Miracle-dz/UniFAR-FTUs huggingface dataset:
Critical path-based thread placement for NUMA systems

Multicore multiprocessors use Non Uniform Memory Architecture (NUMA) to improve their scalability. However,NUMA introduces performance penalties due to remote memory accesses. Without efficiently managing data layout and thread mapping to cores, scientific applications, even if they are optimized for NUMA, may suffer performance loss. In this paper, we present an algorithm that optimizes the placement of OpenMP threads on NUMA processors. By collecting information from hardware counters and defining new metrics to capture the effects of thread placement, the algorithm reduces NUMA performance penalty by minimizing the critical path of OpenMP parallel regions and by avoiding local memory resource contention. We evaluate our algorithm with NPB benchmarks and achieve performance improvement between 8.13% and 25.68%, compared to the OS default scheduling.
Resource control and strong normalisation

We introduce the \emph{resource control cube}, a system consisting of eight intuitionistic lambda calculi with either implicit or explicit control of resources and with either natural deduction or sequent calculus. The four calculi of the cube that correspond to natural deduction have been proposed by Kesner and Renaud and the four calculi that correspond to sequent lambda calculi are introduced in this paper. The presentation is parameterized with the set of resources (weakening or contraction), which enables a uniform treatment of the eight calculi of the cube. The simply typed resource control cube, on the one hand, expands the Curry-Howard correspondence to intuitionistic natural deduction and intuitionistic sequent logic with implicit or explicit structural rules and, on the other hand, is related to substructural logics. We propose a general intersection type system for the resource control cube calculi. Our main contribution is a characterisation of strong normalisation of reductions in this cube. First, we prove that typeability implies strong normalisation in the ''natural deduction base"of the cube by adapting the reducibility method. We then prove that typeability implies strong normalisation in the ''sequent base"of the cube by using a combination of well-orders and a suitable embedding in the ''natural deduction base". Finally, we prove that strong normalisation implies typeability in the cube using head subject expansion. All proofs are general and can be made specific to each calculus of the cube by instantiating the set of resources.
System Interactions in Sociotechnical Transitions : Extending the Multi Level Perspective

This paper discusses contextual issues in sociotechnical systems and transitions under the Multi Level Perspective (MLP). It emphasises inter system interactions, for which a typology is developed drawing on a review and meta level analysis of published transition case studies. The typology is subsequently associated to the MLP transitions pathways. A novel transition pathway, is derived through this process, namely new system emergence, for systems that emerge from contributions of existing antecedent sociotechnical systems.
Stochastic Methods in Neuroscience

PREFACE NOMENCLATURE 1. A brief introduction to some basic stochastic processes 2. Markov chain models of ion channels and calcium release sites 3. Stochastic dynamic bifurcations and excitability 4. Neural coherence and stochastic resonance 5. Noisy oscillators 6. The role of variablity in populations of spiking neuons 7. Population density methods in large-scale neural network modelling 8. A population density model of the driven LGN/PGN 9. Syanptic "noise": experiments, computatioal consequences and methods to analyze experimental data 10. Statistical models of spike trains 11. Stochastic simulations of neurons, axons, and action potentials 12. Numerical simulations of SDEs and SPDEs from neural systems using SDELAB
DCASE 2018 CHALLENGE BASELINE WITH CONVOLUTIOANL NEURAL NETWORKS Technical Report

Detection and classification of acoustic scenes and events (DCASE) 2018 challenge is a well known IEEE AASP challenge consists of several audio classification and sound event detection tasks. DCASE 2018 challenge includes five tasks: 1) Acoustic scene classification, 2) Audio tagging of Freesound, 3) Bird audio detection, 4) Weakly labeled semi-supervised sound event detection and 5) Multi-channel audio tagging. In this paper we open source the python code of all of Task 1 5 of DCASE 2018 challenge. The baseline source code contains the implementation of the convolutioanl neural networks (CNNs) including the AlexNetish and the VGGish from the image processing area. We researched how the performance varies from task to task when the configuration of the neural networks are the same. The experiment shows deeper VGGish network performs better than AlexNetish on Task 2 5 except Task 1 where VGGish and AlexNetish network perform similar. With the VGGish network, we achieve an accuracy of 0.680 on Task 1, a mean average precision (mAP) of 0.928 on Task 2, an area under the curve (AUC) of 0.854 on Task 3, a sound event detection F1 score of 20.8% on Task 4 and a F1 score of 87.75% on Task 5.
SESSION 6 TOOLS FOR COGNITIVE ANALYSIS

A menu-driven software system was developed to implement schemata organization in a constraint satisfaction neural network. The current neural-net model presents several advantages and modifi cations over previous related models. On the one hand, the schemata behavior shown by the present model is based on conceptual definitions and ratings obtained empirically from human subjects rather than on the idiosyncratic knowledge database of a single programmer. On the other hand, this property is most valuable to experimental research in which the current knowledge status of the subjects is critical for the experiments (e.g., word-recognition experiments). The present paper describes a menu-driven software system called Semantic Analyzer of Schemata Organiza tion (SASO). This program was developed to implement schemata organization in a constraint-satisfaction neural network similar to the connectionist model for schemata postulated by Rumelhart, Smolensky, McClelland, and Hinton in 1986. However, the current neural-net model presents several advantages and modifications over pre vious related models. First, the schemata behavior shown by the present neural net is based on conceptual defini tions and ratings obtained empirically from human sub jects rather than on the idiosyncratic knowledge database of a single programmer. This property is especially well suited to experimental research in which the knowledge status of the subjects is critical for the experiments (e.g. , word-recognition experiments). Second, SASO provides the user with a set of utilities to process raw data gener ated by the subjects. It also automatically sets up the weight-connectivity matrix among concepts and generates the interface data files needed to run schemata simula tions on the constraint-satisfactionneural-net program pro vided by McClelland and Rumelhart in 1988. A psychological experiment and computer neural-net simulations were carried out to test schemata organization
The France Telecom Orange Labs (Beijing) Video Semantic Indexing Systems - TRECVID 2012 Notebook Paper

In this paper, we describe FTRDBJ’s systems and experiments for TRECVID2012 SIN task. This year, a new type of runs named “concept pair” was evaluated, for which we tried many different models. We submitted two “full” runs and two “pair” runs. For the “full” runs, our systems are very similar to the old ones used in 2011. A 6-feature and a 9-feature composite-kernel SVM systems were used to detect the concepts. For the “pair” runs, we submitted a confidence based run and an OWA based run. The final results show that the first one worked better because a simpler model usually works more robust.
A Review of Image Fusion Techniques

The technique of blending two images or more than two images which produces outcome as the composite fused image. The obtained fused image is the upgraded version of original images because it has all the salient information. The present applications makes majority usage of this fused image to speed up their processing tasks in their respective fields. Recent real-time applications which require image fusion are remote sensing applications, medical applications, surveillance application, photography applications etc. The broad categorization of image fusion techniques are Non-transform domain or spatial domain and Transform domain or frequency domain. This paper initiates with the introduction of image fusion. In the second section it explains the levels of fusion. The third section explains generic image fusion strategy. Further sections elaborates the taxonomy of image fusion techniques and their comparative tables lists all the merits and demerits of the same.
CONFU: Configuration Fuzzing Testing Framework for Software Vulnerability Detection Master's Thesis

Many software security vulnerabilities only reveal themselves under certain conditions, i.e., particular configurations and inputs together with a certain runtime environment. One approach to detecting these vulnerabilities is fuzz testing that feeds randomly generated inputs to the software and witnesses its failures. However, typical fuzz testing makes no guarantees regarding the syntactic and semantic validity of the input, or of how much of the input space will be explored. To address these problems, we present a new testing methodology called Configuration Fuzzing. Configuration Fuzzing is a technique whereby the configuration of the running application is mutated at certain execution points, in order to check for vulnerabilities that only arise in certain conditions. As the application runs in the deployment environment, this testing technique continuously fuzzes the configuration and checks "security invariants'' that, if violated, indicate a vulnerability. We discuss the approach and introduce a prototype framework called ConFu (CONfiguration FUzzing testing framework) implementation. We also present the results of case studies that demonstrate the approach's feasibility and evaluate its performance.
Image Indexing and Retrieval

Nowadays the WWW has rapidly growing with the expansion of image databases. From the huge amount of image databases, users have to retrieve relevant images by using an effective and efficient mechanism for image indexing and retrieval. Many techniques have come to fulfill this requirement. One way to fulfill this requirement is the traditional image database indexing and retrieval capabilities in which the image data has to be indexed and fully convert the image data to an electronic presentation. But there are many factors which prohibit the traditional image indexing including lower quality of text and higher cost. Problems of traditional image indexing has led to raise the interest level in investigating the techniques for retrieving images automatically by using intermediate features such as color, shape and texture etc. In this paper, the problem of image indexing and retrieval has been addressed in the context of Content-Based Image Retrieval (CBIR).
The Complete Analysis of a Polynomial Factorization Algorithm over Nite Elds the Complete Analysis of a Polynomial Factorization Algorithm over Nite Elds the Complete Analysis of a Polynomial Factorization Algorithm over Finite Fields

A uniied treatment of parameters relevant to factoring polynomials over nite elds is given. The framework is based on generating functions for describing parameters of interest and on singularity analysis for extracting asymptotic values. An outcome is a complete analysis of the standard polynomial factorization chain that is based on elimination of repeated factors, distinct degree factorization, and equal degree separation. Several basic statistics on polynomials over nite elds are obtained in the course of the analysis. L'analyse compl ete d'un algorithme de factorisation de polyn^ omes sur les corps nis R esum e : Cet article propose un cadre unii e pour l'analyse des param etres qui intervien-nent dans la factorisation de polyn^ omes sur un corps ni. L' etude repose d'une part sur les s eries g en eratrices utilis ees pour d ecrire les principaux param etres, d'autre part sur l'analyse de singularit e qui fournit les informations asymptotiques correspondantes. Est ainsi obtenue une analyse compl ete d'une cha^ ne classique de factorisation fond ee sur l' elimination des fac-teurs r ep et es, la factorisation en degr e disticts, et la s eparation des degr es egaux. Plusieurs statistiques de base relatives aux polyn^ omes sur les corps nis r esultent de cette analyse. Abstract. A uniied treatment of parameters relevant to factoring polynomials over nite elds is given. The framework is based on generating functions for describing parameters of interest and on singularity analysis for extracting asymptotic values. An outcome is a complete analysis of the standard polynomial factorization chain that is based on elimination of repeated factors, distinct degree factorization, and equal degree separation. Several basic statistics on polynomials over nite elds are obtained in the course of the analysis. 1. Introduction Factoring polynomials over nite elds intervenes in many areas like polynomial factorization over the integers 8, 31], cryptography 7, 33, 36], number theory 3], or coding theory 2]. The implications include nding complete partial fraction decompositions (a problem itself useful for symbolic integration), designing cyclic redundancy codes, computing the number of points on elliptic curves, and building arithmetic public key cryptosystems. In particular, the factorization of random polynomials over nite elds is needed in the index calculus method for computing discrete logarithms over nite elds 36]. This paper derives basic probabilistic properties of random polynomials over nite elds that are of interest in the study of polynomial factorization algorithms. We show that …
Use cases and challenges in telecom big data analytics

There has been much hype about big data analytics – a collection of technologies, including the Hadoop distributed file system, NoSQL databases, and machine learning tools. One study estimated that it can generate hundreds of billions of dollars of value across industries [1]. Another study reported that 75 of telecom operators surveyed would implement big data initiatives by 2017 [2]. Every operator is seeking new ways to increase operational efficiency and marketing effectiveness by leveraging big data technologies. But the question is how does big data analytics differ from prior arts such as data warehousing and statistical methods, in terms of the capabilities of uncovering insights from large volume of datasets? What are the compelling use cases in telecom, and what are the challenges? This paper provides a retrospect on how telecom operators have been striving, before the era of big data, to analyze large volumes of data in order to support their business and operation. We then examine the driving forces of big data analytics in the telecom domain and the benefits it offers. Finally we provide example use cases of big data analytics and the associated challenges, with the hope to inspire new research ideas that can eventually benefit the practice of the telecommunication industry.
The Skeleton In The Cognitive Map

Experts seem to find routes in complex environments by finding a connection from the source to a “skeleton” of major paths, then moving within the skeleton to the neighborhood of the destination, making a final connection to the destination. The authors present a computational hypothesis that describes the skeleton as emerging from the interaction of three factors: (a) The topological map is represented as a bipartite graph of places and paths, where a path is a one-dimensional ordered set of places; (b) a traveler incrementally accumulates topological relationships, including the relation of a place to a path serving as a dividing boundary separating two regions; and (c) the wayfinding algorithm prefers paths rich in boundary relations so they are likely to acquire more boundary relations. This positive-feedback loop leads to an oligarchy of paths rich in boundary relations. The authors present preliminary computational and empirical tests for this hypothesis, and provide initial results.
Adaptive sliding mode controller design for a supercavitating vehicle

Supercavitating vehicles have special characteristics from traditional underwater vehicles because of supercavitation. The motion of the vehicle tends to be unstable, and the dynamics of it is nonlinear and strongly coupled. Due to the time-varying factors, delay-dependent behavior and unmodeled dynamics of system, a simplified model is developed. For the supercavitating vehicle with the mismatched uncertainties, continuous sliding mode controller is designed, with an adaptive technology which is used to estimate the unknown upper bound of mismatched uncertainties. Meanwhile, upper bound of parameter uncertainties is not required. Simulation results show the effectiveness of the controller designed in the paper.
Ecient Parsing for Bilexical Context-free Grammars and Head Automaton Grammars

Several recent stochastic parsers use bilexical grammars, where each word type idiosyncratically prefers particular complements with particular head words. We present O(n) parsing algorithms for two bilexical formalisms, improving the prior upper bounds of O(n). For a common special case that was known to allow O(n) parsing (Eisner, 1997), we present an O(n) algorithm with an improved grammar constant.
A unified view of TD algorithms, introducing Full-gradient TD and Equi-gradient descent TD

This paper addresses policy evaluation in MDP. It provides a unified view of algorithms such as TD(λ), LSTD(λ), iLSTD, and residualgradient TD. We assert that they all consist of minimizing a gradient function and differ in the form of this function and their means of minimizing it. Building on this unified view, two new schemes are introduced: Full-gradient TD which uses a generalization of the principle introduced in iLSTD, and EGD TD which reduces the gradient by successive equigradient descents. These three algorithms share the worthy property of using much more efficiently the samples than TD, while keeping the good properties of gradient descent schemes. 1 The policy evaluation problem A Markov Decision Process (MDP) [1] describes a dynamical system in which an agent has to learn a behavior so as to reach a given goal, in an optimal way. In this paper, the state of the system s ∈ S may be either discrete, or continuous. The agent applies an action u ∈ U at each time step t ∈ N . This drives the system to a state s′ = u(s) at the next time step, where u is generally nondeterministic. A reward r ∈ R ⊂ R is associated to each transition. A policy π defines the behavior of the agent on the system: it is a mapping from S to U . One objective is to find a policy that maximizes the rewards. To this end, we need to evaluate the performance of any policy, and define its value function v:
Privacy Mechanisms for Drones : Perceptions of Drone Controllers and Bystanders in the

Drones can enable innovative applications but also raise heightened privacy concerns such as surveillance and stalking. To mitigate these concerns, various technology-based and policy-based mechanisms have been proposed. However, most of these mechanisms are voluntary. Therefore, it is unclear how drone controllers and bystanders perceive these mechanisms and whether people intend to adopt them. We report results from two rounds of online survey with 169 drone controllers and 717 bystanders. When considering individual mechanisms, drone owner registration and face blurring received most support from both controllers and bystanders. Under specific drone usage scenarios, our respondents suggested using multiple mechanisms together as they may improve different aspects of privacy. Our results also uncover a sense of distrust between controllers and bystanders. We outline a set of important questions for future privacy designs and policies for drones. Implications for privacy design: Besides the promising results on face blurring, future designs should further explore ways to engender trust between drone controllers and bystanders. These may include ways that have helped companies to build consumer trust such as adopting fair information practices and presenting privacy policies as well as ways to improve interpersonal trust such as providing transparency in decision-making (e.g., why use drones to take pictures) and holding people accountable. We also found that while bystanders valued their privacy, controllers were also concerned about protecting their own privacy. For instance, when considering mechanisms such as owner registration, many controllers did not want bystanders to know their information. This suggests future designs and policies for drones should strike a good balance between the interests (e.g., privacy) of both controllers and bystanders. Implications for public policy: Many bystander respondents considered these privacy mechanisms ineffective because of their voluntary nature. They suggested making some of these mechanisms (e.g., no-fly-zone) required by laws or enforced automatically via technical means (e.g., implementing in firmware).
Economic Aspects of Bankruptcy and Restructuring in Bankruptcy

Izvadak iz ocjene znanstvenog doprinosa doktorske disertacije: Znanstveni doprinos doktorske disertacije Domagoja Sajtera sastoji se u: 1. interdisciplinarnosti, odnosno dubinskoj integraciji polja ekonomije i prava na podrucju stecajeva, jer je autor prisao objektu istraživanja sa nove, drugacije pozicije, te rasvijetlio brojna pitanja koja se ticu stecajeva sa aspekta ekonomske znanosti, 2. sirokoj, cjelovitoj, i potpunoj analizi postojece domace i strane literature, 3. vrlo detaljnom opisu postojeceg stecajnog sustava u Republici Hrvatskoj, zajedno sa brojnim prijedlozima za njegovo moguce unaprjeđenje, 4. analizi legislative i prakse Europske unije na podrucju stecajeva, 5. provedenom istraživanju izvrsenom na temelju prikupljenih podataka iz stecajnih pisarnica trgovackih svih sudova u Republici Hrvatskoj, 6. provedenom istraživanju izvrsenom na temelju prikupljenih podataka iz ankete i intervjua najcescih sudionika stecajnih procesa u Republici Hrvatskoj, 7. provedenom istraživanju izvrsenom na temelju baze podataka iz sudskog registra trgovackih subjekata u Republici Hrvatskoj, 8. ekonometrijskom istraživanju baze podataka financijskih izvjesca trgovackih drustava sa sjedistem u istocnoj Hrvatskoj uporabom metoda visedimenzionalnih skala, logit modela, i diskriminacijske analize, cime je subjektima u praksi dao primjenjive alate za procjenu rizika otvaranja stecaja, i cime je ostvario konkretan i stvaran doprinos prosirenju spektra mogucnosti regionalnog razvoja, te boljem razumijevanju fenomena stecajeva u Republici Hrvatskoj, i 9. sintezi svih navedenih istraživackih procesa u jedinstven, koncizan, i potpun rad.