Search results for: recursive least square algorithm

Authors: G. K. Viswanadh, B. Rajasekhar, G. Venkata Ramana

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Water distribution networks play a vital role in ensuring a reliable supply of clean water to urban areas. However, they face several challenges, including pressure control, pump speed optimization, and burst event detection. This paper combines insights from two studies to address these critical issues in Water distribution networks, focusing on the specific context of Kapra Municipality, India. The first part of this research concentrates on optimizing pressure control and pump speed in complex Water distribution networks. It utilizes the EPANET- MATLAB Toolkit to integrate EPANET functionalities into the MATLAB environment, offering a comprehensive approach to network analysis. By optimizing Pressure Reduce Valves (PRVs) and variable speed pumps (VSPs), this study achieves remarkable results. In the Benchmark Water Distribution System (WDS), the proposed PRV optimization algorithm reduces average leakage by 20.64%, surpassing the previous achievement of 16.07%. When applied to the South-Central and East zone WDS of Kapra Municipality, it identifies PRV locations that were previously missed by existing algorithms, resulting in average leakage reductions of 22.04% and 10.47%. These reductions translate to significant daily Water savings, enhancing Water supply reliability and reducing energy consumption. The second part of this research addresses the pressing issue of burst event detection and localization within the Water Distribution System. Burst events are a major contributor to Water losses and repair expenses. The study employs wireless sensor technology to monitor pressure and flow rate in real time, enabling the detection of pipeline abnormalities, particularly burst events. The methodology relies on transient analysis of pressure signals, utilizing Cumulative Sum and Wavelet analysis techniques to robustly identify burst occurrences. To enhance precision, burst event localization is achieved through meticulous analysis of time differentials in the arrival of negative pressure waveforms across distinct pressure sensing points, aided by nodal matrix analysis. To evaluate the effectiveness of this methodology, a PVC Water pipeline test bed is employed, demonstrating the algorithm's success in detecting pipeline burst events at flow rates of 2-3 l/s. Remarkably, the algorithm achieves a localization error of merely 3 meters, outperforming previously established algorithms. This research presents a significant advancement in efficient burst event detection and localization within Water pipelines, holding the potential to markedly curtail Water losses and the concomitant financial implications. In conclusion, this combined research addresses critical challenges in Water distribution networks, offering solutions for optimizing pressure control, pump speed, burst event detection, and localization. These findings contribute to the enhancement of Water Distribution System, resulting in improved Water supply reliability, reduced Water losses, and substantial cost savings. The integrated approach presented in this paper holds promise for municipalities and utilities seeking to improve the efficiency and sustainability of their Water distribution networks.

Keywords: pressure reduce valve, complex networks, variable speed pump, wavelet transform, burst detection, CUSUM (Cumulative Sum), water pipeline monitoring

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Authors: Suzan Wedyan

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Data mining is one of the main phases in the Knowledge Discovery Database (KDD) which is responsible of finding hidden and useful knowledge from databases. There are many different tasks for data mining including regression, pattern recognition, clustering, classification, and association rule. In recent years a promising data mining approach called associative classification (AC) has been proposed, AC integrates classification and association rule discovery to build classification models (classifiers). This paper surveys and critically compares several AC algorithms with reference of the different procedures are used in each algorithm, such as rule learning, rule sorting, rule pruning, classifier building, and class allocation for test cases.

Keywords: associative classification, classification, data mining, learning, rule ranking, rule pruning, prediction

Procedia PDF Downloads 525

Authors: Basuki Supartono, Nunuk Nugrohowati, Ryan Gamma Andiraldi

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Osteoarthritis of the knee can occur due to scoliosis. The purpose of this study is to determine the effect of scoliosis cause secondary osteoarthritis on the knee. This research use an analytic cross-sectional design. The total sample of 92 athletes scoliosis taken by simple random sampling technique. The data obtained were analyzing with Chi-square test, Fisher and Prevalence Ratio. The results of analysis show that there are influences on the incidence of scoliosis secondary osteoarthritis on the knee in athletes at the National Sports Hospital. Based on the criteria in the Cobbs angle had the results (p = 0.022 (p <0.05)), moderate Cobbs angle degree were 7.5 times more at risk of causing secondary osteoarthritis on the knee than a mild degree. While the shape of the curve scoliosis is getting results (p = 0.038 (p <0.05)), the shape of the S curve scoliosis 3.2 times more at risk of causing secondary osteoarthritis on the knee than the curve C. It can be concluded that there is significant influence between the Cobbs angle, shape of the curve scoliosis on the incidence of secondary osteoarthritis on the knee in National Sports Cibubur Hospital on July 2013- April 2014

Keywords: Cobbs angle, curve shape scoliosis, secondary osteoarthritis on the knee, analytic cross-sectional design

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Authors: Fayez Mostafa Alhamoui, Adnan Hadi Mahdi Al- Helali

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The main issue in designing a wireless sensor network (WSN) is the finding of a proper routing protocol that complies with the several requirements of high reliability, short latency, scalability, low power consumption, and many others. This paper proposes a novel routing algorithm that complies with these design requirements. The new routing protocol divides the WSN into several sub-networks and each sub-network is divided into several clusters. This division is designed to reduce the number of radio transmission and hence decreases the power consumption. The network division may be changed dynamically to adapt with the network changes and allows the realization of the design requirements.

Keywords: wireless sensor networks, routing protocols, AD HOC topology, cluster, sub-network, WSN design requirements

Procedia PDF Downloads 525

Authors: Sasidhar B., Bhaskar Rao N., Ramesh Babu D. R., Ravi Shankar M.

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Segmentation of lung pleura is a preprocessing step in Computer-Aided Diagnosis (CAD) which helps in reducing false positives in detection of lung cancer. The existing methods fail in extraction of lung regions with the nodules at the pleura of the lungs. In this paper, a new method is proposed which segments lung regions with nodules at the pleura of the lungs based on curvature analysis and morphological operators. The proposed algorithm is tested on 06 patient’s dataset which consists of 60 images of Lung Image Database Consortium (LIDC) and the results are found to be satisfactory with 98.3% average overlap measure (AΩ).

Keywords: curvature analysis, image segmentation, morphological operators, thresholding

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Authors: Jeongyeob Hong, Myeonghoon Park, Taeson Yoon

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After the advent of Achaeans which utilize different metabolism pathway and contain conspicuously different cellular structure, they have been recognized as possible materials for developing quality of human beings. Among diverse Achaeans, in this paper, we compared 16s RNA Sequences of four different species of Thermococcus: Achaeans genus specialized in sulfur-dealing metabolism. Four Species, Barophilus, Kodakarensis, Hydrothermalis, and Onnurineus, live near the hydrothermal vent that emits extreme amount of sulfur and heat. By comparing ribosomal sequences of aforementioned four species, we found similarities in their sequences and expressed protein, enabling us to expect that certain ribosomal sequence or proteins are vital for their survival. Apriori algorithms and Decision Tree were used. for comparison.

Keywords: Achaeans, Thermococcus, apriori algorithm, decision tree

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Authors: Morteza Gharibi, Abdolghader Pakniat, Somayeh Bahrampouri

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Introduction: Emergency department (E.R.) crowding is a serious widespread problem in hospitals that leads to irregularities, a slower rate of delivery of services to patients, and a long-term stay. In addition, the long-term stay in the E.D. reduces the possibility of providing services with appropriate quality to other patients who are undergoing medical emergencies, which leads to dissatisfaction among patients. This study aimed to determine the relationship between ED-crowding and the mortality rate of the patients referred to the E.D. In a retrospective cohort study, all patients who expired in first 24 hours of admission were enrolled in the study. Crowding index at the moment of admission was calculated using Edwin Score. The data including history and physical examination, time of arrival in the E.D., diagnosis (using ICD 10 code), time of death, cause of death, demographic information was recoded based on triage forms on admission and patients’ medical files. Data analysis was performed by using descriptive statistics and chi square test, ANOVA tests using SPSS ver. 19. The time of arrival in E.D. to death in crowded E.D. conditions, with an average of five hours and 25 minutes, was significantly higher than the average admission Time of arrival in E.D. to death in active and crowded E.D. conditions. More physicians and nurses can be employed during crowded times to reduce staff fatigue and improve their performance during these hours.

Keywords: mortality, emergency, department, crowding

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Authors: Nusrat Ali, Muhammad Saleem Khan

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Education is the process of bringing individuals aware of their own reality in a manner that leads them to the effective adjustment with the environment. Females’ participation is vital to reducing hunger and poverty and promoting the family welfare. Education is the right of men and women both. Female education is more needed rural areas as compared to urban areas. Without educating the women of the country we cannot think of developing our nation. It is a fact that women are the first teachers of their children. Hence, if mothers are well educated, they can play an important role in shaping and molding of their sons and daughters. The main purpose of study was to identify the barriers of female education and the attitude among the parents. The present study researchers selected a quantitative study to explore the highlighting problem in the particular areas. Through the stratified random sampling selected a sample size from each stratum and generalized whole population. Chi-square test was used to test the validity of the data. The conclusion shows attitudes of parents somehow influence their daughters’ education, particularly those who are living in countryside. Another a big challenge of female education is co-education system in our society is higher which directly subjected to parents unfavorable attitude towards their daughters’ education. In this modern era various organizations are working for female education in rural areas where females are considered as house working ladies, now it’s time to work more to change parent’s attitude towards their daughter’s education.

Keywords: parental attitude, professional education, daughter, unfavorable attitude

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Authors: Jimeng Shi, Mahek Jain, Giri Narasimhan

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Time Series Forecasting (TSF) is used to predict the target variables at a future time point based on the learning from previous time points. To keep the problem tractable, learning methods use data from a fixed-length window in the past as an explicit input. In this paper, we study how the performance of predictive models changes as a function of different look-back window sizes and different amounts of time to predict the future. We also consider the performance of the recent attention-based Transformer models, which have had good success in the image processing and natural language processing domains. In all, we compare four different deep learning methods (RNN, LSTM, GRU, and Transformer) along with a baseline method. The dataset (hourly) we used is the Beijing Air Quality Dataset from the UCI website, which includes a multivariate time series of many factors measured on an hourly basis for a period of 5 years (2010-14). For each model, we also report on the relationship between the performance and the look-back window sizes and the number of predicted time points into the future. Our experiments suggest that Transformer models have the best performance with the lowest Mean Average Errors (MAE = 14.599, 23.273) and Root Mean Square Errors (RSME = 23.573, 38.131) for most of our single-step and multi-steps predictions. The best size for the look-back window to predict 1 hour into the future appears to be one day, while 2 or 4 days perform the best to predict 3 hours into the future.

Keywords: air quality prediction, deep learning algorithms, time series forecasting, look-back window

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Authors: B. Mahfoud, A. Bendjaghlouli

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Natural convection is simulated in a truncated cone filled with nanofluid. Inclined and top walls have constant temperature where the heat source is located on the bottom wall of the conical container which is thermally insulated. A finite volume approach is used to solve the governing equations using the SIMPLE algorithm for different parameters such as Rayleigh number, inclination angle of inclined walls of the enclosure and heat source length. The results showed an enhancement in cooling system by using a nanofluid, when conduction regime is assisted. The inclination angle of inclined sidewall and heat source length affect the heat transfer rate and the maximum temperature.

Keywords: heat source, truncated cone, nanofluid, natural convection

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Authors: M. Vivodík, Ž. Balážová, Z. Gálová

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The aim of this work was to detect genetic variability among the set of 40 castor genotypes using 8 RAPD markers. Amplification of genomic DNA of 40 genotypes, using RAPD analysis, yielded in 66 fragments, with an average of 8.25 polymorphic fragments per primer. Number of amplified fragments ranged from 3 to 13, with the size of amplicons ranging from 100 to 1200 bp. Values of the polymorphic information content (PIC) value ranged from 0.556 to 0.895 with an average of 0.784 and diversity index (DI) value ranged from 0.621 to 0.896 with an average of 0.798. The dendrogram based on hierarchical cluster analysis using UPGMA algorithm was prepared and analyzed genotypes were grouped into two main clusters and only two genotypes could not be distinguished. Knowledge on the genetic diversity of castor can be used for future breeding programs for increased oil production for industrial uses.

Keywords: dendrogram, polymorphism, RAPD technique, Ricinus communis L.

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Authors: Adebimpe Olubunmi Adebanjo

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This study observed students’ attitudes towards reading as a determinant of performance in O’ Level English in Oyo state secondary schools. Random sampling technique was used to select two schools from each of the five geo-political zones of the state while stratified sampling technique was used to select twenty students from each of the ten schools. A researcher designed questionnaire was used to gather information on students’ attitudes while a prepared test based on O’ Level syllabus was stapled to each of the questionnaire to ascertain their level of achievement in O’ Level English. The Percentage, Mean, Standard Deviation, Chi-square and Pearson Contingency Coefficient were used to answer and test the research questions and hypotheses raised. The findings showed that the general attitude of students towards reading was ambivalent; the general level of achievement was also low. The findings also revealed that there was a significant difference in the attitudes of students to reading on the basis of gender and home background. Students from educated homes also had better attitudes towards reading than their counterparts from illiterate homes. The findings also showed that there was a significant relationship between students’ attitudes to reading and their performance in O’ Level English. Students with positive attitude to reading had better grades in O’ Level English than students with ambivalent and negative attitudes. Based on the findings, it was recommended that students should change their attitudes to reading; the school and the home were also advised to always encourage students to read.

Keywords: positive, ambivalent, negative attitudes, o' level English

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Authors: Amar Khoukhi, Mohamed Shahab

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This paper presents the optimal control problem of mobile robot motion as a nonlinear programming problem (NLP) and solved using a direct method of numerical optimal control. The NLP is initialized with a B-Spline for which node locations are optimized using a genetic search. The system acceleration inputs and sampling periods are considered as optimization variables. Different scenarios with different objectives weights are implemented and investigated. Interesting results are found in terms of complying with the expected behavior of a mobile robot system and time-energy minimization.

Keywords: multi-objective control, non-holonomic systems, mobile robots, nonlinear programming, motion planning, B-spline, genetic algorithm

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Authors: R. Mellah, R. Toumi

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This paper presents a new adaptive neuro-fuzzy controller equipped with compensatory fuzzy control (CNFI) in order to not only adjusts membership functions but also to optimize the adaptive reasoning by using a compensatory learning algorithm. The proposed control structure includes both CNFI controllers for which one is used to control in force the master robot and the second one for controlling in position the slave robot. The experimental results obtained, show a fairly high accuracy in terms of position and force tracking under free space motion and hard contact motion, what highlights the effectiveness of the proposed controllers.

Keywords: compensatory fuzzy, neuro-fuzzy, control adaptive, teleoperation

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Authors: Guanlin Wu, Jiajia Yao, Fang Liu, Junshuai Xue, Jincheng Zhang, Yue Hao

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Owing to the excellent thermal conductivity and ultra-wide bandgap, Aluminum nitride (AlN)/Gallium nitride (GaN) is a highly promising material to achieve high breakdown voltage and output power devices among III-nitrides. In this study, we explore the growth and characterization of polarization-induced AlN/GaN heterostructures using plasma-assisted molecular beam epitaxy (PA-MBE) on AlN-on-sapphire templates. To improve the crystal quality and demonstrate the effectiveness of the PA-MBE approach, a thick AlN buffer of 180 nm was first grown on the AlN-on sapphire template. This buffer acts as a back-barrier to enhance the breakdown characteristic and isolate leakage paths that exist in the interface between the AlN epilayer and the AlN template. A root-mean-square roughness of 0.2 nm over a scanned area of 2×2 µm2 was measured by atomic force microscopy (AFM), and the full-width at half-maximum of (002) and (102) planes on the X-ray rocking curve was 101 and 206 arcsec, respectively, using by high-resolution X-ray diffraction (HR-XRD). The electron mobility of 443 cm2/Vs with a carrier concentration of 2.50×1013 cm-2 at room temperature was achieved in the AlN/GaN heterostructures by using a polarization-induced GaN channel. The low depletion capacitance of 15 pF is resolved by the capacitance-voltage. These results indicate that the polarization-induced AlN/GaN heterostructures have great potential for next-generation high-temperature, high-frequency, and high-power electronics.

Keywords: AlN, GaN, MBE, heterostructures

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Authors: Shpresa Agani, Nysret Agani

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Studies have found that women, during the 1st stage of labour, respectively cervical effacement, experience anxiety. This study aims to measure the degree of anxiety during cervical effacement, using Hopkins Symptom Checklist-25 (HSCL-25) for measuring anxiety symptoms (HSCL-25). A randomized prospective study with 300 women during the 1st stage of labour was conducted where cervical effacement percentage in parallel with the symptoms of anxiety was examined. Anxiety degree levels were examined by HSCL-25. Results showed that 81% were primiparous, while 19% were multiparous. All participants experienced anxiety symptoms, and the degree of anxiety depended on the stage of the birth process. Groups-based modeling according to HSCL- 2 identified three distinct groups of anxiety symptoms: group 1 (low degree, 32 cases or 11%), group 2 (mild degree, 186 cases or 62%), and group 3 (high degree, 82 cases or 27%). Depending on the percentage of cervical effacement, the anxiety degree increased. In a cervical effacement of 0-60-%, 125 cases or 41.6% had symptoms of anxiety, while in a cervical effacement of 60-100%, 174 cases or 58.4% had symptoms of anxiety (Chi-Square X2 (4,N=300)=10.755, p=0.02). This study showed a correlation between cervical effacement and the degree of anxiety. Further, it was found that the majority of participants experienced symptoms of anxiety during the cervical effacement process. The degree of anxiety increased in direct proportion to the degree of the cervical effacement process. The higher the percentage of cervical effacement, the higher the degree of anxiety. A continuing assessment of the psychological well-being of women throughout the birth process.

Keywords: anxiety, cervical effacement, pregnancy, HSCL-25

Procedia PDF Downloads 194

Authors: Fina O. Faithpraise, Effiong O. Obisung, Azele E. Peter, Chris R. Chatwin

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This study investigates and identifies consumer attitude as a major influence that results in non-technical losses in the Nigerian electricity supply sector. This discovery is revealed by the combination of quantitative and qualitative research to complete a survey. The dataset employed is a simple random sampling of households using electricity (public power supply), and the number of units chosen is based on statistical power analysis. The units were subdivided into two categories (household with and without electrical meters). The hypothesis formulated was tested and analyzed using a chi-square statistical method. The results obtained shows that the critical value for the household with electrical prepared meter (EPM) was (9.488 < 427.4) and those without electrical prepared meter (EPMn) was (9.488 < 436.1) with a p-value of 0.01%. The analysis demonstrated so far established the real-time position, which shows that the wrong attitude towards handling the electricity supplied (not turning off light bulbs and electrical appliances when not in use within the rooms and outdoors within 12 hours of the day) characterized the non-technical losses in the power sector. Therefore the adoption of efficient lighting attitudes in individual households as recommended by the researcher is greatly encouraged. The results from this study should serve as a model for energy efficiency and use for the improvement of electricity consumption as well as a stable economy.

Keywords: attitudinal change, household, non-technical losses, prepared meter

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Authors: Sheng-Tse Wu, Wu-Sung Yao

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In this paper, a drift assist control system is proposed for remote control (RC) cars to get the perfect drift angle. A steering servo control scheme is given powerfully to assist the drift driving. A gyroscope sensor is included to detect the machine's tail sliding and to achieve a better automatic counter-steering to prevent RC car from spinning. To analysis tire traction and vehicle dynamics is used to obtain the dynamic track of RC cars. It comes with a control gain to adjust counter-steering amount according to the sensor condition. An illustrated example of 1:10 RC drift car is given and the real-time control algorithm is realized by Arduino Uno.

Keywords: drift assist control system, remote control cars, gyroscope, vehicle dynamics

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Authors: Busra Mutlu Ipek, Merve Mutlu, Ahmet Mutlu

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Novel coronavirus COVID-19, which has recently influenced the world, poses a great threat to humanity. In order to overcome this challenging situation, scientists are working on developing effective vaccine against coronavirus. Many experts and researchers have also produced articles and done studies on this highly important subject. In this direction, this special topic was chosen for article to make a contribution to this area. The purpose of this article is to perform RNA sequence analysis of selected virus forms in the Coronaviridae family and predict/classify SARS-CoV-2 (COVID-19) from other selected complete genomes in coronaviridae family using proposed Artificial Neural Network(ANN) algorithm.

Keywords: Coronaviridae family, COVID-19, RNA sequencing, ANN, neural network

Procedia PDF Downloads 136

Authors: Muna A. Eissawi, Safaa Abed Elfataah, Haytham Hago, Fatima E Abukunna, Ibtisam Amin Goreish, Nahid Gornas

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The study examined and analyzed the genetic diversity of DRB1locus of exon 2 of major histocompatibility complex of Sudanese desert sheep using PCR-RFLP and DNA sequencing. Five hundred samples belonging to five ecotypes of Desert Sudanese sheep (Abrag (Ab), Ashgar (Ash), Hamari (H), Kabashi (K) and Watish (W) were included. Amplification of exon 2 of the DRB1 gene yielded (300bp) amplified product in different ecotypes. Nine different digestion patterns corresponding to Five distinct alleles were observed with Rsa1 digestion. Genotype (ag) was the most common among all ecotypes, with a percentage comprised (40.4 %). The Hardy-Weinberg equilibrium (HWE) test showed that the studied ecotypes have significantly deviated from the theoretical proportions of Rsa1 patterns; probability values of the Chi-square test for HWE for MHC-DRB1 gene in SDS were 0.00 in all ecotypes. The constructed phylogenetic tree revealed the relation of 22 Sudanese isolates with each other and showed the shared sequences with 47 published foreign sequences randomly selected from different geographic regions. The results of this study highlight the effect of heterozygosity of MHC genes of the Desert sheep of Sudan which may clarify some of genetic back ground of their disease resistance and adaptation to environment.

Keywords: desert sheep, MHC, Ovar-DRB1, polymerase chain reaction (PCR), restriction fragment length polymorphism (RFLP)

Procedia PDF Downloads 62

Authors: Ruxandra Aursulesei, David O’Callaghan, Cian Ryan, Diarmaid O’Cualain, Viktor Varkarakis, Alina Sultana, Joseph Lemley

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Human errors caused by drowsiness are among the leading causes of road accidents. Neurobiological research gives information about the electrical signals emitted by neurons firing within the brain. Electrical signal frequencies can be determined by attaching bio-sensors to the head surface. By observing the electrical impulses and the rhythmic interaction of neurons with each other, we can predict the mental state of a person. In this paper, we aim to better understand intersubject and intrasubject variability in terms of electrophysiological patterns that occur at the onset of drowsiness and their evolution with the decreasing of vigilance. The purpose is to lay the foundations for an algorithm that detects the onset of drowsiness before the physical signs become apparent.

Keywords: electroencephalography, drowsiness, ADAS, annotations, clinician

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Authors: Akram Khaleghei, Ghosheh Balagh, Viliam Makis

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In this paper, we investigate the residual life prediction problem for a partially observable system subject to two failure modes, namely a catastrophic failure and a failure due to the system degradation. The system is subject to condition monitoring and the degradation process is described by a hidden Markov model with unknown parameters. The parameter estimation procedure based on an EM algorithm is developed and the formulas for the conditional reliability function and the mean residual life are derived, illustrated by a numerical example.

Keywords: partially observable system, hidden Markov model, competing risks, residual life prediction

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Authors: Golnaz Shahtahmassebi, Jose Maria Sarabia

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In this talk, we introduce a new class of conjugate prior distributions obtained from conditional specification methodology. We illustrate the application of such distribution in Bayesian change point detection in Poisson processes. We obtain the posterior distribution of model parameters using a general bivariate distribution with gamma conditionals. Simulation from the posterior is readily implemented using a Gibbs sampling algorithm. The Gibbs sampling is implemented even when using conditional densities that are incompatible or only compatible with an improper joint density. The application of such methods will be demonstrated using examples of simulated and real data.

Keywords: change point, bayesian inference, Gibbs sampler, conditional specification, gamma conditional distributions

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Authors: Alemaw Kefale, Aramde Fetene, Hayal Desta

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This study analyzed the users' and experts' views on the green space quality and planning models in Debre Berhan (DB) and Debre Markos (DM) cities in Ethiopia. A questionnaire survey was conducted on 350 park users (148 from DB and 202 from DM) to rate the accessibility, size, shape, vegetation cover, social and cultural context, conservation and heritage, community participation, attractiveness, comfort, safety, inclusiveness, and maintenance of green spaces using a Likert scale. A key informant interview was held with 13 experts in DB and 12 in DM. Descriptive statistics and tests of independence of variables using the chi-square test were done. A statistically significant association existed between the perception of green space quality attributes and users' occupation (χ² (160, N = 350) = 224.463, p < 0.001), age (χ² (128, N = 350) = 212.812, p < 0.001), gender (χ² (32, N = 350) = 68.443, p < 0.001), and education level (χ² (192, N = 350) = 293.396, p < 0.001). 61.7 % of park users were unsatisfied with the quality of urban green spaces. The users perceived dense vegetation cover as "good," with a mean value of 3.41, while the remaining were perceived as "medium with a mean value of 2.62 – 3.32". Only quantitative space standards are practiced as a green space planning model, while other models are unfamiliar and never used in either city. Therefore, experts need to be aware of and practice urban green models during urban planning to ensure that new developments include green spaces to accommodate the community's and the environment's needs.

Keywords: urban green space, quality, users and experts, green space planning models, Ethiopia

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Authors: Mohamed A. Shanan, Ashraf H. El-Zanaty, Kamal G. Metwally

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This paper presents the effect of concrete compressive strength and rectangularity ratio on strength and ductility of normal and high strength reinforced concrete columns confined with transverse steel under axial compressive loading. Nineteen normal strength concrete rectangular columns with different variables tested in this research were used to study the effect of concrete compressive strength and rectangularity ratio on strength and ductility of columns. The paper also presents a nonlinear finite element analysis for these specimens and another twenty high strength concrete square columns tested by other researchers using ANSYS 15 finite element software. The results indicate that the axial force – axial strain relationship obtained from the analytical model using ANSYS are in good agreement with the experimental data. The comparison shows that the ANSYS is capable of modeling and predicting the actual nonlinear behavior of confined normal and high-strength concrete columns under concentric loading. The maximum applied load and the maximum strain have also been confirmed to be satisfactory. Depending on this agreement between the experimental and analytical results, a parametric numerical study was conducted by ANSYS 15 to clarify and evaluate the effect of each variable on strength and ductility of the columns.

Keywords: ANSYS, concrete compressive strength effect, ductility, rectangularity ratio, strength

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Authors: Lavanya Dharmendran, Shenuka Singh, Sona Baburathanam

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The aim of the study is to understand the level of awareness in a community of a specific region of Kuwait regarding oral cancer and its screening methods so as to enhance the uptake of oral cancer screening methods. This is a cross-sectional study comprising 100 adult participants residing in the governate of Farwaniya, Kuwait. Participants of above 18 years of both genders will be selected using convenience sampling. Data collection includes the administration of a self-administered questionnaire. The questionnaire comprises three sections, each section assessing the knowledge, attitudes and practices of the participants’ opinions about oral cancer and screening methods. Data will be analyzed using Humphris Oral Cancer Knowledge Scale. Inferential statistics will be done using Chi-Square or Fisher’s exact test for categorical data. A level of p<.05 will be established as being significant. All ethical considerations, such as respect for personal confidentiality and informed consent, will be applied in this study. This study revealed that although respondents were aware of the term oral cancer, more than half of the study participants were unaware of the symptoms associated with this condition. Smoking and alcohol were identified as risk factors for oral cancer, but the majority of participants did not identify the Human Papilloma Virus (HPV) as an added risk factor. This suggests a greater need for dental practitioners to include educational strategies in routine dental visits to ensure greater awareness of oral cancer.

Keywords: oral cancer, oral screening, oral public health, oral health

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Authors: Peter Egri, Tamas Kis

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Scheduling problems have been studied by the algorithmic mechanism design research from the beginning. This paper is focusing on a practically important, but theoretically rather neglected field: the project scheduling problem where the jobs connected by precedence constraints compete for various nonrenewable resources, such as materials. Although the centralized problem can be solved in polynomial-time by applying the algorithm of Carlier and Rinnooy Kan from the Eighties, obtaining materials in a decentralized environment is usually far from optimal. It can be observed in practical production scheduling situations that project managers tend to cache the required materials as soon as possible in order to avoid later delays due to material shortages. This greedy practice usually leads both to excess stocks for some projects and materials, and simultaneously, to shortages for others. The aim of this study is to develop a model for the material allocation problem of a production plant, where a central decision maker—the inventory—should assign the resources arriving at different points in time to the jobs. Since the actual due dates are not known by the inventory, the mechanism design approach is applied with the projects as the self-interested agents. The goal of the mechanism is to elicit the required information and allocate the available materials such that it minimizes the maximal tardiness among the projects. It is assumed that except the due dates, the inventory is familiar with every other parameters of the problem. A further requirement is that due to practical considerations monetary transfer is not allowed. Therefore a mechanism without money is sought which excludes some widely applied solutions such as the Vickrey–Clarke–Groves scheme. In this work, a type of Serial Dictatorship Mechanism (SDM) is presented for the studied problem, including a polynomial-time algorithm for computing the material allocation. The resulted mechanism is both truthful and Pareto optimal. Thus the randomization over the possible priority orderings of the projects results in a universally truthful and Pareto optimal randomized mechanism. However, it is shown that in contrast to problems like the many-to-many matching market, not every Pareto optimal solution can be generated with an SDM. In addition, no performance guarantee can be given compared to the optimal solution, therefore this approximation characteristic is investigated with experimental study. All in all, the current work studies a practically relevant scheduling problem and presents a novel truthful material allocation mechanism which eliminates the potential benefit of the greedy behavior that negatively influences the outcome. The resulted allocation is also shown to be Pareto optimal, which is the most widely used criteria describing a necessary condition for a reasonable solution.

Keywords: material allocation, mechanism without money, polynomial-time mechanism, project scheduling

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Authors: Lucas A. Silva, Carla R. Aguiar

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This work presents a proposal to perform contextual sentiment analysis using a supervised learning algorithm and disregarding the extensive training of annotators. To achieve this goal, a web platform was developed to perform the entire procedure outlined in this paper. The main contribution of the pipeline described in this article is to simplify and automate the annotation process through a system of analysis of congruence between the notes. This ensured satisfactory results even without using specialized annotators in the context of the research, avoiding the generation of biased training data for the classifiers. For this, a case study was conducted in a blog of entrepreneurship. The experimental results were consistent with the literature related annotation using formalized process with experts.

Keywords: sentiment analysis, untrained annotators, naive bayes, entrepreneurship, contextualized classifier

Procedia PDF Downloads 383

Authors: Bremmy Laksono, Nurul Qomarilla, Riksa Parikrama, Dyan K. Nugrahaeni, Willyanti Soewondo, Dadang S. H. Effendi, Eriska Rianti, Arlette S. Setiawan, Ine Sasmita, Risti S. Primanti, Erna Kurnikasari, Yunia Sribudiani

Abstract:

Down syndrome is a chromosomal abnormality of chromosome 21 which can appear in man or woman. Maternal age and paternal age, history of radiation are the common risk factors. This study was conducted to observe risk factors which related as causes of Down syndrome. In this case control study using purposive sampling technique, 84 respondents were chosen from Cell Culture and Cytogenetics Laboratory patients in Faculty of Medicine, Universitas Padjadjaran, Indonesia. They were used as study samples and divided into 42 Down syndrome cases and 42 control respondents. This study used univariate and bivariate analysis (chi-square). Samples population were West Java residents, the biggest province in Indonesia in number of population. The results showed maternal age, paternal age, history of radiation exposure and family history were not significantly related to Down syndrome baby. Moreover, all of those factors also did not contribute to the risk of having a child with Down syndrome in patients at Cell Culture and Cytogenetics Laboratory, Faculty of Medicine, Universitas Padjadjaran. Therefore, we should investigate other risk factors of Down syndrome in West Java population.

Keywords: down syndrome, family history, maternal age, paternal age, risk factor

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Authors: A. Benatiallah, D. Benatiallah, F. Abaidi, B. Nasri, A. Harrouz, S. Mansouri

Abstract:

The region of Adrar is located in the south-western Algeria and covers a total area of 443.782 km², occupied by a population of 432,193 inhabitants. The main activity of population is agriculture, mainly based on the date palm cultivation occupies a total area of 23,532 ha. Adrar region climate is a continental desert characterized by a high variation in temperature between months (July, August) it exceeds 48°C and coldest months (December, January) with 16°C. Rainfall is very limited in frequency and volume with an aridity index of 4.6 to 5 which corresponds to a type of arid climate. Geologically Adrar region is located on the edge North West and is characterized by a Precambrian basement cover stolen sedimentary deposit of Phanerozoic age transgressive. The depression is filled by Touat site Paleozoic deposits (Cambrian to Namurian) of a vast sedimentary basin extending secondary age of the Saharan Atlas to the north hamada Tinhirt Tademaït and the plateau of south and Touat Gourara west to Gulf of Gabes in the Northeast. In this work we have study geothermal potential of Adrar region from the borehole data eatable in various sites across the area of 400,000 square kilometres; from these data we developed a GIS (Adrar_GIS) that plots data on the various points and boreholes in the region specifying information on available geothermal potential has variable depths.

Keywords: sig, geothermal, potenteil, temperature

Procedia PDF Downloads 457