Miracle-dz/UniFAR-FTUs huggingface dataset:
Novel Adaptive Equalization Techniques for a Transmit Diversity Scheme

Space-time block coding (STBC) has added a new dimension to broadband wireless communication systems. Applications such as wireless Internet access and multimedia require the transmission of high data rates over frequency selective fading channels. The reliability of the wireless communication system can be increased by using diversity techniques combined with an equalizer at the receiver to eliminate the inter-symbol interference caused by multipath propagation. Generalizing Alamouti’s famous STBC method to frequency selective channels, Time Reversal-Space Time Block Coding (TRSTBC) was first introduced in [1] and has since been shown to be an effective transmit diversity scheme [2, 3, 4]. TR-STBC-based schemes are considered promising candidates for indoor transmission [5] as well as for the enhanced data rates of the global evolution (EDGE) system [2, 3]. The optimal equalizer for a TR-STBC-based transceiver is the Maximum Likelihood Sequence Estimator (MSLE), realized using the Viterbi algorithm. Unfortunately, a Viterbi equalizer is difficult to implement in real-time due its exponential increase in complexity with the number of antennas and the length of the channel impulse response. Thus, we consider an adaptive algorithm-based Decision Feedback Equalizer (DFE). Such a DFE requires only linear processing complexity while maintaining good performance. Theoretically, the two output streams of a 2× 1 TR-STBC decoder are uncoupled in terms of the input signal statistics and uncorrelated in terms of the channel noise statistics. The standard approach to removing the inter-symbol interference from these streams is to use either two parallel independently-adapted Single-Input Single-Output (SISO) equalizers or to use a single Multiple-Input Multiple-Output (MIMO) equalizer. By exploiting the common second-order statistics of the two output streams, we propose
Independent storage of different features of real-world objects in long-term memory.

People can store thousands of real-world objects in visual long-term memory with high precision. But are these objects stored as unitary, bound entities, as often assumed, or as bundles of separable features? We tested this in several experiments. In the first series of studies, participants were instructed to remember specific exemplars of real-world objects presented in a particular state (e.g., open/closed, full/empty, etc.), and then were asked to recognize either which exemplars they had seen (e.g., I saw this coffee mug), or which exemplar-state conjunctions they had seen (e.g., I saw this coffee mug and it was full). Participants had a large number of within-category confusions, for example misremembering which states went with which exemplars, while simultaneously showing strong memory for the features themselves (e.g., which states they had seen, which exemplars they had seen). In a second series of studies, we found further evidence of independence: participants were very good at remembering which exemplars they had seen independently of whether these items were presented in a new or old state, but the same did not occur for features known to be truly holistically represented. Thus, we find through 2 lines of evidence that the features of real-world objects that support exemplar discrimination and state discrimination are not bound, suggesting visual objects are not inherently unitary entities in memory. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
Wavelet-based speech enhancement : a statistical approach

Speech enhancement is the process of removing background noise from speech signals. The equivalent process for images is known as image denoising. While the Fourier transform is widely used for speech enhancement, image denoising typically uses the wavelet transform. Research on wavelet-based speech enhancement has only recently emerged, yet it shows promising results compared to Fourier-based methods. This research is enhanced by the availability of new wavelet denoising algorithms based on the statistical modelling of wavelet coefficients, such as the hidden Markov tree. The aim of this research project is to investigate wavelet-based speech enhancement from a statistical perspective. Current Fourier-based speech enhancement and its evaluation process are described, and a framework is created for wavelet-based speech enhancement. Several wavelet denoising algorithms are investigated, and it is found that the algorithms based on the statistical properties of speech in the wavelet domain outperform the classical and more heuristic denoising techniques. The choice of wavelet influences the quality of the enhanced speech and the effect of this choice is therefore examined. The introduction of a noise floor parameter also improves the perceptual quality of the wavelet-based enhanced speech, by masking annoying residual artifacts. The performance of wavelet-based speech enhancement is similar to that of the more widely used Fourier methods at low noise levels, with a slight difference in the residual artifact. At high noise levels, however, the Fourier methods are superior.
Probabilistic Analysis of Temporal and Sequential Aspects of Activities of Daily Living for Abnormal Behaviour Detection

This paper presents a probabilistic approach for the identification of abnormal behaviour in Activities of Daily Living (ADLs) from dense sensor data collected from 30 participants. The ADLs considered are related to preparing and drinking (i) tea, and (ii) coffee. Abnormal behaviour identified in the context of these activities can be an indicator of a progressive health problem or the occurrence of a hazardous incident. The approach presented considers the temporal and sequential aspects of the actions that are part of each ADL and that vary between participants. The average and standard deviation for the duration and number of steps of each activity are calculated to define the average time and steps and a range within which a behaviour could be considered as normal for each stage and activity. The Cumulative Distribution Function (CDF) is used to obtain the probabilities of abnormal behaviours related to the early and late completion of activities and stages within an activity in terms of time and steps. Analysis shows that CDF can provide precise and reliable results regarding the presence of abnormal behaviour in stages and activities that last over a minute or consist of many steps. Finally, this approach could be used to train machine learning algorithms for abnormal behaviour detection.
Have FSRs Got News for You? Evidence from the Impact of Financial Stability Reports on Market Activity

We investigate the impact that the publication of the Bank of England’s Financial Stability Report (FSR) has on the stock returns and credit default swap spreads of UK financial institutions. Examining a sample of 73 UK-listed banks and other financial institutions, we find that publication of the FSR is, on average, associated with no abnormal returns. We extend our analysis to examine the extent to which policies and the sentiment in the FSR are predictable, which would explain the observed lack of abnormal returns. We find that both sentiment and announced policies are predictable. We also examine the extent to which the release of the FSR reduces information asymmetry in financial markets, but do not find strong evidence.
A Guide to Educating Different Generations in South Africa

The majority of academics teaching Information Systems today were born somewhere between 1943 and 1981 (Baby Boomers or Generation X), while the majority of students were born after 1982 (Net Generation or iGeneration). One generation is always tasked with educating another generation, which has different likes and dislikes. This paper reviews papers written on educating the two different generations in South Africa, what academics (Baby Boomers and Generation X) need to know to better educate students (Net Generation and iGeneration). Six South African papers on learning preferences, and use of Information and Communication Technology (ICT) were reviewed. Over 1500 university students in 7 South African Universities, plus 122 IS academics were involved. Gaps in perceptions and usage were identified between generations, and recommendations made as how to treat the gaps to better facilitate the education of the Net and iGenerations. Vodcasting (video on demand) was introduced to a first year class of 605 students in 2011 at the University of Cape Town, South Africa as a learning supplement. At the end of the course, students were surveyed on amongst other issues, the benefits of vodcasting. The study revealed that the students favoured the use of interactive, practical and visual learning styles. The academics underestimated the students’ affinity for interactive and online learning, and failed to grasp the effects of the use of mobile phones and social networking on students learning styles.
Performance comparison of iterative/integral equalizer/decoder structures for underwater acoustic channels

The use of an adaptive decision feedback equalizer (DFE) in the demodulation of high speed data transmitted through underwater acoustic channels has been well established. In many channels, however, the performance obtained with the conventional DFE and decoder is not adequate for particular applications. This paper considers four different iterative equalization/decoder techniques for improving the performance of the receiver. One technique uses the hard decisions from the decoder output to feed back to the DFE for making additional passes through the data. The second technique uses the soft outputs from the decoder output to feed back to the DFE. The third technique, termed an integral iterative equalization scheme, is designed to mitigate and correct the errors being fed back to the DFE in a block fashion within the data packet. Finally, the fourth technique, called a turbo equalizer, is an iterative scheme which employs a MAP equalizer and a MAP decoder. These iterative/integral equalization/decoding techniques are applied to convolutionally encoded BPSK and QPSK data received during several field tests. The performance of the iterative equalizer/decoder algorithms is compared on the basis of bit error rate and packet statistics.
SUPPORT VECTOR MACHINE AND DECISION TREE BASED CLASSIFICATION OF SIDE-SCAN SONAR MOSAICS USING TEXTURAL FEATURES

Abstract. The diversity and heterogeneity of coastal, estuarine and stream habitats has led to them becoming a prevalent topic for study. Woody ruins are areas of potential riverbed habitat, particularly for fish. Therefore, the mapping of those areas is of interest. However, due to the limited visibility in some river systems, satellites, airborne or other camera-based systems (passive systems) cannot be used. By contrast, sidescan sonar is a popular underwater acoustic imaging system that is capable of providing high- resolution monochromatic images of the seafloor and riverbeds. Although the study of sidescan sonar imaging using supervised classification has become a prominent research subject, the use of composite texture features in machine learning classification is still limited. This study describes an investigation of the use of texture analysis and feature extraction on side-scan sonar imagery in two supervised machine learning classifications: Support Vector Machine (SVM) and Decision Tree (DT). A combination of first- order texture and second-order texture is investigated to obtain the most appropriate texture features for the image classification. SVM, using linear and Gaussian kernels along with Decision Tree classifiers, was examined using selected texture features. The results of overall accuracy and kappa coefficient revealed that SVM using a linear kernel leads to a more promising result, with 77% overall accuracy and 0.62 kappa, than SVM using either a Gaussian kernel or Decision Tree (60% and 73% overall accuracy, and 0.39 and 0.59 kappa, respectively). However, this study has demonstrated that SVM using linear and Gaussian kernels as well as a Decision Tree makes it capable of being used in side-scan sonar image classification and riverbed habitat mapping.
Making Peace or Holding a Grudge? The Role of Publics' Forgiveness in Crisis Communication

This study examines whether organizations can restore reputations and financial performance damaged by crises by seeking forgiveness from publics. This study also investigates the mechanism of forgiveness seeking by testing the effectiveness of crisis communication strategies in different situations. An experiment involving an information security crisis ( N = 800) found that substantive accommodative strategies (i.e., compensation and corrective action) are more effective at winning forgiveness than symbolic accommodative strategies (i.e., apology and showing regards). The effects of accommodative strategies on forgiveness vary in different conditions of severity and precrisis satisfaction.
Principal Sorting and the Distribution of Principal Quality

Numerous studies document the inequitable distribution of teacher quality across schools. We focus instead on the distribution of principal quality, examining how multiple proxies for quality, including experience, teachers’ survey assessments of leaders, and rubric-based practice ratings assigned by principals’ supervisors, vary by measures of school advantage, using administrative data from Tennessee. By virtually every quality measure, we find that schools serving larger fractions of low-income students, students of color, and low-achieving students are led by less qualified, less effective principals. These patterns persist across urban, suburban, and rural settings. Both differential hiring/placement and differential turnover patterns by principal quality across school characteristics contribute to these patterns. Simulation evidence suggests that hiring and turnover vary in relative importance to principal sorting patterns according to the measure of quality examined and that differential principal improvement across contexts may matter as well. Complementary analyses of national survey data corroborate our main results.
Variable orthogonality factor: a simple interface between link and system level simulation for high speed downlink packet access

Detailed simulations of the full physical layer operation of a cellular network are usually performed in two stages, link level and system level. Emergence of new link adaptation and radio resource management techniques together with need for higher modeling accuracy are blurring the line separating these stages. In this paper we address the issue of performing a link level/system level separation and defining the interface between them for simulating high speed downlink packet access (HSDPA), a part of WCDMA standard. The main challenge is to model frequency selective fading on the system level, while retaining the Rake receiver on the link level. We present available strategies and propose a novel interface based on variable orthogonality factor (OF), which serves as a compact description of the momentary channel impulse response. Finally, we present HSDPA simulation results demonstrating the high accuracy of our approach.
Monetary and fiscal interactions : a behavioral DSGE model for Brazil

This dissertation builds a behavioral dynamic stochastic general equilibrium DSGE model for the Brazilian economy to study monetary and fiscal policies interactions, under different policy regimes. Behavioral in this case means economic agents such as consumers and firms are rationally bounded or inattentive to future events. The model is inspired by Gabaix [2018], who constructed a micro founded behavioral New Keynesian model. In order to incorporate Brazil’s economic policy, fiscal and monetary authorities are designed to follow the country’s current rules of government primary budget surplus and inflation targeting as done in the SAMBA model by Castro et al. [2011]. A Bayesian estimation is then conducted to find proper parameters based on Brazilian historical data. In particular, Gabaix’s cognitive discount factors for consumers and firms, M and M f , respectively, are estimated for the country’s economy for the first time under different model specifications and briefly compared with the author’s results. In the main specification, M and M f estimations are 0.7580 and 0.8649, respectively. The model then is set to simulate monetary and fiscal dominance situations by changing certain parameter values. Based on the model’s variance results for product and inflation, which are used as proxies for social welfare, this dissertation’s results also include: (i) under monetary dominance, the central bank should fiercely pursue its targets while the fiscal authority should consider its objectives carefully not to cause instability in the economy’s product and prices; and (ii) under fiscal dominance, the central bank should accommodate for fiscal policy and public debt trajectory while it carefully chooses its responses to inflation, so that it does not cause higher inflation variances.
The pattern of contact lens uses among university female students at Hafr Al-Batin university, Saudi Arabia

Background: Contact lens (CL) are widely used in Saudi Arabia, and interest in the lens among the population is increasing rapidly especially among the younger population. CL has become more important as an optical correction method. Many people compromise their visual health due to bad habits for wearing a contact lens.Aim: The present study aimed to assess the pattern of CL uses among university female students.Methods: Descriptive cross-sectional study design was used. 225 students were agreed to participate in the study from four colleges. A structured questionnaire was developed to collect necessary information regarding; socio-demographic characteristics, history of using CL and eye complains.Results: The findings revealed that the majority 74.7% of university students using lens mostly for cosmetic purpose and 45.2% wear CL from 5-12/day.Conclusions: Based on the results of the present study, health education programs incorrect and careful practice regarding CL wear should be directed to the university students to prevent complications resulting from the wearer's inappropriate behavior.
Heterogeneous effects of single monetary policy on unemployment rates in the largest EMU economies

This paper studies the effects of monetary policy on the national rates of unemployment in Germany, France, Italy and Spain, the four largest economies of the European Monetary Union (EMU), since the introduction of the euro in 1999 and before and after the Global Financial Crisis (GFC) of 2007-09. Estimating and simulating a version of a canonical medium-scale New Keynesian dynamic stochastic general equilibrium (DSGE) model with indivisible labor that incorporates unemployment developed by Gali, Smets and Wouters (2012), the paper compares the relative importance of monetary policy shocks, risk premium shocks, wage markup shocks and labor supply shocks and studies their effects on other labor market variables, such as labor force participation and real wages. We find that the same monetary policy of the European Central Bank (ECB) has had heterogeneous effects on unemployment rates and other labor market variables in these four major EMU economies. Moreover, in all of them monetary policy shocks are the second largest source of unemployment rate variability in the short, medium and long run, only preceded by risk premium shocks. Our results also confirm that the post-GFC zero lower bound environment has rendered ECB's interest rate policy much less powerful in affecting EMU unemployment rates. In addition to the heterogeneity documented in the effects of monetary policy along various labor market dimensions across the countries in our sample, we also reveal that the EMU economies are, further, characterized by important differences along these dimensions with respect to the United States (US).
Power Characteristics of Wireless Charging for Sensor Networks in Tunnels

In order to generate wireless microwave power charging technology in coal mine tunnels, it is necessary to know the power characteristics of wireless electromagnetic wave along the tunnel walls. In this paper, the experimental results of narrowband wireless electromagnetic wave propagation measurements are presented, and a statistical model of the power characteristics at 2.4 GHz in real rectangular mine tunnels is proposed. Two standard half-wave dipole antennas were used to perform the field experiments in tunnels with different wall materials. A 10-meter wireless charging distance belongs to the free-space propagation zone. The path loss exponents rely heavily on the location of the receiver and antenna polarizations. To obtain more power, the locations of the receiver should match the corresponding polarizations.
PROSPECTIVE SECONDARY TEACHERS' BELIEFS ABOUT MATHEMATICAL PROBLEM SOLVING

The main purpose of this study was to explore prospective teachers' beliefs on mathematical problem solving. This research was a survey study that uses a questionnaire to collect data from prospective secondary teachers at the Faculty of Education. The data was analyzed using Statistical Packages for Social Sciences (SPSS) version 16.0. Findings from this study reveals the following; that majority of prospective mathematics teachers held positive beliefs on the importance of understanding mathematics problems, problems with multiple ways of solution, the kind of mathematics instruction that are emphasized by the principles of new mathematics curriculum. Considering the aforementioned findings from analysis of questionnaires the study concludes that; those prospective mathematics teachers' beliefs about mathematical problem solving have strong connection to their study level and prospective teachers have both traditional and contemporary views about mathematical problem solving. In view of the study findings and conclusions, the researcher advice educational policy makers to ensure that more researches on teacher beliefs are conducted and an ongoing mathematical problem solving beliefs assessment should be a major component at Teacher Training Institutes. Teacher educators should raise student teachers' awareness about mathematical problem solving once they join programs. A revision of teachers' mathematics pedagogical courses and content courses should be a continuous process at Universities of Education. Keyword: Beliefs, Prospective Teachers, Mathematical Problem solving, Secondary Students, Malaysia.
From monitoring users to controlling user actions: A new perspective on the user-centred approach to CALL

It is argued in this article that user actions need to be monitored to understand what has happened during the learning process. Monitoring on its own is not enough; user actions also need to be controlled to some degree so that users can receive the guidance they need to help them to the successful completion of the learning tasks in CALL programs. To verify this empirically, a study was conducted to investigate both learning outcome and learning process of two versions of a Computer Assisted Vocabulary Learning program for Chinese learners. In one version, the user actions were controlled and guided; in the other, the user had complete freedom in deciding how to use the program. The results show that both the learning outcome and the learning process were more satisfactory in the controlled condition than in the uncontrolled condition.