. Utilizing EEGLAB under the cross platform MATLAB®, the electrodes most stimulated during the study were defined. Data outputs from EEGLAB were analyzed using IBM SPSS Statistics® Version 20. This aided in determining the electrodes to use in the development of a brain-machine interface (BMI) using real-time EEG signals from the Emotiv EEG Neuroheadset. Signal processing and feature extraction were accomplished via the Simulink® signal processing toolbox. An Arduino™ Duemilanove microcontroller was used to link the Emotiv EEG Neuroheadset and the right and left Mecha TE™ Hands.

Keywords: brain-machine interface, EEGLAB, emotiv EEG neuroheadset, OpenViBE, simulink

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Authors: Trapti Sharma, Devesh Kumar Srivastava

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This paper is basically a analysis study of above MapReduce implementation and also to verify and validate the MapReduce solution model for Parallel K-Mediod algorithm on Hadoop Cluster. MapReduce is a programming model which authorize the managing of huge amounts of data in parallel, on a large number of devices. It is specially well suited to constant or moderate changing set of data since the implementation point of a position is usually high. MapReduce has slowly become the framework of choice for “big data”. The MapReduce model authorizes for systematic and instant organizing of large scale data with a cluster of evaluate nodes. One of the primary affect in Hadoop is how to minimize the completion length (i.e. makespan) of a set of MapReduce duty. In this paper, we have verified and validated various MapReduce applications like wordcount, grep, terasort and parallel K-Mediod clustering algorithm. We have found that as the amount of nodes increases the completion time decreases.

Keywords: hadoop, mapreduce, k-mediod, validation, verification

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Authors: Sergey Ermolin, Olga Ermolin

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A Deep Convolution Neural Network with Triplet Loss is used to identify duplicate images in real-estate advertisements in the presence of image artifacts such as watermarking, cropping, hue/brightness adjustment, and others. The effects of batch normalization, spatial dropout, and various convergence methodologies on the resulting detection accuracy are discussed. For comparative Return-on-Investment study (per industry request), end-2-end performance is benchmarked on both Nvidia Titan GPUs and Intel’s Xeon CPUs. A new real-estate dataset from San Francisco Bay Area is used for this work. Sufficient duplicate detection accuracy is achieved to supplement other database-grounded methods of duplicate removal. The implemented method is used in a Proof-of-Concept project in the real-estate industry.

Keywords: visual recognition, convolutional neural networks, triplet loss, spatial batch normalization with dropout, duplicate removal, advertisement technologies, performance benchmarking

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Authors: Catharina O. Vianna Dias da Silva, Amanda F. Batista, Ana Clara C. Burgos Lessa, Carolina S. Lucchesi Ramacciotti, Maria Clara B. de Andrade, Roberto de B. Silva

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This article aims to analyze the bioethical aspects related to the historical practices of experiments on humans that occurred in Nazi Germany during the period of World War II (1939-1945). The method was based on the bibliographic review of articles published in databases such as SciELO and Pubmed. In the discussion, historical and humanistic aspects that contributed to the construction of a genocidal culture practiced during this period were analyzed. Additionally, an ethical question arises: should the information acquired during this dark period be used by science? After analysis, it was found that these Nazi experiments went over medical and ethical principles, being a deplorable milestone in history. It was also concluded that, although they generated potentially 'useful' results in the scientific field, they should be discarded as an ethical question of principle, of never daring to validate such a deplorable way of obtaining knowledge.

Keywords: Nazism, bioethics, human experimentation, human rights, genocide, torture, medicine

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Authors: S. Talebnezhad, S. Pourmahdian, D. Soudbar, M. Khosravani, J. Merasi

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Adding toughened polypropylene and plastomer in FFS 3 layered blown film formulation resulted in superior dart impact and MD tear resistance along with acceptable tensile properties in TD and MD. The optimum loading of toughened polypropylene and plastomer in each layer depends on miscibility of polypropylene in polyethylene medium, mechanical properties, welding characteristics in bags top and bottoms and friction coefficient of film surfaces. Film property tests and efficiency of FFS machinery during processing in industrial scale showed that about 4% loading of plastomer and 16% of toughened polypropylene (reactor grade) in middle layer and loading of 0-1% plastomer and 5-19% of toughened polypropylene in other layers results optimum characteristics in the formulation based on 1-butene LLDPE grade with MFR of 0.9 and LDPE grade with MFI of 0.3. Both the plastomer and toughened polypropylene had the MFI of blow 1 and the TiO2 and processing aid masterbatches loading was 2%. The friction coefficient test results also represented the anti-block masterbatch could be omitted from formulation with adding toughened polypropylene due to partial miscibility of PP in PE which makes the surface of films somewhat bristly.

Keywords: FFS 3 layered blown film, toughened polypropylene, plastomer, dart impact, tear resistance

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Authors: Alon Cohen, Jeffrey Kantor, Shalom Levy

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Technology adoption models are extensively used in the literature to explore drivers and inhibitors affecting the adoption of Computer Assisted Audit Techniques and Tools (CAATTs). Further studies from recent years suggested additional factors that may affect technology adoption by CPA firms. However, the adoption of CAATTs by financial auditors differs from the adoption of technologies in other industries. This is a result of the unique characteristics of the auditing process, which are expressed in the audit risk elements and the risk-based auditing approach, as encoded in the auditing standards. Since these audit risk factors are not part of the existing models that are used to explain technology adoption, these models do not fully correspond to the specific needs and requirements of the auditing domain. The overarching objective of this qualitative research is to fill the gap in the literature, which exists as a result of using generic technology adoption models. Followed by a pretest and based on semi-structured in-depth interviews with 16 Israeli CPA firms of different sizes, this study aims to reveal determinants related to audit risk factors that influence the adoption of CAATTs in audits and proposes a new modeling approach for the successful adoption of CAATTs. The findings emphasize several important aspects: (1) while large CPA firms developed their own inner guidelines to assess the audit risk components, other CPA firms do not follow a formal and validated methodology to evaluate these risks; (2) large firms incorporate a variety of CAATTs, including self-developed advanced tools. On the other hand, small and mid-sized CPA firms incorporate standard CAATTs and still need to catch up to better understand what CAATTs can offer and how they can contribute to the quality of the audit; (3) the top management of mid-sized and small CPA firms should be more proactive and updated about CAATTs capabilities and contributions to audits; and (4) All CPA firms consider professionalism as a major challenge that must be constantly managed to ensure an optimal CAATTs operation. The study extends the existing knowledge of CAATTs adoption by looking at it from a risk-based auditing approach. It suggests a new model for CAATTs adoption by incorporating influencing audit risk factors that auditors should examine when considering CAATTs adoption. Since the model can be used in various audited scenarios and supports strategic, risk-based decisions, it maximizes the great potential of CAATTs on the quality of the audits. The results and insights can be useful to CPA firms, internal auditors, CAATTs developers and regulators. Moreover, it may motivate audit standard-setters to issue updated guidelines regarding CAATTs adoption in audits.

Keywords: audit risk, CAATTs, financial auditing, information technology, technology adoption models

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Authors: Mohammad Javaherian, Siamak Bashardoust Tajali, Monavvar Hadizadeh

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Objective: This systematic review study was conducted to evaluate the effects of Pulsed Electromagnetic (PEMF) and Static Magnetic Fields (SMG) on pain relief and functional improvement in patients with musculoskeletal Low Back Pain (LBP). Methods: Seven electronic databases were searched by two researchers independently to identify the published Randomized Controlled Trials (RCTs) on the efficacy of pulsed electromagnetic, static magnetic, and therapeutic nuclear magnetic fields. The identified databases for systematic search were Ovid Medline®, Ovid Cochrane RCTs and Reviews, PubMed, Web of Science, Cochrane Library, CINAHL, and EMBASE from 1968 to February 2016. The relevant keywords were selected by Mesh. After initial search and finding relevant manuscripts, all references in selected studies were searched to identify second hand possible manuscripts. The published RCTs in English would be included to the study if they reported changes on pain and/or functional disability following application of magnetic fields on chronic musculoskeletal low back pain. All studies with surgical patients, patients with pelvic pain, and combination of other treatment techniques such as acupuncture or diathermy were excluded. The identified studies were critically appraised and the data were extracted independently by two raters (M.J and S.B.T). Probable disagreements were resolved through discussion between raters. Results: In total, 1505 abstracts were found following the initial electronic search. The abstracts were reviewed to identify potentially relevant manuscripts. Seventeen possibly appropriate studies were retrieved in full-text of which 48 were excluded after reviewing their full-texts. Ten selected articles were categorized into three subgroups: PEMF (6 articles), SMF (3 articles), and therapeutic nuclear magnetic fields (tNMF) (1 article). Since one study evaluated tNMF, we had to exclude it. In the PEMF group, one study of acute LBP did not show significant positive results and the majority of the other five studies on Chronic Low Back Pain (CLBP) indicated its efficacy on pain relief and functional improvement, but one study with the lowest sessions (6 sessions during 2 weeks) did not report a significant difference between treatment and control groups. In the SMF subgroup, two articles reported near significant pain reduction without any functional improvement although more studies are needed. Conclusion: The PEMFs with a strength of 5 to 150 G or 0.1 to 0.3 G and a frequency of 5 to 64 Hz or sweep 7 to 7KHz can be considered as an effective modality in pain relief and functional improvement in patients with chronic low back pain, but there is not enough evidence to confirm their effectiveness in acute low back pain. To achieve the appropriate effectiveness, it is suggested to perform this treatment modality 20 minutes per day for at least 9 sessions. SMFs have not been reported to be substantially effective in decreasing pain or improving the function in chronic low back pain. More studies are necessary to achieve more reliable results.

Keywords: pulsed electromagnetic field, static magnetic field, magnetotherapy, low back pain

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Authors: Monika Soni, Shovonlal Bhowmick, Chandra Bhattacharya, Jitendra Sharma, Prafulla Dutta, Jagadish Mahanta

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Aedes aegypti and Aedes albopictus are considered as two major vectors to transmit dengue virus. In North-east India, two states viz. Assam and Arunachal Pradesh are known to be high endemic zone for dengue and Chikungunya viral infection. The taxonomical classification of medically important vectors are important for mapping of actual evolutionary trends and epidemiological studies. However, misidentification of mosquito species in field-collected mosquito specimens could have a negative impact which may affect vector-borne disease control policy. DNA barcoding is a prominent method to record available species, differentiate from new addition and change of population structure. In this study, a combined approach of a morphological and molecular technique of DNA barcoding was adopted to explore sequence variation in mitochondrial cytochrome c oxidase subunit I (COI) gene within dengue vectors. The study has revealed the map distribution of the dengue vector from two states i.e. Assam and Arunachal Pradesh, India. Approximate five hundred mosquito specimens were collected from different parts of two states, and their morphological features were compared with the taxonomic keys. The analysis of detailed taxonomic study revealed identification of two species Aedes aegypti and Aedes albopictus. The species aegypti comprised of 66.6% of the specimen and represented as dominant dengue vector species. The sequences obtained through standard DNA barcoding protocol were compared with public databases, viz. GenBank and BOLD. The sequences of all Aedes albopictus have shown 100% similarity whereas sequence of Aedes aegypti has shown 99.77 - 100% similarity of COI gene with that of different geographically located same species based on BOLD database search. From dengue prevalent different geographical regions fifty-nine sequences were retrieved from NCBI and BOLD databases of the same and related taxa to determine the evolutionary distance model based on the phylogenetic analysis. Neighbor-Joining (NJ) and Maximum Likelihood (ML) phylogenetic tree was constructed in MEGA6.06 software with 1000 bootstrap replicates using Kimura-2-Parameter model. Data were analyzed for sequence divergence and found that intraspecific divergence ranged from 0.0 to 2.0% and interspecific divergence ranged from 11.0 to 12.0%. The transitional and transversional substitutions were tested individually. The sequences were deposited in NCBI: GenBank database. This observation claimed the first DNA barcoding analysis of Aedes mosquitoes from North-eastern states in India and also confirmed the range expansion of two important mosquito species. Overall, this study insight into the molecular ecology of the dengue vectors from North-eastern India which will enhance the understanding to improve the existing entomological surveillance and vector incrimination program.

Keywords: COI, dengue vectors, DNA barcoding, molecular identification, North-east India, phylogenetics

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Authors: Oleg Oborin

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This paper is dedicated to the development of the model, which can be used to evaluate the effectiveness of long-term corporate strategies and identify the best strategies. The theoretical model of the relatively homogenous product market (such as iron and steel industry, mobile services or road transport) has been developed. In the model, the market consists of a large number of companies with different internal characteristics and objectives. The companies can perform mergers and acquisitions in order to increase their market share. The model allows the simulation of long-time dynamics of the market (for a period longer than 20 years). Therefore, a large number of simulations on random input data was conducted in the framework of the model. After that, the results of the model were compared with the dynamics of real markets, such as the US steel industry from the beginning of the XX century to the present day, and the market of mobile services in Germany for the period between 1990 and 2015.

Keywords: Economic Modelling, Long-Time Strategy, Mergers and Acquisitions, Simulation

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Authors: Edward Ridyard, Vinary Varadarajan

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Background and Aims: The first year as a doctor in any country represents a major career transition in any physician's life. During this period, many physicians concentrate on obtaining clinical skills but may not obtain the important skills necessary to cope with stress. In this study we elucidate stress levels amongst FY1 doctors regarding the transitioning into specialty career choices, working in the NHS and anxiety about future career success. Methods: A prospective single blinded analysis of Foundation Year one (FY1) trainees using a non-mandatory online questionnaire was distributed. No exclusion criteria were applied. The only inclusion criteria was the doctor was in a full-time FY1 post and this was their first job in the UK. A total of n= 22 doctors were included in the study. After data collection, statistical analysis using chi-squared testing was applied. Results: The large majority of FY1 doctors (72.7%) already knew what specialty they wished to pursue (p=0.0001). With regards to their future careers 45.5% of FY1 doctors stated "above average" stress levels. The majority of FY1 doctors (64.3%) stated their stress levels working in the NHS were either "above average" or "high". Finally, 81.8% of respondents know colleagues who have been put off from pursuing specialties due to the stress of competition. Conclusions: A large majority of FY1 doctors already know at this early stage what area they would like to specialise in. With this in mind, a large proportion have above "average" levels of stress with regards to securing this future career path. The most worrying finding is that 64.3% of FY1s stated they had "above average" or "high" stress levels working in the NHS. We therefore recommend formal stress management education to be incorporated into the foundation programme curriculum.

Keywords: stress, anxiety, junior doctor, education

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Authors: Jude K. Safo

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Knowledge Graphs KG) and their relation to Graph Embeddings (GE) represent a unique data structure in the landscape of machine learning (relative to image, text and acoustic data). Unlike the latter, GEs are the only data structure sufficient for representing hierarchically dense, semantic information needed for use-cases like supply chain data and protein folding where the search space exceeds the limits traditional search methods (e.g. page-rank, Dijkstra, etc.). While GEs are effective for compressing low rank tensor data, at scale, they begin to introduce a new problem of ’data retreival’ which we observe in Large Language Models. Notable attempts by transE, TransR and other prominent industry standards have shown a peak performance just north of 57% on WN18 and FB15K benchmarks, insufficient practical industry applications. They’re also limited, in scope, to next node/link predictions. Traditional linear methods like Tucker, CP, PARAFAC and CANDECOMP quickly hit memory limits on tensors exceeding 6.4 million nodes. This paper outlines a topological framework for linear mapping between concepts in KG space and GE space that preserve cardinality. Most importantly we introduce a traceable framework for composing dense linguistic strcutures. We demonstrate performance on WN18 benchmark this model hits. This model does not rely on Large Langauge Models (LLM) though the applications are certainy relevant here as well.

Keywords: representation theory, large language models, graph embeddings, applied algebraic topology, applied knot theory, combinatorics

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Authors: Kashish Sareen, Jatinder Singh Bal

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The use of wireless sensor networks (WSNs) has grown vastly in the last era, pointing out the crucial need for scalable and energy-efficient routing and data gathering and aggregation protocols in corresponding large-scale environments. Wireless Sensor Networks have now recently emerged as a most important computing platform and continue to grow in diverse areas to provide new opportunities for networking and services. However, the energy constrained and limited computing resources of the sensor nodes present major challenges in gathering data. The sensors collect data about their surrounding and forward it to a command centre through a base station. The past few years have witnessed increased interest in the potential use of wireless sensor networks (WSNs) as they are very useful in target detecting and other applications. However, hierarchical clustering protocols have maximum been used in to overall system lifetime, scalability and energy efficiency. In this paper, the state of the art in corresponding hierarchical clustering approaches for large-scale WSN environments is shown.

Keywords: clustering, DLCC, MLCC, wireless sensor networks

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Authors: Anes Enakoa, Yawei Liang

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Question Answering (QA) system is one of the most important and demanding tasks in the field of Natural Language Processing (NLP). In QA systems, the answer generation task generates a list of candidate answers to the user's question, in which only one answer is correct. Answer selection is one of the main components of the QA, which is concerned with selecting the best answer choice from the candidate answers suggested by the system. However, the selection process can be very challenging especially in Arabic due to its particularities. To address this challenge, an approach is proposed to answer questions with multiple answer choices for Arabic QA systems based on Textual Entailment (TE) recognition. The developed approach employs a Support Vector Machine that considers lexical, semantic and syntactic features in order to recognize the entailment between the generated hypotheses (H) and the text (T). A set of experiments has been conducted for performance evaluation and the overall performance of the proposed method reached an accuracy of 67.5% with C@1 score of 80.46%. The obtained results are promising and demonstrate that the proposed method is effective for TE recognition task.

Keywords: information retrieval, machine learning, natural language processing, question answering, textual entailment

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Authors: Tatiana Tunon, Gottfried Pestal

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Government agencies responsible for the management of fisheries resources publish many types of grey literature, and these materials are increasingly accessible to the public on agency websites. However, scope and quality vary considerably, and end-users need meta-data about the report series when deciding whether to use the information (e.g. apply the methods, include the results in a systematic review), or when prioritizing materials for archiving (e.g. library holdings, reference databases). A proposed taxonomy for these report series was developed based on a review of 41 report series from 6 government agencies in 4 countries (Canada, New Zealand, Scotland, and United States). Each report series was categorized according to multiple criteria describing peer-review process, content, and purpose. A robust classification tree was then fitted to these descriptions, and the resulting taxonomic groups were used to compare agency output from 4 countries using reports available in their online repositories.

Keywords: classification tree, fisheries, government, grey literature

Procedia PDF Downloads 283