Search results for: statistical machine translation

Authors: Toni Maristela C. Estabillo, Michaela V. Matienzo, Mikaela L. Sabangan, Rosette M. Tienzo, Justine L. Bahinting

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This study is about blind watermarking on images with different categories and properties using two algorithms namely, Discrete Wavelet Transform and Patchwork Algorithm. A program is created to perform watermark embedding, extraction and evaluation. The evaluation is based on three watermarking criteria namely: image quality degradation, perceptual transparency and security. Image quality is measured by comparing the original properties with the processed one. Perceptual transparency is measured by a visual inspection on a survey. Security is measured by implementing geometrical and non-geometrical attacks through a pass or fail testing. Values used to measure the following criteria are mostly based on Mean Squared Error (MSE) and Peak Signal to Noise Ratio (PSNR). The results are based on statistical methods used to interpret and collect data such as averaging, z Test and survey. The study concluded that the combined DWT and Patchwork algorithms were less efficient and less capable of watermarking than DWT algorithm only.

Keywords: blind watermarking, discrete wavelet transform algorithm, patchwork algorithm, digital watermark

Procedia PDF Downloads 268

Authors: Gi Ryung Song, Kyoung Seok Kim

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This study reviewed the literature that focused on similarity of various characteristics such as values, personality, or demographics between employee and other elements in its organization for example employee with leader, job, and organization. We divided a body of this study into two parts and organized and demonstrated recent studies in first part. Three issues appeared in this part, which are statistical ways of measuring similarity, supervisor-subordinate similarity, and person-organization fit with person-job fit. In the latter part, based on the three issues of recent studies, we suggested three propositions about points that the recent studies missed or the studies did not orient. First proposition argued about the direction of similarity, which could also be interpreted as there is causal relation between employee and its workplace environments. Second, we suggested a consideration of eliminating common variance buried in one’s characteristics or its profiles. Third proposition was about the similarity of extra role behavior between individual and organization, and we treated this organization’s level of extra role behavior as a kind of its culture. In doing so, similarity of individual’s extra role behavior and organization’s has the meaning that individual’s congruence against their organization culture.

Keywords: similarity, person-organization fit, supervisor-subordinate similarity, literature review

Procedia PDF Downloads 284

Authors: Rusudan Kinkladze, Guguli Kurashvili, Ketevan Chitaladze

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Foreign direct investment is a driving force in the development of the interdependent national economies, and the study and analysis of investments is an urgent problem. It is particularly important for transitional economies, such as Georgia, and the study and analysis of investments is an urgent problem. Consequently, the goal of the research is the study and analysis of direct foreign investments in Georgia, and identification and forecasting of modern trends, and covers the period of 2006-2015. The study uses the methods of statistical observation, grouping and analysis, the methods of analytical indicators of time series, trend identification and the predicted values are calculated, as well as various literary and Internet sources relevant to the research. The findings showed that modern investment policy In Georgia is favorable for domestic as well as foreign investors. Georgia is still a net importer of investments. In 2015, the top 10 investing countries was led by Azerbaijan, United Kingdom and Netherlands, and the largest share of FDIs were allocated in the transport and communication sector; the financial sector was the second, followed by the health and social work sector, and the same trend will continue in the future. 

Keywords: foreign direct investments, methods, statistics, analysis

Procedia PDF Downloads 331

Authors: Ntaganda J.M., Maniraguha J.D., Mukeshimana S., Harelimana D, Bizimungu T., Ruataganda E.

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This paper presents the design of Graphic User Interface (GUI) in Matlab as interaction tool between human and machine. The designed GUI can be used by medical doctors and other experts particularly the physiologists. Matlab packages and estimated parameters of the mathematical model of cardiovascular-respiratory system developed in Rwandan context are used in GUI. The ordinary differential equations (ODE’s) govern a mathematical model in designing GUI in Matlab and a window that sets model estimated parameters and the measured parameters by any user. For healthy subject, these measured parameters include heart rate, systolic blood and diastolic blood pressure, partial pressure of oxygen in arterial blood, partial pressure of carbon dioxide in arterial blood, concentration of bound and dissolved oxygen in the mixed venous blood entering the lungs, and concentration of bound and dissolved carbon dioxide in the mixed venous blood entering the lungs. The results of numerical test give a consistent appearance as empirically known results.

Keywords: Graphic User Interface, mathematical model, cardiovascur-respiratory system, walking physical activity, blood pressure, oxygen

Procedia PDF Downloads 118

Authors: Adrian-Gabriel Chifu, Sebastien Fournier

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One of the challenges of natural language understanding is to deal with the subjectivity of sentences, which may express opinions and emotions that add layers of complexity and nuance. Sentiment analysis is a field that aims to extract and analyze these subjective elements from text, and it can be applied at different levels of granularity, such as document, paragraph, sentence, or aspect. Aspect-based sentiment analysis is a well-studied topic with many available data sets and models. However, there is no clear definition of what makes a sentence difficult for aspect-based sentiment analysis. In this paper, we explore this question by conducting an experiment with three data sets: ”Laptops”, ”Restaurants”, and ”MTSC” (Multi-Target-dependent Sentiment Classification), and a merged version of these three datasets. We study the impact of domain diversity and syntactic diversity on difficulty. We use a combination of classifiers to identify the most difficult sentences and analyze their characteristics. We employ two ways of defining sentence difficulty. The first one is binary and labels a sentence as difficult if the classifiers fail to correctly predict the sentiment polarity. The second one is a six-level scale based on how many of the top five best-performing classifiers can correctly predict the sentiment polarity. We also define 9 linguistic features that, combined, aim at estimating the difficulty at sentence level.

Keywords: sentiment analysis, difficulty, classification, machine learning

Procedia PDF Downloads 89

Authors: Herjuno Bagus Wicaksono, Emma Almira Fauni, Salma Amelia Dina

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The Efficient Market Hypothesis (EMH) states that, in an efficient capital market, price fully reflects the information available in the market. This theory has influenced many investors behavior in trading in the stock market. Advanced researches have been conducted to test the efficiency of the stock market in particular countries. Indonesia, as one of the emerging countries, has performed substantial growth in the past years. Hence, this paper aims to examine the efficiency of Islamic stock market in Indonesia in its weak form. The daily stock price data from Indonesia Sharia Stock Index (ISSI) for the period October 2015 to October 2016 were used to do the statistical tests: Run Test and Serial Correlation Test. The results show that there is no serial correlation between the current price with the past prices and the market follows the random walk. This research concludes that Indonesia Islamic stock market is weak form efficient.

Keywords: efficient market hypothesis, Indonesia sharia stock index, random walk, weak form efficiency

Procedia PDF Downloads 460

Authors: Nino Grigolaia

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Introduction: The article discusses the experience of the EU in the social field, analyzes the peculiarities of the functioning of the social system in Georgia, and reveals the priority and importance of social policy. Methodology: Different research methods are applied in the presented paper. There are used induction, deduction, analysis, synthesis, analogy, correlation, and statistical observation methodologies in the work. Main Findings: Based on the analysis of social security reforms in Georgia, the main systematic problems are detected, the recommendations on social security system components, integration of the social security field in the unified insurance system, the formation of the national social system, perfection of the legislative, regulatory framework of social protection, adoption of foreign experience are developed in the article. Conclusion: The article concludes that the social protection system in Georgia is at an early stage of development, with the significant impact of factors such as high level of unemployment, low pensions, a large number of families living under the poverty line, and other ones. Accordingly, it is well-established that the study of the social security problem in Georgia is still actual. Based on the analysis, appropriate suggestions in the field of social security are made, and relevant recommendations are proposed.

Keywords: social security, social system, social policy, social security models

Procedia PDF Downloads 147

Authors: Byung Ho Jung, Dong Hoon Lim

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Logistic regression is a statistical method for analyzing a dataset in which there are one or more independent variables that determine an outcome. Logistic regression is used extensively in numerous disciplines, including the medical and social science fields. In this paper, we address the problem of estimating parameters in the logistic regression based on MapReduce framework with RHadoop that integrates R and Hadoop environment applicable to large scale data. There exist three learning algorithms for logistic regression, namely Gradient descent method, Cost minimization method and Newton-Rhapson's method. The Newton-Rhapson's method does not require a learning rate, while gradient descent and cost minimization methods need to manually pick a learning rate. The experimental results demonstrated that our learning algorithms using RHadoop can scale well and efficiently process large data sets on commodity hardware. We also compared the performance of our Newton-Rhapson's method with gradient descent and cost minimization methods. The results showed that our newton's method appeared to be the most robust to all data tested.

Keywords: big data, logistic regression, MapReduce, RHadoop

Procedia PDF Downloads 285

Authors: Gihan Mosaad, Bakr Gomaa, Rana Elbadri

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Modern parts of Alexandria city lack in vibrancy, causing a number of problems such as urban areas with poor security measures as well as weak economic state. Vibrancy provides a livable, attractive and secure environments; it also boosts the city’s economy and social life. Vibrant city is a city full of energy and life. To achieve this, a number of resources are needed; namely specific urban density, the availability of alternative modes of transportation and finally diversity of land-uses. Literature review shows no comprehensive study that assesses vibrancy in the streets of modern Alexandria. This study aims to measure the vibrancy potential in Sidi-Gaber station area thought the assessment of existing resources performance. Methods include literature reviews, surveying of existing case, questionnaire as well as GIS techniques. Expected results include GIS maps defining the vibrancy potentials in land use, density and statistical study regarding public transportation use in the area.

Keywords: Alexandria, density, mixed use, transportation, vibrancy

Procedia PDF Downloads 294

Authors: Simon Ayorinde Okanlawon

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This study examines residents’ assessment of with infrastructural facilities in the urban fringe of Ibadan, Nigeria. Random sampling technique was used in selecting four Local Government Areas out of the six suburban LGAs of the city. Google earth and ground trotting were used in capturing and selecting seven hundred and forty-two new houses. The questionnaires administered on house owners were harvested on the spot. The information collected includes socio-economic and demographic characteristics of residents as well as characteristics of infrastructural facilities. The study utilised both descriptive and inferential statistical analyses; Facility Availability Index (FAI) Facility Functionality Index (FFI) and Residents’ Satisfactions Index (RSI) were used to compare respectively residents’ perceived levels of availability of, the functionality of, and satisfaction with facilities across Local Government Areas. The study shows that levels of both availability of, and satisfaction with infrastructural facilities are low with respective overall FAI (0.8) and RSI (0.05), while the functionality of the facilities is generally very poor IFFI = - 0.58). Strategies were proposed to enhance the good, livable, and healthy environment.

Keywords: infrastructural facilities, infrastructural perception index, residents’ satisfaction, urban fringe of Ibadan

Procedia PDF Downloads 223

Authors: Sepehr Moradi, Mehdi Asadi Rad

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The aim of this study is to evaluate and compare carcass weight of pure and mixed races Namebar 30-day pigeons to investigate about their sex, race, and some auxiliary variables. In this paper, 68 pieces of pigeons as 34 male and female pairs with equal age are studied randomly. A natural incubation was done from each pair. All produced chickens were slaughtered at 30 days age after 12 hours hunger. Then their carcasses were weighted by a scale with one gram precision. A covariance analysis was used since there were many auxiliary variables and unequal observations. SAS software was used for statistical analysis. Mean weight of carcass in pure race (Namebar-Namebar) with 8 records, 219.5±61.3 gr and mixed races of Kabood-Namebar, Parvazy-Namebar, Tizpar-Namebar, Namebar-Kabood, Namebar-Tizpar, and Namebar-Parvazy with 8, 10, 8, 12, 12, and 10 records were 369.9±54.6, 338.3±52.7, 224.5±73.6, 142.3±67.8, 155.6±56.2, and 170.2±55 gr, respectively.. Difference carcass weight of 30-day of Namebar-Namebar race with Namebar-Kabood, Namebar-Parvazy, Namebar-Tizpar, Parvazy-Namebar and Tizpar-Namebar mixed races was not significant, and was significant in level 5% with Kabood- Namebar (P < 0.05). Effect of sex and age were also significant in 1% level (P < 0.01), but mutual effect of sex and race was not significant. The results showed that most and least weights of carcass belonged to Kabood-Namebar and Namebar-Kabood.

Keywords: squab, Namebar race, 30-day carcass weight, pigeons

Procedia PDF Downloads 180

Authors: Masaumi Nakahara, Sou Watanabe, Hiromichi Ogi, Atsuhiro Shibata, Kazunori Nomura

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In the Japan Atomic Energy Agency, three types of experimental research, advanced reactor fuel reprocessing, radioactive waste disposal, and nuclear fuel cycle technology, have been carried out at the Chemical Processing Facility. The facility has generated high level radioactive liquid and solid wastes in hot cells. The high level radioactive solid waste is divided into three main categories, a flammable waste, a non-flammable waste, and a solid reagent waste. A plastic product is categorized into the flammable waste and molten with a heating mantle. The non-flammable waste is cut with a band saw machine for reducing the volume. Among the solid reagent waste, a used adsorbent after the experiments is heated, and an extractant is decomposed for its stabilization. All high level radioactive solid wastes in the hot cells are packed in a high level radioactive solid waste can. The high level radioactive solid waste can is transported to the 2nd High Active Solid Waste Storage in the Tokai Reprocessing Plant in the Japan Atomic Energy Agency.

Keywords: high level radioactive solid waste, advanced reactor fuel reprocessing, radioactive waste disposal, nuclear fuel cycle technology

Procedia PDF Downloads 159

Authors: Onuchukwu Chika Christian, Chukwude Augustine Ejike

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We carried out a statistical analyse of microglitches events on a sample of radio pulsars. The distribution of microglitch events in frequency (ν) and first frequency derivatives ν˙ indicates that the size of a microglitch and sign combinations of events in ν and ν˙ are purely randomized. Assuming that the probability of a given size of a microglitch event occurring scales inversely as the absolute size of the event in both ν and ν˙, we constructed a cumulative distribution function (CDF) for the absolute sizes of microglitches. In most of the pulsars, the theoretical CDF matched the observed values. This is an indication that microglitches in pulsar may be interpreted as an avalanche process in which angular momentum is transferred erratically from the flywheel-like superfliud interior to the slowly decelerating solid crust. Analysis of the waiting time indicates that it is purely Poisson distributed with mean microglitch rate <γ> ∼ 0.98year^−1 for all the pulsars in our sample and <γ> / <∆T> ∼ 1. Correlation analysis, showed that the relative absolute size of microglitch event strongly with the rotation period of the pulsar with correlation coefficient r ∼ 0.7 and r ∼ 0.5 respectively for events in ν and ν˙. The mean glitch rate and number of microglitches (Ng) showed some dependence on spin down rate (r ∼ −0.6) and the characteristic age of the pulsar (τ) with (r ∼ −0.4/− 0.5).

Keywords: method-data analysis, star, neutron-pulsar, general

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Authors: Wafaa Salah, Mostafa A. Salama, Jane Doe

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Recently, the corporate social performance (CSP) is not less important than the corporate financial performance (CFP). Debate still exists about the nature of the relationship between the CSP and CFP, whether it is a positive, negative or a neutral correlation. The objective of this study is to explore the relationship between corporate social responsibility (CSR) reports and CFP. The study uses the accounting-based and market-based quantitative measures to quantify the financial performance of seven organizations listed on the Egyptian Stock Exchange in 2007-2014. Then uses the information retrieval technologies to quantify the contribution of each of the three dimensions of the corporate social responsibility report (environmental, social and economic). Finally, the correlation between these two sets of variables is viewed together in a model to detect the correlations between them. This model is applied on seven firms that generate social responsibility reports. The results show a positive correlation between the Earnings per share (market based measure) and the economical dimension in the CSR report. On the other hand, total assets and property, plant and equipment (accounting-based measure) are positively correlated to the environmental and social dimensions of the CSR reports. While there is not any significant relationship between ROA, ROE, Operating income and corporate social responsibility. This study contributes to the literature by providing more clarification of the relationship between CFP and the isolated CSR activities in a developing country.

Keywords: financial, social, machine learning, corporate social performance, corporate social responsibility

Procedia PDF Downloads 311

Authors: Rafi Ullah, Shah Muhammad Emaduddin, Taha Jilani

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Vehicle Adhoc Networks (VANET) belongs to a special class of Mobile Adhoc Network (MANET) with high mobility. Network is created by road side vehicles equipped with communication devices like GPS and Wifi etc. Since the environment is highly dynamic due to difference in speed and high mobility of vehicles and weak stability of the network connection, it is a challenging task to design an efficient routing protocol for such an unstable environment. Our proposed algorithm uses heuristic for the calculation of optimal path for routing the packet efficiently in collaboration with several other parameters like geographical location, speed, priority, the distance among the vehicles, communication range, and networks congestion. We have incorporated probabilistic, heuristic and machine learning based approach inconsistency with the relay function of the memory buffer to keep the packet moving towards the destination. These parameters when used in collaboration provide us a very strong and admissible heuristics. We have mathematically proved that the proposed technique is efficient for the routing of packets, especially in a medical emergency situation. These networks can be used for medical emergency, security, entertainment and routing purposes.

Keywords: heuristics routing, intelligent routing, VANET, route optimization

Procedia PDF Downloads 178

Authors: M. D. Saeed, S. O. Oladeji

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The level of cobalt was determined in wastewater and vegetable (carrot, lettuce, onion, spinach, cabbage, tomato and okro) samples collected on seasonal basis from December, 2012 to September 2014 along Kubanni stream channels in Zaria. The results showed cobalt concentrations in wastewater were in the range of 3.77 – 15.20 mg/L for the year 2013 and 4.74 – 15.20 mg/L in 2014 while the vegetable had concentrations in the range of 1.25 – 8.75 mg/Kg for the year 2013 and 2.76 – 12.45 mg/Kg in 2014. Statistical analysis revealed a significant difference in cobalt levels across the locations for wastewater and vegetables whereas seasons (harmattan, dry and rainy) showed no significant difference in wastewater and vegetables analyzed. Pearson correlation revealed substantial (r = 0.726) relationship between cobalt levels in wastewater for the year 2013 and 2014 likewise, substantial (r = 0.750) relationship was also obtained for vegetables cultivated in 2013 and 2014 respectively. Cobalt concentrations obtained in this study was higher than Maximum Contaminant Levels set by Standard Organization such as W.H.O. and F.A.O. for wastewater; however, vegetables indicated no contamination with cobalt metal.

Keywords: cobalt, concentration, wastewater, vegetable

Procedia PDF Downloads 374

Authors: Vimala Rani P, Narasimha Malikarjunan, Mercy Shalinie S

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Data Networking was brought forth as an instantiation of information-centric networking. The attackers can send a colossal number of spoofs to take hold of the Pending Interest Table (PIT) named an Interest Flooding attack (IFA) since the in- interests are recorded in the PITs of the intermediate routers until they receive corresponding Data Packets are go beyond the time limit. These attacks can be detrimental to network performance. PIT expiration rate or the Interest satisfaction rate, which cannot differentiate the IFA from attacks, is the criterion Traditional IFA detection techniques are concerned with. Threshold values can casually affect Threshold-based traditional methods. This article proposes an accurate IFA detection mechanism based on a Multiple Feature-based Extreme Learning Machine (MF-ELM). Accuracy of the attack detection can be increased by presenting the entropy of Internet names, Interest satisfaction rate and PIT usage as features extracted in the MF-ELM classifier. Furthermore, we deploy a queue-based hostile Interest prefix mitigation mechanism. The inference of this real-time test bed is that the mechanism can help the network to resist IFA with higher accuracy and efficiency.

Keywords: information-centric network, pending interest table, interest flooding attack, MF-ELM classifier, queue-based mitigation strategy

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Authors: Bedilu A. Ejigu, Eshetu Wencheko, Kiros Berhane

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Anaemia is a condition in which the haemoglobin concentration falls below an established cut-off value due to a decrease in the number and size of red blood cells. The current study aimed to assess the spatial pattern and identify predictors related to anaemia using the third Ethiopian demographic health survey which was conducted in 2010. To achieve this objective, this study took into account the clustered nature of the data. As a result, multilevel modeling has been used in the statistical analysis. For analysis purpose, only complete cases from 15,909 females, and 13,903 males were considered. Among all subjects who agreed for haemoglobin test, 5.49 %males, and 19.86% females were anaemic. In both binary and ordinal outcome modeling approaches, educational level, age, wealth index, BMI and HIV status were identified to be significant predictors for anaemia prevalence. Furthermore, it was noted that pregnant women were more anaemic than non-pregnant women. As revealed by Moran's I test, significant spatial autocorrelation was noted across clusters. The risk of anaemia was found to vary across different regions, and higher prevalence was observed in Somali and Affar region.

Keywords: anaemia, Moran's I test, multilevel models, spatial pattern

Procedia PDF Downloads 425

Authors: Abdollah Aliesmaeili

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The purpose of this research is to present a different perspective on the basic math teaching method called meta-instruction, which reverses the learning path. Meta-instruction is a method of teaching in which the teaching trajectory starts from brain education into learning. This research focuses on the behavior of the mind during learning. In this method, students are not instructed in mathematics, but they are educated. Another goal of the research is to "criticize Bloom's classification in the cognitive domain and reverse it", because it cannot meet the educational and instructional needs of the new generation and "substituting math education instead of math teaching". This is an indirect method of teaching. The method of research is longitudinal through four years. Statistical samples included students ages 6 to 11. The research focuses on improving the mental abilities of children to explore mathematical rules and operations by playing only with eight measurements (any years 2 examinations). The results showed that there is a significant difference between groups in remembering, understanding, and applying. Moreover, educating math is more effective than instructing in overall learning abilities.

Keywords: applying, Bloom's taxonomy, brain education, mathematics teaching method, meta-instruction, remembering, starmath method, understanding

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Authors: Zhengkun Guo, Yanbin Li, Wenqing Wang, Bo Zou

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The statically fused converted position and doppler measurements Kalman filter (SF-CMKF) with additive debiased measurement conversion has been previously presented to combine the resulting states of converted position measurements Kalman filter (CPMKF) and converted doppler measurement Kalman filter (CDMKF) to yield the final state estimates under minimum mean squared error (MMSE) criterion. However, the exact compensation for the bias in the polar-to-cartesian and spherical-to-cartesian conversion are multiplicative and depend on the statistics of the cosine of the angle measurement errors. As a result, the consistency and performance of the SF-CMKF may be suboptimal in large-angle error situations. In this paper, the multiplicative unbiased position and Doppler measurement conversion for 2D (polar-to-cartesian) tracking are derived, and the SF-CMKF is improved to use those conversions. Monte Carlo simulations are presented to demonstrate the statistical consistency of the multiplicative unbiased conversion and the superior performance of the modified SF-CMKF (SF-UCMKF).

Keywords: measurement conversion, Doppler, Kalman filter, estimation, tracking

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Authors: Karim Kootahi, Seyed Abolhasan Naeini

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The soil-water characteristic curve (SWCC), which represents the relationship between suction and water content (or degree of saturation), is an important property of unsaturated soils. The conventional method for determining SWCC is through specialized testing procedures. Since these procedures require specialized unsaturated soil testing apparatus and lengthy testing programs, several index properties-based correlations have been developed for estimating the SWCC of fine-grained soils. There are, however, considerable inconsistencies among the published correlations and there is no validation study on the predictive ability of existing correlations. In the present study, all existing index properties-based correlations are evaluated using a high quality worldwide database. The performances of existing correlations are assessed both graphically and quantitatively using statistical measures. The results of the validation indicate that most of the existing correlations provide unacceptable estimates of degree of saturation but the most recent model appears to be promising.

Keywords: SWCC, correlations, index properties, validation

Procedia PDF Downloads 177

Authors: Medya Fathi

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When public transportation projects were delivered through design-bid-build and later design-build, governments found a serious issue: inadequate funding. With population growth, governments began to develop new arrangements in which the private sectors were involved to cut the financial burden. This arrangement, known as Public-Private Partnership (PPP), has its own risks; however, performance outputs can motivate or discourage its use. On top of such output's list are time and budget, which can be affected by the type of project delivery methods. Project completion within or ahead of schedule as well as within or under budget is among any owner’s objectives. With a higher application of PPP in the highway industry in the US and insufficient PPP research, the current study addresses the schedule and cost performance of PPP highway projects and determines which one outperforms the other. To meet this objective, after collecting performance data of all PPP projects, schedule growth and cost growth are calculated, and finally, statistical analysis is conducted to evaluate the PPP performance. The results and conclusions will be provided. This study can assist practitioners in applying PPP for transportation projects by showing its ability to save time and/or cost.

Keywords: cost, delivery method, highway, public-private partnership, schedule, transportation

Procedia PDF Downloads 176

Authors: Avinash Thakur, Parmjit S. Panesar, Manohar Singh

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The distribution coefficient, KD for the reactive extraction of lactic acid from aqueous solutions of lactic acid using 10-30% (v/v) tri-n-octyl amine (extractant) dissolved in n-hexane (inert diluent) and 20% (v/v) oleyl alcohol (modifier) was optimized by using response surface methodology (RSM). A three level Box-Behnken design was employed for experimental design, analysis of the results and to depict the combined interactive effect of seven independent variables, viz lactic acid concentration (cl), pH, TOA concentration in organic phase (ψ), treat ratio (φ), temperature (T), agitation speed (ω) and batch agitation time (τ) on distribution coefficient of lactic acid. The regression analysis recommended that the quadratic model is significant (R2 and adjusted R2 are 98.72 % and 98.69 % respectively) for analysis. A numerical optimization had resulted in maximum lactic acid distribution coefficient (KD) of 3.16 at the optimized values for test variables, cl, pH, ψ, φ, T, ω and τ as 0.15 [M], 3.0, 22.75% (v/v), 1.0 (v/v), 26°C, 145 rpm and 23 min respectively. A good agreement between the predicted and experimentally obtained values for distribution coefficient using the optimized conditions was exhibited.

Keywords: Distribution coefficient, tri-n-octylamine, lactic acid, response surface methodology

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Authors: Allmin Susaiyah, Aki Härmä, Milan Petković

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Automatic generation of insights from data using insight mining systems (IMS) is useful in many applications, such as personal health tracking, patient monitoring, and business process management. Existing IMS face challenges in controlling insight extraction, scaling to large databases, and generalising to unseen domains. In this work, we propose a hybrid approach consisting of rule-based and neural components for generating insights from data while overcoming the aforementioned challenges. Firstly, a rule-based data 2CNL component is used to extract statistically significant insights from data and represent them in a controlled natural language (CNL). Secondly, a BERTSum-based CNL2NL component is used to convert these CNLs into natural language texts. We improve the model using task-specific and domain-specific fine-tuning. Our approach has been evaluated using statistical techniques and standard evaluation metrics. We overcame the aforementioned challenges and observed significant improvement with domain-specific fine-tuning.

Keywords: data mining, insight mining, natural language generation, pre-trained language models

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Authors: Taylor Kolody, Farkhund Iqbal, Rabia Batool, Benjamin Fung, Mohammed Hussaeni, Saiqa Aleem

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The rising threat of climate change has led to an increase in public awareness and care about our collective and individual environmental impact. A key component of this impact is our use of cars and other polluting forms of transportation, but it is often difficult for an individual to know how severe this impact is. While there are applications that offer this feedback, they require manual entry of what transportation mode was used for a given trip, which can be burdensome. In order to alleviate this shortcoming, a data from the 2016 TRIPlab datasets has been used to train a variety of machine learning models to automatically recognize the mode of transportation. The accuracy of 89.6% is achieved using single deep neural network model with Gated Recurrent Unit (GRU) architecture applied directly to trip data points over 4 primary classes, namely walking, public transit, car, and bike. These results are comparable in accuracy to results achieved by others using ensemble methods and require far less computation when classifying new trips. The lack of trip context data, e.g., bus routes, bike paths, etc., and the need for only a single set of weights make this an appropriate methodology for applications hoping to reach a broad demographic and have responsive feedback.

Keywords: classification, gated recurrent unit, recurrent neural network, transportation

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Authors: Samson Henry Dogo, Allan Clark, Elena Kulinskaya

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The objective in meta-analysis is to combine results from several independent studies in order to create generalization and provide evidence based for decision making. But recent studies show that the magnitude of effect size estimates reported in many areas of research finding changed with year publication and this can impair the results and conclusions of meta-analysis. A number of sequential methods have been proposed for monitoring the effect size estimates in meta-analysis. However they are based on statistical theory applicable to fixed effect model (FEM). For random-effects model (REM), the analysis incorporates the heterogeneity variance, tau-squared and its estimation create complications. In this paper proposed the use of Gombay and Serbian (2005) truncated CUSUM-type test with asymptotically valid critical values for sequential monitoring of REM. Simulation results show that the test does not control the Type I error well, and is not recommended. Further work required to derive an appropriate test in this important area of application.

Keywords: meta-analysis, random-effects model, sequential test, temporal changes in effect sizes

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Authors: Andreia Guimaraes Farnese, Mateus Fernandes Reu Urban, Leandro Procopio, Renato Zangaro, Regiane Albertini

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Senescence changes include postural balance, inferring the risk of falls, and can lead to fractures, bedridden, and the risk of death. Physical activity, e.g., cardiovascular exercises, is notable for improving balance due to brain cell stimulations, but fine coordination exercises also elevate cell brain metabolism. This study aimed to verify whether the elderly person who performs fine motor activity has a balance similar to that of those who practice physical activity. The subjects were divided into three groups according to the activity practice: control group (CG) with seven participants for the sedentary individuals, motor coordination group (MCG) with six participants, and activity practitioner group (PAG) with eight participants. Data comparisons were from the Berg balance scale, Time up and Go test, and stabilometric analysis. Descriptive statistical and ANOVA analyses were performed for data analysis. The results reveal that including fine motor activities can improve the balance of the elderly and indirectly decrease the risk of falls.

Keywords: balance, barapodometer, coordination, elderly

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Authors: Tulio Sulbaran, Sandeep Langar

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Architects are an integral part of the construction industry and are continuously incorporating decisions that influence projects during their life cycle. These decisions aim at selecting best alternative from the ones available. Unfortunately, this decision making process is mainly unexplored in the construction industry. No instrument to measure construction decision, based on knowledgebase of decision-makers, has existed. Additionally, limited literature is available on the topic. Recently, an instrument to gain an understanding of the construction decision-making process was developed by Dr. Tulio Sulbaran from the University of Texas, San Antonio. The instrument’s name is 'Construction Decision Making Inventory (CDMI)'. The CDMI is an innovative idea to measure the 'What? When? How? Moreover, Who?' of the construction decision-making process. As an innovative idea, its statistical validity (accuracy of the assessment) is yet to be assessed. Thus, the purpose of this paper is to describe the results of a case study with architects in the south-east of the United States aimed to determine the CDMI validity. The results of the case study are important because they assess the validity of the tool. Furthermore, as the architects evaluated each question within the measurements, this study is also guiding the enhancement of the CDMI.

Keywords: decision, support, inventory, architect

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Authors: Zhou Xiong, Kang Shao Bo, Yang Bo

Abstract:

To date, high-performance structural steel has been widely used for columns in construction practices due to its significant advantages over conventional steel. However, the same design approach with conventional steel columns is still adopted in the design of high-performance steel columns. As a result, its superior properties cannot be fully considered in design. This paper conducts a test and finite element analysis on the overall stability behaviour of welded Q460GJ steel box columns. In the test, four steel columns with different slenderness and width-to-thickness ratio were compressed under an axial compression testing machine. And finite element models were established in which material nonlinearity and residual stress distributions of test columns were included. Then, comparisons were made between test results and finite element result, it showed that finite element analysis results are agree well with the test result. It means that the test and finite element model are reliable. Then, we compared the test result with the design value calculated by current code, the result showed that Q460GJ steel box columns have the higher overall buckling capacity than the design value. It is necessary to update the design curves for Q460GJ steel columns so that the overall stability capacity of Q460GJ box columns can be designed appropriately.

Keywords: axial compression, box columns, global buckling, numerical simulations, Q460GJ steel

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Authors: Yeliz Mert Kantar, İsmail Yeni̇lmez, Ibrahim Arik

Abstract:

In this study, the efficiency measurement of the top fifty Turkish Universities has been conducted. The top fifty Turkish Universities are listed by The Scientific and Technological Research Council of Turkey (TÜBITAK) according to the Entrepreneur and Innovative University Index every year. The index is calculated based on four components since 2018. Four components are scientific and technological research competency, intellectual property pool, cooperation and interaction, and economic and social contribution. The four components consist of twenty-three sub-components. The 2021 list announced in January 2022 is discussed in this study. Efficiency analysis have been carried out using the Stochastic Frontier Model. Statistical significance of the sub-components that make up the index with certain weights has been examined in terms of the efficiency measurement calculated through the Stochastic Frontier Model. The relationship between the efficiency ranking estimated based on the Stochastic Frontier Model and the Entrepreneur and Innovative University Index ranking is discussed in detail.

Keywords: efficiency, entrepreneur and innovative universities, turkish universities, stochastic frontier model, tübi̇tak

Procedia PDF Downloads 89