Miracle-dz/UniFAR-FTUs huggingface dataset:
Physical Computing Resource Scheduling on Distributed Stream Processing System

Recently, distributed stream computing has emerged as a popular model for real-time data stream analytics. This paper focuses on computing resources scheduling of distributed stream processing. To adapt to the fluctuation of data stream, distributed stream processing system must elastically provision the computing resources based on the observed workload. However, there is no system that satisfies all these requirements. Motivated by this, this paper presents a physical resource scheduling algorithm for elastic scheduling computing resources of stream processing task. Base on existing task tier elastic resource scheduling and system-tier resource scheduling, this paper proposes a collaborative algorithm. According to the fluctuant workload, task-tier dynamic resource scheduler config computing resource of stream processing task. Meanwhile, based on the scheduling decision of task-tier scheduler, the system-tier resource scheduler is assign physical computing resources to stream processing tasks.
Fixed-b Inference in the Presence of Time-Varying Volatility

The fixed-b asymptotic framework provides refinements in the use of heteroskedasticity and autocorrelation consistent variance estimators. The resulting limiting distributions of t-statistics are, however, not pivotal when the unconditional variance changes over time. Such time-varying volatility is an important issue for many financial and macroeconomic time series. To regain pivotal fixed-b inference under time-varying volatility, we discuss three alternative approaches. We (i) employ the wild bootstrap (Cavaliere and Taylor, 2008, ET), (ii) resort to time transformations (Cavaliere and Taylor, 2008, JTSA) and (iii) consider to select test statistics and asymptotics according to the outcome of a heteroscedasticity test, since small-b asymptotics deliver standard limiting distributions irrespective of the socalled variance profile of the series. We quantify the degree of size distortions from using the standard fixed-b approach assuming homoskedasticity and compare the effectiveness of the corrections via simulations. It turns out that the wild bootstrap approach is highly recommendable in terms of size and power. An application to testing for equal predictive ability using the Survey of Professional Forecasters illustrates the usefulness of the proposed corrections.
Coding, designing and networking: fostering learning through social connections

Trends in digital technologies and new social practices are calling for innovative models of learning in education. A recent development in the learning sciences, which conceptualises learning activity as networked learning, can offer deeper insight into how digital learning spaces influence the ensuing activity of learners. The networked approach coupled with social semiotics is applied in the analysis of Peep – a computer-based platform with social networking features that supports an undergraduate design course. This article illustrates how the networked learning approach and social semiotics reveal elements of the platform that enable design learning and foster social connections amongst students and lecturers. The article also examines the distribution of students’ activity and changes in their patterns of interaction over time. Published : 3 April 2018 Citation : Research in Learning Technology 2018, 26 : 2006 - http://dx.doi. org/10.25304/rlt.v26. 2006
A Secure Proof of Ownership Scheme for Efficient Client-Side Deduplication in Cloud

Client-side deduplication is a technique used by cloud storage providers to reduce the cost of storage services by avoiding uploading multiple copies of the same data. Nevertheless, this strategy can be abused by malicious users in order to get access to files that they do not have in their possession. Thus, efficient Proof of Ownership (PoW) schemes should be employed by storage service providers to verify that a client possesses a file. This paper presents a novel secure and efficient PoW scheme for client side deduplication in the cloud. Unlike existing schemes, the proposed scheme disallows adversaries from engaging in a successful PoW without possessing the entire content of the file and thereby the scheme is robust against collusion attacks. Besides, the amount of data exchanged between client and server upon a PoW session is minimized. Moreover, the proposed scheme utilizes convergent encryption (CE) to encrypt the entire file, using the digest of its content as a key, prior to uploading it to the server in order to prevent honest-but-curious servers from revealing the content of the uploaded files. Simulation results demonstrate that the proposed scheme outperforms existing PoW schemes with respect to both client response and client-side initialization.
Sequencing partial Steiner triple systems

A partial Steiner triple system of order n is sequenceable if there is a sequence of length n of its distinct points such that no proper segment of the sequence is a union of point‐disjoint blocks. We prove that if a partial Steiner triple system has at most three point‐disjoint blocks, then it is sequenceable.
Advantages from the Application of Decision Support Models in Droughts’ Early Warning and Management

Drought prevention and management can have important inputs from Decision Support models, as tools to facilitate drought indicators / indices evaluation, as well as to forecast potential impacts resulting form droughts. Focusing on the advantages coming from the application of these models for drought management, it is considered the complementary use of the Temez model (Temez, 1977), model for hydrologic simulation that enables the quantification of natural availabilities for a certain region, based on precipitation and potential evapotrasnpiration, or temperature values, and the Aquatool model (Andreu et al., 1996), of water balance, that completes the first one, integrating the evaluation of storage volumes (surface and graoundwater) and runoff, with the main existing water uses. The application of these two models is undertaken for two of the main water sources in Guadiana’s river basin. Within the results presented in this work it is included a comparison with correspondent meteorological drought indexes evaluation, focusing on the potential use of these models as basis for the development of drought early warning and management systems.
A Review on Clustering Techniques

The World Wide Web keeps on developing vault of site pages and connections at an exponential rate which makes abusing all valuable data a standing test. It has as of late an extensive variety of uses in E-trade site and E-administrations, for example, building intelligent showcasing systems, Web proposal and Web personalization. Web utilization mining is the way toward separating helpful use designs from the web information. Web personalization utilizes web utilization digging strategy for the procedure of information obtaining done by investigating the client navigational examples premium. These days, the Web is an essential wellspring of data recovery, and the clients getting to the Web are from various foundations. The use data about clients is recorded in web logs. Examining web log documents to extricate helpful examples is called Web Usage Mining. Web use mining approaches incorporate bunching, affiliation lead mining, successive example mining and so forth. This article gives a study of the accessible writing on Web utilization mining and audits the exploration and application issues in web use mining. Keywords— Web usage mining, server log file, web logs, clustering, fuzzy logic.
Reciprocity in Two-sided Reputation Systems: Evidence from an Experiment on Airbnb

Reciprocity in feedback may distort information and lead to inefficient outcomes in digital marketplaces. We analyze a large-scale field experiment on Airbnb in which the treatment was a simultaneous reveal review system that eliminated the ability of second reviewers to condition feedback on the content of the first review. The treatment had small negative effects on ratings and content, which points to a limited role of strategic reciprocity in shaping review content prior to the introduction of simultaneous reveal. The treatment also induced 9.7% more host reviews and 1.8% more guest reviews, consistent with a desire to reveal information about a counterparty’s review by submitting a review. We fail to reject the null of no treatment effect on subsequent transactions by guests and hosts. Even in the absence of strategic reciprocity, there is evidence that some feedback may be distorted. For instance, when a guest does not recommend a host in a private and anonymous response, 19% of public reviews contain a high rating. Using plausibly exogenous variation in observational data, we show that this mismatch is partially explained by market participants interacting in a social manner and consequently omitting negative information in reviews. ∗We are grateful to Chris Dellarocas, Liran Einav, Chiara Farronato, Shane Greenstein, John Horton, Caroline Hoxby, Ramesh Johari, Jon Levin, Mike Luca, Jeff Naeckfer, Fred Panier, Catherine Tucker, and seminar participants at Microsoft, MIT, eBay, HKU, ACM EC’15, NBER Summer Institute, CODE, and the Advances in Field Experiments Conference for comments. We thank Matthew Pearson for early conversations regarding this project. The views expressed in this paper are solely the authors’ and do not necessarily reflect the views of Airbnb, Inc. Fradkin and Holtz were employed by Airbnb, Inc. for part of the time that this paper was written. †Primary Author: fradkin@bu.edu ‡Primary Experiment Designer: elena.grewal@airbnb.com §dholtz@mit.edu
PatTR: Patent Translation Resource

PatTR is a sentence-parallel corpus extracted from the MAREC patent collection. The current version contains more than 22 million German-English and 18 million French-English parallel sentences collected from all patent text sections as well as 5 million German-French sentence pairs from patent titles, abstracts and claims. The corpus is sorted by language pairs and by text sections of a patent document, namely title, abstrac t, claims and description. Parallel data from title, abstract and claims sections were extracted from documents belonging to the European Patent Office ( EPO) and the World Intellectual Property Organization (WIPO) corpora in MAREC. Both resources feature multilingual documents that contain for example both an English and a German abstract. Since there are no multilingual descriptions, data from this section were collected by exploiting patent families to align German and French documents from the EPO corpus to English documents from the United S tates Patent and Trademark Office (USPTO) corpus, following Utiyama, Masao and Isahara, Hitoshi: A Japanese-English patent parallel corpus. MT summit XI (2007), 475--482. All sections were sentence-aligned using the Gargantua aligner. Preprocessing was done automatically. Sentence boundaries were detected using the Europarl processing tools. For a detailed description of the corpus construction process, please see the publications above.
Spaces of intention as exclusionary practice : Exploring ethical limits to ‘ alternative ’ sustainable consumption

The rise of sustainable consumption as a privileged form of market-driven political action is now widely recognised. Through the promotion of fair trade, organic production and similar movements, an ‘alternative’ politics of consumption has become widespread in the North and now increasingly so in the South too. In the process, relatively affluent consumers and (often) poor producers are assumed to have united, through bonds that are forged based on notions of fairness, ecological sustainability and product quality. Yet these ‘spaces of intention’ are premised on the creation of borders that exclude people and knowledge even as they seek to define new communities of the seemingly ‘like-minded’. This paper assesses these exclusionary practices using selective examples from the Dominican Republic, Costa Rica, Mexico and Malaysia in order to highlight some of the possible ethical ambiguities and limits to sustainable consumption. In doing so, we hope to contribute to a growing critical literature on the meaning and utility of alternative market-driven solutions to contemporary social and environment problems.
Road Surface Obstacle Detection using Vision and LIDAR for Autonomous Vehicle

The project aims to present a system that detects and estimates road surface obstacles potholes and speed humps using low-cost camera and LIDAR sensor. Regions are determined using histogram-based data from gray-scale image. Image segmentation and spectral clustering are used for identification and rough estimation of potholes. Speed hump; on the other hand, are detected by integrating the LIDAR measurements in time, relative to the motion of the vehicle. The algorithm is implemented in C++ with Open Source Computer Vision (OpenCV) Library. The pothole detection system can detect potholes 1.6m to 5m away from the vehicle with 86.18 percent accuracy, while the speed hump detection system can detect speed humps at an optimal distance of 4.13m with an accuracy of 98.36 percent. Errors during the detection are due to the algorithms implemented, and hardware limitations. When the two systems are cascaded, the resulting system is reliable with 80.83 percent accuracy in pothole detection, and 98.46 percent accuracy in speed hump detection. However, this is only true if the number of potholes and speed humps to be detected are minimal. The limitation of the cascaded system is imposed by the single execution capability of the processing module. Thus, to be able to use the system together, separate processing module should be used for each system. Index Terms – Autonomous Vehicle, Pothole Detection, Speed Hump Detection, Single Camera and 2D LIDAR System
Beam Bundle Model of Human Fingertip during Pre-Slide Phase

Among many senses, tactile perception is considered to as one of the most important factors for both human and robots, which permits acquisition of the outside world information, especially the grasped object’s characteristics for stable/dexterous manipulation. Research on tactile perception in robotics has been conducted for over 30 years, mainly focusing on mimicking human’s fingertip ranging from shape, function, and distribution of mechanoreceptors. As a result, it is indispensable for robotics researchers to understand functions and characteristics of human fingertip. Among multiple modalities that human finger can sense; including temperature, force, vibration, etc.; deformation of skin has played an important role in touch sensation. It stimulates four types of mechanoreceptor cells lying right beneath the skin, then stimulated cells send signal to brain for processing. Thus, recently, there has been many researches utilized skin stretch in haptic devices. Minamizawa [1] has developed haptic device for displaying grasping and weight sensations based on cutaneous stimuli, in which two motors’s motion creates controlled skin stretch on the fingertip depending on tele-operative objects. Nakatani and Kawasoe [2] developed a device for studying hatic behaviors via skin deformation of human fingertip. Thus, there is also an increasing need for modeling skin deformation of human fingertip during contact with object, especially during pre-slide or sliding phases. Konyo and Okamoto [3] has attempted to model human fingertip with simple model of mass-spring-damper to investigate stick-slip events. Nonetheless, it is not a sufficient model since the structure of human fingertip is far different. In this research, we attempted to employ our proposed Beam Bundle Model (see [4], [5]) into modeling human fingertip. In order to implement this, we utilized Magnetic Resonant Images (MRI) of one subject’s fingertip to construct mathematical model of fingertip’s structure. We also succeeded in representation of localized displacements (also referred to as skin local stretch) during pre-slide phase of the fingertip, which is considered crucial to assess stick/slip events on the contact surface during contact with outside world. This work can be utilized in haptic sensation, and development of sensors for detection of slippage.
Tracking of Deformable Human Avatars through Fusion of Low-Dimensional 2 D and 3 D Kinematic Models Bill Zhou

We propose a method to estimate and track the 3D posture as well as the 3D shape of the human body from a single RGB-D image. We estimate the full 3D mesh of the body and show that 2D joint positions greatly improve 3D estimation and tracking accuracy. The problem is inherently very challenging because due to the complexity of the human body, lighting, clothing, and occlusion. The solve the problem, we leverage a custom MobileNet implementation of OpenPose CNN to construct a 2D skeletal model of the human body. We then fit a low-dimensional deformable body model called SMPL to the observed point cloud using initialization from the 2D skeletal model. We do so by minimizing a cost function that penalizes the error between the estimated SMPL model points and the observed real-world point cloud. We further impose a pose prior define by the pre-trained mixture of Gaussian model to penalize out unlikely poses. We evaluated our method on the Cambridge-Imperial APE (Action Pose Estimation) dataset showing comparable results with non-real time solutions.
Describing the technological scope of Industry 4.0 - a review of survey publications

Background: The paper addresses common difficulties of understanding the scope and the underlying technologies of “Industry 4.0”. Existing definitions comprise a variety of technologies and applications, processes as well as business models. Their difficult differentiation has led to a complicated understanding of the topic altogether. Therefore, this study aims at a structuring of the scope of “Industry 4.0” using the average importance of its underlying technologies, as it is represented in 38 survey publications dedicated on Industry 4.0. Methods : Based on a review of existing survey literature on Industry 4.0, relevant technologies are identified. Next, these technologies are recapped in five technology areas. Furthermore, all technologies are assessed according to their relevance to Industry 4.0 using citation indices of the respective publication. Finally, two-dimensional figures are used to present an overview structure of all cited technologies, their structural connections and their relevance. In summary, a structuring of “Industry 4.0” through the cited technologies and their evolution over the years 2013 until 2016 is displayed to facilitate the understanding of significant research trends and promising application areas within “Industry 4.0”. Conclusion: Compared to existing reviews and empirical approaches on the topic, this paper focusses on a review of survey literature specifically dedicated to an understanding of the concept of Industry 4.0. The results allow an overview of the respective relevance of technologies within the comprehensive scope of the topic. It shows the most often used technologies (web services with a relative importance of 3.46/5) as well as the evolvement of the importance of each technology within the period of 2013-2016.
1 J 6 . 1 VERIFYING THE REANALYSIS AND CLIMATE MODELS OUTPUTS USING A 56-YEAR DATA SET OF RECONSTRUCTED GLOBAL PRECIPITATION

In recent years, several merged analyses of global monthly precipitation have been produced and applied successfully in climate analysis and numerical model verifications (e.g. Huffman et al., 1997; Xie and Arkin, 1997). These analyses, however, cover only the most recent two decades due to their dependence on estimates from satellite observations. A precipitation analysis with extended temporal coverage is desired for many applications. To this end, a new data set of global monthly precipitation has been constructed at the NOAA Climate Prediction Center (CPC). Called PREC (Precipitation REConstruction), this monthly analysis covers the globe from 60S to 75N on both land and ocean and extends over a 56-year period from 1948 to the present. The purpose of this paper is to provide a brief description of the new data set and to present an illustration of its potential applications in verifying numerical models.
COUPLING METHODS FOR HEAT-TRANSFER AND HEAT-FLOW: OPERATOR SPLITTING AND PARAREAL

In this paper, we propose an operator splitting method for coupling heat-transfer and heat-flow equations. The motivation arose of industrial software packages, which have developed independently heat-transfer solvers (e.g. Aura-Fluid software package) and heat-flow solvers (e.g. Openfoam). Such packages are often simple coupled by A-B splitting and they simulate the influence of solar heat in car bodies. One of the main problems is to accelerate the code by iterative operator splitting methods and with a parallel interfaces. We propose Parareal as well applicable for parallel method for parabolic problems and also a speedup to mixed parabolic and hyperbolic problems is possible and delicate. Our idea is to combine the splitting schemes as a time-splitting method to adapt the time steps with Parareal as a timeparallelization method. Our analysis of these new splitting techniques provides error estimates which are validated at certain benchmark problems.
ENRICHED LAWVERE THEORIES FOR OPERATIONAL SEMANTICS

Formal systems are not always explicitly connected to how they operate in practice. Lawvere theories [18] are an excellent formalism for describing algebraic structures obeying equational laws, but they do not specify how to compute in such a structure, for example taking a complex expression and simplifying it using rewrite rules. In a Lawvere theory the objects are types and the morphisms are terms; however there are no relations between terms, only equations. The process of computing one term into another should be given by hom-objects with more structure. In operational semantics, program behavior is often specified by labelled transition systems, or labelled directed graphs [28]. The edges of such a graph represent rewrites. We can use an enhanced Lawvere theory in which, rather than merely sets of morphisms, there are graphs or perhaps categories. To be clear, this is certainly not a new idea. Using enriched Lawvere theories for operational semantics has been explored in the past. For example, category-enriched theories have been studied by Seely [32] for the λ-calculus, and poset-enriched ones by Ghani and Lüth [21] for understanding “modularity” in term rewriting systems. They have been utilized extensively by Power, enriching in ω-complete partial orders to study recursion [29] – in fact, there the simplified “natural number” enriched theories which we explore were implicitly considered. In the context of these works, the purpose of the present paper is to provide a simple, general exposition of enriched theories: we hope to familiarize computer scientists with enriched category theory, and prove some basic results to show that one does not need to leave the nice computational world of cartesian closed categories to enjoy the benefits of enrichment. For an enriching category V, we take a V-theory to be a V-enriched Lawvere theory with natural number arities. There is a “spectrum” of enriching categories which allow us to examine the semantics of term calculi at various levels of detail. We discuss how functors between enriching categories induce change-of-base 2-functors between their 2-categories of enriched categories, and we show that functors preserving finite products induce change-of-semantics: that is, they map theories to theories and models to models. Our main examples arise from this chain of adjunctions: