Miracle-dz/UniFAR-FTUs huggingface dataset:
Teacher perceptions of the impact of public examinations on curriculum practices : a survey in two districts of Kigali-City, Rwanda.

This study is an exploratory investigation on teachers' perceptions of the extent to which the national examinations that are written at the end of primary schooling in Rwanda influence their curriculum practices. The study used a structured questionnaire for data collection, and simple descriptive statistics for data analysis. The study, firstly, examined teachers' views on the link between national examinations and the aims of primary education. The results showed that teachers perceived the national examinations as assessing the prerequisite knowledge for secondary education, on one hand; and to some extent social skills needed for life in the community and society. This is in line with the aim of primary education in Rwanda according to government policy. Secondly, the study explored the impact of the national examinations on teachers' practices as well as on teacher self image. Findings were that a good success rate in these examinations was the main goal-direction for teachers and had a major influence on the curriculum practices. Most teachers indicated that they aimed to produce a large number of candidates who were classified highly on national scale, and were socially well skilled. The impact of the national examination on their practices is evident in some of the strategies they use in negotiating and mediating the curriculum: the focus on the main examination subjects, on the previous examination topics, and on academically good and borderline students who have a greater chance of scoring high grades in the national examination. Finally, the study explored factors that teachers perceived to influence candidates' success and failure in the national examinations. Teacher commitment to preparing candidates for the examinations was most frequently reported, as a factor associated with student success, whereas the very limited places
InP DHBT Distributed Amplifiers With Up to 235-GHz Bandwidth

Three wideband amplifiers in double-heterojunction bipolar transistor technology have been designed and measured. The amplifiers use different types of distributed amplifier (DA) topologies, all based on cascode gain cells. A single-stage DA design achieves 7.5-dB gain and 192-GHz bandwidth and a two-cascaded single-stage DA achieves an average gain of 16 dB with a bandwidth of 235 GHz. The third circuit is a conventional DA with more than 10-dB gain from 70 kHz up to 180 GHz. To the authors' best knowledge, the single-stage DA and the two-cascaded single-stage DA are the widest band amplifiers in any technology reported to date. Furthermore, the conventional DA has a record bandwidth for circuits in conventional DA topology with gain from near dc.
A Comparative Study of Usability Methods for Mobile Applications

: conducting sufficient usability test requires planning and attention to the evaluation details. In common, usability test methods for software take into considerations, planning usability questions, selecting a representative sample and recruiting participants, and preparing the test materials and actual test environment. Several issues were reported while choosing the suitable usability test method for mobile applications, especially for indicating the way for conducting the test. Therefore, this paper aims to demonstrate the most used testing methods for the evaluation purposes of mobile applications.
A-6G and A-20C Polymorphisms in the Angiotensinogen Promoter and Hypertension Risk in Chinese: A Meta-Analysis

Background Numerous studies in Chinese populations have evaluated the association between the A-6G and A-20C polymorphisms in the promoter region of angiotensinogen gene and hypertension. However, the results remain conflicting. We carried out a meta-analysis for these associations. Methods and Results Case–control studies in Chinese and English publications were identified by searching the MEDLINE, EMBASE, CNKI, Wanfang, CBM, and VIP databases. The random-effects model was applied for dichotomous outcomes to combine the results of the individual studies. We finally selected 24 studies containing 5932 hypertensive patients and 5231 normotensive controls. Overall, we found significant association between the A-6G polymorphism and the decreased risk of hypertension in the dominant genetic model (AA+AG vs. GG: P = 0.001, OR = 0.71, 95%CI 0.57–0.87, Pheterogeneity = 0.96). The A-20C polymorphism was significantly associated with the increased risk for hypertension in the allele comparison (C vs. A: P = 0.03, OR = 1.14, 95%CI 1.02–1.27, Pheterogeneity = 0.92) and recessive genetic model (CC vs. CA+AA: P = 0.005, OR = 1.71, 95%CI 1.18–2.48, Pheterogeneity = 0.99). In the subgroup analysis by ethnicity, significant association was also found among Han Chinese for both A-6G and A-20C polymorphisms. A borderline significantly decreased risk of hypertension between A-6G and Chinese Mongolian was seen in the allele comparison (A vs. G: P = 0.05, OR = 0.79, 95%CI 0.62–1.00, Pheterogeneity = 0.84). Conclusion Our meta-analysis indicated significant association between angiotensinogen promoter polymorphisms and hypertension in the Chinese populations, especially in Han Chinese.
Performance modeling of optical transmission systems through pearson fitting and multicanonical Monte-Carlo simulations

In this paper we propose and compare two different methods, based either on multicanonical Monte-Carlo (MMC) simulations or Pearson fitting, for performance evaluation of realistic wavelength-division-multiplexed (WDM) optical transmission systems. Both methods are able to account for linear and nonlinear propagation effects, and can be applied to any modulation format. As regards MMC, we estimate the distribution of the received sample, accounting for noise, inter-symbol interference (ISI) and inter-channel nonlinearities, by adopting a combined noise and pattern perturbation method. As an alternative to simulations, Gaussian or chi-square fitting techniques have been proposed in the literature. Anyway, none of them is able to provide accurate performance estimation for both on-off keying (OOK) and differential (quadrature) phase-shift keying (D(Q)PSK) modulations. In this work we show that the pdf of the received sample is well approximated by Pearson distributions in all the above-mentioned cases. Pearson distributions are completely determined by their first four moments, which can be estimated by standard Monte Carlo (MC) simulations with less computational burden than typically needed by the MMC method. Finally, for each modulation format, we assess the accuracy of the various fitting techniques by comparing the fitted distributions with those obtained by either MMC simulations in the nonlinear propagation regime, or exact analytical methods in the linear propagation regime.
Computation of invariant sets for piecewise affine discrete time systems subject to bounded disturbances

Piecewise affine (PWA) systems are useful models for describing non-linear and hybrid systems. One of the key problems in designing controllers for these systems is the inherent computational complexity of controller synthesis and analysis. These problems are amplified in the presence of state and input constraints and additive but bounded disturbances. In this paper, we exploit set invariance and parametric programming to devise an efficient robust time optimal control scheme. Specifically, the state is driven into the maximal robust invariant set /spl Omega//sub /spl infin// in minimum time. We show how to compute /spl Omega//spl tilde//sub /spl infin// and derive conditions for finite time computation.
Fast global segmentation based on the dual formulation of TV-norm

A fast global minimization segmentation model based on total variation is presented around Functional modeling and algorithm constructing. Firstly, a new active contour model is developed by maximum a-posterior probability (MAP), and a total variation model based on gradient information is constructed by the hint of geodesic active contour (GAC) model. So the improved M-S segmentation model is given by combining the upper two models. Secondly, we establish theorems on the existence of the global minimum of this model by equivalent conversion. Thirdly, a new numerical practical algorithm is given through a dual formulation of the total variation norm(TV-norm), which avoids the usual drawback of initializing and re-initializing in the active contour model. We apply our segmentation algorithms on many synthesized and real-world images, and the results show the efficiency by assigning only one or two parameters for melanoma segmenting.
More about the Difference between Men and Women: Evidence from Linear Neural Networks and the Principal-Component Approach

The ability of a statistical/neural network to classify faces by sex by means of a pixel-based representation has not been fully investigated. Simulations with pixel-based codes have provided sex-classification results that are less impressive than those reported for measurement-based codes. In no case, however, have the reported pixel-based simulations been optimized for the task of classifying faces by sex. A series of simulations is described in which four network models were applied to the same pixel-based face code. These simulations involved either a radial basis function network or a perceptron as a classifier, preceded or not by a preprocessing step of eigendecomposition. It is shown that performance comparable to that of the measurement-based models can be achieved with pixel-based input (90%) when the data are preprocessed. The effect of the eigendecomposition preprocessing of the faces is then compared with spatial-frequency analysis of face images and analyzed in terms of the perceptual information it captures. It is shown that such an examination may offer insight into the facial aspects important to the sex-classification process. Finally, the contribution of hair information to the performance of the model is evaluated. It is shown that, although the hair contributes to the sex-classification process, it is not the only important contributor.
Software-Defined mobile backhaul for future Train to ground Communication services

Software Defined Networking (SDN) has attracted tremendous interest in the telecommunication industry due to its ability to abstract, manage and dynamically re-configure end-to-end networks from a centralized controller. Though SDN is considered to be a suitable candidate for various use cases in mobile networks, none of the work so far has discussed its advantages and actual realization for Train-to-Wayside Communication System (TWC). In this paper, for the first time, the architecture and use cases of SDN controlled mobile backhauling framework for TWC is proposed. We discuss how our proposed architecture can efficiently handle mobility management and also provide dynamic quality-of-service (QoS) for different services on board. As a first step, a software prototype is developed using industrial standard OpenDayLight SDN controller to have our architecture evaluated. Since the automotive sector is being considered to be an important driver for 5G network, our SDN based mobile backhauling solution can be positioned in 5G where SDN plays an important role.
Recurrent-Neural-Network for Language Detection on Twitter Code-Switching Corpus

Mixed language data is one of the difficult yet less explored domains of natural language processing. Most research in fields like machine translation or sentiment analysis assume monolingual input. However, people who are capable of using more than one language often communicate using multiple languages at the same time. Sociolinguists believe this "code-switching" phenomenon to be socially motivated. For example, to express solidarity or to establish authority. Most past work depend on external tools or resources, such as part-of-speech tagging, dictionary look-up, or named-entity recognizers to extract rich features for training machine learning models. In this paper, we train recurrent neural networks with only raw features, and use word embedding to automatically learn meaningful representations. Using the same mixed-language Twitter corpus, our system is able to outperform the best SVM-based systems reported in the EMNLP'14 Code-Switching Workshop by 1% in accuracy, or by 17% in error rate reduction.
Automatic pipe negotiation control for snake-like robot

In this paper, the purpose is to realize self-propelling ability of a snake like robot which travels in pipes. The robot consists of thirteen intelligent actuators and each actuator has a DC motor and a micro processor including a motor driver and communication function. Three control algorithms, force control, adjusting controls to changing pipe diameter and to curved pipe are proposed and programmed in the processors. As the experimental results, automatically the robot can negotiate several kinds of pipes such as different diameter, elbow shape, T branch shape and vertical setting without overloaded.
Factors affecting hamster sarcoma growth in the cheek pouch.

Summary A methylcholanthrene-induced hamster sarcoma showed accelerated growth after transplantation to 2–3-week-old animals, in contrast to 6–8-week adult hamsters, with increased growth of metastases as well. Second transplants, after primary grafts were excised, showed delayed growth. Nidation and vascularization of second transplants were also delayed in the presence of a rapidly growing metastasis. Cortisone in the doses used showed host toxicity and delayed tumor growth.
Hardware-Accelerated Vehicle License Plate Detection at High-Definition Image

Localizing license plate in an image enables vehicle detection and identification. Processing at high-definition (HD) image allows a better access of visual information but also enhances the necessity of multi-resolution analysis because license plates may appear in various sizes and shapes. A great computational burden is accompanied by processing the great number of candidate windows during multi-resolution analysis. This paper proposes a hardwired license plate detector capable of conducting feature analysis on millions of candidate windows with the size of 100-by-100 pixel in average for one HD image. It employed a multiple-layer classification analyzing color, gradient and texture features at the rate of thirty frames per second. Candidate window fusion subsequent to classification compensates the over-detection occurred during multi-resolution analysis. A dual-loop processing is adopted to schedule the efforts in feature extraction to achieve a real-time system. Compared to the pure software implementation, a third-order speed up was found for the same algorithm with hardwired acceleration in FPGA emulation.
Design and Evaluation of Socially Just Scheduling Policies

Queueing for service occurs in technical applications as well as in common d aily life, and scheduling should manage queues in a satisfactory way. Performance metrics are influ enced by the service order, thus, scheduling policies should be designed with respect to the main performance metrics of interest. For human customers psychological effects and performance metrics other than delay play a cr ucial ole in judging a service facility. Metrics related to social justice are of major importance, where individual pe rce tions of justice are strongly coupled with an equal treatment of customers. We quantify and measure social ju stice based on two types of customer discriminations: being overtaken and long waiting for single customers with larg e service requirements. In order to improve perceived justice of customers two scheduling policies, alternating FCFS/SJF and MFD (Most Frequently Discriminated), are proposed and shown to be useful. The prize th at has to be paid to improve justice oriented queue metrics at the cost of higher expected delay or higher dela y vari bility is examined by comparing the potential increases in expected delay and delay variability to the potential in crease of social justice. A discrete event simulation study is provided for queueing systems operating under the traditional FCFS and SJF policies and under the new policies. Our results show that the new policies significan tly improve social justice without too much worsening the delay metrics and that MFD even reduces the delay varia bility. Key–Words:Queueing, Scheduling, Social Justice, Discrimination Frequency, Discre te Ev nt Simulation Study
Vision based localization of humanoid robots by inverse pose-estimation using a small set of fixed landmark features

We propose a vision based methodology to solve the robot localization problem by estimating the pose of the robot's camera with respect to a model of the environment represented by a small set of landmark features. The methodology proposed constructs a regression model based on the pinhole camera projection model by combining the information of several observed features. In this regression model the unknowns are the X and Y coordinates of the location vector of the robot with respect to the environment, and the depths of each of the observed features. We use a RoboCup Humanoid KidSize field as a test bed for experimental validation of this methodology.
Tandem-L forest parameter performance analysis

Tandem-L is a satellite mission being currently studied at DLR. It foresees the deployment of two L-band SAR platforms that will fly in close formation enabling bistatic operations. The mission is intended to serve a number of different science objectives with applications in the lithosphere, biosphere and cryosphere. The variety of applications and their competition for the use of the system require that we develope performance models suitable for system and mission design. In this paper we present the main concepts developed for height structure retrieval and performance characterization considering the combination of single pass acquisitions. We use the Cram´ Rao bound for a layered model and we study the impact of the baseline number and distribution. We also describe simulations with the Covariance Matching and Polarization Coherence Tomography techniques and argue in favor of better modeling for forest vertical structure in the case of limited number of obervations. Tandem-L is a proposal for an innovative radar mission that enables the systematic monitoring of dynamic processes on the Earth surface. Important application areas are global forest structure and forest vegetation monitoring, measurements of Earth deformation due to tectonic processes, observation of 3-D structure changes in ice, and the monitoring of ocean surface currents. The mission goals will be achieved through the deployment of two satellite platforms with quad-polarimetric L-band SARs that will be operated for five years. It is already clear that this mission is intended to serve many applications and on a global scale. At least 60 million square kilometers are involved for forest applications and some 35 millions for the global tectonic monitoring campaign. Moreover a high resolution is required. These factors make the mission design a difficult challenge in terms of instrument operation, fuel for orbit maneuvers, data rate and so on. It is therefore necessary to develope performance models for each of the main applications in order to optimize the instrument usage and mission acquisition scenario. Forest height and forest structure are two important products that we plan to derive from multi-baseline and polarimetric acquisitions. They can be considered final products in their own right but also as precursors for aboveground biomass estimation.
Real-Time Volume Visualization with VolumePro Hanspeter Pfister

Over the last decade, volume rendering has become an invaluable visualization technique for a wide variety of applications. Mitsubishi Electric’s VolumePro is the world’s first single-chip realtime volume rendering system for consumer PCs. VolumePro achieves significantly higher levels of performance and image quality than has previously existed. The system renders 500 million interpolated, Phong illuminated, composited samples per second. This is sufficient to render volumes with up to 16 million voxels (e.g.,256) at 30 frames per second. VolumePro is a breakthrough enabling technology that will revolutionize the field of volume visualization by making real-time volume rendering widely available on common PCs for the first time.
Finding Duplicates of Your Yet Unwritten Bug Report

Software projects often use bug-tracking tools to keep track of reported bugs and to provide a communication platform to discuss possible solutions or ways to reproduce failures. The goal is to reduce testing efforts for the development team. However, often, multiple bug reports are committed for the same bug, which, if not recognized as duplicates, can result in work done multiple times by the development team. Duplicate recognition is, in turn, tedious, requiring to examine large amounts of bug reports. Previous work addresses this problem by employing natural-language processing and text similarity measures to automate bug-report duplicate detection. The downside of these techniques is that, to be applicable, they require a reporting user to go through the time-consuming process of describing the problem, just to get informed that the bug is already known. To address this problem, we propose an approach that only uses stack traces and their structure as input to machine-learning algorithms for detecting bug-report duplicates. The key advantage is that stack traces are available without a written bug report. Experiments on bug reports from the Eclipse project show that our approach performs as good as state-of-the-art techniques, but without requiring the whole text corpus of a bug report to be available.
A Tone Reservation-Based Optical OFDM System for Short-Range IM/DD Transmission

This paper investigates the use of tone reservation for optical orthogonal frequency-division multiplexing (OFDM) transmission in a short-range, intensity-modulated, direct-detected (IM/DD) optical channel. Due to the unipolarity of the IM/DD channel, any asymmetric clipping of the bipolar OFDM signal and associated nonlinear distortion will result in an unfavorable dc power and significant performance penalty. Using a detailed analysis of the clipping distortion, we propose a new framework to enable IM/DD optical OFDM transmission, where certain subchannels are reserved to produce a negative peak cancellation (NPC) signal via a frequency-domain digital filter. This NPC signal guarantees a unipolar OFDM signal, hence eliminating any additional biasing and/or clipping. It also produces no in-band or out-of-and distortions and requires no transmission of any side information. Beneficial tradeoffs are identified that enable an efficient use of both the available power and spectrum.
CS 224 N : Final Project Investigating the Web ’ s Dark Matter

People populate the web with content relevant to their lives, content that millions of others rely on for information and guidance. However, the web is not a perfect representation of lived experience: some topics appear in greater proportion online than their true incidence in our population, while others are deflated. This paper presents a large scale data collection study of this phenomenon. We collect webpages about 21 topics of interest capturing roughly 200,000 webpages, and then compare each topic’s popularity to representative national surveys as ground truth. We find that rare experiences are inflated on the web (by a median of 7x), while common experiences are deflated (by a median of 0.7x). We further examine topics reflecting opinions and personal views by training supervised machine learning classifiers using crowdsourced page annotations, and find that simple logistic regression classification performs with nearly perfect accuracy on the simpler classification task, but much lower accuracy on more complex classification.