Miracle-dz/UniFAR-FTUs huggingface dataset:
Finite control set model predictive control with feedback correction for power converters

As an open-loop model predictive control algorithm, finite control set model predictive control (FCS-MPC) scheme in power converter system is based on assumption that responses of optimal control implemented on prediction model agree well with actual system. The influence of model parameter mismatches and environment disturbance on control performance of scheme is neglected. Then, based on feedback correction strategy in traditional model predictive control algorithm, we derive a finite control set model predictive control with feedback correction scheme (FCS-MPCFC) that allows us to adjust prediction model output at current instant by model prediction error at previous instant, and the closed-loop correction of prediction model output is achieved. Simulations comparison analyses on a two-level three-phase inverter with multi-type model parameter mismatches controlled by traditional and improved FCS-MPC scheme are presented. Experiments are carried out on DSP controller platform.
Self-* distributed query region covering in wireless sensor networks

S elf-* D istribu ted Query Region Covering in W ireless Sensor Netw orks by Preethi Linga Dr. Ajoy K. Datta, Examination Committee Chair School of Computer Science University of Nevada, Las Vegas Dr. M aria Gradinariu, Examination Committee Co-Chair IR ISA , Campus de Beaulieu, France Late M ark Weiser envisioned the next (i.e., the post-PC) era of computing, called wifows computing. In ubiquitous world, we expect to see thousands of invisible computing devices used per person, maybe, even in a household. Recent technological advances in microsensors, wireless networking and communications, and embedded processing made it possible. We can now build ad-hoc networks composed of a large number of low-cost, lowpower, and small sensor nodæ. The sensor networks are expected to be very large. In many applications, they w ill be densely deployed. These networks are energy constrained. The topology also is expected to change very hrequently. Considering all the constraints discussed above, the sensor network must be sey-con^gur*»g and sey-recou/igwring or sey-Aeolmg. In sensor networks, gucries are sent &om some devices (could be a PDA, a laptop, or any computer) to sense some data/events over some time period and a geographical region, called guerg regio». The query region is usually a subset of the total region covered by all the sensors in the network. Since the sensors are usually densely deployed, there are usually
Iranian infertile couples' strategies to manage social interactions after unsuccessful treatment with assisted reproductive technologies

Abstract Many infertile couples feel vulnerable after failed treatment cycles and find insensitive remarks or inappropriate support distressing. They fear that the stress of failed treatment cycles may affect their marriage and lead to marriage breakdown. This study explored the strategies a sample of infertile couples used to manage social interactions after unsuccessful treatment with assisted reproductive technologies. A descriptive qualitative study was conducted with 34 participants including nine infertile couples, nine infertile women and two infertile men with primary infertility, two relatives, and three fertility clinic staff. The participants were selected through purposive sampling at an infertility centre in Iran, between 2016 and 2017. Data were collected using semi-structured face-to-face interviews and analysed by qualitative content analysis approach. Participants found some social interactions after failed assisted reproductive treatment cycles to be distressing and painful. They described tolerating painful emotions which cause them sadness and sorrow as well as feeling embarrassed. As a result, they found they needed to maintain their adopting concealment strategies with their families through not permitting speculation, selective disclosure, not giving details and hiding the truth. This study showed that social interactions following failed assisted reproductive cycles can be upsetting for infertile couples. Couples use different strategies to manage potentially distressing social interactions. Healthcare providers and psychologists may provide a space for safe social interactions in order to help couples to use appropriate strategies in these circumstances.
Deep Learning for Identification of Adverse Effect Mentions In Twitter Data

Social Media Mining for Health Applications (SMM4H) Adverse Effect Mentions Shared Task challenges participants to accurately identify spans of text within a tweet that correspond to Adverse Effects (AEs) resulting from medication usage (Weissenbacher et al., 2019). This task features a training data set of 2,367 tweets, in addition to a 1,000 tweet evaluation data set. The solution presented here features a bidirectional Long Short-term Memory Network (bi-LSTM) for the generation of character-level embeddings. It uses a second bi-LSTM trained on both character and token level embeddings to feed a Conditional Random Field (CRF) which provides the final classification. This paper further discusses the deep learning algorithms used in our solution.
WeightMentor: A New Automated Chatbot for Weight Loss Maintenance

Obesity and Overweight ! are significant risk factors for many chronic conditions, such as type 2 diabetes. Weight loss is difficult and maintaining weight loss is a greater challenge. Effective communication is hindered by conflicting information and the sensitivity of the subject of obesity. Recent technological solutions for weight loss maintenance are limited. A chatbot would be appropriate for supporting weight loss as it does not require a human operator, is available 24 hours a day, and supports natural communication while maintaining anonymity. Such a system may also be integrated with popular social media platforms such as Facebook Messenger. This paper describes the design and development of the WeightMentor chatbot, a self-help motivational tool for weight loss maintenance. Chatbots may have the potential to contribute to obesity prevention and management.
Capacity Building toward Resilience: How Communities Recover, Learn, and Change in the Aftermath of Extreme Events

When faced with natural disasters, communities respond in diverse ways, with processes that reflect the extent of damage experienced by the community, their resource availability, and stakeholder needs. Local-level processes drive decisions about mitigating future flood risks, such as if, how, and where to rebuild, as well as changes in zoning practices and public outreach programs. Because of their potentially recurring nature, floods offer an opportunity for communities to learn from and adapt to these experiences with the goal of increasing resiliency through deliberation, modification of former policies, and adoption of new policies. By following the response to the September 2013 floods in seven Colorado communities, this study investigates if, how, and why communities successfully learn from extreme events and change their local government policies to increase resilience and decrease vulnerability to future floods. We find that greater openness of post-flood decision process is associated with more in-depth deliberation, learning, and more substantive and frequent policy change.
A Comparison of Readability and Understandability in Second Language Acquisition Textbooks for Pre-service EFL Teachers

Teachers must be able to comprehend their textbooks in order to fully benefit from their preparation programs. However, it is yet unclear whether textbooks used to teach challenging content to pre-service non-native speaking English teachers might be beyond their ability. To investigate this question, a textbook readability analysis was performed with the Coh-Metrix text analysis tool. Textbook understandability was also assessed by means of maze passages given to teacher candidates in a pre-service English teacher education program. Readability analyses results indicated that the majority of the texts are excessively challenging for L2 readers at the level of the participants. Understandability findings revealed that many texts were able to be read independently but that all texts could be understood with scaffolding. Contrary to prior understandability research findings that showed that these textbooks were too difficult, this study found them to be suitable for their audience. However, a correlation between text understandability and course grades indicates that ability to comprehend the text could relate to course performance. Implications are that EFL teacher educators must recognize the importance of readability for textbook selection criteria and provide learners with access to other supplementary materials to scaffold their learning.
Investigation of the influence of the length of the rope suspension of the bridge crane and the length of displacement of the cargo in the controlled sway mode on the time of displacement

The formulas for a complete analytical solution of the problem of moving cargo on a pendulum suspension of constant length along a given trajectory in a plane setting are presented. To set the desired trajectory as a time dependence of the linear horizontal coordinate of the cargo in a limited time interval, two-point Hermite polynomials are used. The field of application of the method is the automatic control of the movement of bridge and gantry cranes, as well as modeling of crane working processes. The application is limited to small angles of deviation of the cargo rope of the bridge crane from the gravitational vertical. The method makes it possible to quickly synthesize the optimal trajectory of the point of cargo suspension movement, which accurately provides the required trajectory of cargo movement. For a series of constant values of the maximum acceleration developed by the point of suspension of the cargo during a single transient process, graphs of the moving time dependences from moving length and cargo rope length are revealed. The functions obtained are not smooth and have a fracture. This makes it impractical to approximate them using the regression equation, due to the high error of the latter. The resulting graphs can be used to determine the time of movement of the cargo depending on the specified length of moving, the length of the cargo rope and the maximum acceleration developed by the drive of the cargo suspension.
Spatial sound rendering in Max/MSP with ViMiC

Originally conceptualized [2] for the software Pure Data, ViMiC was recently reﬁned and extended for release to the Max/MSP community. ViMiC (Virtual Microphone Control) is a tool for real-time spatialization synthesis, particularly for concert situations and site-speciﬁc immersive installations, and especially for larger or non-centralized audiences. Based on the concept of virtual microphones positioned within a virtual 3D room, ViMiC supports loudspeaker reproduction up to 24 discrete channels for which the loudspeakers do not necessarily have to be placed uniformly and equidistant around the audience. Also, through the integrated Open Sound Control protocol (OSC), ViMiC is easily accessed and manipulated.
Exploration and Practice of Mathematical Modeling Teaching and Competition Activities

数学建模是与传统数学教育有着极大区别，将理论与实际紧密相结合的重要载体，并衍生出数学实验，引发教学体制改革，积极广泛开展数学建模培训活动，激发学生对数学的积极性，建模教学与竞赛迅猛发展为各领域开辟新天地，无论是在国内还是国际都产生了深远影响。 本文通过深入分析数学建模教学与传统数学教学的区别、建模竞赛的发展方式和意义、数学建模的社会应用等方面探索改革的途径。 Mathematical modeling is an important carrier which has a great difference with the traditional mathematics education and closely combines the theory with practice. It derived mathematical experiments and caused the teaching reform. We should widely and actively carry out the activi-ties of mathematical modeling training to stimulate the enthusiasm of the students of mathematics. The swift and violent development of modeling teaching and contest breaks new ground in every field, which has produced a profound influence no matter at home and abroad. We explore the way of reform through in-depth analysis of the difference between mathematical modeling teaching and traditional teaching of mathematics, the development method and significance of mathematical contest in modeling and the social application of mathematical modeling.
Hardware-accelerated evolutionary hard real-time task mapping for wormhole network-on-chip with priority-preemptive arbitration

Network-on-Chip (NoC) is an alternative on-chip interconnection paradigm to replace existing ones such as Point-to-Point and shared bus. NoCs designed for hard real-time systems need to guarantee the system timing performance, even in the worst-case scenario. A carefully planned task mapping which indicates how tasks are distributed on a NoC platform can improve or guarantee their timing performance. While existing offline mapping optimisations can satisfy timing requirements, this is obtained by sacrificing the flexibility of the system. In addition, the design exploration process will be prolonged with the continuous enlargement of the design space. Online mapping optimisations, by contrast, are affected by low success rates for remapping or a lack of guarantee of systems timing performance after remapping, especially in hard real-time systems. The existing limitations therefore motivate this research to concentrate on the mapping optimisation of real-time NoCs, and specifically dynamic task allocation in hard real-time systems. Four techniques and implementations are proposed to address this issue. The first enhances the evaluation efficiency of a hard real-time evaluation method from a theoretical point of view. The second technique addresses the evaluation efficiency from a practical point of view to enable online hard real-time timing analysis. The third technique advocates a dynamic mapper to enhance the remapping success rate with the accelerated model and architecture. The final technique yields a dynamic mapping algorithm that can search schedulable task allocation for hard real-time NoCs at run time, while simultaneously reducing the task migration cost after remapping.
Waking from Mao’s Dream: Communist Ideological Imprinting and the Internationalization of Entrepreneurial Ventures in China

We theorize how an ideological imprint—ideology formed through past events—serves as an information filter that persistently affects individuals’ decision making and how subsequent behaviors of the imprinter—the entity that established the imprint—may alter it. We test our model with a longitudinal dataset of Chinese private entrepreneurs from 1993 to 2012, investigating the influence of a founder’s communist ideological imprint, which characterizes foreign capitalism as evil, and subsequent dynamics introduced by the imprinter—the Communist Party–led government of China—on two internationalization strategies that deal with foreign investors and markets: firms’ efforts to attract foreign capital and to expand globally. Our findings show that Chinese entrepreneurs’ communist ideological imprint negatively affects the internationalization of their ventures, while available and credible information contradicting communism—coming from the government directly, government-created industry social networks for entrepreneurs, or observing governmental support of internationalization—weakens the influence of the imprint. Our study contributes to a better understanding of imprinting and its decay, the effects of corporate decision makers’ political ideology, and the internationalization of firms.
Path Planning for Highly Automated Driving on Embedded GPUs

The sector of autonomous driving gains more and more importance for the car makers. A key enabler of such systems is the planning of the path the vehicle should take, but it can be very computationally burdensome finding a good one. Here, new architectures in ECU are required, such as GPU, because standard processors struggle to provide enough computing power. In this work, we present a novel parallelization of a path planning algorithm. We show how many paths can be reasonably planned under real-time requirements and how they can be rated. As an evaluation platform, an Nvidia Jetson board equipped with a Tegra K1 SoC was used, whose GPU is also employed in the zFAS ECU of the AUDI AG.
A prosódia na leitura da criança disléxica

O presente trabalho tem como objetivo conhecer o funcionamento prosodico da leitura em voz alta das criancas dislexicas. Apresentamos, inicialmente, uma revisao bibliografica que consta de um breve apanhado das principais teorias sobre o desenvolvimento normal da linguagem escrita e seus aspectos linguisticos, neurologicos e cognitivos. Passamos a uma conceituacao do termo dislexia, suadescricao e etiologia. Em seguida, introduzimos o campo de estudo da prosodia e sua aplicacao aos estudos sobre a dislexia. A nossa metodologia consistiu na gravacao da leitura de um texto, com posterior atividade de reconto e interpretacao deste por 40 estudantes, sendo 10 dislexicos (grupo clinico) e 30 do grupo naoclinico, com idade entre 9 e 14 anos, cursando da 3a a 5a serie. Os dados foram analisados acusticamente, utilizando-se o programa WinPitch, alem da analiseperceptiva. Foram analisados os aspectos prosodicos temporais e melodicos da leitura oral e do reconto dos sujeitos, com correlacao desses achados com os dados obtidos pelos testes objetivos de interpretacao. Os resultados nos permitem delinear uma tendencia na estruturacao entonativa e temporal da leitura em voz alta das criancas dos dois grupos estudados, apontando para caracteristicas peculiares aos sujeitos dislexicos pesquisados, como: aspectos relacionados a variacao da frequencia fundamental (tais sujeitos demonstram, visivelmente, uma restricao na habilidade de variar a melodia e tambem de marcar a modalidade frasal atraves deste recurso), aspectos relacionados ao processamento temporal (utilizacao excessiva das pausas e fora da sua localizacao habitual; velocidade de leitura earticulacao reduzidas) e as dificuldades na marcacao ritmica e da tonicaproeminente. A prosodia apresenta-se, neste contexto, como um reflexo das habilidades de interpretacao e tambem de decodificacao, servindo como uma medida diagnostica dessas capacidades.
Improving Science Students’ Data Visualizations: A STEAM-Based Approach

A course at the University of Nevada, Reno (UnR) teaches science students an interdisciplinary approach for designing data visualizations, in combination with big data computation and statistical analysis. This 15­week, undergraduate­level course, titled “Computational Skills for Big Data: Analysis, Statistics, and Visualization,” is co­taught by visual communication design, math, and physics faculty, and is an example of a pedagogy rooted in a stEAm 1 ­based approach that combines instruc­ tion in art or design with instruction in science, technology, engineering or mathematics. This paper introduces the interdisciplinary data visualization typology that formed the basis of this course’s visualization component: data visualization for facilitating analysis and data visualization for sharing knowledge. Data visualization for facilitating analysis is the use of visualization among an expert audience who are intimately familiar with the represented data, and data visualization for sharing knowledge is the use of visualization to represent data in a way that is intelligible to a non­expert audience. The authors argue that most of the extant data visualization education and science education literature can be classified as referring to one or the other of these types, and that this classification can help aid planning and facilitating instruction in data visualization (the design and use of graphical representations of data). This paper outlines the general structure of the course, and its data visualization components, in detail, and then provides an overview of how and why the course was assessed as it was, and finally reflects on its potential reproducibility. An analysis of work produced by students as the course progressed suggests that challenging stEm 2 undergraduate students to distinguish between data visualization for facilitating analysis and data visualization for sharing knowledge is a helpful typology to guide teaching data visualization. The paper also argues for greater collaboration between visual communication design faculty and STEM faculty in under­ graduate courses, and posits that their collaborative efforts to teach data visualization is an effec­ tive way to do this.
Fire weather of a Canterbury Northwester on 6 February 2011 in South Island, New Zealand

Foehn winds, known locally as the "Canterbury Northwester", occurred on 6 February 2011 and were associated with extreme fire weather in the lee of the Southern Alps and across the eastern South Island of New Zealand. A peak air temperature of 40.7 ̊C was recorded at Timaru, which compares with the national record of 42.4 ̊C set at Rangiora in 1973 during another Northwester. The primary objective of this study was to investigate the fire weather and the synoptic and mesoscale atmospheric processes associated with the Northwester. This was achieved through analysis of weather station data and a high-resolution Weather Research and Forecasting (WRF) model simulation. The fire weather was assessed through consideration of observable weather variables and New Zealand's version of the Fire Weather Index (FWI) in the Canadian Forest Fire Danger Rating System. The WRF model results suggest that internal gravity waves were present in the lee of the Southern Alps and considerably affected fire weather across the eastern South Island. The FWI was recorded at extreme values, due to a combination of high air temperatures and wind speeds, and low relative humidity. This study provides a better understanding of the mesoscale atmospheric dynamics and fire weather associated with the Canterbury Northwester. Colin Simpson et al. Fire weather of a Canterbury Northwester
A Technique for Resolution of the Assignment Problem Containers in a Container Terminal

A container terminal is a complicated system made up of several components in interdependence. Several materials handle possible to move containers at the port to better meet the needs of ships awaiting loading or unloading. In order to effectively manage this area, it is necessary to know the location of each container. Containers search times can be considerable and lead to delays that cause financial penalties for terminal management operators. In this chapter, the authors propose an approach to solve the problem of placement of containers through the description of a model that optimizes available storage space to handle the distance travelled between the containers and the storage locations in a seaport. In other words, a model that minimizes the total number of unnecessary movement while respecting the constraints of space and time. This work develops a software tool enabling identification of the best location of a container using the methodological resolution Branch and Bound. A Technique for Resolution of the Assignment Problem Containers in a Container Terminal