Search results for: conflicting claim on credit of discovery of ridge regression

Authors: Joseph Gear, Yue Xu, Ernest Foo, Praveen Gauravaran, Zahra Jadidi, Leonie Simpson

Abstract:

Deep learning methods have been seeing an increasing application to the long-standing security research goal of automatic vulnerability detection for source code. Attention, however, must still be paid to the task of producing vector representations for source code (code embeddings) as input for these deep learning models. Graphical representations of code, most predominantly Abstract Syntax Trees and Code Property Graphs, have received some use in this task of late; however, for very large graphs representing very large code snip- pets, learning becomes prohibitively computationally expensive. This expense may be reduced by intelligently pruning this input to only vulnerability-relevant information; however, little research in this area has been performed. Additionally, most existing work comprehends code based solely on the structure of the graph at the expense of the information contained by the node in the graph. This paper proposes Semantic-enhanced Code Embedding for Vulnerability Discovery (SCEVD), a deep learning model which uses semantic-based feature selection for its vulnerability classification model. It uses information from the nodes as well as the structure of the code graph in order to select features which are most indicative of the presence or absence of vulnerabilities. This model is implemented and experimentally tested using the SARD Juliet vulnerability test suite to determine its efficacy. It is able to improve on existing code graph feature selection methods, as demonstrated by its improved ability to discover vulnerabilities.

Keywords: code representation, deep learning, source code semantics, vulnerability discovery

Procedia PDF Downloads 131

Authors: Olivier Mesly

Abstract:

This article examines the likelihood of deception on the part of borrowers wishing to obtain credit from institutional or private lenders. In our first study, we identify five explanatory variables that account for nearly forty percent of the propensity to act deceitfully: a poor credit history, debt, risky behavior, and to a much lesser degree, irrational behavior and disconnection from the bundle of needs, goals, and preferences. For the second study, we remodeled the initial questionnaire to adapt it to the needs of institutional bankers and borrowers, especially those that engage in money on-line peer-to-peer lending, a growing business fueled by the COVID pandemic. We find that the three key psychological variables that help to indirectly predict the likelihood of deceitful behaviors and possible default on loan reimbursement, i.e., risky behaviors, ir-rationality, and dis-connection, interact with each other to form a loop. This study presents two benefits: first, we provide evidence that it is to some degree possible to tighten control over lending practices. Second, we offer a pragmatic tool: a questionnaire, that lenders can use or adapt to gauge potential borrowers’ deceit, notably by combining their results with standard hard-data measures of risk.

Keywords: bundle of needs, default, debt, deception, risk, peer-to-peer lending

Procedia PDF Downloads 109

Authors: Tahani Salman Alangari

Abstract:

Student success can be impacted by internal factors such as their emotional well-being and external factors such as organizational support and instructional support in the classroom. This study is to identify at least one factor that forecasts student engagement. It is a cross-sectional, conducted on 6206 teachers and encompassed three years of data collection and observations of math instruction in approximately 50 schools and 300 classrooms. A multiple linear regression revealed that a model predicting student engagement from emotional support, classroom organization, and instructional support was significant. Four linear regression models were tested using hierarchical regression to examine the effects of independent variables: emotional support was the highest predictor of student engagement while instructional support was the lowest.

Keywords: student engagement, emotional support, organizational support, instructional support, well-being

Procedia PDF Downloads 55

Authors: Seydou Sinde

Abstract:

The aims of this paper are to formulate mathematical expressions that can be used to estimate the standpipe pressure (SPP). The developed formulas take into account the main factors that, directly or indirectly, affect the behavior of SPP values. Fluid rheology and well hydraulics are some of these essential factors. Mud Plastic viscosity, yield point, flow power, consistency index, flow rate, drillstring, and annular geometries are represented by the frictional pressure (Pf), which is one of the input independent parameters and is calculated, in this paper, using Herschel-Bulkley rheological model. Other input independent parameters include the rate of penetration (ROP), applied load or weight on the bit (WOB), bit revolutions per minute (RPM), bit torque (TRQ), and hole inclination and direction coupled in the hole curvature or dogleg (DL). The technique of repeating parameters and Buckingham PI theorem are used to reduce the number of the input independent parameters into the dimensionless revolutions per minute (RPMd), the dimensionless torque (TRQd), and the dogleg, which is already in the dimensionless form of radians. Multivariable linear and polynomial regression technique using PTC Mathcad Prime 4.0 is used to analyze and determine the exact relationships between the dependent parameter, which is SPP, and the remaining three dimensionless groups. Three models proved sufficiently satisfactory to estimate the standpipe pressure: multivariable linear regression model 1 containing three regression coefficients for vertical wells; multivariable linear regression model 2 containing four regression coefficients for deviated wells; and multivariable polynomial quadratic regression model containing six regression coefficients for both vertical and deviated wells. Although that the linear regression model 2 (with four coefficients) is relatively more complex and contains an additional term over the linear regression model 1 (with three coefficients), the former did not really add significant improvements to the later except for some minor values. Thus, the effect of the hole curvature or dogleg is insignificant and can be omitted from the input independent parameters without significant losses of accuracy. The polynomial quadratic regression model is considered the most accurate model due to its relatively higher accuracy for most of the cases. Data of nine wells from the Middle East were used to run the developed models with satisfactory results provided by all of them, even if the multivariable polynomial quadratic regression model gave the best and most accurate results. Development of these models is useful not only to monitor and predict, with accuracy, the values of SPP but also to early control and check for the integrity of the well hydraulics as well as to take the corrective actions should any unexpected problems appear, such as pipe washouts, jet plugging, excessive mud losses, fluid gains, kicks, etc.

Keywords: standpipe, pressure, hydraulics, nondimensionalization, parameters, regression

Procedia PDF Downloads 61

Authors: Hyon I. Paek, Sang Rim Kim, Hyon A. Ryu

Abstract:

In functional linear regression, one typical problem is to reduce dimension. Compared with multivariate linear regression, functional linear regression is regarded as an infinite-dimensional case, and the main task is to reduce dimensions of functional response and functional predictors. One common approach is to adapt functional principal component analysis (FPCA) on functional predictors and then use a few leading functional principal components (FPC) to predict the functional model. The leading FPCs estimated by the typical FPCA explain a major variation of the functional predictor, but these leading FPCs may not be mostly correlated with the functional response, so they may not be significant in the prediction for response. In this paper, we propose a supervised functional principal component analysis method for a functional response model with FPCs obtained by considering the correlation of the functional response. Our method would have a better prediction accuracy than the typical FPCA method.

Keywords: supervised, functional principal component analysis, functional response, functional linear regression

Procedia PDF Downloads 42

Authors: Fatima Z. Cherhabil, Mammar Sedrati, Sonia-Sabrina Bendib‎

Abstract:

In order to support the continued growth, critical latency of ‎IoT ‎applications, and ‎various obstacles of traditional data centers, ‎mobile edge ‎computing (MEC) has ‎emerged as a promising solution that extends cloud data-processing and decision-making to edge devices. ‎By adopting a MEC structure, IoT applications could be executed ‎locally, on ‎an edge server, different fog nodes, or distant cloud ‎data centers. However, we are ‎often ‎faced with wanting to optimize conflicting criteria such as ‎minimizing energy ‎consumption of limited local capabilities (in terms of CPU, RAM, storage, bandwidth) of mobile edge ‎devices and trying to ‎keep ‎high performance (reducing ‎response time, increasing throughput and service availability) ‎at the same ‎time‎. Achieving one goal may affect the other, making task offloading (TO), ‎resource allocation (RA), and service placement (SP) complex ‎processes. ‎It is a nontrivial multi-objective optimization ‎problem ‎to study the trade-off between conflicting criteria. ‎The paper provides a survey on different TO, SP, and RA recent multi-‎objective optimization (MOO) approaches used in edge computing environments, particularly artificial intelligent (AI) ones, to satisfy various objectives, constraints, and dynamic conditions related to IoT applications‎.

Keywords: mobile edge computing, multi-objective optimization, artificial ‎intelligence ‎approaches, task offloading, resource allocation, ‎ service placement

Procedia PDF Downloads 86

Authors: Irfan Ahmad Afip

Abstract:

This main research objective is to accurately identify the possibility for a Leptospirosis outbreak severity of a certain area based on its input features into a multivariate regression model. The research question is the possibility of an outbreak in a specific area being influenced by this feature, such as social demographics and hydrometeorological extremes. If the occurrence of an outbreak is being subjected to these features, then the epidemic severity for an area will be different depending on its environmental setting because the features will influence the possibility and severity of an outbreak. Specifically, this research objective was three-fold, namely: (a) to identify the relevant multivariate features and visualize the patterns data, (b) to develop a multivariate regression model based from the selected features and determine the possibility for Leptospirosis outbreak in an area, and (c) to compare the predictive ability of multivariate regression model and machine learning algorithms. Several secondary data features were collected locations in the state of Negeri Sembilan, Malaysia, based on the possibility it would be relevant to determine the outbreak severity in the area. The relevant features then will become an input in a multivariate regression model; a linear regression model is a simple and quick solution for creating prognostic capabilities. A multivariate regression model has proven more precise prognostic capabilities than univariate models. The expected outcome from this research is to establish a correlation between the features of social demographic and hydrometeorological with Leptospirosis bacteria; it will also become a contributor for understanding the underlying relationship between the pathogen and the ecosystem. The relationship established can be beneficial for the health department or urban planner to inspect and prepare for future outcomes in event detection and system health monitoring.

Keywords: geographical information system, hydrometeorological, leptospirosis, multivariate regression

Procedia PDF Downloads 86

Authors: Encarnación Álvarez, Rosa M. García-Fernández, Juan F. Muñoz, Francisco J. Blanco-Encomienda

Abstract:

The problem of estimating a proportion has important applications in the field of economics, and in general, in many areas such as social sciences. A common application in economics is the estimation of the headcount index. In this paper, we define the general headcount index as a proportion. Furthermore, we introduce a new quantitative method for estimating the headcount index. In particular, we suggest to use the logistic regression estimator for the problem of estimating the headcount index. Assuming a real data set, results derived from Monte Carlo simulation studies indicate that the logistic regression estimator can be more accurate than the traditional estimator of the headcount index.

Keywords: poverty line, poor, risk of poverty, Monte Carlo simulations, sample

Procedia PDF Downloads 400

Authors: Oktay Cinar

Abstract:

The aim of this study is to investigate the acquisition of Overt Pronoun Constraint (OPC) by adult Korean L2 Turkish speakers in order to find out how constraints regulating the syntax of null and overt subjects are acquired. OPC is claimed to be a universal feature of all null subject languages restricting the co-indexation between overt embedded pronoun and quantified or wh-question antecedents. However, there is no such restriction when the embedded subject is null or the antecedent is a referential subject. Considered as a principle of Universal Grammar (UG), OPC knowledge of L2 speakers has been widely tested with different language pairs. In the light of previous studies on OPC, it can be argued that L2 learners display early sensitivity to OPC constraints during their interlanguage grammar development. Concerning this, the co-indexation between overt embedded pronoun o (third person pronoun) and referential matrix subject is claimed to be controversial in Turkish, which poses problems with the universality of OPC. However, the current study argues against this claim by providing evidence from advanced Korean speakers that OPC is universal to all null subject languages and OPC knowledge can be accessed with direct access to UG. In other words, the performances of adult Korean speakers on the syntax of null and overt subjects are tested to support this claim. In order to test this, OPC task is used. 15 advanced speakers and a control group of adult native Turkish participants are instructed to determine the co-reference relationship between the subject of embedded clause, either overt pronominal o or null, and the subject of the matrix clause, either quantified pronoun and wh-question or referential antecedent. They are asked to select the interpretation of the embedded subject, either as the same person as in the matrix subject or another person who is not the same person in the matrix subject. These relations are represented with four conditions, and each condition has four questions (16 questions in total). The results claim that both control group and Korean L2 Turkish speakers display sensitivity to all constraints that OPC has, which suggests that OPC works in Turkish as well.

Keywords: adult Korean speakers, binding theory, generative second language acquisition, overt pronoun constraint

Procedia PDF Downloads 282

Authors: S. Dey, T. Mukhopadhyay, S. Adhikari

Abstract:

This paper presents an exhaustive comparative investigation on sampling techniques of polynomial regression model based stochastic natural frequency of composite plates. Both individual and combined variations of input parameters are considered to map the computational time and accuracy of each modelling techniques. The finite element formulation of composites is capable to deal with both correlated and uncorrelated random input variables such as fibre parameters and material properties. The results obtained by Polynomial regression (PR) using different sampling techniques are compared. Depending on the suitability of sampling techniques such as 2k Factorial designs, Central composite design, A-Optimal design, I-Optimal, D-Optimal, Taguchi’s orthogonal array design, Box-Behnken design, Latin hypercube sampling, sobol sequence are illustrated. Statistical analysis of the first three natural frequencies is presented to compare the results and its performance.

Keywords: composite plate, natural frequency, polynomial regression model, sampling technique, uncertainty quantification

Procedia PDF Downloads 483

Authors: Suzan Anwar, Utkarsh Goyal

Abstract:

Heart rate (HR) is a predictor of cardiovascular, cerebrovascular, and all-cause mortality in the general population, as well as in patients with cardio and cerebrovascular diseases. Machine learning (ML) significantly improves the accuracy of cardiovascular risk prediction, increasing the number of patients identified who could benefit from preventive treatment while avoiding unnecessary treatment of others. This research examines relationship between the individual's various heart health inputs like age, sex, cp, trestbps, thalach, oldpeaketc, and the likelihood of developing heart disease. Machine learning techniques like logistic regression and decision tree, and Python are used. The results of testing and evaluating the model using the Heart Failure Prediction Dataset show the chance of a person having a heart disease with variable accuracy. Logistic regression has yielded an accuracy of 80.48% without data handling. With data handling (normalization, standardscaler), the logistic regression resulted in improved accuracy of 87.80%, decision tree 100%, random forest 100%, and SVM 100%.

Keywords: heart rate, machine learning, SVM, decision tree, logistic regression, random forest

Procedia PDF Downloads 117

Authors: Yoonsuh Jung, Steven N. MacEachern

Abstract:

Check loss function is used to define quantile regression. In the prospect of cross validation, it is also employed as a validation function when underlying truth is unknown. However, our empirical study indicates that the validation with check loss often leads to choosing an over estimated fits. In this work, we suggest a modified or L2-adjusted check loss which rounds the sharp corner in the middle of check loss. It has a large effect of guarding against over fitted model in some extent. Through various simulation settings of linear and non-linear regressions, the improvement of check loss by L2 adjustment is empirically examined. This adjustment is devised to shrink to zero as sample size grows.

Keywords: cross-validation, model selection, quantile regression, tuning parameter selection

Procedia PDF Downloads 410

Authors: Merle Van Den Akker, Neil Stewart, Andrea Isoni

Abstract:

Contactless methods of payment referred to as tap&go, have become increasingly popular globally. However, little is known about the consequences of this payment method on spending, spending habits, personal finance management, and debt accumulation. The literature on other payment methods such as credit cards suggests that, through increased ease and reduced friction, the pain of paying in these methods is reduced, leading to higher and more frequent spending, resulting in higher debt accumulation. Within this research, we use a dataset of 300 million transactions of 165.000 individuals to see whether the onset of using contactless methods of payment increases the occurrence of overdraft fees. Using the R package MatchIt, we find, when matching people on initial overdraft occurrence and salary, that people who do start using contactless incur a significantly higher number of overdraft fees, as compared to those who do not start using contactless in the same year. Having accounted for income, opting-in, and time-of-year effects, these results show that contactless methods of payment fall within the scope of earlier theories on credit cards, such as the pain of paying, meaning that this payment method leads to increasing difficulties managing personal finance.

Keywords: contactless, debt accumulation, overdraft fees, payment methods, spending

Procedia PDF Downloads 96

Authors: Mohammad A. U. Khan, Tariq M. Khan, Yinan Kong

Abstract:

Fingerprint image enhancement is one of the most important step in an automatic fingerprint identification recognition (AFIS) system which directly affects the overall efficiency of AFIS. The conventional fingerprint enhancement like Gabor and Anisotropic filters do fill the gaps in ridge lines but they fail to tackle scar lines. To deal with this problem we are proposing a method for enhancing the ridges and valleys with scar so that true minutia points can be extracted with accuracy. Our results have shown an improved performance in terms of enhancement.

Keywords: fingerprint image enhancement, removing noise, coherence, enhanced diffusion

Procedia PDF Downloads 490

Authors: Ciza Didier

Abstract:

By definition, homosexuality designates the sexual or amorous attraction towards a person of the same sex or of the same gender as one's own. The Burundi country has superficially 27834km2 with 13 millions of population. There are groups of certain people assuming that they are homosexual and that they want to claim their rights. Burundian homosexuals often organise seminars in the premises of the National Health Security Agency (NHSA) located at Kigobe quarter, in Bujumbura, this is the place where they meet to try to exchange and create their association for claim their rights. There are 2 categories of homosexuals: - gays: homosexuality between men (male sex) - lesbians: homosexuality between women (female sex) In the gay couple, there is one who behaves like a woman and often wears feminine styles while the other always remains like a man and always wears masculine styles. In the lesbian couple, there is one who behaves like a man and wears men's styles while the other remains as she is like a woman. In general, Burundian society is against homosexuality. Our society sees them as pariahs carrying a curse. According to Burundian culture and customs, homosexuality is satanic, therefore it is a great sin. In April 2011, Burundian President Pierre Nkurunziza signed a law criminalizing homosexual acts and providing for a sentence of three months to two years in prison, as well as a fine of BIF 50,000 to BIF 100,000 for any homosexual behavior. The investigation recently done shows that out of 300 people questioned, 299 were against homosexuality saying that it is against Burundian culture and 1 was for homosexuality. All Burundians are not against homosexuality. Their country must therefore take into consideration the small party of people who are for homosexuality. Homosexuals, too, need to live like others.

Keywords: homosexuality, lesbian, gay, law

Procedia PDF Downloads 41

Authors: Y. H. Wu, Ji-Yuan Lin, Yu-Ming Liou

Abstract:

This study aims to set up the landslide susceptibility map of County Route 89 at Ren-Ai Township in Nantou County using the Instability Index Method and Logistic regression. Seven susceptibility factors including Slope Angle, Aspect, Elevation, Distance to fold, Distance to River, Distance to Road and Accumulated Rainfall were obtained by GIS based on the Typhoon Toraji landslide area identified by Industrial Technology Research Institute in 2001. To calculate the landslide percentage of each factor and acquire the weight and grade the grid by means of Instability Index Method. In this study, landslide susceptibility can be classified into four grades: high, medium high, medium low and low, in order to determine the advantages and disadvantages of the two models. The precision of this model is verified by classification error matrix and SRC curve. These results suggest that the logistic regression model is a preferred method than instability index in the assessment of landslide susceptibility. It is suitable for the landslide prediction and precaution in this area in the future.

Keywords: instability index method, logistic regression, landslide susceptibility, SRC curve

Procedia PDF Downloads 261

Authors: Elachouri Mostafa, Fakchich Jamila, Lazaar Jamila, Elmadmad Mohammed, Marhom Mostafa

Abstract:

Of course, there has been a great growth in scientific information about medicinal plants in recent decades, but in many ways this has proved poor compensation, because such information is accessible, in practice, only to a very few people and anyway, rather little of it is relevant to problems of management and utilization, as encountered in the field. Active compounds are used in most traditional medicines and play an important role in advancing sustainable rural livelihoods through their conservation, cultivation, propagation, marketing and commercialization. Medicinal herbs are great resources for various pharmaceutical compounds and urgent measures are required to protect these plant species from their natural destruction and disappearance. Indeed, there is a real danger of indigenous Arab medicinal practices and knowledge disappearing altogether, further weakening traditional Arab culture and creating more insecurity, as well as forsaking a resource of inestimable economic and health care importance. As scientific approach, the ethnopharmacological investigation remains the principal way to improve, evaluate, and increase the odds of finding of biologically active compounds derived from medicinal plants. As developing country, belonging to the Mediterranean basin, Morocco country is endowed with resources of medicinal and aromatic plants. These plants have been used over the millennia for human welfare, even today. Besides, Morocco has a large plant biodiversity, in fact, its medicinal flora account more than 4200 species growing on various bioclimatic zones from subhumide to arid and Saharan. Nevertheless, the human and animal pressure resulting from the increase of rural population needs has led to degradation of this patrimony. In this paper, we focus our attention on ethnopharmacological studies carried out in Morocco. The goal of this work is to clarify the importance of herbs as platform for drugs discovery and further development, to highlight the importance of ethnopharmacological study as approach on discovery of natural products in the health care field, and to discuss the limit of ethnopharmacological investigation of drug discovery in Morocco.

Keywords: Morocco, medicinal plants, ethnopharmacology, natural products, drug-discovery

Procedia PDF Downloads 289

Authors: Daniel Gidey, Kunwar Siddarth Dadhwal, Tagel Wondimu

Abstract:

There are numerous ways for ending conflict; hitherto, most conflicts are resolved either through negotiated or victor's peace, this article is about the former. Negotiations entail concessions, consensus-building, and mutual trust in order to transform a belligerent situation into a settlement. In such a context, regional and sub-regional organizations play a critical role in mediating conflicting parties so as to prevent, manage, and resolve conflicts between and among conflicting parties. This article is about the AU-led negotiated peace deal on the bloody conflict between the Tigray Peoples Liberation Front (TPLF) and the Federal Democratic Republic of Ethiopia (FDRE) by undertaking the Pretoria Peace Accord as a case study. In terms of research method, the article is based on a critical evaluation of the literature and content analysis on the very research topic. Findings of the study revealed that the AU, through Olusegun Obasanjo and other dignitaries, played a critical role in nurturing compromise and mutual trust between the TPLF and the Ethiopian federal government so as to take along the Pretoria peace deal. Through critical literature review and content analysis of the Peace deal, the article has concluded that negotiated peace is likely, at least, to achieve negative peace.

Keywords: regional organizations, peace promotion, African Union, negotiating conflicts, Northern Ethiopia, conflict resolution

Procedia PDF Downloads 43

Authors: Aliasghar Mehdizadeh Dastjerdi, Francisco Camara Pereira

Abstract:

The increasing complexity and demand of transport services strains transportation systems especially in urban areas with limited possibilities for building new infrastructure. The solution to this challenge requires changes of travel behavior. One of the proposed means to induce such change is multimodal travel apps. This paper describes a study of the intention to use a real-time multi-modal travel app aimed at motivating travel behavior change in the Greater Copenhagen Region (Denmark) toward promoting sustainable transport options. The proposed app is a multi-faceted smartphone app including both travel information and persuasive strategies such as health and environmental feedback, tailoring travel options, self-monitoring, tunneling users toward green behavior, social networking, nudging and gamification elements. The prospective for mobility management travel apps to stimulate sustainable mobility rests not only on the original and proper employment of the behavior change strategies, but also on explicitly anchoring it on established theoretical constructs from behavioral theories. The theoretical foundation is important because it positively and significantly influences the effectiveness of the system. However, there is a gap in current knowledge regarding the study of mobility-management travel app with support in behavioral theories, which should be explored further. This study addresses this gap by a social cognitive theory‐based examination. However, compare to conventional method in technology adoption research, this study adopts a reverse approach in which the associations between theoretical constructs are explored by Max-Min Hill-Climbing (MMHC) algorithm as a hybrid causal discovery method. A technology-use preference survey was designed to collect data. The survey elicited different groups of variables including (1) three groups of user’s motives for using the app including gain motives (e.g., saving travel time and cost), hedonic motives (e.g., enjoyment) and normative motives (e.g., less travel-related CO2 production), (2) technology-related self-concepts (i.e. technophile attitude) and (3) use Intention of the travel app. The questionnaire items led to the formulation of causal relationships discovery to learn the causal structure of the data. Causal relationships discovery from observational data is a critical challenge and it has applications in different research fields. The estimated causal structure shows that the two constructs of gain motives and technophilia have a causal effect on adoption intention. Likewise, there is a causal relationship from technophilia to both gain and hedonic motives. In line with the findings of the prior studies, it highlights the importance of functional value of the travel app as well as technology self-concept as two important variables for adoption intention. Furthermore, the results indicate the effect of technophile attitude on developing gain and hedonic motives. The causal structure shows hierarchical associations between the three groups of user’s motive. They can be explained by “frustration-regression” principle according to Alderfer's ERG (Existence, Relatedness and Growth) theory of needs meaning that a higher level need remains unfulfilled, a person may regress to lower level needs that appear easier to satisfy. To conclude, this study shows the capability of causal discovery methods to learn the causal structure of theoretical model, and accordingly interpret established associations.

Keywords: travel app, behavior change, persuasive technology, travel information, causality

Procedia PDF Downloads 116

Authors: Zhanxing Li, Liqi Zhu

Abstract:

Authorities often intervene in children’s property conflicts, which may affect young children’s ownership understanding. First possession is a typical rule of ownership judgment. We recruited Chinese preschoolers as subjects and investigated their ownership reasoning regarding first possession, by setting three conditions via a conflicting cues method, in which a third party (mother or peer friend)’s testimony was always opposite to the cue of first possession (authority/non-authority testimony condition), or only the cue of first possession was present (no testimony condition). In Study A, we examined forty-two 3- and 5-year olds’ attribution and justification of ownership. The results showed while 5-year olds gave more support for the first possessor as the owner across three conditions, 3-year olds’ choice for the first possessor had no difference from the non-first possessor in the authority testimony condition. Moreover, 3-year olds tended to justify by reference to what mother said in the authority testimony condition, 5-year olds consistently referred to the first possession in three conditions. In Study B, we added two ownership questions to quantify children’s ability of ownership reasoning with four age groups (n = 32 for the 3-year-olds, n = 33 for the 4-year-olds, n = 27 for the 5-year olds and n = 30 for the adults) to explore the developmental trajectory further. It revealed that while 5-year olds’ performances were similar to the adults’ and always judged the first possessor as owner in three conditions, 3- and 4-year olds’ performed at chance level in the authority testimony condition. The results imply that Chinese young preschooler’s ownership reasoning was susceptible to authority’s testimony. Family authority may play an important role in diluting children’s adherence to ownership principles, which will be helpful for children to learn to share with others.

Keywords: authority, ownership judgment, preschoolers, testimony

Procedia PDF Downloads 170

Authors: Wondmnew Derebe Yohannis

Abstract:

Farming irrigation plays a crucial role in rural development strategies, impacting both annual household income and livelihood. This research aims to evaluate the factors influencing irrigation participation and assess the impact of small-scale irrigation on rural households' annual income. The study collected data from 287 farmers in the Dahana district of northern Ethiopia. The research investigates the driving forces behind farmers' decisions to adopt small-scale irrigation and its effect on annual income gain. The findings reveal that several factors positively influence the probability of adoption, including access to credit, cultivated land size, livestock holding, extension contact, and the education level of the household head. Conversely, the distance to local markets and water schemes negatively affects the likelihood of adoption. To understand the differences in annual income between farm households that adopted irrigation and those that did not, a simultaneous equations model with endogenous switching regression is estimated. This accounts for the heterogeneity in the adoption decision and unobservable characteristics of farmers and their farms. The analysis compares the expected income gain under actual and counterfactual scenarios, considering whether the farm household adopted irrigation or not. The study reveals that the group of farm households that adopted irrigation has distinct characteristics compared to those that did not adopt it. Furthermore, the research demonstrates that the adoption of irrigation practices leads to an increase in annual income. Interestingly, the impact of small-scale irrigation on annual income is greater for the farm households that actually adopted irrigation compared to those in the counterfactual scenario where they did not adopt. Based on the findings, the researcher concludes that small-scale irrigation is a practical solution for meeting household financial needs in the study area. It is recommended that investments in small-scale irrigation continue to further improve the livelihoods of rural farming communities by enhancing annual income gains.

Keywords: small-scale irrigation, income, rural farm households, endogenous switching regression, user, non-user

Procedia PDF Downloads 26

Authors: Deyadeen Ali Alshibani

Abstract:

In the literature, the multi-armed bandit problem as a statistical decision model of an agent trying to optimize his decisions while improving his information at the same time. There are several different algorithms models and their applications on this problem. In this paper, we evaluate the Regret-regression through comparing with Q-learning method. A simulation on determination of optimal treatment regime is presented in detail.

Keywords: optimal, bandit problem, optimization, dynamic programming

Procedia PDF Downloads 426

Authors: Jihye Jeon

Abstract:

This paper analyzes the conceptual framework of three statistical methods, multiple regression, path analysis, and structural equation models. When establishing research model of the statistical modeling of complex social phenomenon, it is important to know the strengths and limitations of three statistical models. This study explored the character, strength, and limitation of each modeling and suggested some strategies for accurate explaining or predicting the causal relationships among variables. Especially, on the studying of depression or mental health, the common mistakes of research modeling were discussed.

Keywords: multiple regression, path analysis, structural equation models, statistical modeling, social and psychological phenomenon

Procedia PDF Downloads 606

Authors: Sanja Podunavac-Kuzmanović, Strahinja Kovačević, Lidija Jevrić, Evgenija Djurendić, Jovana Ajduković

Abstract:

There are several methods for determination of the lipophilicity of biologically active compounds, however chromatography has been shown as a very suitable method for this purpose. Chromatographic (C18-RP-HPLC) analysis of a series of 24 17-picolyl and 17-picolinylidene androstane derivatives was carried out. The obtained retention indices (logk, methanol (90%) / water (10%)) were correlated with calculated physicochemical and lipophilicity descriptors. The QSRR analysis was carried out applying principal component regression (PCR) and partial least squares regression (PLS). The PCR and PLS model were selected on the basis of the highest variance and the lowest root mean square error of cross-validation. The obtained PCR and PLS model successfully correlate the calculated molecular descriptors with logk parameter indicating the significance of the lipophilicity of compounds in chromatographic process. On the basis of the obtained results it can be concluded that the obtained logk parameters of the analyzed androstane derivatives can be considered as their chromatographic lipophilicity. These results are the part of the project No. 114-451-347/2015-02, financially supported by the Provincial Secretariat for Science and Technological Development of Vojvodina and CMST COST Action CM1105.

Keywords: androstane derivatives, chromatography, molecular structure, principal component regression, partial least squares regression

Procedia PDF Downloads 244

Authors: Mohammad Namazi, Mohammad Sadeghzadeh Maharluie

Abstract:

Predicting earnings management is vital for the capital market participants, financial analysts and managers. The aim of this research is attempting to respond to this query: Is there a significant difference between the regression model and neural networks’ models in predicting earnings management, and which one leads to a superior prediction of it? In approaching this question, a Linear Regression (LR) model was compared with two neural networks including Multi-Layer Perceptron (MLP), and Generalized Regression Neural Network (GRNN). The population of this study includes 94 listed companies in Tehran Stock Exchange (TSE) market from 2003 to 2011. After the results of all models were acquired, ANOVA was exerted to test the hypotheses. In general, the summary of statistical results showed that the precision of GRNN did not exhibit a significant difference in comparison with MLP. In addition, the mean square error of the MLP and GRNN showed a significant difference with the multi variable LR model. These findings support the notion of nonlinear behavior of the earnings management. Therefore, it is more appropriate for capital market participants to analyze earnings management based upon neural networks techniques, and not to adopt linear regression models.

Keywords: earnings management, generalized linear regression, neural networks multi-layer perceptron, Tehran stock exchange

Procedia PDF Downloads 399

Authors: Erindi Allaj

Abstract:

This paper studies arbitrage pricing theory in financial markets with transaction costs. We extend the existing theory to include the more realistic possibility that the price at which the investors trade is dependent on the traded volume. The investors in the market always buy at the ask and sell at the bid price. Transaction costs are composed of two terms, one is able to capture the implicit transaction costs and the other the price impact. Moreover, a new definition of a self-financing portfolio is obtained. The self-financing condition suggests that continuous trading is possible, but is restricted to predictable trading strategies which have left and right limit and finite quadratic variation. That is, predictable trading strategies of infinite variation and of finite quadratic variation are allowed in our setting. Within this framework, the existence of an equivalent probability measure is equivalent to the absence of arbitrage opportunities, so that the first fundamental theorem of asset pricing (FFTAP) holds. It is also proved that, when this probability measure is unique, any contingent claim in the market is hedgeable in an L2-sense. The price of any contingent claim is equal to the risk-neutral price. To better understand how to apply the theory proposed we provide an example with linear transaction costs.

Keywords: arbitrage pricing theory,
transaction costs, fundamental theorems of arbitrage, financial markets

Procedia PDF Downloads 326

Authors: Shahadut Hossain, Jacek Wesolowski, Zahirul Hoque

Abstract:

In many epidemiological and environmental studies covariate measurements are subject to the detection limit. In most applications, covariate measurements are usually truncated from below which is known as left-truncation. Because the measuring device, which we use to measure the covariate, fails to detect values falling below the certain threshold. In regression analyses, it causes inflated bias and inaccurate mean squared error (MSE) to the estimators. This paper suggests a response-based regression calibration method to correct the deleterious impact introduced by the covariate detection limit in the estimators of the parameters of simple logistic regression model. Compared to the maximum likelihood method, the proposed method is computationally simpler, and hence easier to implement. It is robust to the violation of distributional assumption about the covariate of interest. In producing correct inference, the performance of the proposed method compared to the other competing methods has been investigated through extensive simulations. A real-life application of the method is also shown using data from a population-based case-control study of non-Hodgkin lymphoma.

Keywords: environmental exposure, detection limit, left truncation, bias, ad-hoc substitution

Procedia PDF Downloads 213

Authors: Scott Staring

Abstract:

This paper critically examines the claim that Canada represents a uniquely ‘postnational’ model of political existence. Canadian political thinkers and politicians alike have played a role in casting their country as the vanguard of an order wherein national sovereignty is gradually being eclipsed, while political authority is increasingly integrated at the international level. Proponents of this view frequently cite as evidence Canada’s high number of foreign-born citizens, its official policy of multiculturalism, its ready embrace of international institutions, and its enthusiasm for international trade deals like NAFTA, CETA and the TPP. This paper builds on historical research to show that the postnationalist thesis has precedents in a Whig-inspired view of Canada that has long challenged the role of a strong central state in the country. An alternative portrait of Canada will be put forward, one that contests both the historical evidence for the Whig view as well as its theoretical presuppositions. The claim will be made that Canada’s celebrated diversity and openness is not the product of a nation-state in retreat; instead, it is largely the product of a strong and sovereign state that has intervened to create a sense of a shared concern amongst its citizens. Canada does indeed offer the world a model of cosmopolitanism, but it is a model that is rooted in the nation-state rather than its eclipse.

Keywords: Canada, cosmopolitanism, postnationalism, statism

Procedia PDF Downloads 178

Authors: Nabilah Filzah Mohd Radzuan, Andi Putra, Zalinda Othman, Azuraliza Abu Bakar, Abdul Razak Hamdan

Abstract:

Precipitation forecast is important to avoid natural disaster incident which can cause losses in the involved area. This paper reviews three techniques logistic regression, decision tree, and random forest which are used in making precipitation forecast. These combination techniques through the vector auto-regression (VAR) model help in finding the advantages and strengths of each technique in the forecast process. The data-set contains variables of the rain’s domain. Adaptation of artificial intelligence techniques involved in rain domain enables the forecast process to be easier and systematic for precipitation forecast.

Keywords: logistic regression, decisions tree, random forest, VAR model

Procedia PDF Downloads 419

Authors: Melahat Çevik

Abstract:

The discovery of fabric has a quite old historical perspective because of veiling, heating and shelter needs of human. Since the days which fashion has a say, this situation has pasted beyond needs and has become status symbols. For the theater art drama which tell people by people, in the concern of reflecting daily life there will be such regards also we may see alternative products to artistically reshaped fabric. The stage is determined in the consensus of costume designer and director. Costume Designer does the research, taking into account the alternative products. Approaching nature as inventor, discovering products, shapes the work because in this work, cost is considerable. All types of fabric will be used but also new materials which are not presented to clothing industry yet are of great importance. In the discovery of new materials there priorities of the costume designer. In the scene everything should be determined in the axis of actor. The material discussed should have positive qualities which allow the performer to move and invigorate him or her in terms of physical and also should be positive in terms of health. This point must be approached in a more precise in high action plays and the obtained material should be tested before the presentation process.

Keywords: fabric, stage design, alternative materials, clothing industry

Procedia PDF Downloads 546