Miracle-dz/UniFAR-FTUs huggingface dataset:
Filter by trust policies Transform ( map ) with provenance Update DBMS instance + – + – + –

Sharing structured data today requires standardizing upon a single schema, then mapping and cleaning all of the data. This results in a single queriable mediated data instance. However, for settings in which structured data is being collaboratively authored by a large community, e.g., in the sciences, there is often a lack of consensus about how it should be represented, what is correct, and which sources are authoritative. Moreover, such data is seldom static: it is frequently updated, cleaned, and annotated. The ORCHESTRA collaborative data sharing system develops a new architecture and consistency model for such settings, based on the needs of data sharing in the life sciences. In this paper we describe the basic architecture and implementation of the ORCHESTRA system, and summarize some of the open challenges that arise in this setting.
Multipath Routing Sensor Network for Finding Crack in Metallic Structure Using Fuzzy Logic

changes in Dynamic Source Routing (DSR) protocol is proposed. At each hop level, route-ranking technique is used for distributing packets to different selected routes dynamically. For calculating rank of a route, different parameters like: delay, residual energy and probability of packet loss are used. A hybrid topology of DMPR(Disjoint Multi Path Routing) and MMPR(Meshed Multi Path Routing) is formed, where braided topology is used in different faulty zones of network. For reducing energy consumption, variant transmission ranges is used instead of fixed transmission range. For reducing number of packet drop, a fuzzy logic inference scheme is used to insert different types of delays dynamically. A rule based system infers membership function strength which is used to calculate the final delay amount to be inserted into each of the node at different clusters. In braided path, a proposed 'Dual Line ACK Link' scheme is proposed for sending ACK signal from a damaged node or link to a parent node to ensure that any error in link or any node-failure message may not be lost anyway. This paper tries to design the theoretical aspects of a model which may be applied for collecting data from any large hanging iron structure with the help of wireless sensor network. But analyzing these data is the subject of material science and civil structural construction technology, that part is out of scope of this paper.
Human-Robot Interaction

Sara Kiesler is an experimental social psychologist with interests in technology (including robotics), communication, groups, and organizations. She is a professor in the Human Computer Interaction Institute, Carnegie Mellon University, Pennsylvania. Pamela J. Hinds studies the impact of technology on individuals and groups. She is an Assistant Professor in the Department of Management Science and Engineering at Stanford University.
Temperature Management in Datacenters Cranking Up the Thermostat Without Feeling the Heat

George Amvrosiadis is a PhD student in computer science at the University of Toronto. His research interests include storage reliability and idleness characterization, detection, and utilization. He completed his BS at the University of Ioannina in Greece, with a thesis on namespace management of federated file systems. gamvrosi@cs.toronto. edu Andy A. Hwang is a PhD student at the University of Toronto under the supervision of Professor Bianca Schroeder. He received his BAS from the University of Waterloo and MS from the University of Toronto. Andy works on enhancing the reliability and performance of computer systems, both as a whole and for specific components such as DRAM. hwang@cs.toronto. edu
Eurographics Symposium on Geometry Processing (2005) Swept Volumes of Many Poses

We consider the swept volume A (X) of a rigid body X which assumes a general set A of positions. A special case of this is a one-parameter motion of X, where the set of poses is curve-like. Here we consider a full-dimensional subset A of the motion group. Such a set of poses can be seen as the tolerance zone of an imprecisely defined pose. Alternatively, a set of poses may be obtained by by measurements or simulation. We analyze the geometric properties of such sets of poses and give algorithms for computing the boundary ∂A (X) in the case that A is a discrete pose cloud. The dimension of the problem, which equals six a priori, is reduced to two.
Improvement of the global prediction system of the COVID-19 pandemic based on the ensemble empirical mode decomposition (EEMD) and autoregressive moving average (ARMA) model in a hybrid approach-COVID-19

In 2020, the COVID-19 pandemic spreads rapidly around the world. To accurately predict the number of daily new cases in each country, Lanzhou University has established the Global Prediction System of the COVID-19 Pandemic (GPCP). In this article, the authors use the ensemble empirical mode decomposition (EEMD) model and autoregressive moving average (ARMA) model to improve the prediction results of GPCP. In addition, the authors also conduct direct predictions for those countries with a small number of confirmed cases or are in the early stage of the disease, whose development trends of the pandemic do not fully comply with the law of infectious diseases and cannot be predicted by the GPCP model. Judging from the results, the absolute values of the relative errors of predictions in countries such as Cuba have been reduced significantly and their prediction trends are closer to the real situations through the method mentioned above to revise the prediction results out of GPCP. For countries such as El Salvador with a small number of cases, the absolute values of the relative errors of prediction become smaller. Therefore, this article concludes that this method is more effective for improving prediction results and direct prediction. 2020 , (COVID-19) . , COVID-19 (GPCP). , (EEMD) (ARMA) GPCP , , , GPCP . , , , . , , .
S ELF -S UPERVISED

Self-supervised learning achieves superior performance in many domains by extracting useful representations from the unlabeled data. However, most of traditional self-supervised methods mainly focus on exploring the inter-sample structure while less efforts have been concentrated on the underlying intra-temporal structure, which is important for time series data. In this paper, we present SelfTime: a general Self-supervised Time series representation learning framework, by exploring the inter-sample relation and intra-temporal relation of time series to learn the underlying structure feature on the unlabeled time series. Specifically, we first generate the inter-sample relation by sampling positive and negative samples of a given anchor sample, and intra-temporal relation by sampling time pieces from this anchor. Then, based on the sampled relation, a shared feature extraction backbone combined with two separate relation reasoning heads are employed to quantify the relationships of the sample pairs for inter-sample relation reasoning, and the relationships of the time piece pairs for intra-temporal relation reasoning, respectively. Finally, the useful representations of time series are extracted from the backbone under the supervision of relation reasoning heads. Experimental results on multiple real-world time series datasets for time series classification task demonstrate the effectiveness of the proposed method. Code and data are publicly available 1.
Computer Intrusion Detection and Network Monitoring: A Statistical Viewpoint

From the Publisher: "This book covers the basic statistical and analytical techniques of computer intrusion detection. It is aimed at both statisticians looking to become involved in the data analysis aspects of computer security and computer scientists looking to expand their toolbox of techniques for detecting intruders. " "The book is self-contained, assuring no expertise in either computer security or statistics. It begins with a description of the basics of TCP/IP, followed by chapters dealing with network traffic analysis, network monitoring for intrusion detection, host-based intrusion detection, and computer viruses and other malicious code. Each section develops the necessary tools as needed. There is extensive discussion of visualization as it relates to network data and intrusion detection. The book also contains an extensive bibliography covering the statistical, machine learning, and pattern recognition literature related to network monitoring and intrusion detection. "--BOOK JACKET.
in Computer

— The complexity of today's distributed computing environment is such that the presence of bugs and security holes is statistically unavoidable. A very promising approach to the present issue is to implement a self-protected system. Self-protection refers to the ability for a system to detect illegal behaviors. This article demonstrates the implementation of self-protection manager which targets clustered distributed systems. Our approach is based on the global database of the clustered distributed applications. This knowledge permits to detect known and unknown attacks if an prohibited (illegal) access is performed. The prototype is designed using access detection.
Tuning, interference and false shallow gas signatures in geohazard interpretations: Beyond the ‘λ/4’ rule

Shallow gas presents a significant geohazard for drilling operations, with implications for costly well deviations and inherent blowout risks. The archetypal seismic signature of shallow gas—a “bright spot”—can be falsely induced by tuning, whereby reflections from closely separated horizons stack and constructively interfere. According to established guidelines, maximum constructive interference is typically expected where horizons are separated by one-quarter wavelength (λ/4) of the seismic wavelet. Here, we test the circumstances in which false gas signatures can be induced from tuning and the conditions in which the “λ/4” guidelines for interference become problematic. We simulate normal-incidence seismic data for a variety of reflectivity models, incorporating different contrasts in reflectivity magnitude and polarity. We simulate acoustic impedance by supplying initial geological parameters to Gassmann’s rock physics equations, allowing bulk density and compressional (P-) wave velocity to vary between 1200–2100 kg/m3 and 1460–1670 m/s, respectively, for non-gassy sediments and 1160 kg/m3 and 170–200 m/s for gassy sediments. Tuning is considered for a Ricker wavelet source pulse, having both peak frequency and effective bandwidth of 60 Hz. Tuning effects are able to mask a gas pocket, corresponding to a “false negative” signature that represents a significant hazard for drilling operations. Furthermore, the widely adopted λ/4 assumption for constructive interference is not always valid as the brightest seismic responses can appear for thicker ( “λ/16”) beds, depending upon the stratigraphy. Similar observations are made both qualitatively and quantitatively for real seismic responses, in which reflections from a series of dipping clinoforms interfere with those from an overlying unconformity. We conclude that greater attention should be paid to the interpretation of shallow gas risk; specifically, the effect of reflector geometries should not be overlooked as a means of producing or masking seismic amplitudes that could be indicative of a hazardous gas accumulation.
Walking through the Forest: a Fast EUF Proof-Checking Algorithm

The quantiﬁer-free logic of equality with uninterpreted function symbols (EUF) is at the core of SMT solvers. However, there exist several competing proof formats to validate EUF proofs. As EUF proof, we advocate for the proof forest that is the artifact proposed by Nieuwenhuis and Oliveras to extract eﬃciently EUF unsatisﬁable cores. An advantage of this proof format is that it can be generated by the SMT solver for almost free. Our preliminary experiments show that our proof forest veriﬁer outperforms other EUF veriﬁers and that proof forests appear to be more concise than existing EUF proofs.
Digital Apprehension © and First Year University Students

The mere presence of global connections creates the need for higher education to be internationally competitive—economically, culturally, and academically. The ‘latest’ digital tools can be heralded from the ‘best’ institutions enticing local and international students to come to their particular university. However, with the combination of global connection, the diversity of the contemporary university population, and technology, a new concern is appearing. While learning technologies are being increasingly utilised in the delivery of university programs, students may not use the technology to the full advantage. The aim of this study was to identify and characterise Digital Apprehension© among first year university students (N = 30). This was achieved by thematic analyses of data gathered from focus group interviews, and development of a 12-item questionnaire. Findings revealed that one in three first year university students were frustrated with the learning technology.
Improving the Performance of Read Operations in Distributed File System

Distributed file systems are used in distributed systems to support scalable storage and to enable the parallel and distributed processing of data. Sharing the data stored in the distributed file system among authorized users is a major requirement of the distributed file system. Popular distributed file systems use session semantics to share the data among the users. In this paper, we have proposed a read algorithm developed based on speculative semantics which permits the read process to read the updates done by the concurrent write process from the distributed file system provided such a reading does not affect data consistency.
Special Issue on Artificial Intelligence and Social Application

This paper presents a learning environment where a mining algorithm is used to learn patterns of interaction with the user and to represent these patterns in a scheme called item descriptors. The learning environment keeps theoretical information about subjects, as well as tools and exercises where the student can put into practice the knowledge gained. One of the main purposes of the project is to stimulate collaborative learning through the interaction of students with different levels of knowledge. The students' actions, as well as their interactions, are monitored by the system and used to find patterns that can guide the search for students that may play the role of a tutor. Such patterns are found with a particular learning algorithm and represented in item descriptors. The paper presents the educational environment, the representation mechanism and learning algorithm used to mine social-affective data in order to create a recommendation model of tutors. Ketwords — Collaboration, Learning Environment, Recommender Systems, Social-Affective Data.
A Blockchain based Access Control System for Cloud Storage

: Multi-user system for access control to datasets stored in an untrusted cloud environment. Cloud storage like any other untrusted environment needs the ability to secure share information. Our approach provides an access control over the data stored in the cloud without the provider participation. The main tool of access control mechanism is cipher text-policy attribute-based encryption scheme with dynamic attributes. Using a block chain based decentralized ledger, our system provides immutable log of all meaningful security events, such as key generation, access policy assignment, change or revocation, access request. We propose a set of cryptographic protocols ensuring privacy of cryptographic operations requiring secret or private keys. Only cipher texts of hash codes are transferred through the block chain ledger. The prototype of our system is implemented using smart contracts and tested on Ethereum block chain platform.
THE COST 258 SIGNAL GENERATION TEST ARRAY

The evaluation of Speech Synthesis Coders (SSC) provided in the literature is often informal and results cannot be compared. The COST258 signal generation test array aims to provide a benchmark for testing the ability and performance of SSC in achieving different prosodic modifications. The benchmark consists in performing various prosodic transplantations from a given natural utterance to various prosodic “variants” of the same sentence. These prosodic “variants” were recorded by the same speaker in order to obtain both credible prosodic transplantations and reference target signals.
City Research Online

Depicting spatial and temporal aspects of trafﬁc ﬂows of different types is challenging. We use a treemap-based technique that is able to show multiple aspects of large quantities of spatial and temporal trafﬁc data simultaneously. Treemaps present multivariate data as a hierarchy of rectangles that are nested within each other. Each level of the hierarchy is used to carry information about one variable, with rectangle size, arrangement and colour being potential information-carrying ‘channels’ for reﬂecting properties of the data. We show information about the vehicles operated by eCourier (UK) Ltd. by location, vehicle type, day of the week and hour of the day. Our two maps use colour to show the volumes and speeds of trafﬁc at each of 82,320 combinations of location, vehicle type, day of week and hour of day, concurrently. Crucially, we use a regular grid to represent location, give all the treemap nodes a constant size and order them spatially. This cartographic representation allows multiple aspects of large trafﬁc datasets to be viewed concurrently, such that spatial and temporal patterns can be identiﬁed.
Aerosol Optical Depth Pathways and Sources; Lake Victoria Basin*

The air mass back-trajectory clustering analysis was combined with Aerosol Optical Depth (AOD) of fine mode, coarse mode and fine mode fraction in order to evaluate the long-range effects of transportation patterns of trajectories for the ground based station at ICIPE Mbita which is located on longitude and latitude of 34.2°E, 0.417°S respectively at 1125 meters above sea level. In order to get a clear picture of the source and sinking points of aerosols, monthly means of a 72 hour backward trajectories data ranging from 2013 to 2015 were used in categorizing the cluster into five classes. Most of the air trajectories analysis from this paper shows evidence that the major sources and pathways for the aerosols into the receptor station commonly originate from as far as the Arabian deserts and Sahara deserts from the Northern Hemisphere and Indian Ocean and central Africa in the Southern Hemisphere.
A Comparison of Projective Reconstruction Methods for Pairs of Views Charlie ROTHWELL, Olivier FAUGERAS and Gabriella CSURKA

Recently, diierent approaches for uncalibrated stereo have been suggested which permit proo jective reconstructions from multiple views. These use weak calibration which is represented by the epipolar geometry, and so we require no knowledge of the intrinsic or extrinsic camera paa rameters. In this paper we consider projective reconstructions from pairs of views, and compare a number of the available methods. Projective stereo algorithms can be categorized by the way in which the 3D coordinates are computed. The rst class is similar to traditional stereo algorithms in that the 3D world geometry is made explicit; the initial phase of the processing always involves the estimation of the camera matrices from which the 3D coordinates are computed. We show how the camera matrices can be computed either from point correspondences, or how they are constrained by the fundamental matrices. The second class of algorithms are based on implicit image measurements which are used to compute projective invariants from image correspondences. The invariants are based on the Cayley algebra and on cross ratios. In all cases, the invariants are functionally dependent on the 3D coordinates. We report on the stabilities of the diierent methods using a range of meaningful synthetic and real images. From these we can conclude which methods are most likely to be of use in applications that are dependent on 3D uncalibrated reconstructions.
Sentiment Analysis for Helpful Reviews Prediction

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