Miracle-dz/UniFAR-FTUs huggingface dataset:
EMBEDDED CONTROL SYSTEM FOR MOBILE ROBOTS WITH DIFFERENTIAL DRIVE

This article deals with design and implementation of control system for mobile robots with differential drive using embedded system. This designed embedded system consists of single control board featuring ARM based microcontroller which control the peripherals in real time and perform all low-level motion control. Designed embedded system can be easily expanded with additional sensors, actuators or control units to enhance applicability of mobile robot. Designed embedded system also features build-in communication module, which can be used for data for data acquisition and control of the mobile robot. Control board was implemented on two different types of mobile robots with differential drive, one of which was wheeled and other was tracked. These mobile robots serve as testing platform for Fault Detection and Isolation using hardware and analytical redundancy using Multisensor Data Fusion based on Kalman filters.
Identifying multiple changes for a functional data sequence with application to freeway traffic segmentation

Motivated by the study of road segmentation partitioned by shifts in traffic conditions along a freeway, we introduce a two-stage procedure, Dynamic Segmentation and Backward Elimination (DSBE), for identifying multiple changes in the mean functions for a sequence of functional data. The Dynamic Segmentation procedure searches for all possible changepoints using the derived global optimality criterion coupled with the local strategy of at-most-one-changepoint by dividing the entire sequence into individual subsequences that are recursively adjusted until convergence. Then, the Backward Elimination procedure verifies these changepoints by iteratively testing the unlikely changes to ensure their significance until no more changepoints can be removed. By combining the local strategy with the global optimal changepoint criterion, the DSBE algorithm is conceptually simple and easy to implement and performs better than the binary segmentation-based approach at detecting small multiple changes. The consistency property of the changepoint estimators and the convergence of the algorithm are proved. We apply DSBE to detect changes in traffic streams through real freeway traffic data. The practical performance of DSBE is also investigated through intensive simulation studies for various scenarios.
English Across the Fracture Lines

So much of human progress is based on our ability to communicate with one another, and modern technology has greatly expanded the means via which we can communicate. Learning additional languages, such as English, expands the range of people with whom we can communicate. English Across Fracture Lines, a collection of 17 chapters edited by Elizabeth J Erling and published by the British Council, shares stories from a wide range of contexts in which the learning of English has led to or at least given hope for human progress based on better communication. Before beginning this review, we want to state our admiration to the authors who have placed themselves in potentially perilous circumstances while attempting to heal fractures in the human landscape.
Ensuring the Safe and Secure Operation of Electronic Control Units in Road Vehicles

With the increasing connectivity and complexity of road vehicles, security heavily impacts the safety of vehicles. In fact, researchers demonstrated that the lack of security in vehicles can lead to dangerous and even life-threatening situations. A threat that has been insufficiently addressed in existing vehicular security solutions are software attacks, in which the adversary compromises the software of Electronic Control Units (ECUs). A promising technique to defend against software attacks is remote attestation, as it enables to detect compromised devices. This paper presents a novel attestation scheme that ensures the software integrity of ECUs to warrant the vehicle's safety. In our scheme, a trusted master ECU verifies the integrity of all safety-critical ECUs and refuses to start the engine in case an untrustworthy, and hence, unsafe state is detected. As modern vehicles are highly heterogeneous system of systems, we propose two different attestation techniques that enable the attestation of simple ECUs, such as basic sensors or actuators, as well as advanced, more complex ECUs like sensor fusion systems. We implement our attestation scheme on an exemplary automotive network that incorporates CAN and Ethernet, and show that our solution imposes an imperceptible overhead for passengers.
UV-Deflectometry : No parasitic reflections

With Phase Measuring Deflectometry (PMD) there exists an established optical method to measure specular freeform surfaces [1]. As shown in the left part of Fig. 2, a projector generates a sinusoidal pattern on a screen which is observed via the specular surface of the object. Using standard phase shifting techniques, one receives the observed location on the screen for every camera pixel. Because of the known camera calibration, one can calculate directly the local slope of the specimen.
Running Head: EXPLORATORY FACTOR ANALYSIS AND VALIDITY

This paper reviews the basic processes of exploratory factor analysis (EFA) with regard to evaluating test score validity. Construct validity is the focus of the paper. The similarity between the processes of construct validation and EFA is described and the use of EFA as a tool to explore score validity is explored. Factor analysis is a method for determining the number and nature of the variables that underlie large numbers of variables or measures. It tells the researcher what tests or measures belong together. Construct validity is studied when the test user wants to draw an inference from the test score to performances that can be grouped under the label of a particular psychological construct. Factor analysis, long associated with construct validity, is a useful tool to evaluate score validity. It is emphasized that validity is not a property of tests, but rather a property of test scores. The identification of the number of factors that underlie a set of variables and the determination of whether factors are correlated or uncorrelated can be helpful in evaluating test score validity. (Contains 24 references.) (SLD) ******************************************************************************** Reproductions supplied by EDRS are the best that can be made from the original document. ********************************************************************************
Brussel Reinforcement Learning 101 with a Virtual Reality

Our proof-of-concept demonstrates how Virtual Reality can be used to explain the basic concepts of Reinforcement Learning. This application visualizes the learning process of Watkins’ Q(λ), a fundamental algorithm in the field, in the form of an interactive treasure hunt game. A player takes the role of an autonomous agent, and must learn the shortest path to a hidden treasure through experience. The application also allows an audience to follow the game from an external display.
Superpixel and Stereo Matching Optic Disc Segmentation for the Diagnosis of Glaucoma

Glaucoma is an optic neuropathy resulting in progressive vision loss. It is the leading cause of global irreversible blindness. The reported prevalence among the population in New Zealand is 2% over the age of 40 years. About 10 % of those over 70 years are diagnosed with this disease. Population-based studies report high rates of undiagnosed glaucoma with over 50% of the population with glaucoma living in developed countries remaining undiagnosed and unaware of their disease. Clinical diagnosis rests on the detection of the characteristic optic disc signs. Stereo optic-disc imaging improves intra and inter-observer agreement in the detection of optic disc abnormalities. We propose a robust method to detect some abnormalities in stereo optic-disc images using stereo vision and superpixel segmentation concepts. A stereo vision system produces a disparity map for the input stereo images of the retina in which abnormalities are more distinguishable. The produced disparity map is then segmented using two different superpixel segmentation algorithms (simple linear-iterative clustering and simple non-iterative clustering) to detect abnormalities. The original stereo images are also segmented using the same concept; results are compared with the segmented disparity map.
Algorithm-SoC Co-Design for Energy-Efficient Continuous Vision ∗

Domain-specific architectures (DSAs) are widely recognized as a promising solution to the Dark Silicon challenge. Due to the high non-recurring engineering (NRE) cost of designing custom architectures and hardware chips, we must identify key application domains whose demands are large enough and whose social impacts are high enough to justify the efforts of designing DSAs. We focus on the domain of continuous computer vision, which encapsulates a class of emerging applications that extract visual insights from real-time camera streams to guide high-level decision making. Continuous vision applications are widely deployed in both consumer mobile devices and “always-on” embedded systems such as Unmanned Aerial Vehicles, Augmented Reality, and smart-city sensing. Continuous vision applications impose an enormous compute requirement, which in turn consumes excessive energy. Consider a typical mobile power budget of 3W; continuous vision algorithms that operate on 720p (1280 × 720) resolution images at 30 frames per second (FPS) can only afford an energy budget of about 110 nJ/pixel. In contrast, today’s CNN accelerators consume about 10,000 nJ/pixel [6], indicating an energy gap of two orders of magnitude. Today’s most prevalent efforts to close this energy gap, have largely focused on optimizing hardware (micro-)architecture for the vision kernels of interest, with little regard to the widersystem. Fundamentally, these approaches treat frames in realtime video streams as independent entities, and optimize the execution efficiency of each frame. In contrast, this work takes a step back and re-examines the inherent execution model of continuous vision at the system-level. In particular, we harness a key trait of continuous vision: visual information changes only incrementally across frames in a real-time video stream. Therefore, the vision results can be incrementally computed from one frame to another without having to reexecute the entire vision algorithm on each frame. We propose a new algorithm that encodes frame pixel changes as object motion, and leverages the motion data to simplify the vision computation for the majority of real-time frames. Along with the new algorithm is the co-designed Systemson-Chip (SoC) architecture. To maximize the efficiency of the incremental vision computation, the new SoC architecture
Understanding Cultural Differences in News Videos

As the digital archive of our world grows exponentially, international events are widely covered around the globe, and most of them are available as news videos from different cultural perspectives. However, searching for another culture’s response upon a specific event can be potentially challenging, as there usually exist language boundaries and user-preference disparities between one culture and another. In this work, we aim to capture the cultural differences by detecting the culture-specific tags: given a short video clip about an international event, we aim to retrieve the most relevant feedback from a specific cultural affinity group. To achieve that goal, we start from targeting the determining characteristic of the international events that get widely covered in different cultures. Datasets covering several interesting international news event is gathered, and we propose several techniques to filter out the noisy contents in the crawled data. To further automate the analysis process, visual and multilingual features are extracted by state-of-theart neural models, and then mapped onto a joint latent embedding space through canonical correlation analysis and its variations. To bridge the gap between different languages, we only extract the text features using native text models trained in that language. As temporal information is critical for video understanding, we propose several possible ways to embed the temporal information into the joint space. We test our pipeline on several popular international news event, and further experiments are conducted to show the effectiveness of our algorithm.
Hughes’s Reverspectives: Radical Uses of Linear Perspective on Non-Coplanar Surfaces

Two major uses of linear perspective are in planar paintings—the flat canvas is incongruent with the painted 3-D scene—and in forced perspectives, such as theater stages that are concave truncated pyramids, where the physical geometry and the depicted scene are congruent. Patrick Hughes pioneered a third major art form, the reverse perspective, where the depicted scene opposes the physical geometry. Reverse perspectives comprise solid forms composed of multiple planar surfaces (truncated pyramids and prisms) jutting toward the viewer, thus forming concave spaces between the solids. The solids are painted in reverse perspective: as an example, the left and right trapezoids of a truncated pyramid are painted as rows of houses; the bottom trapezoid is painted as the road between them and the top forms the sky. This elicits the percept of a street receding away, even though it physically juts toward the viewer. Under this illusion, the concave void spaces between the solids are transformed into convex volumes. This depth inversion creates a concomitant motion illusion: when a viewer moves in front of the art piece, the scene appears to move vividly. Two additional contributions by the artist are discussed, in which he combines reverse-perspective parts with forced and planar-perspective parts on the same art piece. The effect is spectacular, creating objects on the same planar surface that move in different directions, thus “breaking” the surface apart, demonstrating the superiority of objects over surfaces. We conclude with a discussion on the value of these art pieces in vision science.
The Impact of Culture on the Consumption and Preferences of the Private Brand Versus the National Brand

This study has two objectives: First, this research attempts to probe into how private brands and national brands increase consumers’ willingness to pay through building brand equity. Secondly, this study examines into how a consumer’s culture influences their preference and willingness to pay on private brands (PBs) and national brands (NBs). In particular, it utilizes Hofstede’s four cultural dimensions, which are individualism versus collectivism (IDV), power distance (PDI), uncertainty avoidance (UAI) and masculinity versus femininity (MAS). Based on past literature and theory, this study finds that NBs are in overall more preferred to PBs in Hofstede’s four cultural dimensions.
Robust Beam-Alignment for TWDP Fading Millimeter Wave Channels

In this paper, we consider hybrid transmit and receive beam-alignment in wireless millimeter wave transmissions. As several channel measurement campaigns have shown, the millimeter wave channel exhibits a limited number of scattering clusters, where each cluster can be well modeled by a small number of rays. To account for this behavior, we consider a clustered channel model with each cluster being modeled as two-wave with diffuse power (TWDP) fading. It is well known that TWDP fading can lead to worse outage performance than Rayleigh fading. We therefore propose several hybrid beam selection and power loading strategies to achieve robust transmission and we investigate their outage performance by means of Monte Carlo simulations.
Term Structure Decompositions at the Zero Lower Bound

This paper employs a Zero Lower Bound (ZLB) consistent shadow-rate model to decompose UK nominal yields into expectation and term premia components. Compared to a standard affine term structure model, it performs relatively better in a ZLB setting and effectively captures the countercyclical nature of term premia. The ZLB model is then exploited to estimate inflation expectations and risk premia. This entails jointly pricing and decomposing nominal and real UK yields. We find that the asset purchases programme, launched in March 2009, was successful in re-anchoring inflation expectations in the aftermath of Lehman Brothers’ bankruptcy. JEL classification numbers: E31, E43, E52, E58, G12
The Correlation between Innovative Capabilities and Economic Development

The purpose of this paper is to emphasize the correlation between innovative capabilities and economic development, starting from the theories in the field. In this respect, we analysed Gross Domestic Product per capita in current US$ (GDP/capita), as dependent variable, and Global Innovation Index (GII), as independent one. Using the IBM® SPSS® Statistics Version 21 software, we empirically tested different types of models. The results showed a significant correlation between GDP/capita and GII, which is best described by the power model, as 72.5% of the variation in the GDP/capita was due to the variation of GII. Therefore, we consider that Global Innovation Index as a measure of innovative capabilities of a country is representative when testing the correlation with GDP/capita.
Puerto Rican Label Hierarchy Inconsistent Prediction Single-Path Prediction Mandatory Leaf Node Prediction Non-mandatory Leaf Node Prediction Yelp Business X X ROOT Restaurants Caribbean American Italian Bars Nightlife Beer

While existing hierarchical text classification (HTC) methods attempt to capture label hierarchies for model training, they either make local decisions regarding each label or completely ignore the hierarchy information during inference. To solve the mismatch between training and inference as well as modeling label dependencies in a more principled way, we formulate HTC as a Markov decision process and propose to learn a Label Assignment Policy via deep reinforcement learning to determine where to place an object and when to stop the assignment process. The proposed method, HiLAP, explores the hierarchy during both training and inference time in a consistent manner and makes inter-dependent decisions. As a general framework, HiLAP can incorporate different neural encoders as base models for end-to-end training. Experiments on five public datasets and four base models show that HiLAP yields an average improvement of 33.4% in Macro-F1 over flat classifiers and outperforms state-of-the-art HTC methods by a large margin.1
Proline enhances antioxidative enzyme activity , photosynthesis and yield of Cicer arietinum L . exposed to cadmium stress

Seeds of chickpea inoculated with Rhizobium were sown in pots supplemented with different doses of cadmium (0, 25, 50 or 100 mg per kg of soil). At the stage of 30 days after sowing (DAS), the plants were sprayed with 20 mM solution of proline and were sampled at 90 DAS to assess the various parameters. The foliar treatment of proline resulted in the alleviation of the adverse effects generated by metal exposure, which was expressed in terms of the increase in plant growth. The activity of carbonic anhydrase in the cadmium-fed plants sprayed with proline was higher than that of control. The proline applied as foliar spray increased the photosynthetic attributes and yield characteristics in the cadmium-stressed plants. The activity of antioxidative enzymes increased with increasing concentration of cadmium. Maximum values were recorded in the plants exposed to 100 mg cadmium per kg of soil.
Local Rates of New Firm Formation: An Empirical Exploration Using Swedish Data

We assess the empirical literature on the determinants of spatial variations in new-firm formation rates by undertaking a systematic empirical analysis of the relative roles of different demand- and supply-side factors. Using instrumental variables to address endogeneity, we find that local growth drives local entrepreneurship exclusively in services industries. Average establishment size has a robust negative influence on local new-firm formation rates, but its effect varies across industries. Local industry diversity is only positive for new-firm formation in high-tech and knowledge-intensive activities. There is also some evidence of that longer distances to urban centers is associated with higher new-firm formation rates. The only local factor with a consistent positive effect on new-firm formation across industries is local density of skilled workers. We conclude that industry structure, geography and agglomeration matter, but in the end, new firms are started by people, so it is unsurprising that the main factor driving local entrepreneurship is the characteristics of the local residents.
iTrustSO: An Intelligent System for Automatic Detection of Insecure Code Snippets in Stack Overflow

Despite the apparent benefits of modern social coding paradigm such as Stack Overflow, its potential security risks have been largely overlooked (e.g., insecure codes could be easily embedded and distributed). To address this imminent issue, in this paper, we bring a significant insight to leverage both social coding properties and code content for automatic detection of insecure code snippets in Stack Overflow. To determine if the given code snippets are insecure, we not only analyze the code content, but also utilize various kinds of relations among users, badges, questions, answers and code snippets in Stack Overflow. To model the rich semantic relationships, we first introduce a structured heterogeneous information network (HIN) for representation and then use meta-path based approach to incorporate higher-level semantics to build up relatedness over code snippets. Later, we propose a novel hierarchical attention-based sequence learning model named CodeHin2Vec to seamlessly integrate node (i.e., code snippet) content with HIN-based relations for representation learning. After that, a classifier is built for insecure code snippet detection. Integrating our proposed method, an intelligent system named iTrustSO is accordingly developed to address the code security issues in modern software coding platforms. Comprehensive experiments on the data collections from Stack Overflow are conducted to validate the effectiveness of our developed system iTrustSO by comparisons with alternative methods.
Aligning Project Management Office and Strategy: A Brazilian Case Study

INTRODUCTION In the turbulence of the new economy, characterized by discontinuous, abrupt and sometimes unmanageable changes, companies should be able to make fast and responsive actions and innovative strategies in order to survive (Hamel, 1996). The great majority of companies already has this information and prepare themselves to compete in this new era through the elaboration of daring strategies, although feasible. According to Porter (1996), the strategy essence remains in choosing activities to be made in a different manner or in the execution of different activities in relation to the competitors. What happens, many times, is that the strategies are not put in operation because they do not arrive until the lower organization’s hierarchical levels or because they don not have an ideal medium to implement it. So the strategic planning in a business environment could be defined as the process of creating and implementing decisions about the organization future (Kerzner, 2001).