Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of Automatic Backward Model Selection Criterion on the Bias of the Parameters in Logistic Regression Model

Logistic regression model is one of the popular mathematical models for analysis of binary data with applications in health, behavioural and statistical sciences. The main mathematical concept under the logistic regression model is the logit or the natural logarithm of an odds ratio. It is one of the most commonly used models to account for confounders in medical literature. This research sought to evaluate the impact of automatic backward model selection criterion on the bias of the parameters for large sample size. This study used a data set simulated in R-package using different kinds of controlled variables and also diabetic data obtained from Coast General Provincial hospital, Mombasa. The automatic backward selection method was used because they are faster and objective since they use the p -value to find the optimal model in which the fitted values are closest to the true outcome probabilities. The overall result was an inclusive logistic regression model with a subset of statistically significant predictors that best explain the variability in their observations. -------------------------------------------------------------------------------------------------------------------------------------Date of Submission: 12-06-2017 Date of acceptance: 24-07-2017 -------------------------------------------------------------------------------------------------------------------------------------
A Novel Mathematical Based Method for Generating Virtual Samples from a Frontal 2D Face Image for Single Training Sample Face Recognition

This paper deals with one sample face recognition which is a new challenging problem in pattern recognition. In the proposed method, the frontal 2D face image of each person is divided to some sub-regions. After computing the 3D shape of each sub-region, a fusion scheme is applied on them to create the total 3D shape of whole face image. Then, 2D face image is draped over the corresponding 3D shape to construct 3D face image. Finally by rotating the 3D face image, virtual samples with different views are generated. Experimental results on ORL dataset using nearest neighbor as classifier reveal an improvement about 5% in recognition rate for one sample per person by enlarging training set using generated virtual samples. Compared with other related works, the proposed method has the following advantages: 1) only one single frontal face is required for face recognition and the outputs are virtual images with variant views for each individual 2) it requires only 3 key points of face (eyes and nose) 3) 3D shape estimation for generating virtual samples is fully automatic and faster than other 3D reconstruction approaches 4) it is fully mathematical with no training phase and the estimated 3D model is unique for each individual.
The Effect of Groupthink on Institutional Productivity: A study of Federal Tertiary Institutions in Taraba and Adamawa States of Nigeria

This study titled ‘The effects of Groupthink on Institutional Productivity in Federal Tertiary Institutions in Taraba and Adamawa States’ examines the effects of groupthink on institutional productivity. The study employs both quantitative and qualitative methods of obtaining data. Thus, primary data for analysis was obtained through the instrumentality of self-designed questionnaire while secondary sources of data was equally relied upon for literature review. The target population of the study was both academic and non-academic staff of the five (5) selected federal tertiary institutions in Adamawa and Taraba States. Stratified random sampling was used to administer questionnaire to the respondents and their responses was analyzed with the aid of excel software for statistical analysis. Results were determined using percentage and bar chart. The findings of the studyrevealsthat most public institutions studied are plagued by the menace of groupthink. This is because all the antecedent factors of groupthink theory identified by Janis namely; homogeneity, organizational structural faults and situational factors are present in the institutions studied. The absence of the culture of interrogating decisions and lack of feedback mechanism for getting alternative creative ideas which stems from the homogeneous nature of the institutions where recruitments and employments are characterized by kin-ship ties and other parochial considerations instead of merit undermines their effectiveness. Thus the leadership of such institutions are always faced with the dilemma of impartially enforcing rules and maintaining standards.Consequently, absenteeism, late coming to work and lack of commitment to task are very common across the tertiary institutions. These probable effects of groupthink potentially undermine institutional productivity.As a remedy, effective team-based leadership that allows (tolerate) divergent views, tolerate constructive criticism, uncompromisingly build and maintains a culture and atmosphere for debating ideas and create a platform where creativity is rewarded can avert the trend of groupthink leading to enhanced institutional productivity. -------------------------------------------------------------------------------------------------------------------------------------Date of Submission: 03-02-2020 Date of Acceptance: 18-02-2020 -------------------------------------------------------------------------------------------------------------------------------------
Speed Kit: A Polyglot & GDPR-Compliant Approach For Caching Personalized Content

Users leave when page loads take too long. This simple fact has complex implications for virtually all modern businesses, because accelerating content delivery through caching is not as simple as it used to be. As a fundamental technical challenge, the high degree of personalization in today’s Web has seemingly outgrown the capabilities of traditional content delivery networks (CDNs) which have been designed for distributing static assets under fixed caching times. As an additional legal challenge for services with personalized content, an increasing number of regional data protection laws constrain the ways in which CDNs can be used in the first place. In this paper, we present Speed Kit as a radically different approach for content distribution that combines (1) a polyglot architecture for efficiently caching personalized content with (2) a natively GDPR-compliant client proxy that handles all sensitive information within the user device. We describe the system design and implementation, explain the custom cache coherence protocol to avoid data staleness and achieve Δ-atomicity, and we share field experiences from over a year of productive use in the e-commerce industry.
Expert Communication to an Informed Decision Maker

In this model we study a game of strategic information transmission, where a decision maker is partially informed about the state of the world. We analyse the effect of this partial information on communication extending the CrawfordSobel model. There are two forces at work, the bias in preferences leads to less information revelation, whereas the expert benefits ex ante if the decision maker has finer information. We analyse how the decision maker’s partial information in relation to the bias parameter can increase information revelation. We find, that the expected welfare of both agents increases independent of the decision maker’s prior information and communication improves for most information structures. JEL classification: C72, D82, D83
Biometric Template Protection With Robust Semi – Blind Watermarking Using Image Intrinsic Local Property

This paper addresses a biometric watermarking technology sturdy towards image manipulations, like JPEG compression, image filtering, and additive noise. Application scenarios include information transmission between client and server, maintaining e-database and management of signatures through insecure distribution channels. Steps involved in this work are, a) generation of binary signature code for biometric, b) embedding of the binary signature to the host image using intrinsic local property, that ensures signature protection, c) host image is then made exposed to various attacks and d) signature is extracted and matched based on an empirical threshold to verify the robustness of proposed embedding method. Embedding relies on binary signature manipulating the lower order AC coefficients of Discrete Cosine Transformed subblocks of host image. In the prediction phase, DC values of the nearest neighbor DCT blocks is utilized to predict the AC coefficients of centre block. Surrounding DC values of a DCT blocks are adaptively weighed for AC coefficients prediction. Linear programming is used to calculate the weights with respect to the image content. Multiple times embedding of watermark ensures robustness against common signal processing operations (filtering, enhancement, rescaling etc.) and various attacks. The proposed algorithm is tested for 50 different types of host images and public data collection, DB3, FVC2002. FAR and FRR are compared with other methods to show the improvement.
The Role of Pedagogical Factors in Predicting Ghanaian Student Interest in Mathematics –Principal Component Analysis Motivated Regression

The effect of pedagogy on student interest is very important in contemporary educational research. Factor Analysis of Teachers’ Teaching Methodswas carried and how these extracted factors affect students’ interest in Mathematics was investigated. Data was collected from ten (10) senior high schools in Ashanti region of Ghana with one thousand two hundred and sixty-three (1263) students’ randomly selected to participates in the study. The ten factors that influence teaching methods and strategies were reduced to three principal components, and these were further used for regression analysis as predictors of student Mathematics interest. The study concluded that, pedagogical factor oriented model can predict significantly (p-value<0.001) 12% of variance in students’ interest in Mathematics. The third factor which is the use of traditional chalk and board however was found not to influence students’ interest in Mathematics. The study further concludes that the teachers teaching methods can significantly predict student’s interest.
Is hedging for believers? The role of expectations in optimal production and hedging decisions

We study theoretically how firms incorporate their market view into production and hedging decisions. Several motivating examples suggest that optimism reduces the demand for hedging while ambiguity raises it when the firm’s market view is favorable. We analyze the production and hedging decisions of Sandmo’s (1971) competitive firm in a general model of smooth ambiguity aversion (Klibanoff et al., 2005). We distinguish between concordant and discordant uncertainty depending on whether the profitability and behavioral effects of ambiguity go in the same or opposite direction. We then identify restrictions on the firm’s ambiguity preferences that allow for clear comparative static effects of optimism, pessimism, and greater ambiguity on production and hedging. Our results explain how differences in market views and ambiguity preferences generate cross-sectional variation in the demand for hedging and shed new light on so-called “selective hedging. ”
Estimation of greenhouse gas emission reductions based on vegetation changes after rewetting in Drentsche Aa brook valley

Rewetting can effectively reduce greenhouse gas (GHG) emissions from drained peatlands. Reliable emissions estimation approaches are needed for accounting of such reductions and for evaluating the potential in terms of carbon credits. Annual mean water level and vegetation are reliable and widely used proxies for emissions estimation. However, indications of water level based on plant species (e.g. Ellenberg Indicator Values) are qualitative with large variances, and there are insufficient high-quality flux measurement data to support the direct use of vegetation as a proxy for GHG fluxes. Here we combine vegetation and water level proxies to estimate emissions, by using bioindication of vegetation communities for water level together with the linear correlation between annual mean water level and GHG fluxes. This approach is demonstrated in the Drentsche Aa brook valley in The Netherlands, where peatlands were rewetted to restore rich fen vegetation. Biodiversity of the landscape was monitored by repeated vegetation mapping before and after rewetting, which enables the estimation of emissions reduction as a co-benefit. Mean annual water level values are assigned to mapped vegetation types using existing data on water level dynamics from measurements on corresponding plant communities. GHG emissions are estimated using linear regression models of gas fluxes against mean annual water levels. This approach provides spatially explicit and quantitative estimation of mean annual water levels and GHG fluxes. When combined with information on spatial patterns and variances, the resulting estimations can promote recognition of the carbon co-benefits of biodiversity restoration while facilitating more site-specific optimisation of management practices.
Re-purposing the Livelihoods of Afghani Farmers: An Examination of Licit Alternatives to Producing Opium Poppy

As Afghanistan changes and its society and government moves forward, its agricultural sector must remain economically viable to support that progress. Afghani farmers are facing many issues, including challenges that were intensified during the Taliban regime. Poverty has become all too familiar to rural Afghans forcing many to look at alternatives for income generation. In the northern region of Afghanistan, infrastructure is non-existent; roads, electricity, and clean water are often very limited, thus forcing farmers to consider other crops that need little or none of these resources. Although it is against Islamic law, the growing of opium poppy flourishes in this environment and generates incomes well beyond those of licit crops. This paper describes a program designed to help farmers produce licit crops as an alternative to opium poppy production. The Agricultural Marketing and Production Support (AMPS) program described was a vegetable production and support program designed to respond to a market-driven economy. The vegetables grown had high market value, either fresh sales or processed, and transport availability. As a result of participating in the program, it was hoped that farmers’ incomes would increase, therefore, making them less likely to produce illicit crops such as opium poppy. This paper outlines factors addressed by the AMPS program and results derived from its implementation in northern Afghanistan during 2006. Findings from this study may have implications for similar programs in other developing countries, especially in nations that also may be struggling to reduce the production of illicit crops by their farmers.
Factors Influencing Youth Brand Preference associated with Purchase of Laptop: Evidence from the University students of Karachi

Buying preference of youth is the area which is in observation of marketers since considerable amount of time specially in last decade or so special emphasize has been placed upon the preference of youth as they are treated as the major market. Moreover they are also treated as most informed and technologically sound market. But most of the research work carried out related with their preference focused upon their preference regarding fast moving consumer goods and with mobile phone and its accessories, But there are very few researches which focused towards the preference of youth associated with luxurious goods like cars laptops etc. Specially there is a lack of research work in Pakistan’s scenario which will determine the impact of youth preference associated with the luxurious goods. Therefore this research is systematically conducted in order to determine the preference of youth associated with the laptop, i.e. the luxuries good which are treated as the one of most important tool for their social networking as well as for their studies and professional requirements. For this purpose e have collected data from the bachelor level students of reputed higher education institutes operating in Karachi and after the analysis of results through (Software Packs for Social Sciences) SPSS it has been found that the factors on which preference of youth of Karachi depends are somehow similar with the youth of any other location, but there are some factors like celebrity endorsement and brand image which have the different results in comparison to the research work conducted by taking reference of other product category and other geographical locations.
MYO Armband and Leap Motion data fusion with OpenSim based Virtual Reality Environment

In this paper, a novel method combining MYO Armband and Leap Motion is proposed to apply in Virtual Reality display tasks. With the proposed method, we address the Leap Motion's problem of lost detection and improve the Leap Motion's robustness. By integrating MYO and Leap Motion, we can obtain the user's palm's position with MYO, while Leap Motion fails to detect the user's hands. A rigorous analysis is also given in this paper. The validity of the proposed method is verified by simulations with OpenSim.
Habitat Requirements of the White-backed Woodpecker Dendrocopos leucotos lilfordi (Sharpe & Dresser, 1871) (Piciformes: Picidae) in Strandzha Mountain, Bulgaria

White-backed woodpecker (Dendrocopos leucotos) is an old-growth forest specialist and one of the rarest woodpeckers in Europe. The southern subspecies of the white-backed woodpecker (Dendrocopos leucotos lilfordi) is among the least studied. We assessed which environmental variables influence the landscape distribution of the southern white-backed woodpecker applying recursive partitioning. We carried out the study in Strandzha Mts. , Bulgaria, holding one of the largest subpopulations of this subspecies in southeastern Europe. The results indicate that the highest occurrence probability is in Oriental Beech (Fagus orientalis) natural stands of seed origin with average age over 140 years. There is relatively high occurrence also in the natural stands of seed origin, dominated by Oak (Quercus spp.) and Hornbeam (Carpinus spp.) and generally with high percent cover of deciduous forests. The species is rarely found in coppice stands and forest plantations. Based on the results we conclude that the white-backed woodpecker habitat requirements include extensive coverage of deciduous, high-stemmed forest stands that have reached an age that facilitates deadwood formation. We suggest that silvicultural systems such as group selection or irregular shelterwood are implemented to assure continuous forest cover with presence of older patches. We also recommend protection of patches of old-growth, at least 40–50 ha in area, covering not less than 10% of the total area of Strandzha.
International Lending: The Role of Lender’s Home Country

The multinational syndicated loan market has crossed the $7 trillion threshold. Prior literature argues that weak borrower country’s creditor rights is the main limiting factor to cross-border lending. We find that lender country’s creditor rights can partly substitute for weak borrower creditor rights if a lender is from a better creditor rights country. Our results are robust to controlling for a borrower’s country laws, its foreign assets, the loan guarantees provided by its foreign parent, and its choice set of lenders.
Effect of Long-Term Nutrient Management on Soil Organic Carbon Sequestration in Rice–Rice–Fallow Rotation

A study was conducted on long-term (for 31 years) rice–rice–fallow cropping sequence to determine the effect of balanced chemical fertilizer and integrated nutrient management (INM; chemical fertilizer + poultry manure 2 tonne ha –1 ) on soil organic carbon (SOC) sequestration. C mineralization rate (k), microbial population, SOC and C content in the mean water stable soil aggregate (MWDw) were measured from field soil. The C dynamics was described using DSSAT crop and DNDC models. INM increased soil bacteria and improved SOC stock by 27.98%, although C loss was higher with this treatment. A decreasing trend of bacterial population and SOC was observed in the balanced chemical fertilizer (15%) and fertilizer control (46%) treatments compared to initial soil. A positive correlation (r = 0.94) was found between C content of MWDw and soil bacteria population, which provided evidence of vital contribution of soil bacteria for SOC sequestration. In INM treatment, k (incubation study) was 0.011 tonne year –1 , and it was less than DNDC- and DSSAT-generated data. However, k value (0.010 tonne year –1 ) obtained in the incubation study of the balanced chemical fertilizer was similar to DNDC model data. An increasing trend of paddy yield (10 years) was observed in INM compared to balanced chemical fertilizer. In conclusion, microbial population, SOC sequestration and crop yield were high with INM. For sustainable rice production and C sequestration, INM is superior to balanced chemical fertilizer. Between two models used, DNDC is better for prediction of SOC balance.
Making sense of meanings in dialogue

This proposal seeks support for six months focused on grant development for a project with applications in reasoning about textual data. The methods have implications for mathematical reasoning within a social framework. This work will consolidate results from the EU FP7-ICT COINVENT project (611553). This short project will be based at Goldsmiths, University of London, with Professor Simon Colton as PI and Dr Joseph Corneli as named researcher. The primary deliverable in the project is a new multisite grant proposal. Discussions about the content of proposal are already underway with Simon Colton and Teresa Llano (Goldsmiths/Falmouth), Alison Pease (Dundee) and Daniel Winterstein (Winterwell Associates). One of the central themes to be developed in the grant is the role of argumentation in making sense of a given obscure text. Pease et al. (unpublished) have been developing a Lakatos-inspired theory of argumentation in mathematics that will offer a relevant foundation. A more restricted prototype of our argumentative theory was previously applied to evaluate simple concept blends [3]. The proposal builds on earlier research by the RA and close collaborators into dialogues and other forms of social interaction in mathematics [10, 6, 9] and aims to combine theories of discourse with technical knowledge from mathematics domains. The expected long-term impact of this small-scale project is that it will foster the development of computational agents that simulate or participate in MiniPolymath-style discussions. Grant development work will be supported by a small-scale technical pilot study that will help shape the direction of the grant. The distribution of effort will be 3 days a week devoted to grant-writing, 2 days a week to technical work, over a total of 24 work weeks (6 months). A work plan follows.