Search results for: causal inference

Authors: Athanasios Raftopoulos

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In this paper, an attempt is made to explain the evolution or development of human’s representational arsenal from its humble beginnings to its modern abstract symbols. Representations are physical entities that represent something else. To represent a thing (in a general sense of “thing”) means to use in the mind or in an external medium a sign that stands for it. The sign can be used as a proxy of the represented thing when the thing is absent. Representations come in many varieties, from signs that perceptually resemble their representative to abstract symbols that are related to their representata through conventions. Relying the distinction among indices, icons, and symbols, it is explained how symbolic representations gradually emerged from indices and icons. To understand the development or evolution of our representational arsenal, the development of the cognitive capacities that enabled the gradual emergence of representations of increasing complexity and expressive capability should be examined. The examination of these factors should rely on a careful assessment of the available empirical neuroscientific and paleo-anthropological evidence. These pieces of evidence should be synthesized to produce arguments whose conclusions provide clues concerning the developmental process of our representational capabilities. The analysis of the empirical findings in this paper shows that Homo Erectus was able to use both icons and symbols. Icons were used as external representations, while symbols were used in language. The first step in the emergence of representations is that a sensory-motor purely causal schema involved in indices is decoupled from its normal causal sensory-motor functions and serves as a representation of the object that initially called it into play. Sensory-motor schemes are tied to specific contexts of the organism-environment interactions and are activated only within these contexts. For a representation of an object to be possible, this scheme must be de-contextualized so that the same object can be represented in different contexts; a decoupled schema loses its direct ties to reality and becomes mental content. The analysis suggests that symbols emerged due to selection pressures of the social environment. The need to establish and maintain social relationships in ever-enlarging groups that would benefit the group was a sufficient environmental pressure to lead to the appearance of the symbolic capacity. Symbols could serve this need because they can express abstract relationships, such as marriage or monogamy. Icons, by being firmly attached to what can be observed, could not go beyond surface properties to express abstract relations. The cognitive capacities that are required for having iconic and then symbolic representations were present in Homo Erectus, which had a language that started without syntactic rules but was structured so as to mirror the structure of the world. This language became increasingly complex, and grammatical rules started to appear to allow for the construction of more complex expressions required to keep up with the increasing complexity of social niches. This created evolutionary pressures that eventually led to increasing cranial size and restructuring of the brain that allowed more complex representational systems to emerge.

Keywords: mental representations, iconic representations, symbols, human evolution

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Authors: Deniz Karagöz Yüncü

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This study tested a structural model which investigates the relationships among tourists’ need for uniqueness, perceived authenticity (object-based authenticity and existential authenticity) and behavioral intentions to consume cultural and heritage destinations. The sample of the study comprised of 281 participants in a cultural heritage site, in Cappadocia, Turkey. The data were provided via face to face interviews in two months (September and October) which considered the high season. Structural equation modeling was employed to test the causal relationships among the hypotheses. Findings revealed tourists’ creative choice had an influence on object-based authenticity and existential authenticity. Tourists’ avoidance had an influence on object-based authenticity. The study concluded that two dimensions, namely, the object based authenticity and existential authenticity had significant impact on behavioral intentions.

Keywords: needs for uniqueness, perceived existential authenticity, emotions, behavioral intentions

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Authors: Hamed Saremi, Suzan Taghavy, Seyed Mohammad Hanif Sanjari, Mostafa Kahali

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One of the challenges in manufacturing and service companies to provide a product or service is recognized Brand to consumers in target markets. They provide most of their processes under the same capacity. But the constant threat of devastating internal and external resources to prevent a rise Brands and more companies are recognizing the stages are bankrupt. This paper has tried to identify and analyze effective indicators of brand equity and focuses on indicators and presents a model of intelligent create a model to prevent possible damage. In this study, the identified indicators of brand equity are based on literature study and according to expert opinions, set of indicators By techniques DEMATEL Then to used Multi-Step Adaptive Neural-Fuzzy Inference system (ANFIS) to design a multi-stage intelligent system for assessment of brand equity.

Keywords: brand, cosmetic product, ANFIS, DEMATEL

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Authors: Mhaned Oubounyt, Jan Baumbach

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Differences in co-expression networks between two or multiple cells (sub)types across conditions is a pressing problem in single-cell RNA sequencing (scRNA-seq). A key challenge is to define those co-variations that differ between or among cell types and/or conditions and phenotypes to examine small regulatory networks that can explain mechanistic differences. To this end, we developed SCANet, an all-in-one Python package that uses state-of-the-art algorithms to facilitate the workflow of a combined single-cell GCN (Gene Correlation Network) and GRN (Gene Regulatory Networks) pipeline, including inference of gene co-expression modules from scRNA-seq, followed by trait and cell type associations, hub gene detection, co-regulatory networks, and drug-gene interactions. In an example case, we illustrate how SCANet can be applied to identify regulatory drivers behind a cytokine storm associated with mortality in patients with acute respiratory illness. SCANet is available as a free, open-source, and user-friendly Python package that can be easily integrated into systems biology pipelines.

Keywords: single-cell, co-expression networks, drug-gene interactions, co-regulatory networks

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Authors: Alaba M. Dare, Idris A. Ayinde, Adebayo M. Shittu, Sam O. Sam-Wobo

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Households' source of water is one of the core development indicators recently gaining pre-eminence in Nigeria. This study examined rural households' sources of water, Willingness to Pay (WTP) and factors influencing mean WTP. A cross-sectional survey which involved the use of questionnaire was used. A dichotomous choice (DC) with follow up was used as elicitation method. A multi-stage random sampling technique was used to select 437 rural households. Descriptive statistics and Tobit model were used for data estimation. The result revealed that about 70% fetched from unimproved water sources. Most (74.4%) respondents showed WTP for improved water sources. Age (p < 0.01), sex (p < 0.01), education (p < 0.01), occupation (p < 0.01), income (p < 0.01), price of water (P < 0.01), quantity of water (p < 0.01), household size (p < 0.01) and distance (p < 0.01) to existing water sources significantly influenced rural households' WTP for these services. The inference from this study showed that rural dweller sources of water is highly primitive and deplorable. Governments and stakeholders should prioritize the provision of rural water at an affordable price by rural dwellers.

Keywords: households, source of water, willingness to pay (WTP), tobit model

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Authors: Jianhua Wang, Ying Zhou, Xi Zhang

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To establish the influential mechanism of learning engagement on interpreter’s performance, the present study submitted a questionnaire to a sample of 927 English major students with 804 valid ones and used the structural equation model as the basis for empirical analysis and statistical inference on the sample data. In order to explore the mechanism for interpreting learning engagement on student interpreters’ performance, a path model of interpreting processes with three variables of ‘input-environment-output’ was constructed. The results showed that the effect of each ‘environment’ variable on interpreting ability was different from and greater than the ‘input’ variable, and learning engagement was the greatest influencing factor. At the same time, peer interaction on interpreting performance has significant influence. Results suggest that it is crucial to provide effective guidance for optimizing learning engagement and interpreting teaching research by both improving the environmental support and building the platform of peer interaction, beginning with learning engagement.

Keywords: learning engagement, interpreting performance, interpreter training, English major students

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Authors: Azar Khodabakhshi, Elham Bolandnazar

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Agriculture as the most important food manufacturing sector is not only the energy consumer, but also is known as energy supplier. Using energy is considered as a helpful parameter for analyzing and evaluating the agricultural sustainability. In this study, the pattern of energy consumption of strawberry greenhouses of Jiroft in Kerman province of Iran was surveyed. The total input energy required in the strawberries production was calculated as 113314.71 MJ /ha. Electricity with 38.34% contribution of the total energy was considered as the most energy consumer in strawberry production. In this study, Neuro Fuzzy networks was used for function modeling in the production of strawberries. Results showed that the best model for predicting the strawberries function had a correlation coefficient, root mean square error (RMSE) and mean absolute percentage error (MAPE) equal to 0.9849, 0.0154 kg/ha and 0.11% respectively. Regards to these results, it can be said that Neuro Fuzzy method can be well predicted and modeled the strawberry crop function.

Keywords: crop yield, energy, neuro-fuzzy method, strawberry

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Authors: Nael Y. Zabel, Maged E. Georgy, Moheeb E. Ibrahim

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A knowledge-based expert system with the acronym RASPE is developed as an application tool to help decision makers in construction companies make informed decisions about managing risks in pipeline construction projects. Choosing to use expert systems from all available artificial intelligence techniques is due to the fact that an expert system is more suited to representing a domain’s knowledge and the reasoning behind domain-specific decisions. The knowledge-based expert system can capture the knowledge in the form of conditional rules which represent various project scenarios and potential risk mitigation/response actions. The built knowledge in RASPE is utilized through the underlying inference engine that allows the firing of rules relevant to a project scenario into consideration. This paper provides an overview of the knowledge acquisition process and goes about describing the knowledge structure which is divided up into four major modules. The paper shows one module in full detail for illustration purposes and concludes with insightful remarks.

Keywords: expert system, knowledge management, pipeline projects, risk mismanagement

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Authors: Assaad Ghazouani

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Tunisia is ranked among the countries with low energy diversification, but this configuration makes the country too dependent on fossil fuel exporting countries and therefore extremely sensitive to any oil crises, many measures to diversify electricity production must be taken in making use of other forms of renewable and nuclear energy. One of the solutions required to escape this dependence is the liberalization of the electricity industry which can lead to an improvement of supply, energy diversification, and reducing some of the negative effects of the trade balance. This paper examines the issue of renewable electricity and economic growth in Tunisia consumption. The main objective is to study and analyze the causal link between renewable energy consumption and economic growth in Tunisia over the period 1980-2010. To examine the relationship in the short and in the long terms, we used a multidimensional approach to cointegration based on recent advances in time series econometrics (test Zivot - Andrews, Test of Cointegration Johannsen, Granger causality test, error correction model (ECM)).

Keywords: renewable electricity, economic growth, VECM, cointegration, Tunisia

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Authors: Yogendra Sisodia

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Researchers are becoming more interested in extracting useful information from legal documents thanks to the development of large-scale language models in natural language processing (NLP), and deep learning has accelerated the creation of powerful text mining models. Legal fields like contracts benefit greatly from semantic text search since it makes it quick and easy to find related clauses. After collecting sentence embeddings, it is relatively simple to locate sentences with a comparable meaning throughout the entire legal corpus. The author of this research investigated two pre-trained language models for this task: MiniLM and Roberta, and further fine-tuned them on Legal Contracts. The author used Multiple Negative Ranking Loss for the creation of sentence transformers. The fine-tuned language models and sentence transformers showed promising results.

Keywords: legal contracts, multiple negative ranking loss, natural language inference, sentence transformers, semantic textual similarity

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Authors: M. H. Imam, Imran A. Tasadduq, Abdul-Rahim Ahmad, Fahd M. Aldosari

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Learning outcomes of a course (CLOs) and the abilities at the time of graduation referred to as Student Outcomes (SOs) are required to be assessed for ABET accreditation. A question in an assessment must target a CLO as well as an SO and must represent a required level of competence. This paper presents the idea of an Expert System (ES) to select a proper question to satisfy ABET accreditation requirements. For ES implementation, seven attributes of a question are considered including the learning outcomes and Bloom’s Taxonomy level. A database contains all the data about a course including course content topics, course learning outcomes and the CLO-SO relationship matrix. The knowledge base of the presented ES contains a pool of questions each with tags of the specified attributes. Questions and the attributes represent expert opinions. With implicit rule base the inference engine finds the best possible question satisfying the required attributes. It is shown that the novel idea of such an ES can be implemented and applied to a course with success. An application example is presented to demonstrate the working of the proposed ES.

Keywords: expert system, student outcomes, course learning outcomes, question attributes

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Authors: Shurui Bai, Biyun Huang, Khe Foon Hew

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Gamification is defined as the use of game design elements in non-game contexts. The primary purpose of using gamification in an educational context is to engage students in school activities such that their likelihood of completion is increased. But how actually effective is gamification in improving student learning? In order to answer this question, this paper provides a systematic review of prior research studies on gamification in K-12 and university contexts limited to computer science discipline. Unlike other published gamification review works, we specifically analyzed comparison-based studies in quasi-experiment, historical control, and randomization rather than studies with mere anecdotal or phenomenological results. The main purpose for this is to discuss possible causal effects of gamified practices on student performance, behavior change, and perceptual skills following an integrative model. Implications for practice are discussed, along with several suggestions for future research studies.

Keywords: computer science, gamification, learning performance, systematic review

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Authors: Yuan-Lin Chen

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This paper presents an approaching forward collision probability index (AFCPI) for alerting and assisting driver in keeping safety distance to avoid the forward collision accident in highway driving. The time to collision (TTC) and time headway (TH) are used to evaluate the TTC forward collision probability index (TFCPI) and the TH forward collision probability index (HFCPI), respectively. The Mamdani fuzzy inference algorithm is presented combining TFCPI and HFCPI to calculate the approaching collision probability index of the vehicle. The AFCPI is easier to understand for the driver who did not even have any professional knowledge in vehicle professional field. At the same time, the driver’s behavior is taken into account for suiting each driver. For the approaching index, the value 0 is indicating the 0% probability of forward collision, and the values 0.5 and 1 are indicating the 50% and 100% probabilities of forward collision, respectively. The AFCPI is useful and easy-to-understand for alerting driver to avoid the forward collision accidents when driving in highway.

Keywords: approaching index, forward collision probability, time to collision, time headway

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Authors: Bita Mashayekhi, Azadeh Maddahi, Arash Tahriri

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The purpose of this paper is developing a model for audit quality, with regard to the contextual and environmental attributes of the audit profession in Iran. For this purpose, using an exploratory approach, and because of the special attributes of the auditing profession in Iran in terms of the legal environment, regulatory and supervisory mechanisms, audit firms size, and etc., we used grounded theory approach as a qualitative research method. Therefore, we got the opinions of the experts in the auditing and capital market areas through unstructured interviews. As a result, the authors revealed the determinants of audit quality, and by using these determinants, developed an Integrated Audit Quality Model, including causal conditions, intervening conditions, context, as well as action strategies related to AQ and their consequences. In this research, audit quality is studied using a systemic approach. According to this approach, the quality of inputs, processes, and outputs of auditing determines the quality of auditing, therefore, the quality of all different parts of this system is considered.

Keywords: audit quality, integrated audit quality model, demand for audit service, supply of audit, grounded theory

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Authors: D. Garg, S. Luthra, A. Haleem

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Reverse logistics (RL) is supposed to be a systematic procedure that helps in improving the environmental hazards and maintain business sustainability for industries. Industries in Indian are now opting for adoption of RL techniques in business. But, RL practices are not popular in Indian industries because of many barriers for its successful implementation. Therefore, need arises to identify and evaluate the barriers to implement RL practices by taking an Indian industries perspective. Literature review approach and case study approach have been adapted to identify relevant barriers to implement RL practices. Further, Fuzzy Decision Making Trial and Evaluation Laboratory methodology has been brought into use for evaluating causal relationships among the barriers to implement RL practices. Seven barriers out of ten barriers have been categorized into the cause group and remaining into effect group. This research will help Indian industries to manage these barriers towards effective implementing RL practices.

Keywords: barriers, decision making trial and evaluation laboratory (DEMATEL), fuzzy set theory, Indian industries, reverse logistics (RL)

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Authors: Hamid Boustanifar, Geraldo Cerqueiro, María Fabiana Penas

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We exploit state-level changes in the amount of personal wealth individuals can protect under Chapter 7 to analyze the causal effect of debtor protection on income inequality. We find that an increase in state exemptions significantly increases inequality by reducing income for low-income individuals and by increasing income for high-income individuals. The increase in inequality is four times larger among the self-employed than among wage earners, and it is due mainly to a growing income gap between skilled (i.e., individuals with a college degree) and unskilled entrepreneurs. We also find that the employment rate of skilled entrepreneurs significantly increases, while the employment rate of unskilled wage earners falls. Our results are consistent with a recent literature that shows that higher exemptions redistribute credit from low-wealth to high-wealth entrepreneurs, affecting the performance of their businesses.

Keywords: debtor protection, credit markets, income inequality, debtor protection laws

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Authors: Mananya Meenakorn

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The purpose of this study is to examine the impact of public enterprise reform policy on the attributes of organizational commitments in the public energy enterprises in Thailand. It compares three structural types of public energy enterprises: totally state-owned public enterprises, partially transformed public enterprises and totally transformed public enterprises, based on the degree of state ownership and the level of management control that exist in the public reformed organizations, by analyzing the presence of the desirable attributes of organizational commitment as perceived by employees. Findings indicate that there are statistically significant differences in the level of some dimensions of organizational commitment between the three types of public energy enterprises. The results also indicate empirical evidence concerning the causal relationship between the antecedents and organizational commitment. Whereas change-related behaviors show a direct negative influence on organizational commitment, both HRM practices and work-related values indicate direct positive influences on them also.

Keywords: affective commitment, organizational commitment, public enterprise reform organizations, public energy enterprises in Thailand

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Authors: Chang-Uk Kwak, Sun-Joong Kim, Seong-Bae Park, Sang-Jo Lee

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This paper proposes a method of learning topics for broadcasting contents. There are two kinds of texts related to broadcasting contents. One is a broadcasting script which is a series of texts including directions and dialogues. The other is blogposts which possesses relatively abstracted contents, stories and diverse information of broadcasting contents. Although two texts range over similar broadcasting contents, words in blogposts and broadcasting script are different. In order to improve the quality of topics, it needs a method to consider the word difference. In this paper, we introduce a semantic vocabulary expansion method to solve the word difference. We expand topics of the broadcasting script by incorporating the words in blogposts. Each word in blogposts is added to the most semantically correlated topics. We use word2vec to get the semantic correlation between words in blogposts and topics of scripts. The vocabularies of topics are updated and then posterior inference is performed to rearrange the topics. In experiments, we verified that the proposed method can learn more salient topics for broadcasting contents.

Keywords: broadcasting script analysis, topic expansion, semantic correlation analysis, word2vec

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Authors: Magdalena Orth, Gunnar Gotz

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Background: Domestic accountability, budget transparency and public financial management (PFM) are considered vital components of good governance in developing countries. The aid modality budget support (BS) promotes these governance functions in developing countries. BS engages in political decision-making and provides financial and technical support to poverty reduction strategies of the partner countries. Nevertheless, many donors have withdrawn their support from this modality due to cases of corruption, fraud or human rights violations. This exit from BS is leaving a finance and governance vacuum in the countries. The evaluation team analyzed the consequences of terminating the use of this modality and found particularly negative effects for good governance outcomes. Methodology: The evaluation uses a qualitative (theory-based) approach consisting of a comparative case study design, which is complemented by a process-tracing approach. For the case studies, the team conducted over 100 semi-structured interviews in Malawi, Uganda, Rwanda and Zambia and used four country-specific, tailor-made budget analysis. In combination with a previous DEval evaluation synthesis on the effects of BS, the team was able to create a before-and-after comparison that yields causal effects. Main Findings: In all four countries domestic accountability and budget transparency declined if other forms of pressure are not replacing BS´s mutual accountability mechanisms. In Malawi a fraud scandal created pressure from the society and from donors so that accountability was improved. In the other countries, these pressure mechanisms were absent so that domestic accountability declined. BS enables donors to actively participate in political processes of the partner country as donors transfer funds into the treasury of the partner country and conduct a high-level political dialogue. The results confirm that the exit from BS created a governance vacuum that, if not compensated through external/internal pressure, leads to a deterioration of good governance. For example, in the case of highly aid dependent Malawi did the possibility of a relaunch of BS provide sufficient incentives to push for governance reforms. Overall the results show that the three good governance areas are negatively affected by the exit from BS. This stands in contrast to positive effects found before the exit. The team concludes that the relationship is causal, because the before-and-after comparison coherently shows that the presence of BS correlates with positive effects and the absence with negative effects. Conclusion: These findings strongly suggest that BS is an effective modality to promote governance and its abolishment is likely to cause governance disruptions. Donors and partner governments should find ways to re-engage in closely coordinated policy-based aid modalities. In addition, a coordinated and carefully managed exit-strategy should be in place before an exit from similar modalities is considered. Particularly a continued framework of mutual accountability and a high-level political dialogue should be aspired to maintain pressure and oversight that is required to achieve good governance.

Keywords: budget support, domestic accountability, public financial management and budget transparency, Sub-Sahara Africa

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Authors: Routsukol Sunalai

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The purpose of this study is to examine the impact of public enterprise reform policy on the attributes of organizational commitments in the public energy enterprises in Thailand. It compares three structural types of public energy enterprises: Totally state-owned public enterprises (type I), partially transformed public enterprises (type II), and totally transformed public enterprises (type III), based on the degree of state partially transformed public enterprises (type II), and totally transformed public enterprises (type III),based on the degree of reformed organizations, by analyzing the presence of the desirable attributes of organizational commitment as perceived by employees. Findings indicate that there are statistically significant differences in the level of some dimensions of organizational commitment (affective commitment and normative commitment) between the three types of public energy enterprises. The lack of a structural type difference holds for only continuance commitment. The results also indicate empirical evidence concerning the causal relationship between the antecedents and including organizational commitment also.

Keywords: management control, organizational commitment, public enterprises in Thailand, public enterprise reform

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Authors: Oluwayemisi O. Alaba, John O. Olaomi

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The 2013 Nigerian Demographic Health Survey (NDHS) data was used to investigate the determinants of family size in Nigeria using the geo-additive model. The fixed effect of categorical covariates were modelled using the diffuse prior, P-spline with second-order random walk for the nonlinear effect of continuous variable, spatial effects followed Markov random field priors while the exchangeable normal priors were used for the random effects of the community and household. The Negative Binomial distribution was used to handle overdispersion of the dependent variable. Inference was fully Bayesian approach. Results showed a declining effect of secondary and higher education of mother, Yoruba tribe, Christianity, family planning, mother giving birth by caesarean section and having a partner who has secondary education on family size. Big family size is positively associated with age at first birth, number of daughters in a household, being gainfully employed, married and living with partner, community and household effects.

Keywords: Bayesian analysis, family size, geo-additive model, negative binomial

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Authors: A. Zaher, A. Traore, F. Thiéry, T. Talbert, B. Shaer

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In this paper, an intelligent approach is proposed to optimize the orientation of continuous solar tracking systems on cloudy days. Considering the weather case, the direct sunlight is more important than the diffuse radiation in case of clear sky. Thus, the panel is always pointed towards the sun. In case of an overcast sky, the solar beam is close to zero, and the panel is placed horizontally to receive the maximum of diffuse radiation. Under partly covered conditions, the panel must be pointed towards the source that emits the maximum of solar energy and it may be anywhere in the sky dome. Thus, the idea of our approach is to analyze the images, captured by ground-based sky camera system, in order to detect the zone in the sky dome which is considered as the optimal source of energy under cloudy conditions. The proposed approach is implemented using experimental setup developed at PROMES-CNRS laboratory in Perpignan city (France). Under overcast conditions, the results were very satisfactory, and the intelligent approach has provided efficiency gains of up to 9% relative to conventional continuous sun tracking systems.

Keywords: clouds detection, fuzzy inference systems, images processing, sun trackers

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Authors: Erion Luga, Aksel Seitllari, Kemal Pervanqe

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This study investigates the relation between physical and mechanical properties of concrete paving stones using neuro-fuzzy approach. For this purpose 200 samples of concrete paving stones were selected randomly from different sources. The first phase included the determination of physical properties of the samples such as water absorption capacity, porosity and unit weight. After that the indirect tensile strength test and compressive strength test of the samples were performed. İn the second phase, adaptive neuro-fuzzy approach was employed to simulate nonlinear mapping between the above mentioned physical properties and mechanical properties of paving stones. The neuro-fuzzy models uses Sugeno type fuzzy inference system. The models parameters were adapted using hybrid learning algorithm and input space was fuzzyfied by considering grid partitioning. It is concluded based on the observed data and the estimated data through ANFIS models that neuro-fuzzy system exhibits a satisfactory performance.

Keywords: paving stones, physical properties, mechanical properties, ANFIS

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Authors: Messele Kumilachew Aga, Amanpreet Singh

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This study investigates the effect of attitude toward entrepreneurship, subjective norm, and perceived behavioral control on entrepreneurial intentions and examines the moderating role of families’ entrepreneurial background in this causal relationship. Three hundred thirty-five undergraduate students from four universities in Ethiopia filled and returned a self-administrated questionnaire which was analyzed through independent sample t-test and process macro. The result obtained indicated that there was no mean difference in entrepreneurial intentions and its antecedents between students who have families with an entrepreneurial background and not. Besides, the study shows that families’ entrepreneurial background has no moderating effect on entrepreneurial intentions due to attitude toward entrepreneurship, subjective norm, and perceived behavioral control. Hence, the study suggests no need of considering families’ entrepreneurial background in nurturing entrepreneurship for undergraduate students in Ethiopian universities.

Keywords: attitude toward entrepreneurship, entrepreneurial intentions, families’ entrepreneurial background, perceived behavioral control, subjective norm

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Authors: Shahadut Hossain, Jacek Wesolowski, Zahirul Hoque

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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

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Authors: Samaneh Sadat Fattahi Massoom, Hossein Salimi Bajestani

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The study examines loneliness and depression in students who regularly care for themselves after school (latchkey students) in Mashhad and compares them with parent supervised students using a causal-comparative research method. The 270 participants, aged 7 -13, were selected using convenience and cluster random-assignment sampling. Independent t-test results showed significant differences between loneliness (-4.32, p ≤ 0.05) and depression (-3.02, p ≤0.05) among latchkey and non-latchkey students. Using the Pearson correlation test, significant correlation between depression and loneliness among latchkey students was also discovered (r=0.59, p ≤ 0.05). However, regarding non latchkey students, no significant difference between loneliness and depression was observed (r= 0.02. p ≥ 0.05). Multiple regression results also showed that depression variance can be determined by gender (22%) and loneliness (34%). The findings of this study, specifically the significant difference between latchkey and non-latchkey children regarding feelings of loneliness and depression, carries clear implications for parents. It can be concluded that mothers who spend most of their time working out of the house and devoid their children of their presence in the home may cause some form of mental distress like loneliness and depression. Moreover, gender differences affect the degree of these psychological disorders.

Keywords: loneliness, depression, self-care students, latchkey and non-latchkey students, gender

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Authors: Siddharth Satishchandran, Brian Khumalo

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Humans are able to derive semantic content from syntactic and pragmatic sources. Multimodal evidence from signaling theory, which examines communication between individuals within and across species, suggests that non-human primates possess similar syntactic and pragmatic capabilities. However, the extent remains unknown because primate pragmatics are relatively under-examined. Our paper reviews research within communication theory amongst non-human primates to understand current theoretical trends. We examine evidence for primate pragmatic capacities through observational, experimental, and theoretical work on gestures. Given fragmented theoretical perspectives, we provide a unified framework of communication for future research that contextualizes the available research under code biology. To achieve this, we rely on biological semiotics (biosemiotics), the philosophy of biology investigating prelinguistic meaning-making as a function of signs and codes. We close by discussing areas of potential research for studying gestural pragmatics amongst non-human primates, particularly chimpanzees (Pan troglodytes), Diana monkeys (Cercopithecus diana), and other potential candidates.

Keywords: pragmatics, non-human primates, gestural communication, biological semiotics

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Authors: Fakieh Alrabai

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The present study examines the predictive power of foreign language anxiety and motivation, as two significant affective variables, in English as a foreign language (EFL) achievement. It also explores the causal relationship between these two factors (i.e. which variable causes the other); and which one of them best predicts other affective factors including learner attitude, self-esteem, and autonomy. The study utilized experimental treatments among 210 Saudi EFL learners divided into four groups. Group 1 was exposed to anxiety-controlling moments, group 2 was exposed to motivational moments, group 3 was exposed to anxiety-controlling and motivational moments together, and group 4 was exposed to no specific anxiety or motivation strategies. The influence of the treatment on the study variables was evaluated using a triangulation of measurements including questionnaires, classroom observations, and achievement tests. Descriptive analysis, ANOVA, ANCOVA, and regression analyses have been deployed to figure out the study findings. While both motivation and anxiety significantly predicted learners EFL achievement, motivation has been found to be the best predictor of learners’ achievement; and therefore, operates as the mediator of EFL achievement.

Keywords: motivation, anxiety, achievement, autonomy

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Authors: Sumanpreet Kaur, Harjit Pal Singh, Vikas Khullar

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In Wireless Sensor Network (WSN), the sensor containing motes (nodes) incorporate batteries that can lament at some extent. To upgrade the energy utilization, clustering is one of the prototypical approaches for split sensor motes into a number of clusters where one mote (also called as node) proceeds as a Cluster Head (CH). CH selection is one of the optimization techniques for enlarging stability and network lifespan. Deterministic Stable Election Protocol (DSEP) is an effectual clustering protocol that makes use of three kinds of nodes with dissimilar residual energy for CH election. Fuzzy Logic technology is used to expand energy level of DSEP protocol by using fuzzy inference system. This paper presents protocol DSEP using Fuzzy Logic (DSEP-FL) CH by taking into account four linguistic variables such as energy, concentration, centrality and distance to base station. Simulation results show that our proposed method gives more effective results in term of a lifespan of network and stability as compared to the performance of other clustering protocols.

Keywords: DSEP, fuzzy logic, energy model, WSN

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Authors: Farhad Asadi, Mohammad Javad Mollakazemi

Abstract:

In this paper, Bayesian online inference in models of data series are constructed by change-points algorithm, which separated the observed time series into independent series and study the change and variation of the regime of the data with related statistical characteristics. variation of statistical characteristics of time series data often represent separated phenomena in the some dynamical system, like a change in state of brain dynamical reflected in EEG signal data measurement or a change in important regime of data in many dynamical system. In this paper, prediction algorithm for studying change point location in some time series data is simulated. It is verified that pattern of proposed distribution of data has important factor on simpler and smother fluctuation of hazard rate parameter and also for better identification of change point locations. Finally, the conditions of how the time series distribution effect on factors in this approach are explained and validated with different time series databases for some dynamical system.

Keywords: time series, fluctuation in statistical characteristics, optimal learning, change-point algorithm

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