Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Chief Executive Officer Duality on the Profitabilityof Money Deposit Banks

The purpose of this study is to determine the effect of chief executive officer duality on the profitability of money deposit banks. The research design adopted by this study is the quantitative approach. The population of interest for this study comprised the twenty-two deposit money banks listed on the Nigerian Stock Exchange (NSE) as at March (2016) for the period of sixteen years from 2000 to 2016. The study utilized only the secondary source of data. There exists a negative relationship between CEO duality and profitability. This further entails that for the sampled banks, CEO duality contributes negatively to the profitability of the selected money deposit banks in Nigeria. The coefficient of determination which measures the control power of the independent variable over the dependent variable was calculated with the instrument of adjusted R-Squared and it yielded 0.296170. This entails that the variations in profitability of the selected deposit money banks is not significantly influenced by CEO duality. Based on the findings, the study concludes that on the average, effect of chief executive officer duality has no significant effect on the profitability of money deposit banks. This finding reveals that dual role has no positive and significant influence and contribution towards profitability in money deposit banks. This should be thoroughly ascertained for it to be either suspended or significantly minimized
ORGANIZATIONAL DESIGN, INTERNAL COLLABORATION AND PERFORMANCE: AN EMPIRICAL ASSESSMENT IN LATVIA

We live in the time of transformations and in response to environmental challenges, traditional forms of organizational designs are changing towards more networked ones. Human resource practitioners claim that ‘Organization of the future’ requires freedom to act, flexible working practices, outcome-based performance management, and high-trust working relationships, however, there is limited empirical attention directed to the elements of organizational structures, and organizational design aspects have not been explicitly addressed. This research aims to identify which organizational design mechanisms facilitate collaboration within organizations and positively contribute to organizational performance. The quantitative study uses data from a structured survey of Latvian organizations. The research findings provide empirical evidence of the positive impact of decentralization, outcome-based performance management and internal trust on collaboration within the organizational boundaries and performance measured as customer satisfaction. Assessing differences between organisations it was found that internal trust appears to be even more important collaboration ensuring factor for large organizations than for smaller ones. Research results show that managers should establish internal trust-based relationships within their organizations since the effect of trust on collaboration could not be overestimated.
Doing everything they can or everything that pays: the impact of financial incentives on two non-profit organisations

This thesis explores the impact of financial incentives on non-profit organisations delivering outcomes-based contracts in UK public services to understand how they affect intra-organisational behaviour and the motivation of staff members. These issues are examined in comparative case studies of two non-profit organisations delivering public services through a Social Impact Bond (SIB), an outcomes-based payment for results (PbR) contract. In a SIB, government purchasers collaborate with private investors or social investors (seeking a blend of financial return and social value) to fund interventions tackling social problems. The SIBs generated direct financial incentives to the organisation and indirect financial incentives for managers and front line staff. This thesis examines the impact of these incentives on organisational, team, and staff behaviour at the managerial and front-line level. This analysis draws on economic theory about the agency relationship, incentives, and non-profit organisations to understand the impact of these direct and indirect incentives on the behaviour of providers delivering outcomes-based contracts. The research examines the applicability of theories of intrinsic motivation crowding from the economics and social psychology literature to understand the impact of indirect financial incentives on the staff’s intrinsic motivation. The analysis of the SIB contracts identified the potential for unintended consequences and suboptimal allocations of resources. The strategic importance senior leadership placed on direct financial incentives influenced how team managers organised staff structure and service delivery. Front line staff understood and prioritised the preferences of their team managers in their choices to apply a client- or outcomes-centred approach to the client group. Incentives ‘crowded in’ intrinsic motivation for staff that supported the outcomes targets and had autonomy over their work. This study argues that the highly-geared incentives in these outcomes-based contracts had complex effects on public services delivery.
Wearable Games - An Approach for Defining Design Principles

This paper describes the efforts on designing games for wearable computing technology taken by the 23 students of the project PEnG Physical Environment Games. Creating wearable game concepts we are faced with a lack of good design principles and therefore found out that some of our concepts are not very playable. Finding out where our concepts failed will result in knowledge about what rules a good design principle for wearable games must follow.
A Unified Scheduling For Multi-Hop WirelessWith Order Optimal Per Flow Delay

Wireless multi hop networks, end-to-end (e2e) delay are a critical parameter for quality of service (QoS) guarantees. For the long flows, the end-to-end delay may grow quadratic ally with the number of hops. It is difficult to control the end-to-end delay of each flow. Proposed a new joint congestion control and scheduling algorithm for multi hop wireless networks. It contains fixed-route flows operated under a general interference model. The proposed system explicitly quantifies the tradeoff between throughput and delay of every flow. The proposed system introduces three techniques to reduce the congestion and to increase the throughput. They are window based flow control, virtual rate computation and finally the scheduling. The window based flow control controls the number of packets in the network. The packets to be sent are first injected in the window. The window injects each packet in the network only after receiving the acknowledgement for the previously sent packet. The scheduling is performed by the virtual rates computed by the virtual rate computation. The virtual rates are computed based on the flows in the node to be transmitted and then the capacity of the link. According to this scheduling.
Full-CMOS 2-GHz WCDMA direct conversion transmitter and receiver

This paper presents a full-CMOS transmitter and receiver for 2.0-GHz wide-band code division multiple access with direct conversion mixers and a DC-offset cancellation scheme. The direct conversion scheme combined with a multiphase sampling fractional-N prescaler alleviates the problems of the direct conversion transmitter and receiver. Digital gain control is merged into the baseband filters and variable-gain amplifiers to optimize the linearity of the system, reduce the noise, and improve the sensitivity. Variable-gain amplifiers with DC-offset cancellation loop eliminate the DC-offset in each stage. The chip implemented in 0.35-/spl mu/m CMOS technology shows the experimental results of 6 dBm maximum output power with 38-dB adjacent channel power rejection ratio at 1.92 MHz, 50-dB dynamic range, and 363-mW power consumption in the transmitter. The receiver shows -115.4 dBm sensitivity, a 4.0-dB noise figure, and a dynamic range of 80-dB with 396-mW power consumption.
A Study on Big Knowledge and Its Engineering Issues

After entering the big data era, a new term of ‘big knowledge’ has been coined to deal with challenges in mining a mass of knowledge from big data. While researchers used to explore the basic characteristics of big data, we have not seen any studies on the general and essential properties of big knowledge. To fill this gap, this paper studies the concepts of big knowledge, big-knowledge system, and big-knowledge engineering. Ten massiveness characteristics for big knowledge and big-knowledge systems, including massive concepts, connectedness, clean data resources, cases, confidence, capabilities, cumulativeness, concerns, consistency, and completeness, are defined and explored. Based on these characteristics, a comprehensive investigation is conducted on some large-scale knowledge engineering projects, including the Fifth Comprehensive Traffic Survey in Shanghai, the China's Xia-Shang-Zhou Chronology Project, the Troy and Trojan War Project, and the International Human Genome Project, as well as the online free encyclopedia Wikipedia. We also investigate the recent research efforts on knowledge graphs, where they are analyzed to determine which ones can be considered as big knowledge and big-knowledge systems. Further, a definition of big-knowledge engineering and its life cycle paradigm is presented. All of these projects are accordingly checked to determine whether they belong to big-knowledge engineering projects. Finally, the perspectives of big knowledge research are discussed.
State‐of‐the‐art in Multi‐Light Image Collections for Surface Visualization and Analysis

Multi‐Light Image Collections (MLICs), i.e., stacks of photos of a scene acquired with a fixed viewpoint and a varying surface illumination, provide large amounts of visual and geometric information. In this survey, we provide an up‐to‐date integrative view of MLICs as a mean to gain insight on objects through the analysis and visualization of the acquired data. After a general overview of MLICs capturing and storage, we focus on the main approaches to produce representations usable for visualization and analysis. In this context, we first discuss methods for direct exploration of the raw data. We then summarize approaches that strive to emphasize shape and material details by fusing all acquisitions in a single enhanced image. Subsequently, we focus on approaches that produce relightable images through intermediate representations. This can be done both by fitting various analytic forms of the light transform function, or by locally estimating the parameters of physically plausible models of shape and reflectance and using them for visualization and analysis. We finally review techniques that improve object understanding by using illustrative approaches to enhance relightable models, or by extracting features and derived maps. We also review how these methods are applied in several, main application domains, and what are the available tools to perform MLIC visualization and analysis. We finally point out relevant research issues, analyze research trends, and offer guidelines for practical applications.
Joint MR image super-resolution reconstruction and sparse coefficients estimation

The spatial resolution of magnetic resonance (MR) image is determined by various instrumental limitations and physical considerations. This paper presents a new approach to MR image super-resolution reconstruction. Specifically, we incorporate nonlocal similarity, natural image prior, and sparsity prior into a unified, non-convex minimisation functional that contains both the unknown high-resolution image and the sparse coefficients. We also develop a majorisation-minimisation (MM) approach to solve the target non-convex functional. Experiments on MR image super-resolution reconstruction validate the efficiency of the proposed method.
ANALYSIS OF PRE-SERVICE TEACHERS' COGNITIVE PROFILES

In recent years there has been increased attention to the problem of teachers' competences. The need for developing critical thinking in schools turns the focus also on the teachers' cognitive skills including not only intelligence but also cognitive reflection and implicit theories of intelligence. This study aimed to analyse pre-service teachers' (N = 344) cognitive profiles covering data from cognitive reflection test (CRT), implicit theories of intelligence test and Mannheim intelligence test (MIT, measuring verbal, numerical and spatial abilities). Significant correlations were found between cognitive reflection and other cognitive abilities. However, the implicit theories of intelligence seemed to be independent of cognitive abilities. Significant differences between senior and junior pre-service teachers were found in cognitive reflection and two MIT items. Based on the presented results, we discuss the assessment of pre-service teachers’ competences and the development of critical and higher order thinking in pre-gradual teacher education.
Evaluating machine learning methods: scored receiver operating characteristics (sroc) curves

This thesis addresses evaluation methods used to measure the performance of machine learning algorithms. In supervised learning, algorithms are designed to perform common learning tasks including classification, ranking, scoring, and probability estimation. This work investigates how information, produced by these various learning tasks, can be utilized by the performance evaluation measure. In the literature, researchers recommend evaluating classification and ranking tasks using the Receiver Operating Characteristics (ROC) curve. In a scoring task, the learning model estimates scores, from the training data, and assigns them to the testing data. These scores are used to express class memberships. Sometimes, these scores represent probabilities in which case the Mean Squared Error (Brier Score) is used to measure their quality. However, if these scores are not probabilities, the task is reduced to a ranking or a classification task by ignoring them. The standard ROC curve also eliminates such scores from its analysis. We claim that using non-probabilistic scores as probabilities is often incorrect, and doing it properly would mean imposing additional assumptions on the algorithm or on the data. Ignoring these scores fully, however, is also problematic since, in practice, although they may provide a poor estimate of probabilities, their magnitudes, nonetheless, provide information that can be valuable for performance analysis. The purpose of this dissertation is to propose a novel method that extends the ROC curve to include such scores. We, therefore, call it the scored ROC curve. In particular, we develop a method to construct a scored ROC curve, demonstrate how to reduce it to a standard ROC curve, and illustrate how it can be used to compare learning models. Our experiments demonstrate that the scored ROC curve is capable of measuring similarities as well as differences in the performance of different learning models, and is more sensitive to them than the standard ROC curve. In addition, we illustrate our method's ability to detect changes in data distribution between training and testing.
A comparison of several acoustic representations for speech recognition with degraded and undegraded speech

Several acoustic representations have been compared in speaker-dependent and independent connected and isolated-word recognition tests with undegraded speech and with speech degraded by adding white noise and by applying a 6-dB/octave spectral tilt. The representations comprised the output of an auditory model, cepstrum coefficients derived from an FFT-based mel-scale filter bank with various weighting schemes applied to the coefficients, cepstrum coefficients augmented with measures of their rates of change with time, and sets of linear discriminant functions derived from the filter-bank output and called IMELDA. The model outperformed the cepstrum representations except in noise-free connected-word tests, where it had a high insertion rate. The best cepstrum weighting scheme was derived from within-class variances. Its behavior may explain the empirical adjustments found necessary with other schemes. IMELDA outperformed all other representations in all conditions and is computationally simple. <<ETX>>
MAC Access Delay Analysis of EDCA Mechanism of Wireless LANs

A model is proposed to analyze the MAC (medium access control) access delay of EDCA (enhanced distribution channel access) mechanism of wireless LANs (local area networks), which is based on the moment generating function and signal flow graph. The model gives the probability distribution function (PDF) of MAC access delay and several relative characteristic numbers, including the mean value, variance, standard deviation and deviation coefficient of MAC access delay. The results of the analytical model coincide with simulations, which validates the model proposed. A lot of analyses are presented. Firstly, the model presents the relationship among number of nodes and sending probability, collision probability, freezing probability and mean delay of all ACs (access categories). Secondly, the model discloses the composition of MAC access delay. Thirdly, the model presents the effect of different values of AIFS (arbitration inter frame spacing) on MAC access delay. Lastly, the model presents that the deviation coefficient of MAC access delay is larger than 1, so when the exponential distribution is adopted as the distribution of MAC access delay, the capacity of the queue system will be evaluated wrongly.
Scatterplot matrix techniques for large N

High-performance interaction with scatterplot matrices is a powerful approach to exploratory multivariate data analysis. For a small number of data points, real-time interaction is possible and overplotting is usually not a major problem. However, when the number of plotted points is large, display techniques that deals with overplotting and slow production are important. This paper addresses these two problems in the context of display devices that have a color look-up table. Topics include compromised brushing, film loops, and density representation by gray-scale or by symbol area. The paper also discusses techniques that are generally applicable, including interactive graphical subset selection from any collection of scatterplots, and comparison of scatterplot matrices. 26 refs.
EFICÁCIA DE IMPLANTES DE NORGESTOMET REUTILIZADOS NO CONTROLE DO CICLO ESTRAL DE CABRAS LEITEIRAS

ABSTRACT. Cruz M.H. C. , Cruz J.F. , Moura L.C. O. , Teixeira Neto M.R. , Ferraz R.C. N. , Becker-Silva S.C. & Snoeck P.P.N. [Efficacy of Norgestomet reused implants on the estrous cycle control in dairy goats]. Eficacia de implantes de Norgestomet reutilizados no controle do ciclo estral de cabras leiteiras. Revista Brasileira de Medicina Veterinaria, 32(4):219-224, 2010. Curso de Medicina Veterinaria, Departamento de Ciencias Agrarias e Ambientais, Universidade Estadual de Santa Cruz, Rodovia IlheusItabuna, km 16, Salobrinho, Ilheus, BA 45662-000, Brasil. E-mail: paolasnoeck@uesc.br The aim of this study was to evaluate the efficacy of short-term hormonal treatments using Norgestomet reused implants on the estrous cycle control in dairy goats. Thirty five goats were divided in five homogeneous groups of seven animals each one. All female from the groups T1, T2 and T3 received 1/3 of Norgestomet implant of 1st, 2nd and 3rd use, respectively, + eCG (260 IU) + cloprostenol (75 μg); in the T4 group, ½ Norgetomet implant of 2nd use + eCG (260 IU) + cloprostenol (75 μg) and the T5 group, sponge impregnated with MAP + eCG (260 IU) + cloprostenol (75 μg). The AI was developed 45±1 hours after finishing hormonal treatment. In data analysis the Qui-square test was used to compare hot female number and pregnant rate while the characteristics: the final interval of the treatmentonset estrus (FT-OE), and estrus length (EL), were compared by Duncan tests using the statistic software (SAEG, 2000). The estrus behavior was observed in 100.0%, 85.7%, 85.7%, 100.0% and 100.0% of goats from T1 to T5 groups, respectively. The FT-OE intervals in the T3 and T4 (17.0±5.9 h and 15.4±9.1 hours) were smaller (P<0.05) than T1, T2 and T5 groups (29.1±15.3; 23.0±7.0 and 30.0±6.9 hours; in the same order), which did not differ from each other. The T1 and T3 groups, showed a bigger and a smaller variation on the FTOE interval, respectively (48 and 12 hours). The estrus length was similar in all groups (24.9±9.4; 28.0±9.8; 27.0±6.3; 22.3±5.7 and 24.0±6.9 hours; from T1 to T5). The pregnant rate of the T3 group (14.3%) was smaller (P<0.05) than other groups T1, T2 and T5 that did not differ from each other (71.4%; 71.4%; 85.7% and 71.4%, to T1, T2, T4 and T5, respectively). In conclusion, the use of 1/3 of 3rd use implant, although being effective for estrus induction, it doesn’t provide a satisfactory pregnant rate. On the other hand, the fractions of 1/3 of 1st and 2nd use implant of Norgestomet are efficient for estrus and ovulation synchronization, making possible to achieve satisfactory pregnant rate and recommend its use in fixed-time artificial insemination programs in dairy goats.
On label dependence in multilabel classification

The aim of this paper is to elaborate on the important issue of label dependence in multi-label classication (MLC). Looking at the problem from a statistical perspective, we claim that two dieren t types of label dependence should be distinguished, namely conditional and unconditional. We formally explain the dierences and connections between both types of dependence and illustrate them by means of simple examples. Moreover, we given an overview of state-of-the-art algorithms for MLC and categorize them according to the type of label dependence they seek to capture.
Development of an Omnidirectional Walk Engine for Soccer Humanoid Robots

Humanoid soccer robots must be able to carry out their tasks in a highly dynamic environment which requires responsive omnidirectional walking. This paper explains a new omnidirectional walking engine for a humanoid soccer robot that mainly consists of a foot planner, a zero moment point (ZMP) trajectory generator, a centre of mass (CoM) calculator and an active balance feedback loop. An analytical approach is presented for generating the CoM trajectory, in which the cart-table motion of the equations is solved using the Fourier approximation of the ZMP. With this approach, we propose using a new time segmentation approach in order to parametrize the double-support phase. An active balance method is also proposed which keeps the robot's trunk upright when faced with environmental disturbances.The walking engine is tested on both simulated and real NAO robots. Our results are encouraging given the fact that the robot performs favourably, walking quickly and in a stable manner in any direction in comparison.