Search results for: road condition classification

Authors: S. Malisuwan, J. Sivaraks, N. Madan, N. Suriyakrai

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The ever going evolution of advanced wireless technologies makes it financially impossible for military operations to completely manufacture their own equipment. Therefore, Commercial-Off-The-Shelf (COTS) and Modified-Off-The-Shelf (MOTS) are being considered in military mission with low-cost modifications. In this paper, we focus on the LTE multicast systems for military communication systems under tactical environments with jamming condition. We examine the influence of the colored noise jamming on the performance of the LTE multicast systems in terms of the average throughput. The simulation results demonstrate the degradation of the average throughput for different dynamic ranges of the colored noise jamming versus average SNR.

Keywords: performance, LTE, multicast, jamming, throughput

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Authors: Fatemeh Behbahani, Rubiyah Yusof

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To avoid collision between following vehicles and vehicles in front, it is vital to keep appropriate, safe spacing between both vehicles over all speeds. Therefore, the following vehicle needs to have exact information regarding the speed and spacing between vehicles. This project is conducted to simulate the tuning of controller gain for a vehicle-following system through the selected control strategy, spacing control policy and fixed-time headway policy. In addition, the paper simulates and designs an adaptive gain controller for a road-vehicle-following system which uses information on the spacing, velocity and also acceleration of a preceding vehicle in the proposed one-vehicle look-ahead strategy. The mathematical model is implemented using Kirchhoff and Newton’s Laws, and stability simulated. The trial-error method was used to obtain a suitable value of controller gain. However, the adaptive-based controller system was able to optimize the gain value automatically. Model Reference Adaptive Control (MRAC) is designed and utilized and based on firstly the Gradient and secondly the Lyapunov approach. The Lyapunov approach considers stability. The Gradient approach was found to improve the best value of gain in the controller system with fixed-time headway.

Keywords: one-vehicle look-ahead, model reference adaptive, stability, tuning gain controller, MRAC

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Authors: Asimina Paparrigopoulou, John Pavlopoulos, Maria Konstantinidou

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Dating papyri accurately is crucial not only to editing their texts but also for our understanding of palaeography and the history of writing, ancient scholarship, material culture, networks in antiquity, etc. Most ancient manuscripts offer little evidence regarding the time of their production, forcing papyrologists to date them on palaeographical grounds, a method often criticized for its subjectivity. By experimenting with data obtained from the Collaborative Database of Dateable Greek Bookhands and the PapPal online collections of objectively dated Greek papyri, this study shows that deep learning dating models, pre-trained on generic images, can achieve accurate chronological estimates for a test subset (67,97% accuracy for book hands and 55,25% for documents). To compare the estimates of these models with those of humans, experts were asked to complete a questionnaire with samples of literary and documentary hands that had to be sorted chronologically by century. The same samples were dated by the models in question. The results are presented and analysed.

Keywords: image classification, papyri images, dating

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Authors: Supattra Suanlim

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Nonthaburi province is one of the provinces in the central region of Thailand. There is the Chao Phraya River, which is a large and important river of Thailand passing through the province. With the way of life and social changes since the past. There is a digging canal called Lat canal or Om canal, communities along the canal have dense settlements. Important in life and culture. This research has 3 objectives as follows. 1.To explore cultural and ecotourism attractions in the Om Nont canal area. 2.To explore the facilities in the Om Nont canal tourist attraction. To suggest facilities for tourist attractions in the Om Nont canal, Nonthaburi, Thailand. This research is a qualitative research, using research methods by collecting data and surveying tourist attractions by water traffic. The results of the research can be concluded that There are 21 tourist attractions that have the potential to welcome tourists who want to travel cultural. 16 temples or places of worship, 2 government offices, 1 market, 2 landmarks. Each should be improved to increase the potential of the paths. There should be improvements in the road landscape that is a connection to water traffic. Districts should have signage and signage installation within tourist sites and have guidelines for architectural improvements. And the Nodes should improve the public space of the community. Such as the Nonthaburi pier area to have the idea of designing a tourist center Provide information in both Thai and English.

Keywords: Community, Cultural, Ecotourism, Facility

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Authors: T. H. Derdzyan, K. A. Ghazaryan, G. A. Gevorgyan

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Beta-glucosidase, chitinase, leucine-aminopeptidase, acid phosphomonoestearse and acetate-esterase enzyme activities in the soils under the impact of metallurgical industrial activity in Lori marz (district) were investigated. The results of the study showed that the activities of the investigated enzymes in the soils decreased with increasing distance from the Shamlugh copper mine, the Chochkan tailings storage facility and the ore transportation road. Statistical analysis revealed that the activities of the enzymes were positively correlated (significant) to each other according to the observation sites which indicated that enzyme activities were affected by the same anthropogenic factor. The investigations showed that the soils were polluted with heavy metals (Cu, Pb, As, Co, Ni, Zn) due to copper mining activity in this territory. The results of Pearson correlation analysis revealed a significant negative correlation between heavy metal pollution degree (Nemerow integrated pollution index) and soil enzyme activity. All of this indicated that copper mining activity in this territory causing the heavy metal pollution of the soils resulted in the inhabitation of the activities of the enzymes which are considered as biological catalysts to decompose organic materials and facilitate the cycling of nutrients.

Keywords: Armenia, metallurgical industrial activity, heavy metal pollutionl, soil enzyme activity

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Authors: Balázs Kulcsár

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Today, there is no part of the world that does not bear the mark of man in some way. This process seems unstoppable. So perhaps the best thing we can do is to touch that handprint gently and with the utmost care. There are multiple uses for the same piece of land, the coordination of which requires careful and sustainable spatial planning. The case study of the Rétközlake in north-eastern Hungary illustrates a habitat rehabilitation project in which a number of human uses were coordinated with the conservation and restoration of the natural environment. Today, the good condition of the habitat can only be maintained artificially, but the project has paid particular attention to finding a sustainable solution. The rehabilitation of Lake Rétköz is considered good practice in resolving land-use conflicts.

Keywords: sustainability, ecosystem service, land use conflict, landscape utilization

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Authors: Ramon Hernán, Maria Teresa Corzo

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This study examines the impact and contribution of the main journals in the discipline of behavioral finance to determine the state of the art of the discipline and the growth lines and concepts studied to date. This is a unique and novel study given that a review of the discipline has not been carried out through the keywords of the articles that allows visualizing through this component of the research, which are the main topics of discussion and the relationships that arise between the concepts discussed. To carry out this study, 3,876 articles have been taken as a reference, which includes 15,859 keywords from the main journals responsible for the growth of the discipline.; Journal of Behavioral Finance, Review of Behavioral Finance, Journal of Behavioral and Experimental Economics, Journal of Behavioral and Experimental Economics and Review of Behavioral Finance. The results indicate which are the topics most covered in the discipline throughout the period from 2000 to 2020, how these concepts have been dealt with on a recurring basis along with others throughout the aforementioned period and how the different concepts have been grouped based on the keywords established by the authors for the classification of their articles with a network diagram to complete the analysis.

Keywords: behavioral finance, keywords, co-words, top journals, data visualization

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Authors: Ifeyinwa Rita Kanu, Thomas Aspray, Adebayo J. Adeloye

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As a result of the ambiguity and complexity surrounding anaerobic digester foaming, efforts have been made by various researchers to understand the process of anaerobic digester foaming so as to proffer a solution that can be universally applied rather than site specific. All attempts ranging from experimental analysis to comparative review of other process has been futile at explaining explicitly the conditions and process of foaming in anaerobic digester. Studying the available knowledge on foam formation and relating it to anaerobic digester process and operating condition, this study presents a succinct and enhanced understanding of foaming in anaerobic digesters as well as introducing a simple and novel method to identify the onset of anaerobic digester foaming based on analysis of historical data from a field scale system.

Keywords: anaerobic digester, foaming, biogas, surfactant, wastewater

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Authors: Hisham M. Soliman, Hassan Yousef

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This manuscript presents new results on design saturated power system stabilizers (PSS) to assign system poles within a desired region for achieving good dynamic performance. The regional pole placement is accomplished against model uncertainties caused by different load conditions. The design is based on a sufficient condition in the form of linear matrix inequalities (LMI) which forces the saturated nonlinear controller to lie within the linear zone. The controller effectiveness is demonstrated on a single machine infinite bus system.

Keywords: power system stabilizer, saturated control, robust control, regional pole placement, linear matrix inequality (LMI)

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Authors: Divya Pande

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The dynamics of culture expresses itself in language. Even after India got independence in 1947 English subtly crept in the language of the masses with a silent and powerful flow towards the vernacular. The culture contact resulted in learning and emergence of a new language across the Hindi speaking belt of Northern and Central India. The hybrid words thus formed displaced the original word and got contextualized and absorbed in the language of the common masses. The research paper explores the interesting new vocabulary used extensively in the urban and rural districts of the state of Uttar- Pradesh which is the most populous state of India. The paper adopts a two way classification- formal and contextual for the analysis of the hybrid vocabulary of the linguistic items where one element is necessarily from the English language and the other from the Hindi. The new vocabulary represents languages of the wider world cutting across the geographical and the cultural barriers. The paper also broadly points out to the Hinglish commonly used in the state.

Keywords: assimilation, culture contact, Hinglish, hybrid words

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Authors: Juliza Hidayati, Sawarni Hasibuan

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PT. XYZ is a manufacturing company that produces Crude Palm Oil (CPO). The fierce competition in the global markets not only between companies but also a competition between supply chains. This research aims to analyze the supply chain and value chain of Crude Palm Oil (CPO) in the company. Data analysis method used is qualitative analysis and quantitative analysis. The qualitative analysis describes supply chain and value chain, while the quantitative analysis is used to find out value added and the establishment of the value chain. Based on the analysis, the value chain of crude palm oil (CPO) in the company consists of four main actors that are suppliers of raw materials, processing, distributor, and customer. The value chain analysis consists of two actors; those are palm oil plantation and palm oil processing plant. The palm oil plantation activities include nurseries, planting, plant maintenance, harvesting, and shipping. The palm oil processing plant activities include reception, sterilizing, thressing, pressing, and oil classification. The value added of palm oil plantations was 72.42% and the palm oil processing plant was 10.13%.

Keywords: palm oil, value chain, value added, supply chain

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Authors: Liang Zhou, Xiaojing Zhu, Yin Lu

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Danshen can induce the angiogenesis in advanced ischemic heart disease while inhibiting the angiogenesis in cancer. Additionally, Danshen mainly contains two groups of ingredients: the hydrophilic phenolic acids (danshensu, caffeic acid and salvianolic acid B), and the lipophilic tanshinones (dihydrotanshinone I, tanshinone II A, and cryptotanshinone). The lipophilic tanshinones reduced the VEGF- and bFGF-induced proliferation of HUVECs in dose-dependent manner, but cannot perform in others. Conversely, caffeic acid and salvianolic acid B had the opposite effect. Danshensu inhibited the VEGF- and bFGF-induced migration of HUVECs, and others were not. Most of them interrupted the forming capillary-like structures of HUVECs, except the danshensu and caffeic acid. Oppositely, caffeic acid enhanced the ability of forming capillary-like structures of HUVECs. Ultimately, the lipophilic tanshinones, danshensu and salvianolic acid B inhibited the angiogenesis, whereas the caffeic acid induced the angiogenesis. These data provide useful information for the classification of ingredients of Danshen for angiogenesis.

Keywords: angiogenesis, Danshen, HUVECs, ingredients

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Authors: Nishtha Madaan, Prateek Chaudhury, Nishant Kumar, Srikanta Bedathur

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In modern NLP applications, word embeddings are a crucial backbone that can be readily shared across a number of tasks. However, as the text distributions change and word semantics evolve over time, the downstream applications using the embeddings can suffer if the word representations do not conform to the data drift. Thus, maintaining word embeddings to be consistent with the underlying data distribution is a key problem. In this work, we tackle this problem and propose TransDrift, a transformer-based prediction model for word embeddings. Leveraging the flexibility of the transformer, our model accurately learns the dynamics of the embedding drift and predicts future embedding. In experiments, we compare with existing methods and show that our model makes significantly more accurate predictions of the word embedding than the baselines. Crucially, by applying the predicted embeddings as a backbone for downstream classification tasks, we show that our embeddings lead to superior performance compared to the previous methods.

Keywords: NLP applications, transformers, Word2vec, drift, word embeddings

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Authors: Mohammad Momeenul Islam, U. Johnson Alengaram, Mohd Zamin Jumaat, Iftekhair Ibnul Bashar

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Palm oil industry produces millions of tonnes of industrial wastes and these wastes create huge storage and environmental problems. In order to solve these problems various research works have been performed for past decades. The commonly available wastes are Oil palm shells (OPS) and Palm oil fuel ash (POFA). These materials have already acquired well recognition as alternate of conventional construction materials. OPS has been used as coarse aggregate and compressive strength was found up to 56 MPa for 56-day. It is said that 30 grade Oil Palm shell concrete (OPSC) is possible without adding any cementitious materials. The maximum modulus of elasticity for OPSC was found 18.6 GPa. The Oil palm shell concrete (OPSC) are used in country areas and nearby areas where the palm oil factories are located for houses, road-kerbs, drain blocks, etc. In case of superstructure like beams and slab are also produced by utilizing OPS. Many experimental works have been performed to establish POFA as a substituting binding material in replace of Ordinary Portland cement (OPC). Throughout the research it has been showed that up to 20% of cement by mass can be replaced by POFA. POFA is one of the most enriched pozzolanic materials. The main purpose of this review is to discuss the usage and opportunity of the palm oil industrial wastes as construction materials following the previous experimental research work.

Keywords: construction materials, oil palm shells (OPS), palm oil fuel ash (POFA), aggregates

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Authors: Alberto Alcalá-Alvarez, Pablo Padilla-Longoria

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The present paper describes a framework for constructing mathematical networks encoding relevant musical information from a music score for structural analysis. These graphs englobe statistical information about music elements such as notes, chords, rhythms, intervals, etc., and the relations among them, and so become helpful in visualizing and understanding important stylistic features of a music fragment. In order to build such networks, musical data is parsed out of a digital symbolic music file. This data undergoes different analytical procedures from Graph Theory, such as measuring the centrality of nodes, community detection, and entropy calculation. The resulting networks reflect important structural characteristics of the fragment in question: predominant elements, connectivity between them, and complexity of the information contained in it. Music pieces in different styles are analyzed, and the results are contrasted with the traditional analysis outcome in order to show the consistency and potential utility of this method for music analysis.

Keywords: computational musicology, mathematical music modelling, music analysis, style classification

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Authors: Noor Ismael, Somaya Malkawi, Sherin Al Awady, Taleb Ismael

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Background/Significance: Cancer is a serious health condition that affects individuals’ quality of life during and after the course of this condition. Children who have survived cancer and their caregivers may deal with residual physical, cognitive or social disabilities. There is little research on caregivers’ health and wellbeing after cancer. To the authors’ best knowledge; there is no specific research about how caregivers cope with everyday stressors after cancer. Therefore, this study aimed to explore the coping strategies that caregivers of children who have survived cancer utilize to overcome everyday stressors. Methods: This study utilized a descriptive survey design. The sample consisted of 103 caregivers, who visited the health and wellness clinic at a national cancer center (additional demographics are presented in the results). The sample included caregivers of children who were off cancer treatments for at least two years from the beginning of data collection. The institution’s internal review board approved this study. Caregivers who agreed to participate completed the survey. The survey collected caregiver reported demographic information and the Brief COPE which measures caregivers' frequency of engaging in certain coping strategies. The Brief COPE consisted of 14 coping sub-scales, which are self-distraction, active coping, denial, substance use, use of emotional support, use of instrumental support, behavioral disengagement, venting, positive reframing, planning, humor, acceptance, religion, and self-blame. Data analyses included calculating sub-scales’ scores for the fourteen coping strategies and analysis of frequencies of demographics and coping strategies. Results: The 103 caregivers who participated in this study were 62% mothers, 80% married, 45% finished high school, 50% do not work outside the house, and 60% have low family income. Result showed that religious coping (66%) and acceptance (60%) were the most utilized coping strategies, followed by positive reframing (45%), active coping (44%) and planning (43%). The least utilized coping strategies in our sample were humor (5%), behavioral disengagement (8%), and substance-use (10%). Conclusions: Caregivers of children who have survived cancer mostly utilize religious coping and acceptance in dealing with everyday stressors. Because these coping strategies do not directly solve stressors like active coping and planning coping strategies, it is important to support caregivers in choosing and implementing effective coping strategies. Knowing from our results that some caregivers may utilize substance use as a coping strategy, which has negative health effects on caregivers and their children, there must be direct interventions that target these caregivers and their families.

Keywords: caregivers, cancer, stress, coping

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Authors: A. Biran, P. Sobhe Bidari, A. Almazroe, V. Lakshminarayanan, K. Raahemifar

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Diabetic Retinopathy (DR) is a severe retinal disease which is caused by diabetes mellitus. It leads to blindness when it progress to proliferative level. Early indications of DR are the appearance of microaneurysms, hemorrhages and hard exudates. In this paper, an automatic algorithm for detection of DR has been proposed. The algorithm is based on combination of several image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Also, Support Vector Machine (SVM) Classifier is used to classify retinal images to normal or abnormal cases including non-proliferative or proliferative DR. The proposed method has been tested on images selected from Structured Analysis of the Retinal (STARE) database using MATLAB code. The method is perfectly able to detect DR. The sensitivity specificity and accuracy of this approach are 90%, 87.5%, and 91.4% respectively.

Keywords: diabetic retinopathy, fundus images, STARE, Gabor filter, support vector machine

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Authors: Atef Alaaeddine Sarraj, Brendan Jackman, Frank Walsh

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Tomorrow’s car will be more automated and increasingly connected. Innovative and intuitive interfaces are essential to accompany this functional enrichment. For that, today the automotive companies are competing to offer an advanced driver assistance system (ADAS) which will be able to provide enhanced navigation, collision avoidance, intersection support and lane keeping. These vision-based functions require an accurately calibrated camera. To achieve such differentiation in ADAS requires sophisticated sensors and efficient algorithms. This paper explores the different calibration methods applicable to vehicle-mounted fish-eye cameras with arbitrary fields of view and defines the first steps towards a self-calibration method that adequately addresses ADAS requirements. In particular, we present a self-calibration method after comparing different camera calibration algorithms in the context of ADAS requirements. Our method gathers data from unknown scenes while the car is moving, estimates the camera intrinsic and extrinsic parameters and corrects the wide-angle distortion. Our solution enables continuous and real-time detection of objects, pedestrians, road markings and other cars. In contrast, other camera calibration algorithms for ADAS need pre-calibration, while the presented method calibrates the camera without prior knowledge of the scene and in real-time.

Keywords: advanced driver assistance system (ADAS), fish-eye, real-time, self-calibration

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Authors: Deniz Peksen

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This thesis aims to predict trend movement of closing price of stock and to maximize portfolio by utilizing the predictions. In this context, the study aims to define a stock portfolio strategy from models created by using Logistic Regression, Gradient Boosting and Random Forest. Recently, predicting the trend of stock price has gained a significance role in making buy and sell decisions and generating returns with investment strategies formed by machine learning basis decisions. There are plenty of studies in the literature on the prediction of stock prices in capital markets using machine learning methods but most of them focus on closing prices instead of the direction of price trend. Our study differs from literature in terms of target definition. Ours is a classification problem which is focusing on the market trend in next 20 trading days. To predict trend direction, fourteen years of data were used for training. Following three years were used for validation. Finally, last three years were used for testing. Training data are between 2002-06-18 and 2016-12-30 Validation data are between 2017-01-02 and 2019-12-31 Testing data are between 2020-01-02 and 2022-03-17 We determine Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate as benchmarks which we should outperform. We compared our machine learning basis portfolio return on test data with return of Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate. We assessed our model performance with the help of roc-auc score and lift charts. We use logistic regression, Gradient Boosting and Random Forest with grid search approach to fine-tune hyper-parameters. As a result of the empirical study, the existence of uptrend and downtrend of five stocks could not be predicted by the models. When we use these predictions to define buy and sell decisions in order to generate model-based-portfolio, model-based-portfolio fails in test dataset. It was found that Model-based buy and sell decisions generated a stock portfolio strategy whose returns can not outperform non-model portfolio strategies on test dataset. We found that any effort for predicting the trend which is formulated on stock price is a challenge. We found same results as Random Walk Theory claims which says that stock price or price changes are unpredictable. Our model iterations failed on test dataset. Although, we built up several good models on validation dataset, we failed on test dataset. We implemented Random Forest, Gradient Boosting and Logistic Regression. We discovered that complex models did not provide advantage or additional performance while comparing them with Logistic Regression. More complexity did not lead us to reach better performance. Using a complex model is not an answer to figure out the stock-related prediction problem. Our approach was to predict the trend instead of the price. This approach converted our problem into classification. However, this label approach does not lead us to solve the stock prediction problem and deny or refute the accuracy of the Random Walk Theory for the stock price.

Keywords: stock prediction, portfolio optimization, data science, machine learning

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Authors: Mustafa M. Bob, Norhan Rahman, Abdalla Elamin, Saud Taher

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The objective of this study was to assess the suitability of Madinah city groundwater for irrigation purposes. Of the twenty three wells that were drilled in different locations in the city for the purposes of this study, twenty wells were sampled for water quality analyses. The United States Department of Agriculture (USDA) classification of irrigation water that is based on Sodium hazard (SAR) and salinity hazard was used for suitability assessment. In addition, the residual sodium carbonate (RSC) was calculated for all samples and also used for irrigation suitability assessment. Results showed that all groundwater samples are in the acceptable quality range for irrigation based on RSC values. When SAR and salinity hazard were assessed, results showed that while all groundwater samples (except one) fell in the acceptable range of SAR, they were either in the high or very high salinity zone which indicates that care should be taken regarding the type of soil and crops in the study area.

Keywords: irrigation suitability, TDS, salinity, SAR

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Authors: Fatiha Boudjema, Samia Boudergua, Abdallah Elhirtsi Nour El Houda, Ahmed Mbarek Kaouther

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The main objective of our work is to prepare and characterize a moisturizing lip balm based on natural ingredients such as waxes, vegetable oils, and shea butter. First, the vegetable and essential oils were extracted, and then lip balm was prepared. The extracted oils and the lip balm were submitted to many tests in order to guarantee their quality and effectiveness. These tests show that our balm has a shear thinning behavior with a melting point of 58 °C and that it spreads easily on the skin without showing an allergic reaction. The balm showed a moisturising effect and stability over the two-month period at storage room temperature condition.

Keywords: lip balm, natural products, rheological study, antioxydant activity

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Authors: Suat Erel, Gozde Gur

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Background: Recently a supramalleolar type of dynamic ankle foot orthosis (DAFO) has been increasingly used to support all of the dynamic arches of the foot and redistribute the pressure under the plantar surface of the foot to reduce the muscle tone. DAFO helps to maintain balance and postural control by providing stability and proprioceptive feedback in children with disease like Cerebral Palsy, Muscular Dystrophies, Down syndrome, and congenital hypotonia. Aim: The aim of this study was to investigate the role of Dynamic ankle foot orthosis (DAFO) on temporo-spatial parameters of gait and balance in three children with hereditary spastic paraparesis (HSP). Material Method: 13, 14, and 8 years old three children with HSP were included in the study. To provide correction on weight bearing and to improve gait, DAFO was made. Lower extremity spasticity (including gastocnemius, hamstrings and hip adductor muscles) using modified Ashworth Scale (MAS) (0-5), The temporo-spatial gait parameters (walking speed, cadence, base of support, step length) and Timed Up & Go test (TUG) were evaluated. All of the assessments about gait were compared with (with DAFO and shoes) and without DAFO (with shoes only) situations. Also after six months follow up period, assessments were repeated by the same physical therapist. Results: MAS scores for lower extremity were between “2-3” for the first child, “0-2” for the second child and “1-2” for the third child. TUG scores (sec) decreased from 20.2 to 18 for case one, from 9.4 to 9 for case two and from 12,4 to 12 for case three in the condition with shoes only and also from 15,2 to 14 for case one, from 7,2 to 7,1 for case two and from 10 to 7,3 for case three in the condition with DAFO and shoes. Gait speed (m/sec) while wearing shoes only was similar but while wearing DAFO and shoes increased from 0,4 to 0,5 for case one, from 1,5 to 1,6 for case two and from 1,0 to 1,2 for case three. Base of support scores (cm) wearing shoes only decreased from 18,5 to 14 for case one, from 13 to 12 for case three and were similar as 11 for case two. While wearing DAFO and shoes, base of support decreased from 10 to 9 for case one, from 11,5 to 10 for case three and was similar as 8 for case two. Conclusion: The use of a DAFO in a patient with HSP normalized the temporo-spatial gait parameters and improved balance. Walking speed is a gold standard for evaluating gait quality. With the use of DAFO, walking speed increased in this three children with HSP. With DAFO, better TUG scores shows that functional ambulation improved. Reduction in base of support and more symmetrical step lengths with DAFO indicated better balance. These encouraging results warrant further study on wider series.

Keywords: dynamic ankle foot orthosis, gait, hereditary spastic paraparesis, balance in patient

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Authors: Monika Chuchro

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This paper presents a preliminary attempt to apply classification of time series using meta-clusters in order to improve the quality of regression models. In this case, clustering was performed as a method to obtain a subgroups of time series data with normal distribution from inflow into waste water treatment plant data which Composed of several groups differing by mean value. Two simple algorithms: K-mean and EM were chosen as a clustering method. The rand index was used to measure the similarity. After simple meta-clustering, regression model was performed for each subgroups. The final model was a sum of subgroups models. The quality of obtained model was compared with the regression model made using the same explanatory variables but with no clustering of data. Results were compared by determination coefficient (R2), measure of prediction accuracy mean absolute percentage error (MAPE) and comparison on linear chart. Preliminary results allows to foresee the potential of the presented technique.

Keywords: clustering, data analysis, data mining, predictive models

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Authors: Maha Wiss, Wael Khreich

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Animals, objects, foods, plants, and other non-human terms are commonly used as a source of metaphors to describe females in formal and slang language. Comparing women to non-human items not only reflects cultural views that might conceptualize women as subordinates or in a lower position than humans, yet it conveys this degradation to the listeners. Moreover, the dehumanizing representation of females in the language normalizes the derogation and even encourages sexism and aggressiveness against women. Although dehumanization has been a popular research topic for decades, according to our knowledge, no studies have linked women's dehumanizing language to the machine learning field. Therefore, we introduce our research work as one of the first attempts to create a tool for the automated detection of the dehumanizing depiction of females in English texts. We also present the first labeled dataset on the charted topic, which is used for training supervised machine learning algorithms to build an accurate classification model. The importance of this work is that it accomplishes the first step toward mitigating dehumanizing language against females.

Keywords: gender bias, machine learning, NLP, women dehumanization

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Authors: Sadia Rafiq, Md. Ashab Siddique Zaki, Ananya Roy

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Mountain cycling is a type of off-road bicycle racing that typically takes place on rocky, arid, or other challenging terrains on specially-made mountain cycles. Professional cyclists race while attempting to stay on their bikes in a variety of locales across the world. For safety measures in mountain cycling, as there we have a high chance of injury in case of tire puncture, it’s a preferable way to use an airless tire instead of a pneumatic tire. As airless tire does not tend to go flat, it needs to be replaced less frequently. The airless tire replaces the pneumatic tire, wheel, and tire system with a single unit. It consists of a stiff hub connected to a shear band by flexible, pliable spokes, which is made of poly-composite and a tread band, all of which work together as a single unit to replace all of the components of a normal radial tire. In this paper, an analysis of airless tires in the mountain cycle is shown along with structure and material study. We will be taking the Honeycomb and Diamond Structure of spokes to compare the deformation in both cases and choose our preferable structure. As we know, the tread and spokes deform with the surface roughness and impact. So, the tire tread thickness and the design of spokes can control how much the tire can distort. Through the simulation, we can come to the conclusion that the diamond structure deforms less than the honeycomb structure. So, the diamond structure is more preferable.

Keywords: airless tire, diamond structure, honeycomb structure, deformation

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Authors: Ines Gasmi, Salima Smiti, Makram Soui, Khaled Ghedira

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Credit risk is considered as one of the important issues for financial institutions. It provokes great losses for banks. To this objective, numerous methods for credit risk evaluation have been proposed. Many evaluation methods are black box models that cannot adequately reveal information hidden in the data. However, several works have focused on building transparent rules-based models. For credit risk assessment, generated rules must be not only highly accurate, but also highly interpretable. In this paper, we aim to build both, an accurate and transparent credit risk evaluation model which proposes a set of classification rules. In fact, we consider the credit risk evaluation as an optimization problem which uses a genetic programming (GP) algorithm, where the goal is to maximize the accuracy of generated rules. We evaluate our proposed approach on the base of German and Australian credit datasets. We compared our finding with some existing works; the result shows that the proposed GP outperforms the other models.

Keywords: credit risk assessment, rule generation, genetic programming, feature selection

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Authors: Natia Gavardashvili

Abstract:

On June 13-14 of 2015, a landslide in village Akhaldaba was formed as a result of the intense rains in the water catch basin of the river Vere. As a result of the landslide movement, freshets and mudflows originated, and unfortunately, there were victims: zoo animals and birds were drawn in the flood and 12 people died due to the flooded motor road. The goal of the study is to give the analysis of the results of the field and scientific research held in 2015-2017 and to generalize them to the water catch basins of the erosive-mudflow rivers of other mountain landscapes of Georgia. By considering the field and scientific works, the main geographic, geological, climatic, hydrological and hydraulic properties of the erosive-mudflow tributaries of the water catch basin of the river Vere were evaluated and the probabilities of mudflow formation by considering relevant risk-factors were identified. The typology of the water catch basins of erosive-mudflow rivers of Georgia was identified on the example of the river Vere based on the field and scientific study, and their genesis, frequency of mudflow formation and volume of the drift material was identified. By using the empirical and theoretical dependencies, the amount of solid admixtures in the mudflow formed in the gorge of the river Jokhona, the right tributary of the river Vere was identified by considering the shape of the stones.

Keywords: water catchment basin, erosion, mudflow, typology

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Authors: Somorjeet Sharma Shamurailatpam, Rabindra Das, A. Suchitra Devi

Abstract:

Computer and video display users might complain about Asthenopia, burning, dry eyes etc. The management of dry eyes is often not in the lines of severity. Following systematic evaluation and grading, dry eye disease is one condition that can be practiced at all levels of ophthalmic care. In the present study, different spectrum causing dry eye and prevalence of dry eye disease in computer users of Manipur, India are determined with 600 individuals (300 cases and 300 control). Individuals between 15 and 50 years who used computers for more than 3 hrs a day for 1 year or more were included. Tear break up time (TBUT) and Schirmer’s test were conducted. It shows that 33 (20.4%) out of 164 males and 47 (30.3%) out of 136 females have dry eye. Possible explanation for the observed result is discussed.

Keywords: asthenopia, computer vision syndrome, dry eyes, Schirmer's test, TBUT

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Authors: Chuluundorj Begz

Abstract:

This paper presents the dynamic, psycho-cognitive approach to study of human verbal thinking on the basis of typologically different languages /as a Mongolian, English and Russian/. Topological equivalence in verbal communication serves as a basis of Universality of mental structures and therefore deep structures. Mechanism of verbal thinking consisted at the deep level of basic concepts, rules for integration and classification, neural networks of vocabulary. In neuro cognitive study of language, neural architecture and neuro psychological mechanism of verbal cognition are basis of a vector-based modeling. Verbal perception and interpretation of the infinite set of meanings and propositions in mental continuum can be modeled by applying tensor methods. Euclidean and non-Euclidean spaces are applied for a description of human semantic vocabulary and high order structures.

Keywords: Euclidean spaces, isomorphism and homomorphism, mental lexicon, mental mapping, semantic memory, verbal cognition, vector space

Procedia PDF Downloads 518

Authors: Femy M. Makkar, S. Chandrakaran, N. Sankar

Abstract:

The concept of reinforced earth has been used in the field of geotechnical engineering since 1960s, for many applications such as, construction of road and rail embankments, pavements, retaining walls, shallow foundations, soft ground improvement and so on. Conventionally, planar geosynthetic materials such as geotextiles and geogrids were used as the reinforcing elements. Recently, the use of three dimensional reinforcements becomes one of the emerging trends in this field. So, in the present investigation, three dimensional geogrid is proposed as a reinforcing material. Laboratory scaled plate load tests are conducted on a model square footing resting on 3D geogrid reinforced sand bed. The performance of 3D geogrids in triangular and square pattern was compared with conventional geogrids and the improvement in bearing capacity and reduction in settlement and heave are evaluated. When single layer of reinforcement was placed at an optimum depth of 0.25B from the bottom of the footing, the bearing capacity of conventional geogrid reinforced soil improved by 1.85 times compared to unreinforced soil, where as 3D geogrid reinforced soil with triangular pattern and square pattern shows 2.69 and 3.05 times improvement respectively compared to unreinforced soil. Also, 3D geogrids performs better than conventional geogrids in reducing the settlement and heave of sand bed around the model footing.

Keywords: 3D reinforcing elements, bearing capacity, heavy, settlement

Procedia PDF Downloads 297