Miracle-dz/UniFAR-FTUs huggingface dataset:
Grid Current Control of Microgrid with Cascaded Micro Source Inverters Based on Dynamic Phasors Model

In order to research grid connected operation performance of microgrid with cascaded micro source inverters, the dynamic phasors model of cascaded inverters link is established firstly. Then, the quasi-PR controller in two-phase stationary reference frame and PI controller in synchronization rotating reference frame are used respectively to control the grid current of system. And detailed comparation and analysis are made to the two control methods mentioned above, from the aspect of steady-state error, response speed and grid current quality. Finally, the quasi-PR controller in two-phase stationary reference frame is applied to control the grid current of the microgrid that each phase contains ten cascaded micro source inverters and simulated by MATLAB/Simulink. The simulation results show that the current of system has high power quality and fast response under different operating conditions.
Advances in Automatically Solving the ENEM

Answering questions formulated in natural language is a long standing quest in Artificial Intelligence. However, even formulating the problem in precise terms has proven to be too challenging, which lead many researchers to focus on Multiple-Choice Question Answering problems. One particularly interesting type of the latter problem is solving standardized tests such as university entrance exams. The Exame Nacional do Ensino Médio (ENEM) is a High School level exam widely used by Brazilian universities as entrance exam, and the world's second biggest university entrance examination in number of registered candidates. In this work we tackle the problem of answering purely textual multiple-choice questions from the ENEM. We build on a previous solution that formulated the problem as a text information retrieval problem. In particular, we investigate how to enhance these methods by text augmentation using Word Embedding and WordNet, a structured lexical database where words are connected according to some relations like synonymy and hypernymy. We also investigate how to boost performance by building ensembles of weakly correlated solvers. Our approaches obtain accuracies ranging from 26% to 29.3%, outperforming the previous approach.
Incorporating Battery Energy Storage Systems Into Multi-MW Grid Connected PV Systems

This paper analyzes the configuration, design, and operation of multi-MW grid connected solar photovoltaic (PV) systems with practical test cases provided by a 10-MW field development. In order to improve the capacity factor, the PV system operates at its maximum power point during periods of lower irradiance, and the power output is limited to a rated value at high irradiance. The proposed configuration also incorporates a utility scale battery energy storage system (BESS) connected to the grid through an independent inverter and benefits of the experience gained with a 1-MW 2-MWh BESS large demonstrator. The BESS power smoothing and frequency regulation capabilities are illustrated though combined theoretical and experimental studies. The behavior of the grid connected PV and BESS combined system is studied using a modified IEEE 14 bus test system implemented in PSCAD/EMTDC. This paper also includes a sizing exercise for energy storage in order to provide dispatchable PV power.
SLAM for Direct optimization based Visual-Inertial Fusion

The tightly coupled fusion of inertial sensors and direct visual odometry is extended by a SLAM approach in order to further improve the localization accuracy in case that places are revisited (loop closure). For that keyframes stored along the trajectory are used to represent the SLAM map. If the current position is close to a previously stored keyframe, the transformation to the current frame is calculated using the direct image alignment method. Depth information available from the stereo camera is used as additional measurement for better convergence. On successful calculation the current sensor system pose is corrected according to the found transform and by that the position errors are reduced significantly. Our online SLAM implementation is a filter based approach where the filter state is augmented by the keyframe poses in order to properly model uncertainties and correlation.
Recognition Algorithm of Emitter Signals Based on PCA+CNN

In order to solve the problem of low recognition rate of emitter signal under low SNR by the traditional method, a recognition algorithm based on PCA+CNN is proposed. The radar emitter signal is processed time-frequency image. The image is processed, and is reduced dimensionality by PCA. Learning model is adjusted by pretraining, and the softmax classifier commonly used on the pretraining model adopts supervised sizing and recognition, finally complete the identification task. The simulation results show that the algorithm can achieve high recognition rate, compared with traditional algorithm.
Recurrent Neural Network for MIDI Music Emotion Classification

MIDI(Music Instrument Digital Interface) music is the most widely used music standard format. This paper proposes a MIDI music emotion classification method based on RNN(Recurrent Neural Network). It uses the combination of two notes melody trend as music features to realize the classification of the five kinds of music emotion, with accuracy up to 75.4%. The dropout parameter is added to the RNN network to improve the accuracy rate of nearly 10%. Emotion tagging MIDI music on Youtube are used as the dataset. The learning rate, initial weight and bias, as well as the types of notes, are compared and analyzed between RNN, improved RNN and FNN(Forward Neural Network).
Fast mileage deviation correction method for track dynamic inspection system based on data fusion technology

A new mileage deviation correction method for track dynamic inspection data of high-speed comprehensive inspection train using data fusion technology was proposed and investigated to improve the accuracy of mileage information and the efficiency of deviation correction method. The mileage deviation of track geometric inspection data was corrected using inspected curvature information combined with actual mileage and curvature information. The mileage deviation of axle box acceleration inspection data was corrected using mileage-corrected track geometric inspection data combined with uncorrected velocity information of axle box acceleration inspection data. A 5-points iteration method was proposed and investigated to improve the computational efficiency of mileage deviation correction. Computational and analytic result of measured data demonstrated that 5-points iteration method not only ensured the accuracy of mileage deviation correction, but also significantly saved the computation time for over 80%. Field verifying of actual wave corrugation case indicated that the corrected mileage information of track dynamic inspection data was very close to the actual information, the error being less than 10 m.
Impact of Process Control in Reliability and Efficiency

PID loop controllers are widely used in the industry. Even though advanced process control strategies are commonly implemented, they depend on a good regulatory controller's performance. Despite of this, it is common to find in the industry loops in Manual mode or with a poor closed loop response. There is a margin for improvement that would lead to increasing process reliability and efficiency. This work presents industrial cases where the closed loop performance of controllers was improved, using identification and tuning software developed at the University.
Research on positioning system based on Zigbee communication

This paper presents a three-dimensional layered localization method based on Zigbee communication, can be effectively used for indoor positioning. The three methods of RSSI ranging model and hierarchical positioning algorithm. To solve the problem of traditional Zigbee communication three-dimension large localization error. Using the design of 3D layered localization algorithm of Zigbee communication indoor positioning system based on vertical environment. To effectively solve the error problem, to achieve accurate positioning. The sensing characteristics of Zigbee are analyzed, the calibration of A and effect of n value on Zigbee communication.
Learning compact hashing codes with complex objectives from multiple sources for large scale similarity search

Wang, Qifan Ph.D., Purdue University, May 2015. Learning Compact Hashing Codes with Complex Objectives from Multiple Sources for Large Scale Similarity Search . Major Professor: Luo Si. Similarity search is a key problem in many real world applications including image and text retrieval, content reuse detection and collaborative filtering. The purpose of similarity search is to identify similar data examples given a query example. Due to the explosive growth of the Internet, a huge amount of data such as texts, images and videos has been generated, which indicates that efficient large scale similarity search becomes more important. Hashing methods have become popular for large scale similarity search due to their computational and memory efficiency. These hashing methods design compact binary codes to represent data examples so that similar examples are mapped into similar codes. This dissertation addresses five major problems for utilizing supervised information from multiple sources in hashing with respect to different objectives. Firstly, we address the problem of incorporating semantic tags by modeling the latent correlations between tags and data examples. More precisely, the hashing codes are learned in a unified semi-supervised framework by simultaneously preserving the similarities between data examples and ensuring the tag consistency via a latent factor model. Secondly, we solve the missing data problem by latent subspace learning from multiple sources. The hashing codes are learned by enforcing the data consistency among different sources. Thirdly, we address the problem of hashing on structured data by graph learning. A weighted graph is constructed based on the structured knowledge from the data. The hashing codes are then learned by preserving the graph similarities. Fourthly, we address the problem of learning high ranking quality hashing
Adaptive importance sampling for rare event simulation of queueing networks

Technology advances in computer and communication networks have made rare event analysis more important. For example, standards adopted for ATM (Asynchronous Transfer Mode) networks usually require that buffer overflow probabilities be less than 10$\sp{-9}. $ Estimation of such probabilities is typically computationally intractable when studied using conventional Monte Carlo simulation. Therefore, powerful variance reduction techniques are required. Importance sampling is the most commonly used technique for this purpose. Importance sampling, based on changing probability measures to make rare events occur more often, has been used to improve simulation efficiency successfully in estimating small probabilities in queueing systems which involve only a single queue. However, for most queueing networks, there are no good importance sampling techniques available yet. So far, there is no proposed method for selecting an effective change-of-measure for general networks that works universally. In addition, existing methods generally require that the analyst have a good understanding of the theory of large deviations for the particular network being considered; this is the major obstacle to wide-spread application of these ideas in queueing networks. Therefore, a good system-independent importance sampling method is desirable. In this thesis, we consider generalized open Jackson networks--open networks of GI/G/1 queues with Markovian routing. We develop an adaptive method for estimating the steady-state probability that the total population in the network exceeds K. We call our method SEEKPATH (Scaled Empirical/Efficient Key PATH), because SEEKPATH computes a good change-of-measure by simulating the original system for a small value of K, corresponding to "scaling down" the original rare event. We then simulate the desired rare-event probability, by "scaling up" the change-of-measure suggested by the key paths associated with the small K system. We provide a large number of computational examples. We also compare SEEKPATH to a known asymptotically optimal estimator in a certain class of tandem queues.
Menopausal Transition with a Yogic Lifestyle: Experiences of Thai Yogi Masters

Abstract : This ethnographic study, as part of the larger research project, “Living Healthy through Yoga of Yoga Masters: A Qualitative Inquiry,” sought to explore the experiences of nine female yogi masters as they managed their menopausal transition (i.e., women’s reproductive senescence in the continuum of reproductive aging) via a yogic lifestyle. Their yogic lifestyle included regular yoga practice, healthy food habits, adequate sleep, and the use of nature cure techniques (i.e., fasting, detoxification, selection of suitable food products, and living in well-ventilated houses) that facilitated the art of living in tune with nature. Personal interviews, supplemented with telephonic interviews, partici­pant observations, administration of a questionniare, and field notes were carried out to explore the yogi masters’ experiences. Using Spradley’s method of analysis, qualitative data were gathered and analyzed simultaneously. The findings revealed the yogi masters perceived having: mild menopausal symptoms; positive attitudes towards their menopausal experiences; and, a smooth menopausal transition. Their yogic lifestyle helped the middle-aged Thais deal with their menopausal transition and provided them with a positive step towards healthier aging. Thus, it appears that health professionals need to encourage positive attitudes, among women, towards menopause and mind-body awareness, through use of yoga. บทคดยอ : การวจยเชงชาตพนธวรรณานมวตถประสงคเพอศกษาประสบการณครโยคะไทยใน การเปลยนผานภาวะการหมดประจำเดอนดวยวถโยคะ การคดเลอกกลมตวอยางแบบเฉพาะเจาะจง เปนครโยคะจำนวน 9 คน ทอยในวยภาวะหมดประจำเดอนและกำลงจะหมดประจำเดอน เกบขอมล โดยการสมภาษณเจาะลกรวมกบการสมภาษณทางโทรศพท การสงเกตแบบมสวนรวม และการจด บนทกภาคสนาม เพอศกษาประสบการณการปฏบตโยคะในวถชวต ในชวงของการเปลยนผานภาวะ หมดประจำเดอน การวเคราะหขอมลเชงเนอหาโดยใชรปแบบตามแนวคดของสปราดเล ผลการศกษาพบวา ครโยคะรบรภาวะการหมดประจำเดอนในระดบความรนแรงทตาและม ทศนะคตทดกบภาวะหมดประจำเดอน ซงสามารถกาวผานพนไปไดอยางราบรนไมเกดความทกข ทรมาณจากอาการภาวะหมดประจำเดอน โดยการปฏบตตามแนววถโยคะ คอการปฏบตโยคะอยาง สมำเสมอรวมกบการรบประทานอาหารสขภาพ นอนพกผอนอยางเพยงพอ และใชวถโยคะผสมผสาน กบธรรมชาตบำบด จากผลการวจยครงนแสดงใหเหนวาวถโยคะชวยใหผหญงวยกลางคนเปลยนผานภาวะหมด ประจำเดอนไปไดดวยความราบรนไมเกดความทกขทรมาณ ซงจะสงผลไปสการมชวตในวยสงอายทม สขภาวะตอไป บคลากรทางดานสขภาพควรตระหนกและกระตนใหผหญงมทศนคตทดตอการหมด ประจำเดอนซงเปนเหตการณปกตของชวตและนำโยคะมาปฏบตอยางสมำเสมอจนเกดการตระหนกร ในการดำรงชวตตงแตเนนๆ
Computer support for learners of spoken English

This thesis concerns the use of speech technology to support the process of learning the English language. It applies theories of computer-assisted language learning and second language acquisition to address the needs of beginning, intermediate and advanced students of English for specific purposes. The thesis includes an evaluation of speech-recognition-based pronunciation software, based on a controlled study of a group of immigrant engineers. The study finds that while the weaker students may have benefited from their software practice, the pronun¬ciation ability of the better students did not improve. The linguistic needs of advanced and intermediate Swedish-native students of English are addressed in a study using multimodal speech synthesis in an interactive exercise demonstrating differences in the placement of lexical stress in two Swedish-English cognates. A speech database consisting of 28 ten-minute oral presentations made by these learners is described, and an analysis of pronunciation errors is pre¬sented. Eighteen of the presentations are further analyzed with regard to the normalized standard deviation of fundamental frequency over 10-second long samples of speech, termed pitch variation quotient (PVQ). The PVQ is found to range from 6% to 34% in samples of speech, with mean levels of PVQ per presentation ranging from 11% to 24%. Males are found to use more pitch variation than females. Females who are more proficient in English use more pitch variation than the less profi¬cient females. A perceptual experiment tests the relationship between PVQ and impressions of speaker liveliness. An overall correlation of . 83 is found. Temporal variables in the presentation speech are also studied. A bilingual database where five speakers make the same presentation in both English and Swedish is studied to examine effects of using a second language on presentation prosody. Little intra-speaker difference in pitch variation is found, but these speakers speak on average 20% faster when using their native language. The thesis concludes with a discussion of how the results could be applied in a proposed feedback mechanism for practicing and assessing oral presentations, concept¬ualized as a ‘speech checker. ’ Potential users of the system would include native as well as non-native speakers of English.
Cognitive abilities, interfaces and tasks: effects on prospective information handling in email

This dissertation is focused on new email user interfaces that may improve awareness and handling of task-laden messages in the inbox. The practical motivation for this research was to help email users process messages more effectively.Two user studies were conducted to test hypothesized benefits of the new visual representations and to examine the effects of different levels of selected cognitive abilities on task-laden message handling performance. Task performance on both of the new visual interfaces was faster than on the more traditional textual interfaces, but only when finding date-related information. Selected cognitive abilities were found to impact different dependent measures. Working memory and flexibility of closure had effects on performance time, while visual memory and working memory had effects on user interactions involving manipulation of the visual field, such as scrolling and sorting.A field study was conducted to examine email practices related to handling messages that refer to pending tasks. Individual differences in message handling style were observed, with one group of users transferring such messages out of their email programs to other applications (e.g., calendars), while the other group kept prospective messages in email and used the inbox as a reminder of future events.This research contributes to understanding interactions among cognitive abilities, user interfaces and tasks. These interactions are essential for developing two types of interface: inclusive interfaces that work for users with a wide range of cognitive abilities, and personalized and adaptive interfaces that are fitted to individual characteristics.Two novel graphical user interfaces were designed to facilitate monitoring and retrieval of prospective information from email messages. The TaskView interface displayed task-laden messages on a two-dimensional grid (with time on the horizontal axis). The WebTaskMail interface retained the two-dimensional grid, but extended the representation of pending tasks (added distinction between events and to-do's with deadlines), a vertical date reading line, and more space for email message headers.
The relation of CLR and blocking probability for VBR traffic in the wireless ATM access transport

This paper is focused on the relation between CLR (cell loss ratio) and blocking probability in the wireless ATM access transport. The traffic model of wireless ATM access transport is based on the cell scale, burst scale and call connection level. The CLR due to buffer overflow for wireless access node is derived for variable bit rate (VBR) traffic. The CLR due to transmission errors in the wireless channel is derived. Using the CLR for both the access node and wireless channel, the CLR of wireless ATM access transport is derived. The relation between CLR and blocking probability is analyzed for VBR traffic to evaluate performance of wireless ATM access transport.
The effects of behavioural obesity treatment in Iceland with or without surgical intervention on weight loss, body composition, physical work capacity and physical activity: A 4-year follow-up

5 Ágrip . 7 Þakkir . 9 List of figures . 13 List of tables . 13 List of abbreviations . 14 Introduction . 15 Obesity as a health problem . 15 The role of physical activity . 16 Treatment options for obesity . 17 Behavioural obesity treatment . 18 Behavioural obesity treatment and long-term weight loss . 18 Behavioural obesity treatment and body composition . 19 Behavioural obesity treatment and physical exercise capacity . 21 Gastric bypass surgery . 23 Gastric bypass surgery and long-term weight loss . 24 Gastric bypass surgery and body composition . 27 Gastric bypass surgery and physical exercise capacity . 28 Obesity treatment at Reykjalundur Rehabilitation Centre . 29 The obesity program . 30 The physical exercise component . 31 Previous findings from the Reykjalundur Obesity Treatment Program . 33 The aim of this study . 35 Article . 37 Abstract . 39 Introduction . 40 Materials and methods . 42
Bayesian Analysis for Penalized Spline Regression Using WinBUGS

Penalized splines can be viewed as BLUPs in a mixed model framework, which allows the use of mixed model software for smoothing. Thus, software originally developed for Bayesian analysis of mixed models can be used for penalized spline regression. Bayesian inference for nonparametric models enjoys the flexibility of nonparametric models and the exact inference provided by the Bayesian inferential machinery. This paper provides a simple, yet comprehensive, set of programs for the implementation of nonparametric Bayesian analysis in WinBUGS. Good mixing properties of the MCMC chains are obtained by using low-rank thin-plate splines, while simulation times per iteration are reduced employing WinBUGS specific computational tricks.
Is Private Long-Term Care Insurance Affordable For Older Adults?

IS PRIVATE LONG-TERM CARE INSURANCE AFFORDABLE FOR OLDER ADULTS? by NAYOUNG KIM May 2010 Advisor: Dr. Gail Jensen-Summers Major: Economics Degree: Doctor of Philosophy Nationwide there are fewer than 7 million long-term care (LTC) insurance policies in force. Why do so few Americans buy private long-term care (LTC) insurance? Several theories have been offered as possible explanations, including the availability of Medicaid, misperceptions that Medicare or other policies cover LTC, beliefs that one‟s own risk of needing LTC services is small, or desires to simply rely on children and spouses for LTC. This study examines another possible explanation – that private LTC insurance is simply “unaffordable” for most older Americans, which may be why they don‟t buy it. This study begins by investigating the meaning of affordability in the context of private LTC insurance. I propose several definitions for affordability, drawing on concepts recently developed to gauge the affordability of acute-care health insurance and housing. Then using nationally representative data from the ongoing Health and Retirement Study (HRS) and the Rand HRS data the study examines the incidence of