Miracle-dz/UniFAR-FTUs huggingface dataset:
Theoretical and Experimental Investigation on Rotor Dynamic Behavior of Bladeless Turbine for Innovative Cycles

This paper focuses on rotor dynamic investigation of a bladeless turbine, or Tesla turbine, for application to innovative small scale cycles. Tesla rotor consists of a shaft with several co-rotating disks with small gaps between each other. The flow through the disks creates a momentum exchange by viscous effect, motoring the shaft. Thanks to its simplicity and low cost, the Tesla expander is attractive for energy harvesting and waste heat recovery from low/medium temperature in small and micro scale applications. Rotor assembly and its parts may present dynamic criticalities, due to their structural characteristics: to predict and ensure low vibrations during operations, numerical and experimental studies have been carried out on some prototypes. The activity started considering a non-rotating single Tesla disk both in free and real constrained configuration: an experimental modal analysis was performed, whose results were used to validate a disk numerical model. In this case, an analytical approach with a simplified geometry assumption was considered. All methods results were correlated each other and discrepancies have been identified and analysed. Furthermore, the investigation of a single disk rotor vibrational behaviour has been extended from static conditions to rotating conditions. Numerical analysis has been carried on taking into account the effect of gyroscopic couples and centrifugal field generated by disk rotation. In parallel, a corresponding experimental activity has been done using a dedicated test rig which allowed to perform vibrational operational measurement while the disk was in motion. Campbell diagram of the single rotating disk on the shaft has been obtained from numerical and experimental analysis allowing to identify system dynamic behaviour and to deepen aspects related to critical speeds. Finally, a whole rotor model has been developed, allowing the characterization of the dynamic behaviour of a fully assembled turbine rotor. The developed models, validated with experiments, are powerful tools that can predict the bladeless expander vibrational behaviour at the early phase of design.
TILM: Neural Language Models with Evolving Topical Influence

Content of text data are often influenced by contextual factors which often evolve over time (e.g., content of social media are often influenced by topics covered in the major news streams). Existing language models do not consider the influence of such related evolving topics, and thus are not optimal. In this paper, we propose to incorporate such topical-influence into a language model to both improve its accuracy and enable cross-stream analysis of topical influences. Specifically, we propose a novel language model called Topical Influence Language Model (TILM), which is a novel extension of a neural language model to capture the influences on the contents in one text stream by the evolving topics in another related (or possibly same) text stream. Experimental results on six different text stream data comprised of conference paper titles show that the incorporation of evolving topical influence into a language model is beneficial and TILM outperforms multiple baselines in a challenging task of text forecasting. In addition to serving as a language model, TILM further enables interesting analysis of topical influence among multiple text streams.
Air Traffic Controller’s Behavior Recognition from Still Images by Transfer Learning

The fatigue problem of air traffic controllers is one of the important reasons that en-danger the safety of civil aviation. In this paper, we introduce behavior recognition into the field of fatigue monitoring of civil air traffic controllers. We investigate the method of automatic recognition of controller’s behaviors by using transfer learning and model fusion. The task of behavior recognition for controllers can be regarded as a multi-classification problem (Such as putting heads on desks for a nap, lay with face upward, nod to sleep, talking with others, directing planes normally, Hold up chin on left hand, writing notes on strips radio check, Resting hand on forehead ). Our study solve this problem from three aspects: (1) Set up a data set of controller behavior, including 18247 pictures of 10 actions; (2) Employ two-stream CNN(Resnet50,Inception V3) to extract different features; (3) We investigate different fusion strategy to improve the accuracy of action recognition of controllers. Experiments demonstrate that our method achieves a recognition accuracy of 94.2% and 93.7% on the CAFUC-Controller and Kaggle-Driving datasets.
The Contribution of Pharmacological Agents in the History of Organ Transplantation

More than 200,000 people in the world currently need life-saving organ transplants. Transplantation medicine is the one field of medicine that requires a third party, which is why so much effort is put into ensuring that transplanted organs survive as long as possible. The history of organ transplantation is the story of a battle with immunity, and pharmacological agents have done much to help physicians and patients gain the upper hand in this struggle. This paper provides an overview of the contributions pharmacological agents have made in the history of organ transplantation, with a focus on the field’s early history
Vascular dementia classification based on hilbert huang transform as feature extractor

<a name="_Hlk14121907"></a><span lang="EN-MY">Impairment of cognitive and working memory after stroke was common. Vascular dementia (VaD) was a prevalent type of dementia that was caused by an impaired blood supply to the brain </span><span lang="EN">because of a series of small strokes. </span><span lang="EN-MY">Electroencephalogram (EEG) gives information about brain status and activity, so it had a lot of potential to be used in diagnosing people with dementia. </span><span lang="EN">Since the EEG signal is extremely non-linear and non-stationary data, traditional Fourier analysis such as Fast Fourier Transform (FFT) that broadens sinusoidal signals cannot describe the amplitude contribution of each frequency value in specific time. Meanwhile, Hilbert Huang Transform (HHT) was based on the characteristic local time scale of the signal, it can </span><span lang="EN-MY">efficiently obtain instantaneous frequency and instantaneous amplitude for nonstationary and nonlinear data. In this paper, HHT was employed as feature extraction method to extract </span><span lang="EN">the energy features of frequency bands from post stroke patients and healthy subjects. The extracted features were fed into extreme learning machine (ELM) for classifying post stroke patient with VaD and healthy subjects. The results of classification accuracy using HHT as feature extractor and FFT as feature extractor were compared. The mean accuracy of classification using HHT was 59.14%, respectively, while mean accuracy of classification using FFT was 94.4%, respectively, in classifying post stroke patient with VaD and healthy subjects. </span>
Opacity, Transition, and Design Research

Históricamente, la educación de diseño se estructuró alrededor de proyectos como soluciones en un futuro previsible y cognoscible. Sin embargo, los investigadores que operan en el paisaje del Diseño para la Transición deben lidiar con un terreno mucho menos cierto. Los desafíos quedan fuera del alcance de lo que comúnmente se ha entendido como el ámbito del diseñador. Los proyectos de transición no encajan dentro de los ritmos habituales de los sistemas políticos, económicos y gubernamentales; a menudo requieren una coordinación completa y compleja entre los actores en diferentes sistemas; están dirigidos al cambio social, cultural y psicológico; la ubicación de la práctica es un sistema vivo que no ofrece un conjunto confiable de puntos de inflexión. Teniendo en cuenta la investigación de Diseño para la Transición basada en la práctica, este artículo describe los enfoques adoptados, analiza los desafíos de la realización de investigaciones y propone consideraciones clave para abordar en el trabajo futuro.
Design of a back-end for a camera based person detection system

Wouter Legiest: Design of a back-end for a camera based person detection system Master of Science Thesis Tampere University Master of Electronics and ICT Engineering Technology (KU Leuven) August 2019 In this thesis, a back-end web server is developed for the CityTrack project. The project uses modern Deep Learning techniques to provide object and people detection on embedded devices. By using multiple of these devices, detection nodes, statistical data can be collected about a certain venue or event. To expand this project, a web application is needed to visualise the data with the possibility to watch in real time. In addition to the web application, a central database should be established to provide long-time structured storage for the detection data. To make well-considered choices, different technologies are discussed and weighed against each other. For instance, for the communication between the detection nodes and the web application, the HTTP-based REST architectural style and SOAP protocol are compared to the MQTT protocol. Furthermore, the real time capable communication technologies WebSocket, SeverSent Event and HTTP Long Polling is reviewed. The system uses the REST architectural style due to practical implementation reasons and WebSocket due to the limitations of the other alternatives. The layered architecture is then discussed to arrive at a proposal for a more modern version of the web architecture. The theoretical background and implementations of all components are then discussed. The advantages and disadvantages of each implementation are reviewed and a thoughtful choice was made. To make a sustained choice, the performance of different WSGI server implementations are tested. A WSGI server is an interface between a web server and a Python-based framework. The ApacheBench stress testing tool examines different aspects of the performance. The result is that the uWSGI server performs the best on both latency and throughput aspect compared to the other candidates tested. Also, the performance of the various implementations of ASGI server has been tested analogously. An ASGI interface is a superset of WSGI with additional support for asynchronous communication technologies. Implementations of the ASGI interface are tested on the WSGI functionalities. In this way, it is investigated whether the current implementation of ASGI could replace the WSGI server. The results show that the current implementations of various ASGI servers underperform to replace a WSGI server.
3D Mapping and 6D Pose Computation for Real Time Augmented Reality on Cylindrical Objects

Visual Augmented Reality (AR) typically overlays virtual computer graphics or other virtual contents on the real world videos, attracting much interest from both academic and industrial communities. Although AR techniques on planes are well studied, cylindrical objects are seldom used for augmented reality. In this paper, we propose a new method for 3D reconstruction and 6D pose computation for augmented reality on a cylindrical object. The 6D pose is the relative pose between the camera and the cylindrical object, which is very convenient to make augmented reality. First, we capture some images with a cylindrical object and then reconstruct its 3D model with textures offline by using projective invariance and image contours. Second, according to the 3D model, we track the 6D relative pose between the camera and the cylindrical object online, where we propose a linear P3P RANSAC to remove outliers. Finally, the virtual images are exactly aligned with the cylindrical object in the real world. Experimental results show that the proposed method outperforms the state of the arts in terms of 3D mapping and 6D pose computation on cylindrical objects.
Enhancement of genetic algorithm optimization on distribution operation control by fuzzy inclusion

The optimal control of distribution system operation is presented in this paper. The objective of the control is minimum real power loss simultaneously achieved with voltage profile improvement. The distribution system equipped with Load Tap Changer (LTC) and switchable Shunt Capacitors is optimally controlled by determining the tap position of LTC and switching status of Shunt Capacitor at every hour for the 24-hour period. Two Genetic Algorithms (GAs) are developed for load curve partition and hourly components status determination. The performance of GA for components optimal scheduling is further enhanced by integrating Fuzzy Strategies in fitness evaluation and constraints satisfaction. The scheme of Fuzzy Convex Decision Making (FCDM) that provides flexible objective achievement and soft constraints is employed. This enables considering more extensive solutions that may lead to better optimal control. The proposed control strategy is implemented on 30-bus distribution system and the system improvements are observed. The enhancement of fuzzy integration is highlighted.
Ensino de lógica de programação no ensino fundamental utilizando o jogo Robotizen: um relato de experiência

Este artigo relata a experiência de licenciandos em Computação em ensinar lógica de programação no ensino fundamental. Visando estabelecer um contexto de aprendizagem lúdico e atraente, foi utilizado um jogo educativo digital, denominado Robotizen. O seu game design favorece a experiência de aprender a programar jogando e foi a base para novas estratégias didáticas. A metodologia do projeto guiou-se pelas fases de desenvolvimento cognitivo das crianças e na divisão estratégica dos cenários do Robotizen, a fim de introduzir e fazê-las utilizar conceitos de programação de forma iterativa e colaborativa. Os resultados obtidos sugerem o potencial do uso do jogo para engajar e estabelecer aprendizagem orientada a interesses e descobertas.
Automated Design of Robotic Hands for In-Hand Manipulation Tasks

Grasp planning and motion synthesis for dexterous manipulation tasks are traditionally done given a pre-existing kinematic model for the robotic hand. In this paper, we introduce a framework for automatically designing hand topologies best suited for manipulation tasks given high-level objectives as input. Our pipeline is capable of building custom hand designs around specific manipulation tasks based on high-level user input. Our framework comprises of a sequence of trajectory optimizations chained together to translate a sequence of objective poses into an optimized hand mechanism along with a physically feasible motion plan involving both the constructed hand and the object. We demonstrate the feasibility of this approach by synthesizing a series of hand designs optimized to perform specified in-hand manipulation tasks of varying difficulty. We extend our original pipeline 32 to accommodate the construction of hands suitable for multiple distinct manipulation tasks as well as provide an in depth discussion of the effects of each non-trivial optimization term.
Strategic Factors Enabling Digital Maturity: an Extended Survey

Over the last decade, new opportunities enabled by digital technologies have become the center of attention of companies. In fact, not only digital technologies transform businesses, but they also influence the way people interact and work. Organizations need to adapt to the rapid advances in the digital environment and shift their focus from digital transformation to digital maturity. However, it is still not clear which are the main strategic factors affecting the level of digital maturity of businesses. Based on a survey of 153 digital leaders, this study identifies key strategic factors of digital transformation and examines the relationship between them and digital maturity. Our results indicate that digital maturity is higher when a digital vision is shared by top management, where the vision is adequately communicated within the company, with employees requiring training in digital skills.
What Is Cryptography?

Cryptography's aim is to construct schemes or protocols that can still accomplish certain tasks even in the presence of an adversary. A basic task in cryptography is to enable users to communicate securely over an insecure channel in a way that guarantees their transmissions' privacy and authenticity. Providing privacy and authenticity remains a central goal for cryptographic protocols, but the field has expanded to encompass many others, including e-voting, digital coins, and secure auctions. This paper explains what cryptography is about and how we can scientifically justify a cryptographic scheme's security.
Automated Unbounded Verification of Stateful Cryptographic Protocols with Exclusive OR

Exclusive-or (XOR) operations are common in cryptographic protocols, in particular in RFID protocols and electronic payment protocols. Although there are numerous applications, due to the inherent complexity of faithful models of XOR, there is only limited tool support for the verification of cryptographic protocols using XOR. The Tamarin prover is a state-of-the-art verification tool for cryptographic protocols in the symbolic model. In this paper, we improve the underlying theory and the tool to deal with an equational theory modeling XOR operations. The XOR theory can be freely combined with all equational theories previously supported, including user-defined equational theories. This makes Tamarin the first tool to support simultaneously this large set of equational theories, protocols with global mutable state, an unbounded number of sessions, and complex security properties including observational equivalence. We demonstrate the effectiveness of our approach by analyzing several protocols that rely on XOR, in particular multiple RFID-protocols, where we can identify attacks as well as provide proofs.
Exploring the Typology and Impacts of Audience Gratifications Gained from TV–Smartphone Multitasking

ABSTRACT Using an additional device (i.e., smartphone) while viewing TV is becoming one of the most popular forms of media multitasking, and the motivations of the TV–smartphone multitasking are worthwhile to investigate. Extant studies on gratifications derived from media consumption mainly examined the consumption of a single medium and few studies evaluated gratifications from concurrent media combinations. But the gratifications of media multitasking vary greatly among different forms of multitasking. This study addresses the typology and impacts of gratifications in simultaneous TV–smartphone use through an online national survey in China in 2016 (N = 682), based on the affordance-based framework. The study identifies four kinds of gratifications in TV–smartphone multitasking: emotional, social, habitual, and contextual interaction gratifications. It also finds positive impacts of fear of missing out and social media use on all gratifications. The results finally show that habitual gratifications negatively predict the propensity that the audience select TV as the primary screen.
Spaceborne Azimuth Multichannel BiSAR With Geosynchronous Transmitter and LEO Receiver: High-Resolution Wide-Swath Image Formation

Spaceborne azimuth multichannel bistatic synthetic aperture radar (AMC-BiSAR) system employed inclined geosynchronous (GEO) transmitter and low-Earth-orbit (LEO) receiver is capable of providing a vast area of surveillance and fine spatial resolution, which presents great potentials for Earth observation. Nevertheless, owing to complex geometry and big differences of orbital characteristics, high-resolution wide-swath (HRWS) imaging for GEO-LEO AMC-BiSARs remains three major issues: 1) “Stop-and-Go” approximation is invalid because of long round-trip delay and high receiver velocity; 2) Due to the special bistatic configuration, the conventional effective phase center (EPC) operation for unambiguous signal reconstruction cannot be directly used; 3) Two-dimension spatial-variant characteristics of the echo signal caused by nonlinear and nonparallel trajectories of transmitter and receiver raise challenges for BiSAR focusing. To address these problems, starting from modeling geometry of inclined GEO-LEO AMC-BiSAR, an accurate slant range model without “Stop-and-Go” approximation is derived in the paper. Then the new effective positions of the receiving channels in GEO-LEO AMC-BiSARs are obtained based on the geometry, and the unambiguous Doppler spectrum can be recovered effectively. Finally, a nonlinear chirp scaling imaging algorithm based on the time-domain perturbation (TP-NLCS) is derived and presented, which can correct the variation of range cell migration and azimuth frequency modulation rate. Simulation results show the validity of the proposed method, which can implement GEO-LEO AMC-BiSAR HRWS focusing and has fine phase-preserved capability.
Rastreabilidade de Requisitos em Metodologias Ágeis: um Estudo Exploratório

Agile methodologies are increasingly present in the industry. Known as a methodology that adapts easily to changes, which reduces risk and provides product creation quickly and safely, it has features such as: constant contact with the client, generation of releases at the end of each iteration, prioritizing what has more value to the client, in addition to "embrace" easily the changes requested. Being requirements traceability important when we think of changes as it facilitates activities such as impact analysis, it is possible to realize that it would be a very useful activity in the agile process. However, there are some challenges when trying to apply traceability in agile environments. This paper is aimed to perform an exploratory research to raise the main problems related to traceability in agile environments, thus collecting information to assist in raising requirements for a tool that supports traceability in agile environments, and perform pre-traceability inter-tracking and post-traceability.
National Research Agenda for the Prevention of Occupational Hearing Loss—Part 2

Abstract The National Institute for Occupational Safety and Health (NIOSH) is tasked with generating new knowledge in the field of occupational safety and health and transferring that knowledge into practice for the betterment of workers. In 1996, NIOSH established the National Occupational Research Agenda (NORA), which identified occupational hearing loss as a priority research area. The NORA Hearing Loss Team, composed of representatives from industry, academia, labor, professional organizations, and other governmental agencies, has developed a national research agenda for the prevention of occupational hearing loss. This is Part 2 of that document, outlining research needed to address the problem through effective prevention programs.