Miracle-dz/UniFAR-FTUs huggingface dataset:
Error Analysis Of Students Working About Word Problem Of Linear Program With NEA Procedure

Evaluation and assessment is an important part of learning. In evaluation process of learning, written test is still commonly used. However, the tests usually do not following-up by further evaluation. The process only up to grading stage not to evaluate the process and errors which done by students. Whereas if the student has a pattern error and process error, actions taken can be more focused on the fault and why is that happen. NEA procedure provides a way for educators to evaluate student progress more comprehensively. In this study, students’ mistakes in working on some word problem about linear programming have been analyzed. As a result, mistakes are often made students exist in the modeling phase (transformation) and process skills (process skill) with the overall percentage distribution respectively 20% and 15%. According to the observations, these errors occur most commonly due to lack of precision of students in modeling and in hastiness calculation. Error analysis with students on this matter, it is expected educators can determine or use the right way to solve it in the next lesson.
Resource-Constrained Low-Complexity Video Coding for Wireless Transmission

In this paper, we present a novel objective quality metric that takes the impact of frame rate into account. The proposed metric uses PSNR, frame rate and a content dependent parameter that can easily be obtained from spatial and temporal activity indices. The results have been validated on data from a subjective quality study, where the test subjects have been choosing the preferred path from the lowest quality to the best quality, at each step making a choice in favor of higher frame rate or lower distortion. A comparison with other relevant objective metrics shows that the proposed metric on average provides a more precise correlation with the subjective results.
Comparison of Sojourn Time Distributions in Modeling HIV/AIDS Disease Progression

Summary An application of semi-Markov models to AIDS disease progression was utilized to find best sojourn time distributions. We obtained data on 370 HIV/AIDS patients who were under follow-up from September 2008 to August 2015, from Yirgalim General Hospital, Ethiopia. The study reveals that within the “good” states, the transition probability of moving from a given state to the next worst state has a parabolic pattern that increases with time until it reaches a maximum and then declines over time. Compared with the case of exponential distribution, the conditional probability of remaining in a good state before moving to the next good state grows faster at the beginning, peaks, and then declines faster for a long period. The probability of remaining in the same good disease state declines over time, though maintaining higher values for healthier states. Moreover, the Weibull distribution under the semi-Markov model leads to dynamic probabilities with a higher rate of decline and smaller deviations. In this study, we found that the Weibull distribution is flexible in modeling and preferable for use as a waiting time distribution for monitoring HIV/AIDS disease progression.
Learning A Web Based Course Through Macromedia Breeze

What is the pedagogical ideal to advance web-based students’ learning? There is no simple one-size-fits-all solution to this question, because in order to answer this question, there are three aspects that need to be addressed. The first aspect is: our customer. Every student is different; some learn more efficiently through visualization, some more efficiently through auditory assimilation, while others more efficiently through ability to feel, and ability to rationalize the information presented to them. The second aspect is the dimensions of learning: learning consists of the ability to understand, the ability to recall, and the ability to apply the knowledge meaningfully. The third aspect is the web technology; how much classroom interaction can it replicate? Hence we think the question could be easier answered if it is phrased this way: is there any web-based instructional technique that could catered to all types of learners in a way that they could very efficiently understand, retain, and then meaningfully applied for problem solving. We suspect there is, and we believe Macromedia Breeze has been helping our visual, auditory, kinesthetic, and logical students to understand, recall, and then apply the material they learned from warehouse management class (IT 332) more effectively than students whom have not had the experience via distance at Purdue University. Since web-based learning communicates through the Internet, which is generally a oneway transaction, instructors do not receive real-time response from students as in a classroom. This limitation can be eliminated by the software, Macromedia Breeze. Macromedia Breeze offers many functions that would increase the learning efficiency. In this paper, we will be introducing what Breeze is, what advantages it brings to the four different types of learning experiences, why and how it enhances understanding, retention, and meaningful application. The goal of this study is to raise awareness of Breeze so that future researchers will support or contest these pedagogical hypotheses through follow up empirical analysis. This paper will also present how this experiment was conducted, and what hypotheses were set up.
Noninvasive positive pressure ventilation in COPD

Educational aims To take up the ongoing debate on whether long-term noninvasive positive pressure ventilation (NPPV) should be applied in chronic obstructive pulmonary disease (COPD) patients with chronic hypercapnic respiratory failure. To elucidate the impact of NPPV techniques on NPPV success in COPD. To describe the technique and scientific evidence for the new concept of high-intensity NPPV. To provide practical considerations on how to commence high-intensity NPPV. To outline important unknowns regarding long-term NPPV in COPD patients. Summary Home mechanical ventilation, as provided by long-term NPPV, is a widely accepted treatment option for many patient groups with chronic hypercapnic respiratory failure, including also those with COPD, even though the rationale for long-term NPPV in COPD patients is still disputed. This is based on clinical observations that conventional NPPV using assisted ventilation and low mean inspiratory pressures of <18 cmH2O reportedly failed to effectively improve respiratory function, most importantly gas exchange, while outcomes are also not convincingly improved by the addition of long-term NPPV to long-term oxygen treatment. Recently, however, a promising technique of NPPV has been described, which aims at maximally improving gas exchange by the use of controlled ventilation and considerably higher inspiratory pressures, typically ranging 20–40 cmH2O. This is known as high-intensity NPPV. This approach clearly contrasts with the conventional, low-intensity approach. High-intensity NPPV has been shown to improve physiological parameters such as breathing pattern, gas exchange and lung function. In addition, it also provides clinical benefits, with improvements in dyspnoea, walking distance and specific aspects of health-related quality of life. The superiority of high- over low-intensity NPPV has been clearly established by randomised crossover trials. Increasing evidence now exists to support the contention that long-term high-intensity NPPV offers a new therapeutic option in the treatment of hypercapnic COPD. However, the questions of whether high-intensity NPPV is also capable of improving survival and how to best select candidates to undergo long-term high-intensity NPPV remain pressing. This article also provides detailed practical descriptions of how to initiate high-intensity NPPV.
Applying QFD in the Development of Sensible Brassiere for Middle Aged Women

Quality Function Deployment(QFD) is a product development tool which ensures that the voice of the customer needs is heard and translated into products. To develop a sensible brassiere for middle-aged women QFD was adopted. In this study the applicability and usefulness of QFD was examined through the engineering design process for a sensible brassiere for middle-aged women. The customer needs for the wear comfort of brassiere was made by one-on-one survey of 100 women who aged 30-40. The customer competitive assessment was generated by wearing tests of 10 commercial brassieres. The subjective assessment was conducted in the enviornmental chamber that was controlled at As a results, we developed twenty-one customer needs and corresponding HOWs for the wear comfort of brassiere. The Customer Competitive Assessment was generated by wearing tests of commercial brassiere. The subjective measurement scale and dimension for the evaluation of sensible brassiere were extracted from factor analysis. Four factors were fitting, aesthetic property, pressure sensation, displacement of brassiere due to movement. The most critical design parameter was wire-related property and second one was stretchability of main material of brassiere. Also, wearing comfort of brassiere was affected by the interaction of initial stretchability of wing and support of strap. Engineering design process, QFD was applicable to the development of technical and aesthetic brassieres.
A Handoff using Guard Channels Scheme (HGCS) for Cognitive Radio Networks

Spectrum handoff is a very important phenomenon in Cognitive Radio (CR) networks. It provides flawless transmission upon the arrival of primary user (PU) while the channel is in use by the secondary user (SU). Spectrum handoff process provides the SUs with the opportunity to continue their communication on other unoccupied channels as soon as the PU repossesses its channel. FCC (Federal Communications Commission) has released new White Space rules in September 2010 which eliminate the requirement of spectrum sensing, making CRs more flexible. In addition, the CR is to be equipped with TV channel database. Taking these new rules into account, this paper suggests a new handoff scheme, HGCS (Handoff using Guard Channels Scheme), which makes effective use of the guard channels for communication. A preemptive resume priority (PRP) M/G/1 queuing network model is proposed to assess total service time for the suggested HGCS and comparing it to the existing random proactive-decision handoff scheme. Simulation and numerical results verify that HGCS can minimize the handoff delay, hence reduces the total service time compared to the random proactive approach.
Japanese Students’ Perceptions of Digital Game Use for English-Language Learning in Higher Education

Researchers investigated perceptions of Japanese college students toward the use of digital games in English-language learning. The study was conducted at one large private university in Japan. Undergraduate students who were enrolled in 14 English-language courses were invited to complete a paper-based survey during class time. The survey included the following constructs: ease of use, learning opportunities, experience, preferences, and actual use. Participants were also invited to share potential advantages and disadvantages for digital game use in the classroom. Two hundred and twenty-two students completed the survey. Results indicate that most students viewed the potential integration and utilization of digital games as positive. However, some students expressed concern that the use of games may not be an effective or efficient method of learning.
Adapting a delay-based protocol to heterogeneous environments

Adapting a Delay-based Protocol to Heterogeneous Environments. (August 2008) Kiran Kotla, B.E. , Birla Institute of Technology and Science, Pilani, India Co–Chairs of Advisory Committee: Dr A. L. Narasimha Reddy Dr Riccardo Bettati We investigate the issues in making a delay-based protocol adaptive to heterogeneous environments. We assess and address the problems a delay-based protocol faces when competing with a loss-based protocol such as TCP. We investigate if noise and variability in delay measurements in environments such as cable and ADSL access networks impact the delay-based protocol behavior significantly. We investigate these issues in the context of incremental deployment of a new delay-based protocol, PERT. We propose design modifications to PERT to compete with the TCP flavor SACK. We show through simulations and real network experiments that, with the proposed changes, PERT experiences lower drop rates than SACK and leads to lower overall drop rates with different mixes of PERT and SACK protocols. Delay-based protocols, being less aggressive, have problems in fully utilizing a highspeed link while operating alone. We show that a single PERT flow can fully utilize a high-speed, high-delay link. We performed several experiments with diverse parameters and simulated numerous scenarios using ns-2. The results from simulations indicate that PERT can adapt to heterogeneous networks and can operate well in an environment of heterogeneous protocols and other miscellaneous scenarios like wireless networks (in the presence of
Intrusion Detection using a Novel Hybrid Method Incorporating an Improved KNN

These days, with the tremendous growth of network-based service and shared information on networks, the risk of network attacks and intrusions increases too, therefore network security and protecting the network is getting more significance than before. Intrusion Detection System (IDS) is one of the solutions to detect attacks and anomalies in the network. The ever rising new intrusion or attack types causes difficulties for their detection, therefore Data mining techniques has been widely applied in network intrusion detection systems for extracting useful knowledge from large number of network data to detect intrusions. Many clustering and classification algorithms are used in IDS, therefore improving the functionality of these algorithms will improve IDS performance. This paper focuses on improving KNN classifier in existing intrusion detection task which combines K-MEANS clustering and KNN classification.
Advanced modulation formats and signal processing for high speed spectrally efficient optical communications

Coherent detection in combination with digital signal processing is now the de facto standard for long-haul high capacity optical communications systems operating at 100 Gb/s per channel and beyond. With the advent of high-speed high-resolution digital-to-analog converters, generation of high order modulation formats with digital pulse shaping has become possible allowing the increase of system spectral efficiency. Furthermore, the widespread use of transmission links without in-line dispersion compensation enables elegant analytical optical channel modeling which facilitates the use of powerful tools from information theory and digital signal processing. Relying on these aforementioned tools, the introduction of time-interleaved hybrid modulation formats, multi-dimensional modulation formats, and alternative quadrature amplitude modulation formats is investigated in high-speed optical transmission systems. Their impact on signal processing algorithms and achievable information rate over optical links is studied in detail. Next, the design of next generation transponders based on high symbol rate signals operating at 400 Gb/s and 1 Tb/s is investigated. These systems are attractive to reduce the cost per bit as more capacity can be integrated in a single transponder. Thanks to the development of advanced signal processing algorithms combined with state-of-the-art opto-electronic components, record high-capacity transmission experiments are demonstrated: the first single carrier 400 Gb/s transmission over transatlantic distance (at 6 b/s/Hz) and the first 1 Tb/s net data rate transmission based on the parallel synthesis of multiple spectral slices (at 8 b/s/Hz)
A Laplace Transform Numerical Model for Contaminant Transport in Stratified Porous Media

This paper presents a Laplace transform numerical technique for the description of 1-D and 2-D contaminant transport in stratified porous media, which was verified through comparison to an analytic method and a finite element method. The technique provides a stable approach to solving the advection-dispersion equation describing solute transport in saturated porous media. No time-stepping is required in the Laplace transform numerical method. Thus, a solution can be obtained directly for any point in time.
Feature Selection for Activity Recognition from Smartphone Accelerometer Data

AbstractWe use the public Human Activity Recognition Using Smartphones (HARUS) data-set to investigate and identify the most informative features for determining the physical activity performed by a user based on smartphone accelerometer and gyroscope data. The HARUS data-set includes 561 time domain and frequency domain features extracted from sensor readings collected from a smartphone carried by 30 users while performing specific activities. We compare the performance of a decision tree, support vector machines, Naive Bayes, multilayer perceptron, and bagging. We report the various classification performances of these algorithms for subject independent cases. Our results show that bagging and the multilayer perceptron achieve the highest classification accuracies across all feature sets. In addition, the signal from gravity contains the most information for classification of activities in the HARUS data-set.
A State Space Model for Sensorimotor Control and Learning

Abstract : The report is the first of a two-part presentation which deals with certain computer controlled manipulator problems. This first part discusses a model which is designed to address problems of motor control, motor learning, adaptation, and sensorimotor integration. The problems are outlined and a solution is given which makes use of a state space memory and a piece-wise linearization of the equations of motion. A forthcoming companion article will present the results of tests performed on an implementation of the model.
METODOLOGIA GEODÉSICA PARA LEVANTAMENTO DE LINHA DE COSTA E MODELAGEM DIGITAL DE ELEVAÇÃO DE PRAIAS ARENOSAS EM ESTUDOS DE PRECISÃO DE GEOMORFOLOGIA E DINÂMICA COSTEIRA

Este trabalho apresentou a metodologia geodésica desenvolvida para o levantamento, geração e avaliação de Linhas de Costa (LC) e Modelos Digitais de Elevação (MDE) de litorais arenosos, e um estudo de caso realizado no sistema de ilhas barreiras com praias arenosas e canais de maré intermitentes do Litoral Setentrional do Estado do Rio Grande do Norte (RN), Nordeste do Brasil, sensível ambientalmente e caracterizado pela intensa erosão/acresção costeira sob as atividades petrolíferas. A metodologia permitiu a determinação de LC e MDE a partir de coordenadas geodésicas e de altitudes ortométricas com precisão de poucos centímetros em relação ao Sistema Geodésico Brasileiro (SGB), a partir do posicionamento e da altimetria por GPS no modo relativo. As principais características da metodologia proposta são a precisão, o uso de indicador de LC específico para análises de dinâmica costeira e o emprego de referenciais geodésicos (geográfico e altimétrico) unívocos, fixos e relativamente estáveis no tempo.A metodologia aplicada permite a repetição dos levantamentos nas mesmas condições de maré e com os mesmos referenciais geodésicos, sendo adequada para a comparação multitemporal de levantamentos realizados no domínio espacial e temporal e de grande potencial nos estudos de análise da dinâmica costeira (erosão/acresção sedimentar) de precisão.
Scalability of dynamic traffic assignment

This research develops a systematic approach to analyze the computational performance of Dynamic Traffic Assignment (DTA) models and provides solution techniques to improve their scalability for on-line applications for large-scale networks. DTA models for real-time use provide short-term predictions of network status and generate route guidance for travelers. The computational performance of such systems is a critical concern. Existing methodologies, which have limited capabilities for online large-scale applications, use single-processor configurations that are less scalable, and rely primarily on trade-offs that sacrifice accuracy for improved computational efficiency. In the proposed scalable methodology, algorithmic analyses are first used to identify the system bottlenecks for large-scale problems. Our analyses show that the computation time of DTA systems for a given time interval depends largely on a small set of parameters. Important parameters include the number of origin-destination (OD) pairs, the number of sensors, the number of vehicles, the size of the network, and the number of time-steps used by the simulator. Then scalable approaches are developed to solve the bottlenecks. A constraint generalized least-squares solution enabling efficient use of the sparse-matrix property is applied to the dynamic OD estimation, replacing the Kalman-Filter solution or other full-matrix algorithms. Parallel simulation with an adaptive network decomposition framework is proposed to achieve better load-balancing and improved efficiency. A synchronization-feedback mechanism is designed to ensure the consistency of traffic dynamics across processors while keeping communication overheads minimal. The proposed methodology is implemented in DynaMIT, a state-of-the-art DTA system. Profiling studies are used to validate the algorithmic analysis of the system bottlenecks. The new system is evaluated on two real-world networks under various scenarios. Empirical results of the case studies show that the proposed OD estimation algorithm is insensitive to an increase in the number of OD pairs or sensors, and the computation time is reduced from minutes to a few seconds. The parallel simulation is found to maintain accurate output as compared to the sequential simulation, and with adaptive load-balancing, it considerably speeds up the network models even under non-recurrent incident scenarios. The results demonstrate the practical nature of the methodology and its scalability to large-scale real-world problems. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)
Motion Vector Estimation Search using Hexagon-Diamond Pattern for Video Sequences, Grid Point and Block-Based

Grid and block-based motion vector estimation techniques are proposed for motion tracking in video sequences. The grid technique is referred to the hexagon-diamond pattern. While, block-based technique is referred to 16 × 16 pixels of blocks in a single frame in video sequences. The hexagon and diamond pattern is applied onto the 16 × 16 pixels blocks in a single frame for motion tracking purposes in video sequences. The hexagon grid pattern will conduct a search to capture the motion in a particular block of the hexagon region before the diamond grid pattern takes place for the fine search. The diamond grid pattern provides accuracy to obtain the best grid vector coordinate for motion tracking purposes. The hexagon-diamond grid vector coordinate can be used to determine whether the object is moving toward the horizontal or vertical plane. The information determined at grid vector coordinate can be used as a reference when referring to the previous frame in video sequence processing. The grid vector coordinate will help to determine the area of interest to be examined based on the coordinate obtained. Besides the grid vector estimation, the Point Signal Noise-to-Ratio (PSNR) is also applied to measure the quality of the video.