Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance Characterization of a Novel Plasma Thruster to Provide a Revolutionary Operationally Responsive Space Capability with Micro- and Nano-Satellites

Abstract : Few options currently exist to provide propulsion for extremely small satellites due to design constraints on power, volume, and weight. However, future operation will require a capability to conduct orbital maneuvers, momentum dumping, and precision pointing for these low cost satellites. The research presented here represents the first effort to operate and quantify the performance of a new micro plasma thruster design which provides a novel solution to these disparate competing constraints. The thruster in this study represents a deviation from traditional circular Hall thruster design practices, because it eschews a central magnetic circuit, which results in nearly parallel electric and magnetic field lines within the thruster discharge channel. This design decision reduces thruster complexity and thermal susceptibility, but it also reduces the ionization efficiency. The cornerstone of this study involved the direct measurement of thrust in order to quantify the efficiency and specific impulse of this innovative thruster. The investigation also included characterization of the thruster exhaust plume, voltage-current characteristics, and operating limits. Results are enumerated and suggestions for improvement provided.
Roadway-Vehicle Interaction, Physical Indexes, and Human Judgment of Ride Quality

Present serviceability index (PSI) modeling has been an important subject for decades. Other dynamic indexes characterizing a roadway such as the international roughness index (IRI), averaged rectified slope (ARS), and averaged rectified speed (ARV) have been proposed and studied. However, the roles played by these indexes in the interaction between road, vehicle, and human ratings have not been made clear. A unified physical model linking the static profile of a roadway and the dynamic response of a vehicle to the profile to the serviceability index of the roadway is presented here. Analytical expressions for jerk index, acceleration index, ARV, ARS, and IRI are derived from the developed model in terms of the physical parameters for roadways and the dynamic characteristics of a vehicle. Then a linear relation between the PSI and the logarithm of the jerk index is proposed. Using the jerk index computed from field profile data, the linear functional form for the PSI is verified, and regression R2 values higher than 0.94 are obtained for various types of pavements. The same analysis is performed for other dynamic indexes, and the R2 values are found to be approximately in the range from 0.70 to 0.80. These results indicate that the theoretical model correctly predicts and explains the human rating of ride quality and that the jerk experienced by raters in a moving vehicle dictates the ratings. Moreover, the relationship of the static parameters of roadway profiles with human ratings is discussed using the conventional approach.
Effects on driving task and road safety impact induced by the usage of adaptive cruise control (ACC): a focus groups study

Adaptive cruise control (ACC), through the partial automation of the longitudinal driving task, is expected to increase driving comfort and assure a positive impact on road safety. Previous research showed that some side effects can result from the usage of the ACC. Those studies were mainly performed with drivers who never used the ACC before taking part in the experiments. For this reason, little information is available about how the ACC actually affects the driving task of real users of the system. In order to investigate the topic, two focus groups sessions were performed in Portugal with 13 ACC drivers. The findings revealed users’ satisfaction regarding the comfort and safety provided by the system. On the other hand, some cases of behavioural adaptations to the system were reported. Further research on the problem domain is suggested.
Nonintrusive Detection of Driver Cognitive Distraction in Real Time Using Bayesian Networks

Driver distraction has become an important and growing safety concern as the use of in-vehicle information systems (IVISs), such as cell phones and navigation systems, continues to increase. One approach to allowing people to benefit from IVISs without compromising safety is to create adaptive IVISs that adjust their functions according to driver and roadway state. A critical element of adaptive IVISs involves monitoring driver distraction in real time; with such a monitoring function it is possible to mitigate that distraction. This study applied Bayesian networks (BNs), a data mining method, to develop a real-time approach to detecting cognitive distraction using drivers’ eye movements and driving performance. Data were collected in a simulator experiment involving 10 participants who interacted with an IVIS system while driving. BN models were trained and tested to investigate the influence of three model characteristics on distraction detection: time history of driver behavior, inclusion of hidden nodes in the model structure, and how data are summarized and the length of training sequences. Results showed that BNs could identify driver distraction reliably with an average accuracy of 80.1%. Dynamic BNs (DBNs) that consider time dependencies of driver behavior produced more sensitive models than static BNs (SBNs). Longer training sequences improved DBN model performance. Blink frequency and fixation measures were particularly indicative of distraction. These results demonstrate that BNs, especially DBNs, can detect driver cognitive distraction by extracting information from complex behavioral data. Potential applications include the design of adaptive in-vehicle systems and the evaluation of driver distraction.
The Relationship between Monetary Policy and Asset Prices: Evidence from the Turkish Economy

The developments in the US housing and real estate sectors played an important role during the Global Financial Crisis of 2008. The findings of previous theoretical and empirical studies have revealed that there was a strong relationship between the expansionary monetary policy that included high liquidity and low interest rates in the US economy and the housing price bubble, which played a central role in the development of the crisis. These developments have revealed the importance of the relationship between monetary policies and asset prices.In this direction, the present study aims to conduct an empirical investigation of the relationship between monetary policies and asset prices in the Turkish economy. In line with this purpose, the SVAR approach was used in the study. The period included within the scope of the present study was determined as 2011:5-2018:5. According to the findings obtained, it is observed that the only significant reaction of monetary policies to the variables included within the model was to real effective exchange rate and treasury bill rate. Additionally, the effects of monetary policies on real effective exchange rate, housing price index, BIST 100 index, treasury bill rate and interest of government securities were found to be significant.
Towards a traffic map of the Internet: Connecting the dots between popular services and users

The impact of Internet phenomena depends on how they impact users, but researchers lack visibility into how to translate Internet events into their impact. Distressingly, the research community seems to have lost hope of obtaining this information without relying on privileged viewpoints. We argue for optimism thanks to new network measurement methods and changes in Internet structure which make it possible to construct an "Internet traffic map". This map would identify the locations of users and major services, the paths between them, and the relative activity levels routed along these paths. We sketch our vision for the map, detail new measurement ideas for map construction, and identify key challenges that the research community should tackle. The realization of an Internet traffic map will be an Internet-scale research effort with Internet-scale impacts that reach far beyond the research community, and so we hope our fellow researchers are excited to join us in addressing this challenge.
Performance Analysis of Solar Water Heater

Two solar water heaters of 100 liter and 200 liter were installed on the roof-top of electronics laboratory at Old Academic Building (OAB) of Electrical and Electronics Engineering Department of BUET. The data of 12 months have been collected and analyzed in this paper. It is found that the incoming hot tap water is about 30℃ higher than the room temperature during day time during winter months. This is about 25℃ in afternoon hours.
An Integrated Decision Support System in a Chinese Chemical Plant

In July 1986, the institute of systems engineering at Dalian University of Technology and the Dalian Dyestuff Plant developed and implemented an integrated decision support system DSS at the Dalian Dyestuff Plant, one of the largest chemical dye plants in China. The DSS combines a linear-programming-based optimization model with a rule-based artificial-intelligence model. The system contains subsystems for production planning, accounting and finances, inventory, and information services. Operational results indicate that the system increased the annual profits by at least 4 million RMB in 1987 about one million US dollars; the plant's total profits were about 40 million RMB per year at that time.
Using AI to Analyse Light Curves for GEO Object Characterisation

Characterisation of space objects in Earth orbit is an essential task, particularly with the increase in space traffic and the advent of space traffic management. Proper understanding of an objects shape, size and attitude are vital in predicting its future behaviour. Light curves are increasingly being used to characterise objects, with methods ranging from simple regression analysis through to complex AI solutions. The method presented and demonstrated herein is a machine learning algorithm based on convolutional neural networks, capable of characterising object parameters such as geometry, attitude and materials of an object. The method is intended to be a flexible classification method, which could be extended to all orbits and any type of object, including debris. Herein, intermediate results of the ongoing study are presented, demonstrating the use of a multiclassification and multi-branch classification model. The results demonstrate that the method can successfully, with greater than 80% accuracy classify the shape, size, attitude and main material of an object in geosynchronous orbit from a single full night light curve.
Immigration and work-related injuries

There is increasing evidence that foreign-born workers are over represented in physically demanding jobs. This suggests that they may sort into positions with a relatively higher injury risk than native workers. At the same time, shares of foreign born workers in host economies are growing. Does the increasing presence of migrant workers alleviate natives’ injury risk exposure? This paper provides evidence of the effects of immigration on the incidence and severity of work-related accidents in a context in which occupational mobility of native workers is relatively low. We combine administrative data on the universe of work-place accidents in Italy with the Labour Force Survey from 2009 to 2017. Our approach exploits spatial and temporal variation in the inflow of foreign-born individuals across provinces. Using a fixed-effects and an instrumental variable specification based on historical settlements, we show that inflows of foreign-born residents are associated with a reduction in the rate and severity of work injuries for natives. To investigate mediating mechanisms we use a longitudinal version of the Italian Labor Force Survey (2009-2013). The results support the hypothesis that the drop in injuries does not derive from a reallocation of native workers towards less risky jobs, nor a positive selection of the labor force resulting from higher unemployment or internal mobility. JEL: C55, J61, J28, I1
Optimal Energy Control of a Grid-Connected Solar Wind-Based Electric Power Plant Applying Time-of-Use Tariffs

The paper considers the daily energy consumption variations for low demand season and high demand season weekdays and weekends in order to compare the corresponding fuels cost and analyse the operational efficiency of the PV/PW/DG/battery system for 24 hours period taken as control horizon. Previous researches have assumed a fixed load and uniform daily cost. A load following diesel dispatch strategy is used in this paper and the fuel costs and energy flows are analysed. The results show that a renewable energy system which combines the PV/PW/diesel/battery models achieves a better saving for the fuel during the high demand as well as the low demand seasons for days considered when compared to a model where the diesel generator satisfies the loads on its own.
Microstrip multiplexer with compact in‐line feed structure

A microstrip multiplexer circuit using a compact in‐line feed structure is presented and experimentally demonstrated. The multiplexer consists of four edge‐coupled microstrip bandpass filters that are independently designed using any filter synthesis technique. The bandpass filters are interconnected in a sequential manner using specific lengths of transmission line that isolate the filters from one another at the center frequency of their passbands. © 2007 Wiley Periodicals, Inc. Microwave Opt Technol Lett 49: 3128–3130, 2007; Published online in Wiley Inter‐Science (www.interscience.wiley.com). DOI 10.1002/mop.22945
Fusing image feature and title semantic regularization with adversarial networks for cross-modal retrieval

With the improvement of living standard, people pay more and more attention to their health. Food is the foundation of human life, modern society places more emphasis on a balanced diet, which controls fat, protein, carbohydrate and vitamin intake. So food computing is more and more important. Food retrieval is one of the important research directions in food computing. On the basis of food retrieval, we can predict ingredients and instructions in each dish, according to the ingredients and instructions to speculate on the visual effect of cooking, which can guide human reasonable diet, analyse human diet structure and diet culture and so on. In this paper, we focus on cross-modal retrieval between food image and recipe. Firstly, we analyze the problems existing in the present method. Based on the problems existing in the existing method, a fusion image feature and title regularization with adversarial network is proposed, which uses the idea of generative adversarial to align the modes, fuses the local features and global features of the image, and adds the semantic regularity of title to improve the accuracy of the retrieval.
Harnessing stakeholder motivation: towards a Swiss sustainable building sector

The contribution of stakeholders to the development and implementation of a sustainable built environment has emerged as crucial to the delivery of meaningful change. The inclusion of all affected parties can facilitate the development of patterns, structures and buildings that are sustainable in the social, ecological and economic dimensions. The slow development of a more sustainable building sector often results from the absence of knowledge about possible benefits because of financial constraints or the presence of conflicting interests. Furthermore, in most cases, measures to foster a sustainable building sector do not include all of the relevant stakeholders or are only one-sided. Based on a literature review of stakeholders in the building sector, this paper describes the stakeholders involved in the development of sustainable buildings and the challenges in stakeholder motivation. The practical case of the Network for Sustainable Construction Switzerland demonstrates how to foster sustainable construction by including a wide range of stakeholders and the need to address stakeholders with diverse initiatives. This case study supports the hypothesis that stakeholder motivation cannot be created by a single initiative; rather, a variety of actions are required to deliver change successfully. La contribution des parties prenantes au développement et à la mise en oeuvre d'un cadre bâti durable est apparue comme cruciale pour que des changements significatifs puissent être apportés. L'inclusion de toutes les parties concernées peut faciliter le développement de schémas, de structures et d'immeubles présentant un caractère durable sur les plans sociaux, écologiques et économiques. La lenteur de développement d'un secteur du bâtiment plus durable résulte souvent du fait de ne pas avoir connaissance des avantages possibles en raison des contraintes financières ou de la présence d'intérêts contradictoires. En outre, dans la plupart des cas, les mesures destinées à encourager un secteur du bâtiment durable n'incluent pas l'ensemble des parties prenantes concernées ou ont un caractère partial. Sur la base d'une analyse documentaire des parties prenantes du secteur du bâtiment, cet article décrit les parties prenantes impliquées dans le développement de bâtiments durables et les problèmes qui se posent pour motiver les parties prenantes. Le cas pratique du Réseau pour la construction durable en Suisse montre comment favoriser les constructions durables en incluant un large éventail de parties prenantes et la nécessité de traiter la question des parties prenantes par des initiatives diverses. Cette étude de cas conforte l'hypothèse selon laquelle la motivation des parties prenantes ne peut pas être suscitée par une initiative unique; c'est plutôt une diversité de mesures qui est nécessaire pour réussir à apporter les changements recherchés. Mots clés: secteur du bâtiment, gestion des parties prenantes, motivation des parties prenantes, durabilité, construction durable
Runup Measurements of the December 2004 Indian Ocean Tsunami

We summarize some of the findings and observations from the field surveys conducted in the aftermath of the horrific tsunami of 26 December 2004 and reported in this issue. All these field surveys represent an unprecedented scientific undertaking and involved both local and international scientists working side by side. The 26 December tsunami was the first with transoceanic impact, since comprehensive postevent hydrodynamic surveys began to be conducted in the early 1990s with modern measurement tools. The tsunami impacted at least 16 nations directly: Indonesia, Malaysia, Thailand, Myanmar, India, Sri Lanka, Oman, Somalia, Kenya, Tanzania, Madagascar, the Maldives, Rodrigues, Mauritius, Réunion, and the Seychelles. The death toll included citizens from many other countries in Asia, Europe, the South Pacific, and the Americas, giving this tsunami the grim distinction of being the first universal natural disaster of modern times.
ROLE OF DENIAL- OF -SERVICE IN NETWORK SECURITY

We know that in network systems it is not possible to avoid Denial-of-Service attacks. Denial-of-Service attacks will play important role on security as well as on through put. As Security has their own vulnerability to DoS, this paper studies how to avoid the risk of DoS in security and through put. In this context, we begin building attacker capabilities and a basic network to model the actual protocol operation. Secondly we build an advanced model for evaluation of the risk. After defining the intruder capability with a basic model, the risk evaluation model gives the "Risk-Evolution-Factor" (REF) for the Security and through put. The "Risk- Evolution-Factor" is going to presents the amount of computing resources is expected to lose with a specified level of confidence in security and through put. This model can help end users to have a good understanding of the protocols structures, what they are using, and in addition to that provide help developers and designers to examine their developments and designs and get hints to improve the same.
Real-time and automatic map stitching through aerial images from UAV

Real-time aerial map stitching through aerial images had been done through many different methods. One of the popular methods was a features-based algorithm to detect features and to match the features of two and more images to produce a map. There are several feature-based methods such as ORB, SIFT, SURF, KAZE, AKAZE and BRISK. These methods detect features and compute homography matrix from matched features to stitch images. The aim for this project is to further optimize the existing image stitching algorithm such that it will be possible to run in real-time as the UAV capture images while airborne. First, we propose to use a matrix multiplication method to replace a singular value decomposition method in the RANSAC algorithm. Next, we propose to change the workflow to detect the image features to increase the map stitching rate. The proposed algorithm was implemented and tested with an online aerial image dataset which contain 100 images with the resolution of 640 × 480. We have successfully achieved the result of 1.45 Hz update rate compared to original image stitching algorithm that runs at 0.69 Hz. The improvement shown in our proposed improved algorithm are more than two folds in terms of computational resources. The method introduced in this paper was successful speed up the process time for the program to process map stitching.
Sparse Nonnegative Tensor Decomposition for EEG Data

—Tensor decomposition has become an important tool for EEG data analysis. Using time-frequency representation, the EEG data are transformed into a nonnegative tensor. By nonnegative tensor decomposition, EEG feature components will be extracted. In most cases, the extracted EEG components are not only nonnegative but also sparse. Therefore, additional sparse regularization are necessary to improve the extracted sparse components. In this study, we developed a model of CANDECOMP/PARAFAC tensor decomposition with both nonnegative constraint and sparse regularization. The experimental results of real EEG data demonstrate that our method is efﬁcient to extract more meaningful sparse EEG components.
Improved switching characteristics of fast power MOSFETs applying solder bump technology

The impact of a reduced package stray inductance on the switching performance of fast power MOSFETs is discussed applying advanced 3D packaging technologies. Starting from an overview over new packaging approaches, a solder bump technology using a flexible PI substrate is exemplarily chosen for the evaluation. Measurement techniques to determine the stray inductance are discussed and compared with a numerical solution based on the PEEC method. Experimental results show the improvement of the voltage utilization while there is only a slight impact on total switching losses.