Miracle-dz/UniFAR-FTUs huggingface dataset:
Concept Checking: Binding Parametric Polymorphism in C++

Generic programming in C++ is characterized by the use of template parameters to represent abstract data types (or “concepts”). However, the C++ language itself does not provide a mechanism for explicitly handling concepts. As a result, it can be difficult to insure that a concrete type meets the requirements of the concept it is supposed to represent. Error messages resulting from incorrect use of a concrete type can be particularly difficult to decipher. In this paper we present techniques to check parameters in generic C++ libraries. Our techniques use standard C++ and introduce no run-time overhead.
Maximizing Heterogeneous Processor Performance Under Power Constraints

Heterogeneous processors (e.g., ARM’s big.LITTLE) improve performance in power-constrained environments by executing applications on the ‘little’ low-power core and move them to the ‘big’ high-performance core when there is available power budget. The total time spent on the big core depends on the rate at which the application dissipates the available power budget. When applications with different big-core power consumption characteristics concurrently execute on a heterogeneous processor, it is best to give a larger share of the power budget to applications that can run longer on the big core, and a smaller share to applications that run for a very short duration on the big core. This article investigates mechanisms to manage the available power budget on power-constrained heterogeneous processors. We show that existing proposals that schedule applications onto a big core based on various performance metrics are not high performing, as these strategies do not optimize over an entire power period and are unaware of the applications’ power/performance characteristics. We use linear programming to design the DPDP power management technique, which guarantees optimal performance on heterogeneous processors. We mathematically derive a metric (Delta Performance by Delta Power) that takes into account the power/performance characteristics of each running application and allows our power-management technique to decide how best to distribute the available power budget among the co-running applications at minimal overhead. Our evaluations with a 4-core heterogeneous processor consisting of big.LITTLE pairs show that DPDP improves performance by 16% on average and up to 40% compared to a strategy that globally and greedily optimizes the power budget. We also show that DPDP outperforms existing heterogeneous scheduling policies that use performance metrics to decide how best to schedule applications on the big core.
Study on a new topology of power electronic transformer

Considering the development of electric vehicle (EV), a new topology of power electronic transformer (PET) was proposed firstly. The proposed topology consists of three conversion stages:(1) the input stage adopts MMC structure; (2) the dc/dc converters in isolation stage adopt the connection mode of input serial output parallel;(3) the output stage includes an inverter module and switchable power modules. The switchable power module can both output dc and ac. By changing the output of the switchable power module, the capacity of ac and dc can switch to use. This topology along with ac/dc capacity switching technology has advantages of save PET capacity and improving capacity utilization. Then the control strategy of proposed topology was introduced. Finally, a simulation model was built in PSCAD simulation environment. Simulation results show that the proposed topology and its control strategy are feasible.
Parallelism profiling and wall-time prediction for multi-threaded applications

A detailed and accurate characterization of the parallelism of applications is essential for predicting their wall-time on different platforms, both for an application running in isolation and for a set of consolidated applications executing on the same platform. However, prevailing profilers are often based on sampling and do not provide exact information on the parallelism of the profiled application. In this paper we present a novel profiler that logs all thread scheduling activities within the operating system kernel. These logs enable us to accurately characterize applications' parallelism on a given platform by computing the number of threads that are active at each moment. We also present a simple mathematical prediction model to estimate wall-time for program execution on a k2-core machine using profiles collected using a k1-core machine (of the same architecture and running at the same clock speed). We use our profiler to assess the parallelism of several CPU-bound DaCapo benchmarks and evaluate the accuracy of our prediction model.
Lightweight Temporal Description Logics with Rigid Roles and Restricted TBoxes

We study temporal description logics (TDLs) based on the branching-time temporal logic CTL and the lightweight DL EL in the presence of rigid roles and restricted TBoxes. While TDLs designed in this way are known to be inherently nonelementary or even undecidable over general TBoxes, there is hope for a better computational behaviour over acyclic or empty TBoxes. We begin by showing that the basic DL ALC combined with CTL in the described way is indeed decidable, but still inherently nonelementary. As our main contribution, we identify several TDLs of elementary complexity, obtained by combining EL with CTL fragments that allow only restricted sets of temporal operators. We obtain upper complexity bounds ranging from PTIME to CONEXPTIME and mostly tight lower bounds. This contrasts the fact that the respective ALC variants are already inherently nonelementary.
Multi-stability and non-linearity of large-scale cortical rhythms

Synopsis: Electroencaphalograpic (EEG) data arises from electrical currents averaged over large populations of neocortical neurons. The basic statistical and dynamical properties of EEG data can hence provide vital insights into the nature of largescale neural activity and inform fundamental questions in computational neuroscience. I review two recent studies of EEG data one acquired at rest and the other following sensory perturbations that evidence a surprising richness of complexity and nonlinearity. These findings may have important implications for computational accounts of human cognition.
Behavioral and EEG Evidence for Auditory Memory Suppression

The neural basis of motivated forgetting using the Think/No-Think (TNT) paradigm is receiving increased attention with a particular focus on the mechanisms that enable memory suppression. However, most TNT studies have been limited to the visual domain. To assess whether and to what extent direct memory suppression extends across sensory modalities, we examined behavioral and electroencephalographic (EEG) effects of auditory TNT in healthy young adults by adapting the TNT paradigm to the auditory modality. Behaviorally, suppression of memory strength was indexed by prolonged response time (RTs) during the retrieval of subsequently remembered No-Think words. We examined task-related EEG activity of both attempted memory retrieval and inhibition of a previously learned target word during the presentation of its paired associate. Event-related EEG responses revealed two main findings: (1) a centralized Think > No-Think positivity during auditory word presentation (from approximately 0–500 ms); and (2) a sustained Think positivity over parietal electrodes beginning at approximately 600 ms reflecting the memory retrieval effect which was significantly reduced for No-Think words. In addition, word-locked theta (4–8 Hz) power was initially greater for No-Think compared to Think during auditory word presentation over fronto-central electrodes. This was followed by a posterior theta increase indexing successful memory retrieval in the Think condition. The observed event-related potential pattern and theta power analysis are similar to that reported in visual TNT studies and support a modality non-specific mechanism for memory inhibition. The EEG data also provide evidence supporting differing roles and time courses of frontal and parietal regions in the flexible control of auditory memory.
Hardware Implementations for the ISO/IEC 18033-4:2005 Standard for Stream Ciphers

In this paper the FPGA implementations for four stream ciphers are presented. The two stream ciphers, MUGI and SNOW 2.0 are recently adopted by the International Organization for Standardization ISO/IEC 18033-4:2005 standard. The other two stream ciphers, MICKEY 128 and TRIVIUM have been submitted and are under consideration for the eSTREAM, the ECRYPT (European Network of Excellence for Cryptology) Stream Cipher project. All ciphers were coded using VHDL language. For the hardware implementation, an FPGA device was used. The proposed implementations achieve throughputs range from 166 Mbps for MICKEY 128 to 6080 Mbps for MUGI.
A Comparative of Goal-oriented Approaches to Modelling Requirements for Collaborative Systems

A collaborative system is a software allowing several users to work together and carry out collaboration, communication and coordination tasks. To perform these tasks, the users have to be aware of other user’s actions, usually by means of a set of awareness techniques. However, when these systems have to be specified for development severe difficulties emerge to describe the requirements associated to these special functionalities, usually considered non-functional requirements. Therefore, the selection and use of proper requirements engineering techniques becomes a challenging and important decision. In this paper three Goal-Oriented approaches, namely NFR framework, i* and KAOS, are evaluated in order to determine which one is the most suitable to deal with this problem of requirements specification in collaborative systems.
The Research of SVM Introjecting Fuzzy Theory in Image Affective Recognition

This paper introduces FSVM, which introjects fuzzy theory to SVM, achieves a classification system which classifies image layer by layer to affective semantic level by FSVM, and proposes one kind of image affective semantics classification method. The difficulty is to establish a mapping from image features to image affective semantics and how to select fitting membership function to test image semantic class. The experimental result shows that the system is simple, fast, effective, and so on, therefore our system is proved to be successful in promoting the image semantic classification to affective semantic level.
Edge detection techniques using fuzzy logic

This article reviews and discusses the fuzzy system implementation as an efficient edges detector for the image. Authors that suggested this method used different ways to feed the fuzzy system and different membership functions that depend on the characteristics of the data input. Some techniques feed the data directly with a 2×2 or 3×3 window others process the data with filters before feeding the fuzzy system. The analysis to the input method revealed that fuzzy system can be coined according to their feeding method to Sliding Window and Preprocessing Kernels fuzzy systems. The article is organized according to this naming and the method of each technique has been discussed. MATLAB codes had been implemented to compare the performance of each method on the same image.
Wireless Cloud Networks for the Factory of Things: Connectivity Modeling and Layout Design

Large-scale adoption of dense cloud-based wireless network technologies in industrial plants is mandatorily paired with the development of methods and tools for connectivity prediction and deployment validation. Layout design procedures must be able to certify the quality (or reliability) of network information flow in industrial scenarios characterized by harsh propagation environments. In addition, these procedures must account for possibly coexisting heterogeneous radio access technologies as part of the Internet of Things (IoT) paradigm, easily allow post-layout validation steps, and be integrated by industry-standard CAD-based planning systems. The goal of the paper is to set the fundamentals for comprehensive industry-standard methods and procedures supporting plant designer during wireless coverage prediction, virtual network deployment, and post-layout verification. The proposed methods carry out the prediction of radio signal coverage considering typical industrial environments characterized by highly dense building blockage. They also provide a design framework to properly deploy the wireless infrastructure in interference-limited radio access scenarios. In addition, the model can be effectively used to certify the quality of machine-type communication by considering also imperfect descriptions of the network layout. The design procedures are corroborated by experimental measurements in an oil refinery site [modeled by three-dimensional (3-D) CAD] using industry-standard ISA IEC 62734 devices operating at 2.4 GHz. A graph-theoretic approach to node deployment is discussed by focusing on practical case studies, and also by looking at fundamental connectivity properties for random deployments.
Image segmentation techniques for stem cell tracking

To grow stem cells in vitro is an important task in regenerative medicine. Cell motility that can be derived by cell tracking is a useful index to evaluate the viability and stemness of stem cells. The precision of cell tracking is highly dependent on correct detection of the cell centroids, which are usually determined by cell segmentation process. In this study, a cell segmentation method combining double-thresholding and disk-based reconstruction is proposed to solve the problems arising from shape deformation and uneven illumination during cell culture. The qualitative and quantitative comparisons show that the proposed segmentation method increases accuracy in detection the cell centroid.
Comparison of hand p-Adaptations for Spectral Difference Methods

This paper applies some of the current mesh adaptation approaches to the high-order Spectral Difference (SD) method and investigates their performance on modeling inviscid steady flow. In particular, an entropy-based adjoint approach is used as the adaptation criterion. Both h-, p-refinement and p-coarsening are implemented. A mortar element method is used for treatment of non-conforming interfaces between grids with different sizes or orders. The performance is assessed by the accuracy of certain solution outputs (e.g. the drag coefficient) and the accuracy of capturing local flow features (e.g. shocks). While flow discontinuities are understandably better resolved with h-refinement, it is found that in regions of smooth flow, p-refinement offers a higher accuracy with the same number of degrees of freedom.
Research on Data Structure and File Format for Water-Jet Tactile Display

Tactile device is used to display tactile data in image mode, which is normally received from a computer. In most cases, the original tactile picture is converted from the visual image, and it would be very convenient for saving and data conversion if tactile data was packaged in file format. In this paper, a file format is constructed for saving data in water-jet tactile, and a mapping algorithm is proposed between the RGB data in visual image and the physical stimulation factors in tactile image, including pressure, temperature and frequency. Experiments are designed to verify the validity of the algorithm, and results show that visual images can be transformed to the water-jet tactile image, can also be recovered from the tactile image correctly.
Real-time filtering on interest profiles in Twitter stream

The advent of Twitter has led to the ubiquitous information overload problem with a dramatic increase in the amount of tweets a user is exposed to. In this paper, we consider real-time tweet filtering with respect to users' interest profiles in public Twitter stream. While traditional filtering methods mainly focus on judging relevance of a document, we aim to retrieve relevant and novel documents to address the high redundancy of tweets. An unsupervised approach is proposed to model relevance between tweets and different profiles adaptively and a neural network language model is employed to learn semantic representation for tweets. Experiments on TREC 2015 dataset demonstrate the effectiveness of the proposed approach.
On infinite uniquely partitionable graphs and graph properties of finite character

A graph property is any nonempty isomorphism-closed class of simple (finite or infinite) graphs. A graph property P is of finite character if a graph G has a property P if and only if every finite induced subgraph of G has a property P . Let P1,P2, . ,Pn be graph properties of finite character, a graph G is said to be (uniquely) (P1,P2, . . . ,Pn)partitionable if there is an (exactly one) partition {V1, V2, . , Vn} of V (G) such that G[Vi] ∈ Pi for i = 1, 2, . , n. Let us denote by R = P1◦P2◦ · · · ◦Pn the class of all (P1,P2, . . . ,Pn)-partitionable graphs. A property R = P1◦P2◦ · · · ◦Pn, n ≥ 2 is said to be reducible. We prove that any reducible additive graph property R of finite character has a uniquely (P1,P2, . . . ,Pn)-partitionable countable generating graph. We also prove that for a reducible additive hereditary graph property R of finite character there exists a weakly universal countable graph if and only if each property Pi has a weakly universal graph. 242 J. Bucko and P. Mihok
Chapter 1 Spoken Language Input ( Taken from the Book : “ Survey of the state of the art in human language technology ” ) 1 . 1 Overview

Spoken language interfaces to computers is a topic that has lured and fascinated engineers and speech scientists alike for over five decades. For many, the ability to converse freely with a machine represents the ultimate challenge to our understanding of the production and perception processes involved in human speech communication. In addition to being a provocative topic, spoken language interfaces are fast becoming a necessity. In the near future, interactive networks will provide easy access to a wealth of information and services that will fundamentally affect how people work, play and conduct their daily affairs. Today, such networks are limited to people who can read and have access to computers—a relatively small part of the population, even in the most developed countries. Advances in human language technology are needed to enable the average citizen to communicate with networks using natural communication skills and everyday devices, such as telephones and televisions. Without fundamental advances in user-centered interfaces, a large portion of society will be prevented from participating in the age of information, resulting in further stratification of society and tragic loss of human potential.
The Converse Part of The Theorem for Quantum Hoeffding Bound

We prove the converse part of the theorem for quantum Hoeffding bound on the asymptotics of quantum hypothesis testing, essentially based on an argument developed by Nussbaum and Szkola in proving the converse part of the quantum Chernoff bound. Our result complements Hayashi's proof of the direct (achievability) part of the theorem, so that the quantum Hoeffding bound has now been established.
Image Analysis Based On Segmentation Algorithms.

Image segmentation is the process of partitioning a digital image into multiple segments. Segmentation is fundamental step in analyzing and understanding an image. In this paper, different segmentation algorithms are implemented. Watershed transform is region based segmentation technique. It changes your image into another image whose catchment basins are the objects you want to identify. Whereas, quadtree segmentation uses region splitting tool which allows to divide an image within a complete tree representation, including neighboring information . But both this algorithms causes over segmentation. Therefore, labeling watershed algorithm has been applied. Marker based watershed transform segments an image using internal and external markers. But, as the large number of regions are formed, hence seed region growing algorithm is used to solve the problem caused by marker based watershed transform.
Observationally-induced Algebras in Domain Theory

We investigate the observationally-induced free algebra approach for constructing computational monads in the categories of classical domain theory. Our investigation yields that the free algebra construction exists for all finitary algebraic signatures and computational prototypes. We furthermore investigate the classical powerdomain constructions in the observationally-induced approach. For the Hoare, Smyth and probabilistic powerdomain constructions we build on established results, showing that they can be recovered observationally-induced. However, the Plotkin powerdomain turns out to be more problematic. Here we show that with the obvious prototype algebra, Heckmanns algebra A, one does not get the classical Plotkin powerdomain.
Vehicular Ad-Hoc Networks : An Introduction to Privacy

an application of MANETs that allows for communication between road transport vehicles and promotes safety on roads. There are however situations that could cause harm to the vehicle and/or its occupants; vehicles could be tracked, followed or have their messages monitored. A method to protect the vehicle is to ensure it remains anonymous. This refers to privacy, i.e. hiding the vehicle's real identity. This paper provides an introduction to VANETs and puts into context authentication and privacy in VANETs. Reasons for why privacy and authentication are essential for a secure VANET are provided.
Composition of Estonian infants’ expressive lexicon according to the adaptation of CDI/Words and Gestures

The growth rate and the composition of expressive lexicon was studied in a sample of 903 infants between the age of 0;8 and 1;4 whose parents completed the Estonian adaptation of the MacArthur–Bates Communicative Development Inventory – Words and Gestures. As expected, older children had on average larger vocabularies compared to younger children. At the age of 1;4 the Estonian infants’ lexicon was smaller compared to the American-English children’s lexicon but larger than Italian and British-English infants’ vocabularies. The Estonian infants’ expressive lexicon has the same proportional distribution of semantic categories that other languages have been shown to have. On average, Estonian girls have larger vocabularies compared to boys. There are also some differences between boys and girls regarding the content of most frequently produced words. Results provide additional information about the rate of lexicon learning and proportional distribution of semantic categories in a language with rich morphology.
Separating Presentation and Content in MEI

Common Western music notation is traditionally organized on staves that can be grouped into systems. When multiple systems appear on a page, they are arranged from the top to the bottom of the page, similar to lines of words in a text document. Encoding music notation documents for printing requires this arrangement to be captured. However, in the music notation model proposed by the Music Encoding Initiative (MEI), the hierarchy of the XML sub-tree representing the music emphasizes the content rather than the layout. Since systems and pages do not coincide with the musical content, they are encoded in a secondary hierarchy that contains very limited information. In this paper, we present a complementary solution for augmenting the level of detail of the layout of musical documents; that is, the layout information can be encoded in a separate sub-tree with cross-references to other elements holding the musical content. The major advantage of the proposed solution is that it enables multiple layout descriptions, each describing a different visual instantiation of the same musical content.