Miracle-dz/UniFAR-FTUs huggingface dataset:
The design of a signal processing system for CCD star sensor

The CCD star sensor is a kind of higher accuracy and more advanced technology of attitude sensitive equipment which observes fixed star as benchmark, and it is widely used on satellite attitude control system. It has many advantages which includes high precision, high sensitivity, no attitude accumulative error and so on. This paper describes how to design and develop a signal processing system (SPS) based on FPGA (Field Programmable Gate Array) for CCD star sensor. Above all, an integrated solution to a signal processing system is put forward briefly, which contains the design of system architecture and system function. Secondly, Some Key technologies of design and implementation are described in detail, which contain these designs of data stream, instructions stream, multi-clock data processing and triple modular redundancy (TMR). In practice, hardware and system tests have been carried out, and the results prove that the SPS is reliable and stable, and it has been used successfully in CCD start sensor.
Testing the Links How strong are the links between institutional quality and economic performance ?

GREAT deal of economic research in recent years suggests that institutions are vital for economic development and growth. Typically, economists have looked at the level of economic development, as measured by per capita GDP, and have found that differences in per capita incomes around the globe—ranging from only about $100 a year in parts of sub-Saharan Africa to over $40,000 in some of the advanced economies—are closely related to differences in the quality of institutions. The aim of an IMF research study has been to take stock of recent work relating to the impact of institutions on three dimensions of economic performance—level of economic development, growth, and volatility of growth—and advance the debate through new empirical analysis. In particular, the study tries to estimate the empirical strength of these relationships; the impact that improvements in institutions could have on incomes and growth in different regions; and the role that economic policies play, both in contributing to stronger institutions and in supporting better economic outcomes more generally. To determine to what extent institutions affect economic performance, we developed a simple econometric framework relating the macroeconomic outcomes for each country to (1) a measure of its institutions (see Box 1); (2) a measure (or set of measures) of macroeconomic policy; and (3) a set of exogenous variables. This framework allows one to consider competing explanations that have been put forward in the literature— notably, the roles of institutions, policies, and geography—and to assess their quantitative impact. The study finds that institutional quality does have a significant effect, not only on the level of income but also on growth and the volatility of growth. The findings are also consistent for all measures of institutions, but we rely on the aggregate governance index for the illustrations. Given the dominance of institutional factors in explaining economic performance, is there a role for policies? The results show that there is.
3 D Face Geometry Capture Using Monocular Video

Accurate reconstruction of facial geometry has been one of the oldest tasks in computer vision. Despite being a long-studied problem, many modern methods fail to reconstruct realistic looking faces or rely on highly constrained environments for capture. High fidelity face reconstructions have so far been limited to either studio settings or through expensive 3D scanners. On the other hand, unconstrained reconstruction methods are typically limited by low-capacity models. We aim to capture face geometry with high fidelity using just a single monocular video sequence of the face. Our method reconstructs accurate face geometry of a subject using a video shot from a smartphone in an unconstrained environment. Our approach takes advantage of recent advances in visual SLAM, keypoint detection, and object detection to improve accuracy and robustness. By not being constrained to a model subspace, our reconstructed meshes capture important details while being robust to noise and being topologically consistent. Our evaluations show that our method outperforms current single and multi-view baselines by a significant margin, both in terms of geometric accuracy and in capturing person-specific details important for making realistic looking models. To further the current work on single and multi-view 3D face reconstruction, we also propose a dataset of video sequences of individuals, specifically with the goal to improve deep-learning based reconstruction techniques using self-supervision as a training loss.
ICMIEE-PI-14010110 000 An Android Controlled Mobile Robot for Stereo Vision and Live Streaming with Robotic Arm

Mobile robotics and Android Operating System are two of the most advancing technologies at present. On the other hand, stereo vision technology is becoming more and more popular among the present youth. This project combines all of these advancing and developing technologies for humane purpose. The robot uses two smart phones with android operating system to send videos to the control server continuously and that will generate a stereoscopic image, a 3D live video from those images. In addition to that, a robotic arm is placed in front of that robot to pick any desired object . The whole process is be controlled by another smart phone with android operating system. The robot also can be controlled by the server computer only. Its usage are many. First of all, it can be sent to any place which is humanly impossible and do any task needed. For being small in size, it can be sent to any dangerous places like caves or underground operations also can be done by this robot. We hope this project can reduce the cost, human error, promote human trust and enable a robotic application which never has been possible before .
Localization and Detection in Dense Environment for Tracking

Given an image from a video, we learn features in a supervised manner using deep networks and detect ants in a crowded environment. In order to track the motion of an object in a video, it is essential that we are able to localize and detect most of these objects in every video frame. In this paper, we propose an architecture for our convolutional neural network using which we achieved a precision of 61% and a recall of 50% in detecting ants in the video frame.
Molecular-Docking Study of Anti-Stress Natural Compounds Against GABAa Receptor Portends the Novel Approach to Stress Treatment

© 2018 Abhishek Negi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License -NonCommercialShareAlikeUnported License (http://creativecommons.org/licenses/by-nc-sa/3.0/). *Corresponding Author Shalini Mani; Senior Assitant Professor, Department of Biotechnology, Jaypee Institute of Information Technology, Sector 62, Noida. E-mail: shalini.mani @ jiit.ac. in; mani.shalini @ gmail.com Molecular-Docking Study of Anti-Stress Natural Compounds Against GABAa Receptor Portends the Novel Approach to Stress Treatment
Regional CO Pollution in China Simulated by the High-Resolution Nested-Grid GEOS-Chem Model

1 An updated version of the nested-grid GEOS-Chem model is developed allowing for higher 2 horizontal (0.5 o x 0.667 o ) and vertical resolution as compared to global models. CO transport 3 over a heavily polluted region, the Beijing-Tianjin-Hebei (BTH) city cluster in China, and the 4 pattern of outflow from East China in summertime are investigated. Comparison of the 5 nested-grid with global models indicates that the fine-resolution nested-grid model is capable of 6 resolving individual cities with high associated emission intensities. The nested-grid model 7 indicates the presence of a high CO column density over the Sichuan Basin in summer, 8 attributable to the low-level stationary vortex associated with the Basin’s topographical features. 9 The nested-grid model provides good agreement also with measurements from a suburban 10 monitoring site in Beijing during summer 2005. Tagged CO simulation results suggest that 11 regional emissions make significant contributions to elevated CO levels over Beijing on polluted 12 days and that the southeastward moving cyclones bringing northwest winds to Beijing are the key 13 meteorological mechanisms responsible for dispersion of pollution over Beijing in summer. 14 Overall CO fluxes to the NW Pacific from Asia are found to decrease by a factor of 3-4 from 15 spring to summer. Much of the seasonal change is driven by decreasing fluxes from India and 16 Southeast Asia in summer, while fluxes from East China are only 30% lower in summer than in 17 spring. Compared to spring, summertime outflow from Chinese source regions is strongest at 18 higher latitudes (north of 35 o N). The deeper convection in summer transporting CO to higher 19 altitudes where export is more efficient is largely responsible for enhanced export in summer.
ScienceDirect The Manufacturing Engineering Society International Conference , MESIC 2015 Electroforming applied to manufacturing of microcomponents

Nowadays, there is an increased demand for micro-products and micro-components in many industry sectors therefore development of advanced manufacturing technologies and metrological instrumentation in this range, have thus become a critical issue and an engineering challenge. If a product cannot be measured, although it might be manufactured, it would not be possible to analyse its design in order to improve its functionality. Electroforming could be defined as the highly specialized use of electrodeposition for the manufacturing of metal parts. Due to progress in materials, processes and equipment, electroforming has shown considerable development. Consequently, electroforming is increasingly combined with other micro-manufacturing technologies, giving rise to other processes such as LIGA and UV-LIGA. Thanks to the accumulated experience of Fabricación Integrada y Avanzada research group, of the University of Las Palmas de Gran Canaria in the electroforming process focused on macro-scale, as well as specific equipment available, this paper aims to analyse the potential of electroforming process for microinjection mould manufacturing. © 2016 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of MESIC 2015.
THE STUDY OF THE COMMUNICATION EFFECT ON EMOTIONAL DESIGN IN VIRTUAL REALITY TECHNOLOGY USING VR APPLICATION – FACEBOOK SPACES AS EXAMPLE

With the rapid development of information technology, the speed of information transmission has been greatly enhanced. The relationship between people has gradually become indifferent. As if separated by a wall, communication often results in barriers and misunderstandings. The CEO of Facebook Mark Elliot Zuckerberg at the Oculus developers’ conference launched the first fully immersive virtual reality(VR) software Facebook Space, an online social software that attend to break the distance between people through VR devices. Immersive VR is an interactive human-computer interface that shortens the distance between people through visualization, presence and interaction, Users can share, create, and communicate with each other in different alternative locations. This research adopts an experimental method to use HTC VIVE to operate Facebook Spaces. Based on Norman (2005) who proposed Emotional Design comprised three levels, the (1) visceral (2) behavioural and (3) reflective to explore whether a well-designed VR makes it easier for users to enter the flow experience (Csikszentmihalyi, 1990), thereby reducing the messaging barriers and enhancing their communication effect with the visual characteristics. Finally observations were made through the Technology Accept Model (Davis, 1989) to understand whether the users are willing to continue using the tool when the communication is good. After completed the experiment, a relevant questionnaire. Led to final analysis and data integration and to the conclusions of the experiment. The results of this study found the hypothesis to be supported and the feature of immersion and visualization in a completely immersive VR, reduce the obstacles in the communication process and the sense of distance between people. In addition, this research found that when using information technology, users pay more attention to the ease of use and understanding of the system. At the end of the research, some suggestions are put forward for the future development of VR.
Recent progress on tactile object recognition

Conventional visual perception technology is subject to many restrictions, such as illumination, background clutter, and occlusion. Many intrinsic properties of objects, like stiffness, hardness, and internal state, cannot be effectively perceived by visual sensors. For robots, tactile perception is a key approach to obtain environmental and object information. Different from vision sensors, tactile sensors can directly measure some physical properties of objects and environment. At the same time, humans also utilize touch sensory receptors as an important means to perceive and interact with the environment. In this article, we present a detailed discussion on tactile object recognition problem. We divide the current studies on the tactile object recognition into three subcategories and detailed analysis has been put forward on them. In addition, we also discuss some advanced topics such as visual–tactile fusion, exploratory procedure, and data sets.
A Landsat-based model for retrieving total suspended solids concentration of estuaries and coasts in China

Abstract. Retrieving total suspended solids (TSS) concentration accurately is essential for sustainable management of estuaries and coasts, which plays a key role in the interaction between hydrosphere, pedosphere and atmosphere. Although many TSS retrieval models have been published, the general inversion method that is applicable to different field conditions is still under research. In order to obtain a TSS remote sensing model that is suitable for estimating TSS concentrations with wide range in estuaries and coasts by Landsat imagery, after reviewing a number of Landsat-based TSS retrieval models and improving a comparatively better one among them, this study developed a quadratic model using the ratio of logarithmic transformation of red band and near-infrared band and logarithmic transformation of TSS concentration (QRLTSS) based on 119 in situ samples collected in 2006–2013 from five regions of China. It was found that the QRLTSS model works well and shows a satisfactory performance. The QRLTSS model based on Landsat TM (Thematic Mapper), ETM+ (Enhanced Thematic Mapper Plus) and OLI (Operational Land Imager) sensors explained about 72 % of the TSS concentration variation (TSS: 4.3–577.2 mg L−1, N = 84, P value
Reliability and security in low power circuits and systems

With the massive deployment of mobile devices in sensitive areas such as healthcare and defense, hardware reliability and security have become hot research topics in recent years. These topics, although different in definition, are usually correlated. This dissertation offers an in-depth treatment on enhancing the reliability and security of low power circuits and systems. The first part of the dissertation deals with the reliability of sub-threshold designs, which use supply voltage lower than the threshold voltage (Vth) of transistors to reduce power. The exponential relationship between delay and Vth significantly jeopardizes their reliability due to process variation induced timing violations. In order to address this problem, this dissertation proposes a novel selective body biasing scheme. In the first work, the selective body biasing problem is formulated as a linearly constrained statistical optimization model, and the adaptive filtering concept is borrowed from the signal processing community to develop an efficient solution. However, since the adaptive filtering algorithm lacks theoretical justification and guaranteed convergence rate, in the second work, a new approach based on semi-infinite programming with incremental hypercubic sampling is proposed, which demonstrates better solution quality with shorter runtime. The second work deals with the security of low power crypto-processors, equipped with Random Dynamic Voltage Scaling (RDVS), in the presence of Correlation Power Analysis (CPA) attacks. This dissertation firstly demonstrates that the resistance of RDVS to CPA can be undermined by lowering power supply voltage. Then, an alarm circuit is proposed to resist this attack. However, the alarm circuit will lead to potential denial-of-service due to noise-triggered false alarms. A non-zero sum game model is then formulated and the Nash Equilibria is analyzed.
Can Platform Size Increase Geographical Inequity? Spatial Network Externalities in Ride Sharing

This paper uses both empirical and theoretical methods to conduct a cross-platform study in the ridesharing market. We develop a novel model-free identification strategy with limited data requirements that allows for estimation of geographical demand-supply mismatch in transportation markets. We apply our method to ride-level multi-platform data from New York City (NYC) and show smaller platforms tend to be under-supplied in less densely populated areas. We show, using high-frequency data from NYC, that the under-supply stems from high arrival times, not high prices. We argue using a theoretical model that low platform size distorts the supply of drivers towards more densely populated areas due to network effects. Motivated by this, we estimate a minimum required platform size to avoid geographical supply distortions, which informs the current policy debate in NYC around whether ridesharing platforms should be downsized. We find the minimum-required size to be approximately 3.5M rides/month for NYC, implying that downsizing Lyft and Via –but not Uber– can increase inequity. JEL Codes: L13; R41; D62
Increased Reliability of Supercritical EOS 1 sc Module in iTOUGH 2

A reliable numerical simulator capable of modeling supercritical conditions in geothermal reservoirs is crucial for a better understanding and optimized management of magmatic geothermal systems. This paper describes improvements made to the EOS1sc module in iTOUGH2 for increasing the reliability and speed of the supercritical module. In EOS1sc, the IAPWS-IF97 thermodynamic formulation is used to calculate thermodynamic properties across five regions; liquid, vapor, supercritical, two-phase, and high temperature vapor. Backward equations released for the supercritical region of IAPWS-IF97 were implemented into EOS1sc for calculating specific volume as a function of pressure and temperature. The backward formulation is more reliable than the Newton-Raphson method previously used to iteratively calculate density in the supercritical region and it is approximately eight times faster. In EOS1sc, discrepancies across region boundaries in the IAPWS-IF97 formulation can cause convergence issues. Hence, cubic Bézier curves were implemented to provide a smooth continuous function for thermodynamic properties across the supercritical boundaries. Thereby, poor convergence at intersection points between thermodynamic regions were resolved and the reliability of the supercritical EOS1sc module was increased.
STRESS AND RESILIENCE IN PARENTS OF CHILDREN WITH CEREBRAL PALSY

This study aims to evaluate parenting stress and resilience, to cross-reference quantitative and qualitative ISD variables with the Connor and Davidson Resilience Scale (CD-RISC) and total stress and resilience factors, and to investigate if there is a predictive model for high stress and high resilience. A total of 92 parents of children with cerebral palsy participated in this study. The instruments used were the Socio-demographic Inventory (ISD), the Parenting Stress Index (PSI/SF) and the CD-RISC. The analyses were performed in SPSS version 20.0. The following ISD items ─ time of parents' union, child's age, parents’ age, school adjustment, health problems, government benefit, child attending school, and city of residence ─ interacted with the CD-RISC factors of courage/determination, adaptability, social support and control, tolerance for adversity, self-efficacy, social support and confidence, and total resilience, explaining resilience in the different stress level groups. Finally, the present study showed that there was no predictive model of high stress, but it was found that older parents are more likely to showhigh resilience, as is the case with parents of younger children.
Not Competence-Based ) Group Norms Sharing Moral Values : Anticipated Ingroup Respect as a Determinant of Adherence to Morality-Based ( but

This research examines how moral values regulate the behavior of individual group members. It argues that group members behave in line with moral group norms because they anticipate receiving ingroup respect when enacting moral values that are shared by ingroup members. Data from two experimental studies offer evidence in support. In Study 1 (N = 82), moralitybased (but not competence-based) ingroup norms determined whether members of a low-status group opted for individual versus collective strategies for status improvement. This effect was mediated by anticipated ingroup respect and emerged regardless of whether group norms prescribed collectivistic or individualistic behavior. These effects were replicated in Study 2 (N = 69), where no comparable effect was found as a result of moral norms communicated by a higher status outgroup. This indicates that social identity implications rather than interdependence or more generic concerns about social approval or importance of cooperation drive these effects.
Does the Stock Market Value the Firm ’ s Potential Chemical Risk Released and Transferred ? : Empirical Study on the Japanese Pollutant Release and Transfer Register System

The Japanese Pollutant Release and Transfer Register (PRTR) system could help investors identify a firm’s potential chemical risk related to toxic releases and transfers. If so, investors show a preference for firms with lower risk and the stock market may value the risk. If this is the case, the stock market is likely to play an important role in providing firms with incentives to reduce risk. This paper explores the relationship between company stock market values and quantity of toxic releases and transfers, using Japanese PRTR data. The main finding is that the Japanese stock market negatively values the firm’s chemical pollution risk. However, this is only true of releases not transfers, indicating that investors are distinguishing between different types of pollution risk.