Miracle-dz/UniFAR-FTUs huggingface dataset:
A full-reference stereoscopic image quality metric based on binocular energy and regression analysis

The recent developments of 3D media technology have brought to life numerous applications of interactive entertainment such as 3D cinema, 3DTV and gaming. However, due to the data intensive nature of 3D visual content, a number of research challenges have emerged. In order to optimise the end-to-end content life-cycle, from capture to processing and delivery, Quality of Experience (QoE) has become a major driving factor. This paper presents a human-centric approach to quality estimation of 3D visual content. A fullreference quality assessment method for stereoscopic images is proposed. It is based on a Human Visual System (HVS) model to estimate subjective scores of registered stereoscopic images subjected to compression losses. The model has been trained with four publicly available registered stereoscopic image databases and a fixed relationship between subjective scores and the model has been determined. The high correlation of the relationship over a large number of stimuli has proven its consistency over the state-of-the-art.
Diiracting Trees

Shared counters are among the most basic coordination structures in multiprocessor computation , with applications ranging from barrier synchronization to concurrent-data-structure design. This paper introduces diiracting trees, novel distributed-parallel structures for shared counting and load balancing. Diiracting trees combine a randomized coordination method together with a combinatorial data structure, to yield a logarithmic depth counter that improves on the log 2 depth of counting networks, and overcomes the resiliency drawbacks of combining trees. Empirical evidence , collected on a simulated distributed shared-memory machine and several simulated message passing architectures, shows that diiracting trees scale better and are more robust then both combining trees and counting networks, currently the most eeective known methods for implementing concurrent counters. Diiracting trees have already been used to implement highly eecient pro-ducer/consumer queues, and we believe diiraction will prove to be an eeective alternative paradigm to combining and queue-locking in the design of many concurrent data structures.
ICT Oriented Toward Nyaya: Community Computing in India’s Slums

In many schools across India, access to information and communication technology (ICT) is still a rare privilege. While the Annual Status of Education Report in India (2013) showed a marginal uptick in the amount of computers, the opportunities for children to use those computers have remained stagnant. The lack of access to ICT is especially common in India’s urban slum areas, which is privy to the “Matthew Effect” (Merton, 1968) where the poor become poorer based in part on the scarcity of high-tech resources. This article’s purpose is to describe and report on ICT program interventions that target young people living in India’s slums. Specifically, the article examines a case study of a grassroots effort, called the community computing model, in Bangalore, India. Using Amartya Sen’s work on nyaya and Paulo Freire’s work on conscientization, the article explains how this model of community computing infused and developed a social justice oriented and deeper “critical consciousness” of the slum community where this computer center was situated.
Fixing Implicit Derivatives: Trust-Region Based Learning of Continuous Energy Functions - Supplementary Material

Drawing heavily from the book Practical Methods of Optimization[1], our proof has two parts: (i) show that one iteration of Newton step is sufficient to predict the new location of the minimum in the limit. (ii) Prove that the derivative of one iteration of Newton Step with respect to w exists. The second step is not completely obvious as it relies upon the stability of H−1, something which is fortunately guaranteed by the standard assumption in optimisation that H is positive definite about the minimum.
Fixing Implicit Derivatives: Trust-Region Based Learning of Continuous Energy Functions (Abridged)

We present a new technique for the learning of continuous energy functions that we refer to as Wibergian Learning. One common approach to inverse problems is to cast them as an energy minimisation problem, where the minimum cost solution found is used as an estimator of hidden parameters. Our new approach formally characterises the dependency between weights that control the shape of the energy function, and the location of minima, by describing minima as fixed points of optimisation methods. This allows for the use of gradient-based end-to-end training to integrate deeplearning and the classical inverse problem methods. We show how our approach can be applied to obtain state-ofthe-art results in the diverse applications of tracker fusion and multiview 3D reconstruction. The full paper can be found in the NeurIPS2019 proceedings [14].
Unsupervised hyperspectral feature selection based on fuzzy c-means and grey wolf optimizer

ABSTRACT Hyperspectral image (HSI) with hundreds of narrow and consecutive spectral bands provides substantial information to discriminate various land-covers. However, the existence of redundant features/bands not only gives rise to increasing of computation time but also interferes the classification result of hyperspectral images. Obviously, it is a very challenging problem how to select an effective feature subset from original bands to reduce the dimensionality of the hyperspectral dataset. In this study, a novel unsupervised feature selection method is suggested to remove the redundant features of HSI by feature subspace decomposition and optimization of feature combination. Feature subset decomposition is achieved by the fuzzy c-means (FCM) algorithm. The optimal feature selection is based on the optimization process of grey wolf optimizer (GWO) algorithm and maximum entropy (ME) principle. To evaluate the effectiveness of the proposed method, experiments are conducted on three well-known hyperspectral datasets, Indian Pines, Pavia University, and Salinas. Six state-of-the-art feature selection methods are used to compare with the proposed method. Experimental results successfully confirm the superior performance of our proposal with respect to three classification accuracy indices overall accuracy (OA), average accuracy (AA) and kappa coefficient (κ).
This paper is included

Android introduced runtime permissions in order to provide users with more contextual information to make informed decisions as well as with ﬁner granularity when dealing with permissions. In this work, we identiﬁed that the correct operation of the runtime permission model relies on certain implicit assumptions which can conveniently be broken by adversaries to illegitimately obtain permissions from the background while impersonating foreground apps. We call this detrimental scenario false transparency attacks . These attacks constitute a serious security threat to the Android platform as they invalidate the security guarantees of 1) runtime permissions by enabling background apps to spoof the context and identity of foreground apps when requesting permissions and of 2) Android permissions altogether by allowing adversaries to exploit users’ trust in other apps to obtain permissions. We demonstrated via a user study we conducted on Amazon Mechanical Turk that mobile users’ comprehension of runtime permissions renders them susceptible to this attack vector. We carefully designed our attacks to launch strategically in order to appear persuasive and veriﬁed the validity of our design strategies through our user study. To demonstrate the feasibility of our attacks, we conducted an in-lab user study in a realistic setting and showed that none of the subjects noticed our attacks. Finally, we discuss why the existing defenses against mobile phishing fail in the context of false transparency attacks. In particular, we disclose the security vulnerabilities we identiﬁed in a key security mechanism added in Android 10. We then propose a list of countermeasures to be implemented on the Android platform and on app stores to practically tackle false transparency attacks.
Measurement of sap flow in young apple trees using the average gradient heat-pulse method

The average gradient heat-pulse method (CHMP-AG) has been used to monitor sap flow in very young (1-year-old) apple trees, from budburst through until leaf fall. Data are presented to illustrate how CHPM-AG can resolve the full range of sap flux densities in these small trees. The methodology has been implemented by making a very simple software change to existing CHPM instrumentation.
Static Code Analyzer Source Code Bug Reports Reduced Code Learning from Code Preprocessing False Positive Report Filter Code Patterns Labeling Reports Code Reduction In Out

The large scale and high complexity of modern software systems make perfectly precise static code analysis (SCA) infeasible. Therefore SCA tools often over-approximate, so not to miss any real problems. This, however, comes at the expense of raising false alarms, which, in practice, reduces the usability of these tools. To partially address this problem, we propose a novel learning process whose goal is to discover program structures that cause a given SCA tool to emit false error reports, and then to use this information to predict whether a new error report is likely to be a false positive as well. To do this, we first preprocess code to isolate the locations that are related to the error report. Then, we apply machine learning techniques to the preprocessed code to discover correlations and to learn a classifier. We evaluated this approach in an initial case study of a widelyused SCA tool for Java. Our results showed that for our dataset we could accurately classify a large majority of false positive error reports. Moreover, we identified some common coding patterns that led to false positive errors. We believe that SCA developers may be able to redesign their methods to address these patterns and reduce false positive error reports. CCS Concepts •Theory of computation→ Program analysis; •Computing methodologies→ Machine learning algorithms; Supervised learning by classification; •Software and its engineering→ General programming languages
Sediment-associated organopollutants, metals and nutrients in the Nechako River, British Columbia: a current study with a synthesis of historical data

Abstract The flow-diverted Nechako River is the second largest tributary of the Fraser River which drains 25% of mainland British Columbia, Canada. The watershed provides critical reproductive habitats for anadromous chinook salmon (Oncorhynchus tshawytscha) and sockeye salmon (O. nerka) and year-round habitat for the endangered Nechako white sturgeon (Acipenser transmontanus) population. In this study, the chemical quality of sediment in the upper Nechako River and its major tributaries was examined for polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs), legacy organochlorine (OC) pesticides, polycyclic aromatic hydrocarbons (PAHs), organophosphorus and phenoxy acid herbicides, polychlorinated dibenzo-p-dioxins (PCDDs) and furans (PCDFs), labile (exchangeable) metals/metalloids, and major nutrients (N and P). ΣPCB and ΣPBDE were detected in channel bottom sediments at all Nechako River and tributary sites; hexachlorobenzene (HCB) and 4,4′-DDE (dichlorodiphenyldichloroethylene) were also detected at most sites. Organophosphorus and phenoxy acid herbicides were not detected in any samples. While ΣPCB, ΣPBDE, HCB, and 4,4′-DDE concentrations in bottom sediments were always well below provincial and federal guidelines for the protection of aquatic life, concentrations of total labile As (AsT), CrT, CuT, FeT, MnT, NiT, and ZnT in suspended and/or bottom sediments often exceeded provincial threshold effect levels (TEL) and, in some cases, approached or exceeded probable effect levels. Distinct CuT, NiT, PbT and ZnT concentration maxima in suspended sediments were linked to road and urban densities. Historical PCDD, PCDF and PAH data show that concentrations in bottom sediment samples were highest at a site in the lower Nechako River between Miworth and the City of Prince George where PCDD and PCDF concentrations exceeded the interim federal TEL. Nitrogen and P concentrations in bottom sediments were negatively correlated with water velocity and sediment texture; the evidence suggests that reductions in velocity resulting from the 1952 diversion of the Nechako River have increased the nutrient content of bottom substrates.
2 0 N ov 2 00 2 On the multiresolution structure of Internet traffic traces

Internet traffic on a network link can be modeled as a stochastic process. After detecting and quantifying the properties of this process, using statistical tools, a series of mathematical models is developed, culminating in one that is able to generate “traffic” that exhibits –as a key feature– the same difference in behavior for different time scales, as observed in real traffic, and is moreover indistinguishable from real traffic by other statistical tests as well. Tools inspired from the models are then used to determine and calibrate the type of activity taking place in each of the time scales. Surprisingly, the above procedure does not require any detailed information originating from either the network dynamics, or the decomposition of the total traffic into its constituent user connections, but rather only the compliance of these connections to very weak conditions.
Sedimentary basin investigation using receiver function: an East African Rift case study

We apply receiver function (RF) methodology to map the geometry of a sedimentary basin along a ∼10-km-long profile of broadband seismometers that recorded continuously for approximately 3 months. For a subset of the stations, we apply the Neighbourhood Algorithm inversion scheme, to quantify the geometry of basin bounding fault directly beneath the stations. We compare our results with active reflection seismic data and with the lithostratigraphy from a well located along the profile. We find that the P-to-s conversions from the sediments–basement interface (SBI), recorded in RF data sets together with information on intrabasin structures, are useful for obtaining high resolution images of the basin. The depth of the SBI derived from RF inversion is consistent (within ∼0.4 km) with the estimates from active reflection seismic and the well data. This study highlights that analysis of teleseismic waveforms can retrieve relevant information on the structure of a sedimentary basin.
Human Identification using GAIT Recognition Technique with PAL and PAL entropy, SVM And k-means with LDA

: - Gait recognition is one kind of biometric technology that can be used to monitor people without their cooperation. The controlled environments such as banks; military installations and even airports need to be able to quickly detect threats and provide differing levels of access to different user groups. The Gait shows a particular way or manner of moving on foot and gait recognition is the process of identifying an individual by the manner in which they walk. And Gait is less unobtrusive biometric; which offers the possibility to identify people at a distance; without any interaction or co-operation from the subject; this is the property which makes it so attractive [2]. This paper proposed new method for gait recognition. In this, firstly binary silhouette of a walking person is detected from each frame of an image. Then secondly, the features from each frame are extracted using the image processing operation. The step size length; centre of mass and cycle length are talking as key feature. In the end, SVM, K-means and LDA are used for training and testing purpose. Here, every experiments and tests are done on gait database. At last in this paper, the result shows that the better improvement from the previous result by using SVM, K-means and LDA.
Visually integrating and exploring high throughput Phenome-Wide Association ( PheWAS ) results using PheWAS-View

This peer-reviewed article was published immediately upon acceptance. It can be downloaded, printed and distributed freely for any purposes (see copyright notice below). Articles in BioData Mining are listed in PubMed and archived at PubMed Central. For information about publishing your research in BioData Mining or any BioMed Central journal, go to http://www.biodatamining. org/authors/instructions/ For information about other BioMed Central publications go to http://www.biomedcentral. com/ BioData Mining
Distributional Range Extension of Xeniamia atrithorax (Perciformes: Apogonidae) in the northern South China Sea

The monotypic apogonid genus Xeniamia Fraser and Prokofiev, 2016 is characterized by VIII-I, 9 dorsal-fin rays, one supraneural, two epurals, the first and second hypurals fused, the posterior margin of the preopercle smooth, and a large cluster of melanophores anterior to the pelvic-fin origin (Fraser and Prokofiev 2016). Xeniamia atrithorax was originally described by Fraser and Prokofiev (2016) from specimens collected from Vietnam. However, there have been no subsequent reports of the species. During an ichthyofaunal study in southern Taiwan, seven specimens of X. atrithorax were collected, being the second record of the species. Color photographs taken at the time of collection have enabled the fresh coloration of the species to be described (herein) for the first time.
IFT 6135 Representation Learning ( Programming Assignment 4 ) Names :

In (a), a transposed convolution layer, the forward and backward passes of a traditional convolution layer are reversed. It can be thought of as a gradient of some convolution with respect to its input. With this procedure, the spatial transformation of a regular convolution (with the same parameters) are reversed granting a feature map equal or larger than its input. It has been noted that (a) produces an overlap pattern in two dimensions [5], which is most prominent when outputting unusual colors.
View‐dependent dynamics of articulated bodies

We propose a method for view‐dependent simplification of articulated‐body dynamics, which enables an automatic trade‐off between visual precision and computational efficiency. We begin by discussing the problem of simplifying the simulation based on visual criteria, and show that it raises a number of challenging questions. We then focus on articulated‐body dynamics simulation, and propose a semi‐predictive approach which relies on a combination of exact, a priori error metrics computations, and visibility estimations. We suggest several variants of semi‐predictive metrics based on hierarchical data structures and the use of graphics hardware, and discuss their relative merits in terms of computational efficiency and precision. Finally, we present several benchmarks and demonstrate how our view‐dependent articulated‐body dynamics method allows an animator (or a physics engine) to finely tune the visual quality and obtain potentially significant speed‐ups during interactive or off‐line simulations. Copyright © 2008 John Wiley & Sons, Ltd.
A robust method of image flicker correction for heavily-corrupted old film sequences

The film material of old movies is often degraded heavily by several distortions such as flicker. To promote recycling of old films, we need to improve their picture quality. Image flickers are defined as undesirable image brightness fluctuations which do not originate from the scene, and are perceived as an annoying artifact. Image flickers are caused by several factors: aging of film, instability of chemical processing and telecine conversion. Hence, proper models of image flickers and their correction models are not known at all in advance. This paper deals with a hierarchy of flicker-correction models well suited for correcting image flickers contained in heavily-corrupted old film sequences, and develops a robust flicker-correction method which first estimates the correction-model parameters from the input old film sequence and then corrects its image flickers according to the estimated model without being disturbed by several distortions.
A Transition-Based Directed Acyclic Graph Parser for UCCA

Figure 1 presents the feature templates used by TUPASparse. All feature templates define binary features. The other classifiers use the same elements listed in the feature templates, but all categorical features are replaced by vector embeddings, and all count-based features are replaced by their numeric value. For some of the features, we used the notion of head word, defined by the h∗ function (see Appendix D). While head words are not explicitly represented in the UCCA scheme, these features prove useful as means of encoding word-to-word relations.
On One-Pass CPS Transformations

We bridge two distinct approaches to one-pass CPS transformations, i.e., CPS transformations that reduce administrative redexes at transformation time instead of in a post-processing phase. One approach is compositional and higher-order, and is due to Appel, Danvy and Filinski, and Wand, building on Plotkin's seminal work. The other is non-compositional and based on a syntactic theory of the lambda-calculus, and is due to Sabry and Felleisen. To relate the two approaches, we use Church encoding, Reynolds's defunctionalization, and an implementation technique for syntactic theories, refocusing, developed in the second author's PhD thesis.
Genesis potential estimation of high-impact weather by TIGGE ensemble data

A prototype of a warning potential system for high-impact weather events is proposed, based on the THORPEX Interactive Global Grand Ensemble (TIGGE) data sets. The main events we are interested in are heavy precipitation, tropical cyclone track, heat wave, flooding, drought etc. The basic concept and some examples will be presented; the Northern Vietnam flooding in November 2008 and a sand storm event in Gobi Desert in April 2007.
Newsletter of the European Network of Excellence in AI Planning

In this article, a system devised and implemented to exploit abstraction techniques for solving complex problems is presented. The system is able to automatically generate a hierarchical planner starting from a generic planner P, provided that compliance with the STRIPS subset of PDDL 1.2 standard is ensured. The resulting hierarchical planner delegates to P the actual search at any required level of abstraction -including ground level. Some experiments have been conducted between three selected planners and their hierarchical counterparts. Results show that the proposed approach may speed up the search, especially for problems of medium / high complexity.
Classical computing, quantum computing, and Shor's factoring algorithm

This is an expository talk written for the Bourbaki Seminar. After a brief introduction, Section 1 discusses in the categorical language the structure of the classical deterministic computations. Basic notions of complexity icluding the P/NP problem are reviewed. Section 2 introduces the notion of quantum parallelism and explains the main issues of quantum computing. Section 3 is devoted to four quantum subroutines: initialization, quantum computing of classical Boolean functions, quantum Fourier transform, and Grover's search algorithm. The central Section 4 explains Shor's factoring algorithm. Section 5 relates Kolmogorov's complexity to the spectral properties of computable function. Appendix contributes to the prehistory of quantum computing.