Miracle-dz/UniFAR-FTUs huggingface dataset:
Built-In Test for Circuits with Scan Based on Reseeding of Multiple-Polynomial Linear Feedback Shift Registers

We propose a new scheme for built-in test (BIT) that uses multiple-polynomial linear feedback shift registers (MP-LFSR's). The same MP-LFSR that generates random patterns to cover easy to test faults is loaded with seeds to generate deterministic vectors for difficult to test faults. The seeds are obtained by solving systems of linear equations involving the seed variables for the positions where the test cubes have specified values. We demonstrate that MP-LFSR's produce sequences with significantly reduced probability of linear dependence compared to single polynomial LFSR's. We present a general method to determine the probability of encoding as a function of the number of specified bits in the test cube, the length of the LFSR and the number of polynomials. Theoretical analysis and experiments show that the probability of encoding a test cube with s specified bits in an s-stage LFSR with 16 polynomials is 1-10/sup -6/. We then present the new BIT scheme that allows for an efficient encoding of the entire test set. Here the seeds are grouped according to the polynomial they use and an implicit polynomial identification reduces the number of extra bits per seed to one bit. The paper also shows methods of processing the entire test set consisting of test cubes with varied number of specified bits. Experimental results show the tradeoffs between test data storage and test application time while maintaining complete fault coverage. >
An Integrated Hardware-Software Approach to Transactional Memory

Transactional memory has been proposed as a general and flexible way to allow programs to read and modify disparate primary-memory locations atomically as a single operation, much as a database transaction can atomically modify many records on disk. Hardware transactional memory supports atomicity through architectural means, whereas software transactional memory supports atomicity through languages, compilers, and libraries. Hardware transactional memory can be implemented quite easily with some modificaitons to the processor cache and cache controllers. However, this implementation imposes limitations on the size and length of transactions. On the other hand, software transactional memory does not suffer from these limitations but has a much higher overhead than hardware transactions. In this paper, I propose an integrated hardware-software implementation of transactional memory. The integrated approach gives us the best of both hardware and software transactions. It allows small and short transactions to run in hardware with very low overhead. In the common case, transactions are small and short so it is desirable to run them fast. On the other hand, large and long transactions run slower in software but are nevertheless possible and fully supported. Moreover, the high overhead is also amortized over the common case and thus does not have a significant penalty on overall performance.
Genetic Programming Produced Competitive Soccer Softbot Teams for RoboCup97

At RoboCup, teams of autonomous robots or software softbots compete in simulated soccer matches to demonstrate cooperative robotics techniques in a very difficult, real-time, noisy environment. At the IJCAI/RoboCup97 softbot competition, all entries but ours used human-crafted cooperative decision-making behaviors. We instead entered a softbot team whose high-level decision making behaviors had been entirely evolved using genetic programming. Our team won its first two games against human-crafted opponent teams, and received the RoboCup Scientific Challenge Award. This report discusses the issues we faced and the approach we took to use GP to evolve our robot soccer team for this difficult environment.
The B‐matrix must be rotated when correcting for subject motion in DTI data

To estimate diffusion tensor MRI (DTI) measures, such as fractional anisotropy and fiber orientation, reliably, a large number of diffusion‐encoded images is needed, preferably cardiac gated to reduce pulsation artifacts. However, the concomitant longer acquisition times increase the chances of subject motion adversely affecting the estimation of these measures. While correcting for motion artifacts improves the accuracy of DTI, an often overlooked step in realigning the images is to reorient the B‐matrix so that orientational information is correctly preserved. To the best of our knowledge, most research groups and software packages currently omit this reorientation step. Given the recent explosion of DTI applications including, for example, neurosurgical planning (in which errors can have drastic consequences), it is important to investigate the impact of neglecting to perform the B‐matrix reorientation. In this work, a systematic study to investigate the effect of neglecting to reorient the B‐matrix on DTI data during motion correction is presented. The consequences for diffusion fiber tractography are also discussed. Magn Reson Med, 61:1336–1349, 2009. © 2009 Wiley‐Liss, Inc.
A Column Generation Approach for Graph Coloring

We present a method for solving the independent set formulation of the graph coloring problem (where there is one variable for each independent set in the graph). We use a column generation method for implicit optimization of the linear program at each node of the branch-and-bound tree. This approach, while requiring the solution of a difficult subproblem as well as needing sophisticated branching rules, solves small to moderate size problems quickly. We have also implemented an exact graph coloring algorithm based on DSATUR for comparison. Implementation details and computational experience are presented.
Photometric study of the OB star clusters NGC 1502 and NGC 2169 and mass estimation of their members at the University Observatory Jena

In this work we present detailed photometric results of the trapezium like galactic nearby OB clusters NGC 1502 and NGC 2169 carried out at the University Observatory Jena. We determined absolute BVRI magnitudes of the mostly resolved components using Landolt standard stars. This multi colour photometry enables us to estimate spectral type and absorption as well as the masses of the components, which were not available for most of the cluster members in the literature so far, using models of stellar evolution. Furthermore, we investigated the optical spectrum of the components ADS 2984A and SZ Cam of the sextuple system in NGC 1502. Our spectra clearly confirm the multiplicity of these components, which is the first investigation of this kind at the University Observatory Jena (© 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)
Constraints on opacities from complex asteroseismology of B-type pulsators: the β Cephei star θ Ophiuchi

We present results of a comprehensive asteroseismic modelling of the β Cephei variable θ Ophiuchi. We call these studies complex asteroseismology because our goal is to reproduce both pulsational frequencies and corresponding values of a complex, non-adiabatic parameter, f, defined by the radiative flux perturbation. To this end, we apply the method of simultaneous determination of the spherical harmonic degree, l, of excited pulsational mode and the corresponding non-adiabatic f parameter from combined multicolour photometry and radial velocity data. Using both the OP and OPAL opacity data, we find a family of seismic models which reproduce the radial and dipole centroid mode frequencies, as well as the f parameter associated with the radial mode. Adding the non-adiabatic parameter to seismic modelling of the B-type main-sequence pulsators yields very strong constraints on stellar opacities. In particular, only with one source of opacities it is possible to agree the empirical values of f with their theoretical counterparts. Our results for θ Oph point substantially to preference for the OPAL data.
Perceptual classification of chromatic modulation

(article appeared in Visual Neuroscience (2004), 21, 283–289 Due to a production error, the second author affiliation is incorrectly cited. It should have read as follows: INSERM U371, Cerveau et Vision, IFR 19, Institut Fédératif des Neurosciences, Université Claude Bernard Lyon I, Bron France
Theory reconstruction: a representation learning view on predicate invention

With this positional paper we present a representation learning view on predicate invention. The intention of this proposal is to bridge the relational and deep learning communities on the problem of predicate invention. We propose a theory reconstruction approach, a formalism that extends autoencoder approach to representation learning to the relational settings. Our intention is to start a discussion to define a unifying framework for predicate invention and theory revision.
Classifying Malicious Thread Behavior in PaaS Web Services

Multitenant structure of PaaS cloud delivery model allows customers to share the platform resources in the cloud. However, this structure requires a strong security mechanism that isolates customer applications to prevent interference between different applications. In this paper, a malicious thread behavior detection framework using machine learning algorithms is proposed to classify whether user requests are malicious. The framework uses thread metrics of worker threads and N-Gram frequencies of operations as its features. Test results are evaluated on a real-life scenario using Random Forest, Adaboost and Bagging ensemble learning algorithms and evaluated using different accuracy metrics. It is found that the malicious request detection accuracy of the proposed system is 87.6%.
High temperature characterization of SiC-JFET and modelling

Silicon Carbide (SiC) is considered as the wide band gap semiconductor material that can presently compete with Silicon (Si) material for power switching devices. Compact circuit simulation models for SiC devices are of extreme importance for designing and analyzing converter circuit, in particular, if comparisons with Si devices should be performed. In this paper, three different kinds of Silicon Carbide JFET samples were characterized at temperatures up to 225degC. The characterization is based on the DC (Current - Voltage) characteristic measurements using a curve tracer and on the AC (Capacitance - Voltage) measurements using an impedance analyzer. We keep in mind to establish an analytical model that will be used in the design of a power converter.
Effects of Learning Styles and Interest on Concentration and Achievement of Students in Mobile Learning

Learning concentration deserves in-depth investigation in the field of mobile learning. Therefore, this study examined the interaction effects of learning styles and interest on the learning concentration and academic achievement of students who were asked to learn conceptual knowledge via their mobile phones in a classroom setting. A total of 92 Chinese college students majoring in education participated in the study. With the application of correlation analysis, regression analysis, and analysis of variance (i.e., one, two, and three way), four main findings were obtained: (a) Interest is significantly correlated with concentration. The same case applies to concentration and posttests as well as to immediate and delayed posttests; (b) learning styles have no significant effect both on concentration and achievement; (c) learning styles and interest do not yield interaction effects on the learning concentration of students, but interest alone significantly affects the latter; and (d) learning styles, interest, and concentration do not yield interaction effects on the academic achievement of students. Overall, these findings imply that low interest always leads to lower learning concentration. Thus, appropriate mobile learning materials should be developed and used to educate students on the basis of their respective concentration, interest, and learning styles. The implications, limitations, and future research plans are presented in this article.
Mel-Cepstrum-Based Quantization Noise Shaping Applied to Neural-Network-Based Speech Waveform Synthesis

This paper presents a mel-cepstrum-based quantization noise shaping method for improving the quality of synthetic speech generated by neural-network-based speech waveform synthesis systems. Since mel-cepstral coefficients closely match the characteristics of human auditory perception, the proposed method effectively masks the white noise introduced by the quantization typically used in neural-network-based speech waveform synthesis systems. The paper also describes a computationally efficient implementation of the proposed method using the structure of the mel-log spectrum approximation filter. Experiments using the WaveNet generative model, which is a state-of-the-art model for neural-network-based speech waveform synthesis, showed that speech quality is significantly improved by the proposed method.
Address sequences for march tests to detect pattern sensitive faults

Proposed paper presents a methodology for RAM testing based on counter address sequences. Presented solution allows us to generate and obtain different address sequences for march tests and use them to detect Pattern Sensitive Faults with a very high probability. According to previous investigations, we can use march tests to test modern memory chips, because their transparent versions are very efficient for the faults testing and diagnoses. In this paper, the most important results were done to calculate the best distance between two consecutive address sequences and to find the most efficient method for Pattern Sensitive Faults detection with simple address sequences generation techniques.
Antecedents of Knowledge Sharing in Globally Distributed Software Development Teams

Knowledge is seen as a source of competitive advantage in organizations. The need to cater to global market places, competitive pressures and to avail the best resource possible has given rise to distributed form of working, which is further enabled by technological advances. The prime advantage of distributed form of working is access to diverse sources of knowledge, and hence sharing of knowledge is a prerequisite for effective outcomes. This paper presents a conceptual framework and develops testable propositions by identifying team level antecedents of knowledge sharing in distributed work context. Analysis plan and directions for future research is also discussed in the paper. The key contribution of this study is to view the knowledge sharing process in teams with respect to different dimensions of distributedness, and relational attributes of the team.
Integration of virtual pheromones for mapping/exploration of environments by using multiple robots

The multiple robot coordination strategies have several advantages when compared to strategies based on a single robot, in terms of flexibility, gain of information and reduction of map building time. In this paper, a local pheromone map integration method is proposed based on the inter-robot observations, considering a method for the environment exploration named the Inverse Ant System-Based Surveillance System strategy (IAS-SS). Simulation results show that the map integration method is efficient, the trials are performed considering a variable number of robots in an indoor environment. Results obtained from several experiments confirm that the integration process is effective and suitable to execute the control of the access to pheromones in a virtual way.
A Novel Relationship Between Dynamics and Complexity in Multi-agent Collision Avoidance

This paper examines the relationship between system dynamics and problem complexity of collision avoidance in multi-agent systems. Motivated particularly by results in the field of automated driving, a variant of the reciprocal n-body collision avoidance problem is considered. In this problem, agents must avoid collision while moving according to individual reward functions in a crowded environment. The main contribution of this work is the novel result that there is a quantifiable relationship between system dynamics and the requirement for agent coordination, and that this requirement can change the complexity class of the problem dramatically: from P to NEXP or even NEXPNP. In addition, a constructive proof is provided that demonstrates the relationship and potential realworld applications of the result are discussed.
Sentiment Analysis for Social Media: A Survey

In the past years, the World Wide Web (WWW) has become a huge source of user-generated content and opinionative data. Using social media, such as Twitter, Facebook, etc. user share their views, feelings in a convenient way. Social media, such as Twitter, Facebook, etc, where millions of people express their views in their daily interaction, which can be their sentiments and opinions about particular thing. These ever-growing subjective data are, undoubtedly, an extremely rich source of information for any kind of decision making process. To automate the analysis of such data, the area of Sentiment Analysis has emerged. It aims at identifying opinionative data in the Web and classifying them according to their polarity, i.e., whether they carry a positive or negative connotation. Sentiment Analysis is a problem of text based analysis, but there are some challenges that make it difficult as compared to traditional text based analysis This clearly states that there is need of an attempt to work towards these problems and it has opened up several opportunities for future research for handling negations, hidden sentiments identification, slangs, polysemy. However, the growing scale of data demands automatic data analysis techniques. In this paper, a detailed survey on different techniques used in Sentiment Analysis is carried out to understand the level of work
Building well-balanced CDN

The following document describes building well-balanced CDN evolution process. We start with very intuitive, but unfortunately wrong solution and change it to the one which works almost ideally. We realized our experiments on Planetlab environment, which is a good internet simulation. Every experiment description is in common format for easy comparison. Document include for each experiment methodology: environment description, system architecture, short description of experiments, result analyzing and conclusions.
Mixed-initiative multirobot control in USAR

In Urban Search and Rescue (USAR), human involvement is desirable because of the inherent uncertainty and dynamic features of the task. Under abnormal or unexpected conditions such as robot failure, collision with objects or resource conflicts human judgment may be needed to assist the system in solving problems. Due to the current limitations in sensor capabilities and pattern recognition people are also commonly required to provide services during normal operation. For instance, in the USAR practice (Casper & Murphy 2003), field study (Burke et al. 2004), and RoboCup competitions (Yanco et al. 2004), victim recognition remains primarily based on human inspection. Human control of multiple robots has been suggested as a way to improve effectiveness in USAR. However, multiple robots substantially increase the complexity of the operator’s task because attention must be continually shifted among robots. A previous study showed that when the mental demand overwhelmed the operator’s cognitive resources, operators controlled reactively instead of planning and proactively controlling the robots leading to
The Ontologically based Model for the Integration of the IoT and Cloud ERP Services

On-premise and Cloud ERP systems have become a backbone of almost all businesses. Another recent trend currently in focus of both industry and academy is Internet of Things. The integration of Cloud ERP and the Internet of Things (IoT) should be looked as a new shift in business effectiveness and will have a great momentum in future. In this work, we propose the ontologically based model for the integration of the IoT and Cloud ERP systems by using Semantic Web services. To semantically annotate things as services, we plan to use recently published W3C’s SSN and SOSA ontologies. Furthermore, we plan to extend mentioned ontologies to include classification and descriptions of Cloud ERP APIs. Our integration model proposes usage of Semantic web services and AI planning technique to semi-automatically compose IoT and Cloud ERP services.
Design of multimodal biometrics system based on feature level fusion

Multimodal system aims to fuse two or more biometrics traits of an individual to achieve improvement in FAR and FRR of biometrics system which in turn increases accuracy of system. In this paper we have proposed biometrics system based on biometrics traits face and signature. The performances of face and signature recognition can be enhanced using a proposed feature selection method to select an optimal subset of features. Signature is very important human characteristics which is required in all financial transaction for human identification. In case of financial transaction correct recognition is necessary otherwise it can lead to fraudulent activities. Face is most commonly acceptable and popular biometrics. Proposed algorithm fuses wavelet based features of face and signature. Wavelet based feature fusion method also gave very promising results. Hamming distance classifier is used to take decision whether person is genuine or imposter. Our experiments show that the proposed algorithm can achieve higher classification accuracy than offline signature and face based identification system. We have achieved false accept rate of 5.99% and 3% for multibiometrics system for ORL databases combined with Caltech and Ucoer real signature database resp.
On relay assignment strategy in wireless cellular environment

Relay assignment means assigning the proper relay nodes (RN) to cell-edge users (UE) in order to exploit the spatial diversity through relay nodes and improve cell-edge performance. An optimal algorithm, called ORA, is to maximize the minimum data rate among all users. ORA is shown to find the optimal objective regardless the initial relay node. Although the algorithm is shown to converge (the minimum data rate is maximized), there exist several different RN-to-UE assignment pairs for the remaining UEs assigned to RNs. This paper is motivated to enhance the performance of the relay assignment for the remaining UEs, provided that the minimum data rate is maximized. In this paper, we propose a new strategy whose main objective is to maximize the relative performance improvement, which is a ratio of the performance improvement to original direct transmission, under the max-min constraint. Under the new assignment algorithm, not only the original optimal property of ORA is preserved, but also the performance of remaining UEs assigned to RNs is maximized. Simulation results demonstrate the effectiveness of the proposed approach.