Miracle-dz/UniFAR-FTUs huggingface dataset:
An efficient, model-based CPU-GPU heterogeneous FFT library

General-purpose computing on graphics processing units (GPGPU) is becoming popular in HPC because of its high peak performance. However, in spite of the potential performance improvements as well as recent promising results in scientific computing applications, its real performance is not necessarily higher than that of the current high-performance CPUs, especially with recent trends towards increasing the number of cores on a single die. This is because the GPU performance can be severely limited by such restrictions as memory size and bandwidth and programming using graphics-specific APIs. To overcome this problem, we propose a model-based, adaptive library for 2D FFT that automatically achieves optimal performance using available heterogeneous CPU-GPU computing resources. To find optimal load distribution ratios between CPUs and GPUs, we construct a performance model that captures the respective contributions of CPU vs. GPU, and predicts the total execution time of 2D-FFT for arbitrary problem sizes and load distribution. The performance model divides the FFT computation into several small sub steps, and predicts the execution time of each step using profiling results. Preliminary evaluation with our prototype shows that the performance model can predict the execution time of problem sizes that are 16 times as large as the profile runs with less than 20% error, and that the predicted optimal load distribution ratios have less than 1% error. We show that the resulting performance improvement using both CPUs and GPUs can be as high as 50% compared to using either a CPU core or a GPU.
Robust Nonparametric Cyclic Correlation-Based Spectrum Sensing for Cognitive Radio

Cognitive radios sense the radio spectrum in order to find underutilized spectrum and then exploit it in an agile manner. Spectrum sensing has to be performed reliably in challenging propagation environments characterized by shadowing and fading effects as well as heavy-tailed noise distributions. In this paper, a robust computationally efficient nonparametric cyclic correlation estimator based on the multivariate (spatial) sign function is proposed. Nonparametric statistics provide additional robustness against heavy-tailed noise and when the noise statistics are not fully known. Asymptotic distribution of the spatial sign cyclic correlation estimator under the null hypothesis is established. Tests using constraint on false alarm rate are derived based on the estimated spatial sign cyclic correlation for single-user and collaborative spectrum sensing by multiple secondary users. Theoretical justification for detecting cyclostationary signals using the spatial sign cyclic correlation is provided. A sequential detection scheme for reducing the average detection time is proposed. Simulation experiments and theoretical results comparing the proposed method with cyclostationary spectrum sensing methods employing the conventional cyclic correlation estimator are presented. Simulations demonstrate the reliable and highly robust performance of the proposed nonparametric spectrum sensing method in both Gaussian and non-Gaussian noise environments.
SDN-based Trusted Path Control

Security of sensitive data in the network is a key issue in a world where such sensitive data can easily be transferred between different servers and locations (e.g., in networked clouds). In this context, there is a particular need to control the path followed by the data when they move across the cloud (e.g., to avoid crossing -even encrypted- un-trusted nodes or areas). In this paper we proposed therefore a new approach which aims to leverage the programmability offered by the SDN technology in order to enforce a trusted path for the transfer of sensitive data in the network. Given a policy related to the sensitive data (e.g., the data should not cross a given area), our approach allows sending this policy to an extended SDN controller (called Trusted Path Controller) which automatically enforces this policy in the SDN network. Two architectures have been investigated: the Out-of-Band architecture (the policy being sent to the Trusted Path Controller via a Web Service interface) and the In-Band architecture (the policy being sent to the Trusted Path Controller via a dedicated “signaling packet”). These two architectures have been implemented in a SDN controller. Experimentations and evaluations have also been performed on a test-bed of SDN switches which allow showing the feasibility of this approach as well as its performances.
Sesamin Ameliorates High-Fat Diet–Induced Dyslipidemia and Kidney Injury by Reducing Oxidative Stress

The study explored the protective effect of sesamin against lipid-induced renal injury and hyperlipidemia in a rat model. An animal model of hyperlipidemia was established in Sprague-Dawley rats. Fifty-five adult Sprague-Dawley rats were divided into five groups. The control group was fed a standard diet, while the other four groups were fed a high-fat diet for 5 weeks to induce hyperlipidemia. Three groups received oral sesamin in doses of 40, 80, or 160 mg/(kg·day). Seven weeks later, the blood lipids, renal function, antioxidant enzyme activities, and hyperoxide levels in kidney tissues were measured. The renal pathological changes and expression levels of collagen type IV (Col-IV) and α-smooth muscle actin (α-SMA) were analyzed. The administration of sesamin improved the serum total cholesterol, triglyceride, low-density lipoprotein cholesterol, apolipoprotein-B, oxidized-low-density lipoprotein, and serum creatinine levels in hyperlipidemic rats, while it increased the high-density lipoprotein cholesterol and apolipoprotein-A levels. Sesamin reduced the excretion of 24-h urinary protein and urinary albumin and downregulated α-SMA and Col-IV expression. Moreover, sesamin ameliorated the superoxide dismutase activity and reduced malondialdehyde levels in kidney tissue. Sesamin could mediate lipid metabolism and ameliorate renal injury caused by lipid metabolism disorders in a rat model of hyperlipidemia.
Graphics Recognition in PDF documents

Much of the work on graphics recognition for raster-based input focuses on accurate and rapid discovery of primitives such as lines, arrowheads, and circles. Some of the work goes further to discover higher-level objects such as circuit elements, pie-chart components, and architectural components. Some systems work to discover even higher levels of organization. This paper focuses on graphics recognition of figures in vectorbased PDF documents. The first stage consists of extracting the graphic and text primitives corresponding to figures. The mapping from PDF to the rendered page can be complex, so an interpreter was constructed to translate the PDF content into a set of self-contained graphics and text objects, freed from the intricacies of the original PDF file. The second stage consists of discovering simple graphics entities which we call graphemes, the simplest being a pair of primitive graphic objects satisfying certain geometric constraints. The third stage uses machine learning to classify figures using grapheme statistics as descriptive attributes. Figure recognition can then be accomplished by applying a classifier so trained to the attribute set of a figure to be recognized (classified). The system is implemented in Java. In the study reported here, a boostingbased learner (LogitBoost in the Weka toolkit) was able to achieve 100% classification accuracy in hold-outone training/testing using 16 grapheme types extracted from 36 diagrammatic figures from BioMed Central research papers. The approach can readily be adapted to raster graphics recognition; once primitives are found, graphemes can be constructed from them and used in the learning-based recognition and classification system.
Transformation-aware Exploit Generation using a HI-CFG

Abstract : A common task for security analysts is to determine whether potentially unsafe code constructs (as found by static analysis or code review) can be triggered by an attacker-controlled input to the program under analysis. We refer to this problem as proof-of-concept (POC) exploit generation. Exploit generation is challenging to automate because it requires precise reasoning across a large code base; in practice it is usually a manual task. An intuitive approach to exploit generation is to break down a program's relevant computation into a sequence of transformations that map an input value into the value that can trigger an exploit. We automate this intuition by describing an approach to discover the buffer structure (the chain of buffers used between transformations) of a program, and use this structure to construct an exploit input by inverting one transformation at a time. We propose a new program representation, a hybrid information- and control-flow graph (HI-CFG), and give algorithms to build a HI-CFG from instruction traces. We then describe how to guide program exploration using symbolic execution to efficiently search for transformation pre-images. We implement our techniques in a tool that operates on applications in x86 binary form. In two case studies we discuss how our tool creates POC exploits for (1) a vulnerability in a PDF rendering library that is reachable through multiple different transformation stages and (2) a vulnerability in the processing stage of a specific document format in AbiWord.
Chocs d'offre et optimalité de la politique monétaire dans la zone euro

Cet article evalue les performances de la politique monetaire dans la zone euro en presence de chocs d’offre. A partir d’un modele var structurel, nous determinons les reponses du produit, de l’inflation, de la part du travail et du taux d’interet nominal a un choc d’offre. Nous developpons ensuite un modele dsge avec rigidites nominales et politique monetaire optimale. Ce modele est estime et teste sur la base de sa capacite a reproduire les reponses estimees a l’aide du modele var. Les estimations suggerent les bonnes performances de la politique monetaire en presence de ces chocs.
Stochastic undersampling steepens auditory threshold/duration functions: implications for understanding auditory deafferentation and aging

It has long been known that some listeners experience hearing difficulties out of proportion with their audiometric losses. Notably, some older adults as well as auditory neuropathy patients have temporal-processing and speech-in-noise intelligibility deficits not accountable for by elevated audiometric thresholds. The study of these hearing deficits has been revitalized by recent studies that show that auditory deafferentation comes with aging and can occur even in the absence of an audiometric loss. The present study builds on the stochastic undersampling principle proposed by Lopez-Poveda and Barrios (2013) to account for the perceptual effects of auditory deafferentation. Auditory threshold/duration functions were measured for broadband noises that were stochastically undersampled to various different degrees. Stimuli with and without undersampling were equated for overall energy in order to focus on the changes that undersampling elicited on the stimulus waveforms, and not on its effects on the overall stimulus energy. Stochastic undersampling impaired the detection of short sounds (<20 ms). The detection of long sounds (>50 ms) did not change or improved, depending on the degree of undersampling. The results for short sounds show that stochastic undersampling, and hence presumably deafferentation, can account for the steeper threshold/duration functions observed in auditory neuropathy patients and older adults with (near) normal audiometry. This suggests that deafferentation might be diagnosed using pure-tone audiometry with short tones. It further suggests that the auditory system of audiometrically normal older listeners might not be “slower than normal”, as is commonly thought, but simply less well afferented. Finally, the results for both short and long sounds support the probabilistic theories of detectability that challenge the idea that auditory threshold occurs by integration of sound energy over time.
KSGM: Keynode-driven Scalable Graph Matching

Understanding how a given pair of graphs align with each other (also known as the graph matching problem) is a critical task in many search, classification, and analysis applications. Unfortunately, the problem of maximum common subgraph isomorphism between two graphs is a well known NP-hard problem, rendering it impractical to search for exact graph alignments. While there are several heuristics, most of these analyze and encode global and local structural information for every node of the graph and then rank pairs of nodes across the two graphs based on their structural similarities. Moreover, many algorithms involve a post-processing (or refinement) step which aims to improve the initial matching accuracy. In this paper we note that the expensive refinement phase of graph matching algorithms is not practical in any application where scalability is critical. It is also impractical to seek structural similarity between all pairs of nodes. We argue that a more practical and scalable solution is to seek structural keynodes of the input graphs that can be used to limit the amount of time needed to search for alignments. Naturally, these keynodes need to be selected carefully to prevent any degradations in accuracy during the alignment process. Given this motivation, in this paper, we first present a structural keynode extraction (SKE) algorithm and then use structural keynodes obtained during off-line processing for keynode-driven scalable graph matching (KSGM). Experiments show that the proposed keynode-driven scalable graph matching algorithms produce alignments that are as accurate as (or better than) the state-of-the-art algorithms, with significantly faster online executions.
Efficient algorithm and implementation of Montgomery Multiplication Using Reconfigurable Hardware

In this paper we are presenting an efficient algorithm and architecture for Montgomery multiplication. This algorithm is derived from a Scalable high radix Montgomery Multiplication algorithm presented and proved to be correct in [1]. Radix-4 is widely used in arithmetic, and so we are presenting a radix-4 based scalable algorithm. Scalable means that a fixed-area multiplication module can handle operands of any size. In this design we applied a pipelining methodology to utilize the concurrency in Montgomery Multiplication operation. In order to reduce the delay a design for radix-8 was presented in 2001. Although on one side this design reduces the delay significantly, on the other side the design area increases. In addition to exploring reconfigurable hardware techniques to implement the Montgomery Multiplier under discussion we explore other techniques to get around the area problems of a radix-8 design. The wordby-word algorithm used in the multiplier gives designer the freedom to select the level of parallelism according to the available area. Experimental results are shown to demonstrate that the proposed radix-4 Montgomery Multiplier design has better area/performance tradeoff than previous radix-2 and 8 scalable designs. Keywords—Modular Multiplier, Scalable Architecture, Cryptography, Montgomery Multiplication.
Severe Wound Infection with Photobacterium damselae ssp. damselae and Vibrio harveyi, following a Laceration Injury in Marine Environment: A Case Report and Review of the Literature

Marine microorganisms are uncommon etiologies of skin and skin structure infections, that is, wound infections. We report a case of severe wound infection, caused by the marine Photobacterium damselae (Vibrionaceae), in a 64-year-old male patient, returning from Australia. The isolate tested positive for pPHDD1, a plasmid conferring high-level virulence. Furthermore, the wound was coinfected with Vibrio harveyi, a halophile bacterium, which has never been reported from human infections before. Identification was achieved by use of Matrix-Assisted Laser Desorption-Ionization Time of Flight Mass Spectrometry (MALDI-TOF) and confirmed by 16S rDNA sequencing. Data retrieval from bibliography was complicated since P. damselae has been renamed often with a number of synonyms present in the literature: Photobacterium damsela, Vibrio damselae, Vibrio damsela, Pasteurella damselae, and Listonella damsela. With all synonyms used as query terms, a literature search provided less than 20 cases published worldwide. A majority of those cases presenting as severe wound infection are even fatal following progression into necrotizing fasciitis. Management with daily wound dressing and antibiotic therapy (ofloxacin empirically, followed by doxycycline after availability of microbiology) led in the reported case to a favorable outcome, which seems to be, however, the exception based on a review of the available literature.
Transform domain approach for sequence design and its applications

Many communication and radar systems necessitate the use of sequences with desired autocorrelation (AC) and cross-correlation (CC) properties. This paper presents a systematic method based on the transform domain characterization of the AC and CC constraints to generate new families of sequences that meet the requirements. We demonstrate that some existing families can easily be generated by our approach. Our approach, however, renders new families of sequences with less constraints. The proposed approach is elementary and can easily be extended to synthesize two-dimensional arrays or even higher dimensional waveforms that possess the desired multidimensional correlation properties. A preamble structure based on our new sequence family is suggested and performance of frequency offset and channel estimation algorithms for a multiantenna orthogonal frequency-division multiplexing (OFDM) system that uses such a preamble is given.
An Integrated Open Framework for Heterogeneous MPSoC Design Space Exploration

In recent years, increasing manufacturing density has allowed the development of multi-processor systems-on-chip (MPSoCs). Application-specific instruction set processors (ASIPs) stand out as one of the most efficient design paradigms and could be especially effective as SoC computing engines. However, multiple hurdles which are hindering the productivity of SoC designers and researchers must be solved first. Among them, the difficulty of thoroughly exploring the design space by simultaneously sweeping axes like processing elements, memory hierarchies and chip interconnect fabrics. We tackle this challenge by proposing an integrated approach where state-of-the-art platform modeling infrastructures, at the IP core level and at the system level, meet to provide the designer with maximum openness and flexibility in terms of design space exploration
Union Centralization among Advanced Industrial Societies: An Empirical Study

An electronic transmission controller for determining the shift points of a powered vehicle with a plurality of forward and reverse gears and a neutral gear shift position wherein a throttle setting signal, a vehicle speed signal and a gear range select signal are monitored and processed to produce optimum shift points, gear change commands, forward-reverse shift commands and a throttle inhibit signal to facilitate downshifting of the transmission. With the exception of the throttle transducer, the monitoring and processing means are primarily digital.
RESeED: A Tool for Regular Expression Search over Encrypted Data in Cloud Storage

We present Reseed, a tool that provides user-transparent and Cloud-agnostic regular expression search over encrypted data without requiring trust in the Cloud, or changes to Cloud infrastructure. Upon receiving a search query, Reseed translates it to a finite automata and analyzes efficient and secure representations of the data before asking the Cloud to download the matching encrypted files. We demonstrate and evaluate a working prototype of Reseed and show the scalability and correctness of our approach using data from arXiv.org. For more details see our Technical Report.
Self-efficacy using fuzzy control for long-term communication in robot-assisted language learning

Recently, language education has a great demand from elementary school to adults. Robots are used as teaching assistants in Robot-Assisted Language Learning. It is very effective to use robots for language education. However, the robots may have some problems. One of the problems is to get bored when interacting with robots. This paper deals with this issue by using a method based on social cognitive theory. We discuss the role of robots based on mutual learning in language education. Next, we explain the concept of self-efficacy for evaluating the learning condition of robots. We propose a method to express self-efficacy using fuzzy control. The essence of the proposed method is to adapt to human's state. The experimental results show the effectiveness of the proposed method for long-term communication between a human and a robot.
An Experiment of Lexical-Semantic Tagging of an Italian Corpus

The availability of semantically tagged corpora is becoming a very important and urgent need for training and evaluation within a large number of applications but also they are the natural application and accompaniment of semantic lexicons of which they constitute both a useful testbed to evaluate their adequacy and a repository of corpus examples for the attested senses. It is therefore essential that sound criteria are defined for their construction and a specific methodology is set up for the treatment of various semantic phenomena relevant to this level of description. In this paper we present some observations and results concerning an experiment of manual lexical-semantic tagging of a small Italian corpus performed within the framework of the ELSNET project. The ELSNET experimental project has to be considered as a feasibility study. It is part of a preparatory and training phase, started with the Romanseval/Senseval experiment (Calzolari et al., 1998), and ending up with the lexical-semantic annotation of larger quantities of semantically annotated texts such as the syntacticsemantic Treebank which is going to be annotated within an Italian National Project (SI-TAL). Indeed, the results of the ELSNET experiment have been of utmost importance for the definition of the technical guidelines for the lexical-semantic level of description of the Treebank.