Miracle-dz/UniFAR-FTUs huggingface dataset:
Novel Materialized View Selection in a Multidimensional Database

A multidimensional database is a data repository that supports the efficient execution of complex business decision queries. Query response can be significantly improved by storing an appropriate set of materialized views. These views are selected from the multidimensional lattice whose elements represent the solution space of the problem. Data analysis applications typically aggregate data across many dimensions looking for anomalies or unusual patterns. The SQL aggregate functions and the GROUP BY operator produce zero-dimensional or one-dimensional aggregates. Multidimensional databases store data in multidimensional structure on which analytical operations are performed. A challenge for these systems is how to handle large data sets in a large number of dimensions. Several techniques have been proposed in the past to perform the selection of materialized views for databases with a reduced number of dimensions. When the number and complexity of dimensions increase, the proposed techniques do not scale well. The technique we are proposing not only will reduce the solution space by considering only the relevant elements of the multidimensional lattice and further will support multiple query execution there by reducing the time of result generation and is scalable.
Professors use technology to fight plagiarism

It has become technology versus technology as teachers wage a new type of war against plagiarism. Instructors looking for new ways to fight the problem are turning to plagiarism-detection software, which in turn is becoming increasingly sophisticated. Teachers are utilizing the software to determine when students have used "paper mill" Web sites containing fully written essays, hired someone to write a paper for them, or used cut-and-paste functionality to copy material from digital documents. Demand for the software is also increasing outside academia. For example, publishers use the technology to determine whether submitted articles or books are original material. In addition, institutions are using the software to determine whether research by employees is original.
Quantitative analysis of algorithms for compressed signal recovery

Compressed Sensing (CS) is an emerging paradigm in which signals are recovered from undersampled nonadaptive linear measurements taken at a rate proportional to the signal’s true information content as opposed to its ambient dimension. The resulting problem consists in finding a sparse solution to an underdetermined system of linear equations. It has now been established, both theoretically and empirically, that certain optimization algorithms are able to solve such problems. Iterative Hard Thresholding (IHT) (Blumensath and Davies, 2007), which is the focus of this thesis, is an established CS recovery algorithm which is known to be effective in practice, both in terms of recovery performance and computational efficiency. However, theoretical analysis of IHT to date suffers from two drawbacks: state-of-the-art worstcase recovery conditions have not yet been quantified in terms of the sparsity/undersampling trade-off, and also there is a need for average-case analysis in order to understand the behaviour of the algorithm in practice. In this thesis, we present a new recovery analysis of IHT, which considers the fixed points of the algorithm. In the context of arbitrary matrices, we derive a condition guaranteeing convergence of IHT to a fixed point, and a condition guaranteeing that all fixed points are ‘close’ to the underlying signal. If both conditions are satisfied, signal recovery is therefore guaranteed. Next, we analyse these conditions in the case of Gaussian measurement matrices, exploiting the realistic average-case assumption that the underlying signal and measurement matrix are independent. We obtain asymptotic phase transitions in a proportional-dimensional framework, quantifying the sparsity/undersampling trade-off for which recovery is guaranteed. By generalizing the notion of fixed points, we extend our analysis to the variable stepsize Normalised IHT (NIHT) (Blumensath and Davies, 2010). For both stepsize schemes, comparison with previous results within this framework shows a substantial quantitative improvement. We also extend our analysis to a related algorithm which exploits the assumption that the underlying signal exhibits tree-structured sparsity in a wavelet basis (Baraniuk et al., 2010). We obtain recovery conditions for Gaussian matrices in a simplified proportional-dimensional asymptotic, deriving bounds on the oversampling rate relative to the sparsity for which recovery is guaranteed. Our results, which are the first in the phase transition framework for tree-based CS, show a further significant improvement over results for the standard sparsity model. We also propose a dynamic programming algorithm which is guaranteed to compute an exact tree projection in low-order polynomial time.
Effective Student Outcomes: A Comparison of Online and Face-to-Face Delivery Modes

This study compares outcome measures for identical courses offered in two delivery modes. One delivery mode is Web-based, online, and asynchronous, and the other is face-to-face and synchronous. Outcome measures for both modes include gain scores (difference between pretest and posttest knowledge), grade expressed as a percentage, and student satisfaction. These outcome measures are used to determine whether online students learn as effectively as face-to-face students. Analysis of the data suggests that online students are gaining knowledge comparable to the face-to-face students and that the online students are as satisfied on most dimensions as the face-to-face students. Kolb's Learning Style instrument is utilized to determine if one learning style lends itself better to online learning than other styles.
On iterative learning from different tracking tasks in the presence of time-varying uncertainties

In this paper, we introduce a new iterative learning control (ILC) method, which enables learning from different tracking control tasks. The proposed method overcomes the imitation of traditional ILC in that, the target trajectories of any two consecutive iterations can be completely different. For non-linear systems with time-varying and time-invariant parametric uncertainties, the new learning method works effectively to nullify the tracking error. To facilitate the learning control system design and analysis, in the paper we use a composite energy function (CEF) index, which consists of a positive scalar function and L2 norm of the function approximation error.
Data condentiality and keyword search in the cloud using visual cryptography

Security has emerged as the most feared aspect of cloud computing and a major hindrance for the customers. Current cloud framework does not allow encrypted data to be stored due to the absence of efficient searchable encryption schemes that allow query execution on a cloud database. Storing unencrypted data exposes the data not only to an external attacker but also to the cloud provider itself. Thus, trusting a provider with confidential data is highly risky. To enable querying on a cloud database without compromising data confidentiality, we propose to use data obfuscation through visual cryptography. A new scheme for visual cryptography is developed and configured for the cloud for storing and retrieving textual data. Testing the system with query execution on a cloud database indicates full accuracy in record retrievals with negligible false positives. In addition, the system is resilient to attacks from within and outside the cloud. Since standard encryption and key management are avoided, our approach is computationally efficient and data confidentiality is maintained.
High-power THz-waves using gyrotrons: new physics results

Gyrotrons are high-power coherent radiation sources based on the cyclotron maser instability. Since more than three decades the research and development of gyrotrons has been essentially driven from the need of high-power MW-level sources in the THz frequency range (0.1-1 THz) for electron cyclotron resonance heating of magnetically confined plasmas such as in ITER and DEMO. A more recent spin-off research activity has led to the development of lower power (1-100 W) gyrotrons with frequencies belonging to the THz domain. One of the main applications in the THz domain is in the field of Dynamic Nuclear Polarization Nuclear Magnetic Resonance spectroscopy (DNP/NMR). With a THz gyrotron oscillator developped for DNP/NMR spectroscopy and operating at 260 GHz, novel operational regimes have been recently experimentally demonstrated in which the non-linear interaction excites a finite number of side-bands and eventually ends in a chaotic dynamics of the THz radiation field. The route to chaos via a period doubling cascade dynamics is experimentally observed and is supported by numerical simulations. In presence of phase-locked frequency-equidistant side-bands, a novel regime characterized by high-power nanosecond pulses is experimentally observed and is associated to a self-consistent Q-switch mechanism in which the cavity diffraction quality factor dynamically varies by nearly two orders of magnitude on a subnanosecond timescale. This novel regime is also well predicted with the self-consistent TWANG code and may open up new applications for gyrotrons.
1. LISTENING TO LEARN OR LEARNING TO LISTEN?

Listening is probably the least explicit of the four language skills, making it the most difficult skill to learn. This chapter begins with a brief overview of cognitive processes involved in listening and their implications for L2 listening instruction. Recent research (1998–2003) on a variety of instructional techniques to help L2 listeners process linguistic input is then reviewed, noting insights that can inform listening instruction, particularly techniques that can teach students how to listen. Two approaches to listening instruction are presented: an approach to raise metacognitive awareness about listening (favoring top-down processes) and an approach to develop lexical segmentation and word recognition skills (favoring bottom-up processes). An integrated model for L2 listening instruction is proposed. Finally, recent research on different types of listening (e.g., academic listening, bidirectional listening) and the sociolinguistic dimension of listening are reviewed. The chapter concludes with recommendations for future research. The basic premise underlying this chapter is that, given the critical role of listening in language learning, students need to “learn to listen” so that they can better “listen to learn. ”
The Effectiveness of Web-Based Instruction in Supporting Teachers in Implementing Inquiry-Based Instruction

THE EFFECTIVENESS OF WEB-BASED INSTRUCTION IN SUPPORTING TEACHERS IN IMPLEMENTING INQUIRY-BASED INSTRUCTION By Amanda Jane Harris Byers The purpose of this paper was to investigate the effectiveness of a web-based learning environment in supporting the participants in implementing a new instructional technique. This paper also investigated the expectations of those participants enrolled in the web-based learning environment. The data in this study was obtained during a previous study of a graduate-level on-line course. Pre and post-surveys were given to the participants of the course and a group of teachers who had participated in a previous, more traditional course. The data was analyzed through MANCOVA and ANCOVA. Open-ended questions were summarized to obtain more information about the expectations of the course. The results showed that those who participated in the webbased course felt more supported in implementing the instructional technique in their classrooms than those who had not participated. Qualitative analysis resulted in a variety of course expectations listed by those enrolled in the web-based learning environment. THE EFFECTIVENESS OF WEB-BASED INSTRUCTION IN SUPPORTING TEACHERS IN IMPLEMENTING INQUIRY-BASED INSTRUCTION A Thesis Submitted to the Faculty of Miami University in partial fulfillment of the requirements for the degree of Educational Specialist Department of Educational Psychology by Amanda Jane Harris Byers Miami University Oxford, OH 2005 Advisor_________________________ Aimin Wang, Ph.D. Reader__________________________ Doris Bergen, Ph.D. Reader__________________________ David Shriberg, Ph.D. Reader__________________________ Alfred Joseph, Ph.D.
A study on the information seeking behaviour of Singapore-based Filipino domestic workers

This research examines the information seeking and use behaviour of Filipino domestic workers (FDWs) in Singapore, who collectively make up around 40% of about 173,000 overseas Filipino workers (OFWs) in this city state. It is based on the premise that low-paid migrants are generally typecast as ‘information poor’, who are left with very common, limiting, and homogeneous information sources. The FDWs are drawn to their co-equals to form an information ground where they can exchange information serendipitously. A survey questionnaire was administered to 138 FDWs to learn about their information behaviour and problems encountered during information seeking. A 5-day ethnographic study in their off-work context supplemented the quantitative data. The study found that FDWs inadequately meet the requisites for digital and information literacy, which are indispensable yet lacking among many low-skilled migrants. Implications about public governance, education, and the pedagogical component of technology use through streamlined information dissemination are discussed to benefit these FDWs.
Frequency, phonology, the brain, and second language acquisition: Laying the ground work for a hybrid approach

A hybrid theory of second language acquisitio n is presented, which integrates postulates of Flege’s (1992, 1995, 2003; Flege et al. 2003) Speech Learning Model and Bybee’s (2001) proposals for Usage Based Grammar. As this proposal deviates from the Generative program, which does not permit frequency as an explanatory factor, a review is given of major currents in the literature concerning frequency in phonology and theories which incorporate frequency and patterns of distribution in phonological systems. The conclusion drawn from this review is that frequency is one of many performance factors worth considering as an explanatory factor in theories of phonology. The hybrid model is discussed and extended to a problem in second language acquisition of German by native English speakers. The SLM predicts that learners will not be able to establish a sound category for German dark-schwa, a sound which is remarkably similar to English schwa. A previous study shows that this is not only possible, but a production difference between the two German schwas was documented for relatively inexperienced speakers of the language. The hybrid model accounts for this exception to the SLM by appealing to the fact that the contrast between schwa and dark schwa in German is highly frequent.
Computing probability of errors of linear multiuser detectors in white Gaussian noise and Rayleigh fading channels

We present a tool for rapidly computing the bit error rate of linear multiuser detectors. Computing bit error rates of linear multiuser detectors involves averaging the probability of error over the bits of all the users which is an exponentially complex operation. The technique presented in this paper is based on computing the Laplace inversion integral of the moment generating function of the variate which determines the probability of error of a user. We apply this technique for computing the probability of error of an arbitrary linear multiuser detector operating in an additive white Gaussian noise and in a Rayleigh fading channel.
Distributional Escape Time Algorithm Based on Generalized Fractal Sets in Cloud Environment

Since fractal is widely used in all science domains today, escape time algorithm, which is the most effective algorithm in drawing fractal figures, shows negatively when generation function is complex. In this paper, we improve classic escape time algorithm into cloud environment to improve its performance. At first, we provide a separation method of escape algorithm in cloud environment. Then we calculate complexity of the novel algorithm with a probability model based on allocation policy. At last, we use generalized fractal sets as experimental subjects to validate our conclusion. Experimental results show correctness and rapidness of the novel algorithm.
Paroxetine in the Treatment of Primary Insomnia: Preliminary Clinical and Electroencephalogram Sleep Data

Patients with major affective disorders are more likely to complete suicide than patients in any other medical group. Established risk factors for completed suicide in affective disorders include acute depression (with turmoil, hopelessness, global insomnia, anhedonia, anxiety and/or panic), mixed episodes, rapid cycling, substance abuse, aggression and/or impulsivity, low serotonergic activity, and hypothalamic-pituitary-adrenal axis activation. Although anticonvulsants have mood-stabilizing and antidepressant properties, few data are available on the antisuicide effects of anticonvulsant treatment in manic-depressive patients. On the other hand, as reviewed elsewhere in this issue, massive data have been accumulated on the antisuicide effect of lithium. This article discusses lithium versus anticonvulsants in the prevention of suicide associated with affective disorders and future treatment strategies to reduce this most serious complication of manic-depressive illness.
A multi-resolution assessment of the Community Multiscale Air Quality (CMAQ) model v4.7 wet deposition estimates for 2002–2006

Abstract. This paper examines the operational performance of the Community Multiscale Air Quality (CMAQ) model simulations for 2002–2006 using both 36-km and 12-km horizontal grid spacing, with a primary focus on the performance of the CMAQ model in predicting wet deposition of sulfate (SO4=), ammonium (NH4+) and nitrate (NO3−). Performance of the wet deposition estimates from the model is determined by comparing CMAQ predicted concentrations to concentrations measured by the National Acid Deposition Program (NADP), specifically the National Trends Network (NTN). For SO4= wet deposition, the CMAQ model estimates were generally comparable between the 36-km and 12-km simulations for the eastern US, with the 12-km simulation giving slightly higher estimates of SO4= wet deposition than the 36-km simulation on average. The result is a slightly larger normalized mean bias (NMB) for the 12-km simulation; however both simulations had annual biases that were less than ±15 % for each of the five years. The model estimated SO4= wet deposition values improved when they were adjusted to account for biases in the model estimated precipitation. The CMAQ model underestimates NH4+ wet deposition over the eastern US, with a slightly larger underestimation in the 36-km simulation. The largest underestimations occur in the winter and spring periods, while the summer and fall have slightly smaller underestimations of NH4+ wet deposition. The underestimation in NH4+ wet deposition is likely due in part to the poor temporal and spatial representation of ammonia (NH3) emissions, particularly those emissions associated with fertilizer applications and NH3 bi-directional exchange. The model performance for estimates of NO3− wet deposition are mixed throughout the year, with the model largely underestimating NO3− wet deposition in the spring and summer in the eastern US, while the model has a relatively small bias in the fall and winter. Model estimates of NO3− wet deposition tend to be slightly lower for the 36-km simulation as compared to the 12-km simulation, particularly in the spring. The underestimation of NO3− wet deposition in the spring and summer is due in part to a lack of lightning generated NO emissions in the upper troposphere, which can be a large source of NO in the spring and summer when lightning activity is the high. CMAQ model simulations that include production of NO from lightning show a significant improvement in the NO3− wet deposition estimates in the eastern US in the summer. Overall, performance for the 36-km and 12-km CMAQ model simulations is similar for the eastern US, while for the western US the performance of the 36-km simulation is generally not as good as either eastern US simulation, which is not entire unexpected given the complex topography in the western US.
On the RAKE receiver performance

In this paper we study the RAKE receiver performance for the UMTS FDD mode. We begin by investigating the amount of diversity that we can recover from paths with delays separated by less than the chip period. Then, we evaluate the RAKE performance degradation caused by channel estimation noise. Finally, we study the influence of intersymbol interference for small spreading factors.
Preliminary insights into the influence of mobile phones in micro-trading activities of market women in Nigeria

This paper explores the influence of mobile phones on the micro-trading activities of women traders in Nigeria. This exploratory study adopts a qualitative research approach. A theoretical model based on the Technology Acceptance Model is used to analyse two case studies of the micro-trading activities of Nigerian market women. The findings suggest that, first, the benefits obtained by market women tend to be partly influenced by the extent of mobile access and usage by trading partners in their value chain. Second, the knowledge of the trader plays a critical role in determining the type of mobile functionality used. Market women who innovatively integrate mobile services, like mobile banking, stand to reform their market structural processes and become more economically empowered. In micro-trading activities, enhancing communication and trading processes through mobile phones improves revenue acquisition and enhances decision making and control. The research concludes with an emphasis for research and practice to increase the mobile capabilities of those at the ‘bottom of the pyramid’ to beyond voice calls and text messaging. Research propositions and lessons for future research are also outlined. This paper generates new insights about the usage of mobile telephony for the enhancement of economic effectiveness of micro-traders.
What Helps TESOL Methods Students Learn: Using Q Methodology to Investigate Students' Views of a Graduate TESOL Methods Class

The direction of university courses is often guided by the results of traditional Likert scale student evaluations. Most of these focus on instructors’ characteristics and frequently do not provide useful insights into students’ learning preferences or feedback regarding specific activities and projects in the courses. This study, carried out in a Midwestern U.S. university, reports the use of Q methodology to capture students’ views of 35 activities in a graduate TESOL (Teaching English to Speakers of Other Languages) Methods course as to which were most helpful and least helpful to learning course content. During the last class of the semester 19 students carried out Q sorts about different aspects of the methods course. Factor analysis showed how participants grouped onto 3 factors, expressing 3 unique views on how helpful the 35 different course activities were to their learning. The majority of the students were “group-centered learners” who learned best through various face-to-face interactions with classmates. Two were “self-centered learners” who learned best by working independently, then receiving feedback. One learned best through the course’s online activities. Analysis of students’ different views helped researchers determine whether to redesign various aspects of the course to meet different learning preferences.