Miracle-dz/UniFAR-FTUs huggingface dataset:
Macroscopic Manifestations of Neural Connectivity in EEG Signals

Abstract —Cortical computation involves the formation ofcooperative neuronal assemblies. Traditionally, these as-semblies have been characterized by synchronous oscilla-tory activity, and the cortical connectivity organizing theirformation has been assessed indirectly through measuresof synchronization among cortex regions. However, asynchronization based deﬁnition of connectivity might berestrictive as weak, though important, interactions mightremain unobservable under such a paradigm. Here, themacroscopic manifestation of functional cortico-corticalconnectivity is assessed through a parametric identiﬁcationmethod, out of the synchronization framework, applied tovisual stimuli induced EEG signals. 1. Introduction Theoperationsperformedbythecerebralcortexrequirethecooperative activity of neurons within distributed assem-blies. Consequently, the study of the assemblies formationisofcriticalimportanceinneuroscienceandquestionslike:“How and where assemblies form? ”; “Under which condi-tion (external stimuli)? ”; “How diﬀerent assemblies inter-act? ”; etc., are central in brain studies.In human studies, these assemblies have been identiﬁedwith several methods as fMRI, EEG analysis, or combina-tion of the two, see
Measure of ERP users' satisfaction

It is very difficult in measuring the success of Enterprise resource planning (ERP) systems. Key-users' satisfaction is often used as substitute variable to determine the ERP's success. This study found out that relationship exists between key-user satisfaction and perceived ERP success in China. Especially, the model adopts three factors of the first level one, and i5 items of the second level. The three factors were correlated and the correlations are statistically caused by the second-level factor. ERP suppliers should concentrate on concerned about the quality of products and improvement of user knowledge. ERP users should carefully select suppliers and service personnel.
A Temporal Partitioning Methodology for Reconfigurable High Performance Computers

This paper presents a Design Space Exploration(DSE) methodology based on a temporal partitioning strategy for mapping of massive computational dataflow problems into FPGAs. In this approach the FPGAs work as co-processors in a hypothetic reconfigurable computing architecture. The temporal partitioning is based on Tabu Search strategies and libraries of IP-cores. This methodology allows Design Space Exploration for optimization of dataflow implementation into the FPGA and pre-runtime analysis. Results of this DSE technique, for synthetic benchmarks, have reached very good performance and sometimes better than others in the literature.
Real-time stereo visual servoing control of an UAV having eight-rotors

This paper presents a visual feedback control of a small UAV using image-based visual servoing with stereo vision. In order to control the orientation and the position of flying robot with respect to an object or target well defined, we propose to use a navigation system based on binocular vision system combined with inertial sensors. This combination of sensors, allows us to get a complete characterization of the state of aerial vehicle. It means, using the stereo vision system we are able to estimate the UAV 3D position, while from the inertial sensors we can obtain the orientation of rotorcraft. Real time experiences are developed to validate the performance of navigation system proposed.
Augmenting the Proebsting-watterson Filter Fusion Algorithm

A sequence of processes connected by data streams can be executed using multiple threads, but, given current hardware, are more eeciently executed with a single thread. The Proebsting-Watterson lter fusion algorithm combines adjacent processes into a single process, making it possible to convert a pipeline into a single block of code. This paper reports on work augmenting the Proebsting-Watterson lter fusion algorithm to generate code easier to optimize, and then describes some of the optimizations needed.
Low-complexity audio compression methods for wireless sensors

Wireless sensors are frequently used for recording surrounding speech and then sending it to a base station. Their way of communication via radio waves makes it important to employ some form of audio compression, while their limited RAM and low-capacity CPU restrict the range of methods which can be applied. In this paper a number of such methods are tested, and show that they can indeed be effective: a 30% bandwidth saving was achieved practically without information loss and a 50% bandwidth reduction at the cost of some negligible information loss.
Round-robin routing policy: value functions and mean performance with job- and server-specific costs

We study the Round-Robin (RR) routing to a system of parallel queues. The cost structure comprises two components: a service fee and a queueing delay related component, where both can be job- and queue-specific random variables. With Poisson arrivals, the inter-arrival time to each queue obeys Erlang's distribution. This allows us to study the mean and transient behavior of the queues separately. The service fee is independent of the queueing, and we obtain the corresponding mean cost rate and value function in closed forms. With respect to queueing delay, we first derive integral expressions enabling efficient computation of the corresponding value function. By decomposition, these yield also the value function for the whole system of m parallel queues fed by RR. Given the value function, one can carry out the first policy iteration step with arbitrary holding cost rates (e.g., delay, slowdown etc.) yielding efficient size-, cost- and state-aware policies. Moreover, the mean waiting time in an M/G/m-RR system gets resolved at the same time. The results are demonstrated in the numerical examples, where we compute near optimal task assignment policies for a sample system with two servers.
Desktop Tools for Offline Plagiarism Detection in Computer Programs

Plagiarism in universities has always been a difficult problem to overcome. Various tools have been developed over the past few years to help teachers detect plagiarism in students' work. By being able to categorize the multitude of plagiarism detection tools, it is possible to estimate their capabilities, advantages and disadvantages. In this article I consider modern plagiarism software solutions, paying attention mostly to desktop systems intended for plagiarism detection in program code. I also estimate the speed and reliability of different plagiarism detection systems that are currently available.
The EVALITA 2016 Event Factuality Annotation Task (FactA)

English. This report describes the FactA (Event Factuality Annotation) Task presented at the EVALITA 2016 evaluation campaign. The task aimed at evaluating systems for the identification of the factuality profiling of events. Motivations, datasets, evaluation metrics, and postevaluation results are presented and discussed. Italiano. Questo report descrive il task di valutazione FactA (Event Factaulity Annotation) presentato nell’ambito della campagna di valutazione EVALITA 2016. Il task si prefigge lo scopo di valutare sistemi automatici per il riconoscimento della fattualitá associata agli eventi in un testo. Le motivazioni, i dati usati, le metriche di valutazione, e risultati post-valutazione sono presentati e discussi.
The impact of lens galaxy environments on the image separation distribution

We study the impact of lens galaxy environments on the image separation distribution of lensed quasars. We account for both environmental convergence and shear, using a joint distribution derived from galaxy formation models calibrated by galaxy‐galaxy lensing data and number counts of massive elliptical galaxies. We find that the external field enhances lensing probabilities, particularly, at large image separations; the increase is ∼30 per cent at θ = 3 arcsec and ∼200 per cent at θ = 5 arcsec, when we adopt a power-law source luminosity function �( L) ∝ L −2.1 . The enhancement is mainly driven by convergence, which boosts both the image separation and magnification bias (for a fixed lens galaxy mass). These effects have been neglected in previous studies of lens statistics. Turning the problem around, we derive the posterior convergence and shear distributions and point out that they are strong functions of image separation; lens systems with larger image separations are more likely to lie in dense environments. Ke yw ords: gravitational lensing ‐ cosmology: theory ‐ dark matter.
Coding Last Level STT-RAM Cache for High Endurance and Low Power

STT-RAM technology has recently emerged as one of the most promising memory technologies. However, its major problems, limited write endurance and high write energy, are still preventing it from being used as a drop-in replacement of SRAM cache. In this paper, we propose a novel coding scheme for STT-RAM last level cache based on the concept of value locality. We reduce switching probability in cache by swapping common patterns with limited weight codes (LWC) to make writes less often as well as more uniform. We also define some policies for swapping these patterns. Our evaluation shows that bit write variance in memory cells can be reduced by about 20% on average resulting in a more uniform wear-out directly enhancing lifetime and improving cell reliability. In addition, writes in cache lines can be reduced by about 12% compared to one of the most effective circuit level techniques known as early write termination (EWT) [12]. Our method increases memory hierarchy access time by about 0.08% on average, which is negligible. We have shown that our method doesn't adversely affect last level cache energy-delay2. The non-uniformity caused by the coding scheme can be used for another coding scheme at main memory or L1 cache depending on their technologies.
Finding community structure in complex network based on latent variables

A number of recent studies have focused on detecting community structure in complex network. We develop an algorithm to detect communities by treating nodes as random variables and deriving samples of these variables from adjacency matrix which includes topology information of network. Using factor analysis theory, we represent communities as latent variables and extract the related matrix to uncover the relationship between network nodes and communities. The algorithm proposed in this paper uses the related matrix to improve the testing accuracy and we also notice that the algorithm overcomes the resolution limit possessed by other modularity-based methods in a kind of network topology structure. Experiments in real-world networks reveal that it detects significant and informative community divisions compared with other classic methods.
Inclusive Education in Indonesia from The Perspective of Widyaiswara in Center for Development and Empowerment of Teachers and Education Personnel of Kindergartens and Special Education

Since 2009, Indonesia has an excellent commitment and effort in the field of inclusive education. The government provides equal opportunities in education. Through Centre for Development and Empowerment of Teachers and Education Personnel of Kindergartens and Special Education (PPPPTK TK & PLB), the government provides training and services to teachers in the field of inclusive education and special education. The teacher trainers in PPPPTK TK & PLB are called WidyaIswara. The purpose of this study is to know the implementation of inclusive education in Indonesia from the perspective of WidyaIswara of PPPPTK TK & PLB. The research used qualitative method. This research was conducted on March 2nd, 2017 in PPPPTK TK & PLB located in Bandung, Indonesia. Data were collected using a questionnaire in the interview related to perceptions about special and inclusive education. The interview process used the instrument in interview form to experts that called WidyaIswara with closed-ended questions. A total of 3 Expert in Inclusive Education in PPPPTK participated in this activity. From the findings and discussion of the research, explained about WidyaIswara's perception about: 1) Awareness of students to go to school, 2) Grouping of students with special needs in special and general schools, 3) Distribution of Special Schools in Indonesia, 4) Supporting educational facilities and infrastructure in special and inclusive schools, 5) Teacher in special and inclusive Schools, 6) Learning Activities, 7) Children with special needs after graduation at a level of education, and 8) Government efforts.
Cost Analysis, Cost Reduction and Competition

Rising competition has been repeatedly mentioned as the reason many firms have invested in more extensive management accounting systems. I use a theoretical model to examine this link. In my model firms (1) determine how much cost data to collect and then estimate costs, (2) use the cost estimate to guide their cost reduction investments, and (3) produce and sell output in a Cournot market. Contrary to the common view, my main result shows that increasing the number of competitors leads to a decreased investment in cost reduction subsystems. The intuition is that as competition rises, each firm? s sales drop and any cost reduction investment can be recovered on fewer units. I also show that the highest cost firms need not invest the largest amounts in cost reduction. Finally I demonstrate that firm? s demand for cost data displays a U shape. As competition rises, firms first decrease, then increase their demand for cost data.
Unsupervised saliency detection based on 2D Gabor and Curvelets transforms

Construction of saliency map in multimedia data is useful for applications in multimedia like object segmentation, quality assessment, and object recognition. In this paper, we propose a novel saliency map model called Gabor & Curvelets based Saliency Map (GCSMP) relying on 2D Gabor and Curvelet transforms. Compared with the traditional model based on DOG and wavelets, our model takes advantage of Garbor transforms's spatial localization and Curvelet transform's edge and directional information. We also discuss the influence of center bias and object detectors in our model. Empirical validations on standard dataset demonstrate the effectiveness of the proposed technique.
Translin and Trax differentially regulate telomere-associated transcript homeostasis

Translin and Trax proteins are highly conserved nucleic acid binding proteins that have been implicated in RNA regulation in a range of biological processes including tRNA processing, RNA interference, microRNA degradation during oncogenesis, spermatogenesis and neuronal regulation. Here, we explore the function of this paralogue pair of proteins in the fission yeast. Using transcript analysis we demonstrate a reciprocal mechanism for control of telomere-associated transcripts. Mutation of tfx1+ (Trax) elevates transcript levels from silenced sub-telomeric regions of the genome, but not other silenced regions, such as the peri-centromeric heterochromatin. In the case of some sub-telomeric transcripts, but not all, this elevation is dependent on the Trax paralogue, Tsn1 (Translin). In a reciprocal fashion, Tsn1 (Translin) serves to repress levels of transcripts (TERRAs) from the telomeric repeats, whereas Tfx1 serves to maintain these elevated levels. This reveals a novel mechanism for the regulation of telomeric transcripts. We extend this to demonstrate that human Translin and Trax also control telomere-associated transcript levels in human cells in a telomere-specific fashion.
Roles and Effects of BBS and Personal Websites in Academic Information Exchanges in China

With the advent of the computer networks, Internet becomes the most important information communication media, and electronic bulletin board systems (BBS) and personal websites play more and more important roles in academic information exchanges. The paper discusses the current state of academic BBS and personal websites in China, analyses their advantages and disadvantages in academic information sharing and spreading, and concludes that BBS and personal websites are increasing popular in academic information exchanges in the country.
Neural Net Analysis of the Propensity for Change in Large Software Systems

A novel approach for analyzing the relationship between code metrics and change count histories is presented. Specifically, neural networks are employed to determine a mapping between metrics and change count. While these neural networks can be trained to a high degree of accuracy, their internal workings remain opaque to the user. As such, a fuzzy modeling approach is additionally employed to generate the rules governing the neural computation. These rules are linguistic in nature and are thus more easily interpreted by software project managers. Application of this method to Mozilla change data reveals the importance of fan-out, total lines of code and maximum cyclomatic complexity metrics in predicting amount of change per file.
On Classifying Deformable Contours Using the GeneralizedActive Contour

Recently, we proposed the generalized active contour model (g-snake) to model and extract deformable contours from noisy images. This paper demonstrates the usefulness of g-snake in classifying among several candidate deformable contours. The g-snake is suitable for this task because its shape representation is unique, aane invariant and possesses metric properties. We derive the optimal classiication test and show that this requires marginalization of the distribution. However, as the summation is peaked around the posterior estimate in most practical applications, only small regions need to be considered. Finally, we performed extensive ex-perimentations and report signiicant improvement over matched template in handwritten numeral recognition.
Predictors of Impaired Glucose Regulation in Patients with Non-Alcoholic Fatty Liver Disease

Introduction. Many patients with non-alcoholic fatty liver disease (NAFLD) have impaired glucose regulation or type 2 diabetes mellitus (DM). We investigated characteristics of NAFLD patients associated with hyperglycemia. Methods. During a 2-hour oral glucose tolerance test (OGTT), serum glucose and insulin were measured in 152 NAFLD patients. Results. 48.7% of NAFLD patients had hyperglycemia. Age (odds ratio (OR) = 1.08, 95% confidence interval (CI): 1.03–1.13), body mass index (BMI) (OR = 1.12, 95% CI: 1.01–1.25), and lower high-density lipoprotein cholesterol (HDL-C) (OR = 0.95, 95% CI: 0.92–0.98) proved to be independent predictors of hyperglycemia. After OGTT, 30 min insulin was lower in hyperglycemic patients (74.2 ± 49.7 versus 94.5 ± 53.9 μIU/mL, P = 0.02), while 90 min insulin (170.1 ± 84.6 versus 122.9 ± 97.7 μU/mL, P = 0.01) and 120 min insulin (164.0 ± 101.2 versus 85.3 ± 61.9 μIU/mL, P < 0.01) were higher. Conclusions. NAFLD patients with higher BMI, lower HDL-C, or older age were more likely to have impaired glucose metabolism. An OGTT could be of value for early diagnosis of DM among this population.
Graspability map: A tool for evaluating grasp capabilities

This paper presents the graspability map, a novel approach to represent for a particular object the positions and orientations that a given mechanical hand can adopt to achieve a force closure precision grasp. The algorithm is based on the intersection between the fingertip workspaces and the object, plus the verification of a necessary condition for force closure grasps. The maps are computed offline and can be used for comparing the grasp capabilities of different mechanical hands with respect to some benchmark objects. The maps have also potential applications in online grasp and manipulation planning.
A table-form extraction with artefact removal

We present a novel methodology for extracting the structure of handwritten filled table-forms. The method identifies the table-form line intersections, detecting and correcting wrong intersections produced by faulty line segments or by table artefacts. Examples of artefacts are overlapping data, broken segments, and smudges. A novel method for artefact identification and deletion is also proposed. The last step performs the extraction of table-form cells. A database of 350 table-form images was used for evaluation, showing that the artefact identification method improves the performance of the table-forms structure extractor. The proposed approach reached a success rate of 85%.
Modified self — Adaptive Plateau Histogram Equalization with mean threshold for brightness preserving and contrast enhancement

Histogram Equalization (HE) is a simple, effective and widely used contrast enhancement technique as it can automatically define the intensity transformation function based on statistical characteristics of the image, but it tends to change the mean brightness of the image to the middle level of the gray level range. HE also produces saturation effects by extremely pushing the intensities towards the right or the left side of the histogram. To surmount these drawbacks, Clipping or Plateau Histogram Equalization techniques for brightness preserving and contrast enhancement have been proposed, but, these are not suitable for automatic systems because of manual selection of threshold level. Self-Adaptive Plateau Histogram Equalization (SAPHE) selects the threshold level automatically, but the process is relatively complicated and sometimes fails in execution. To overcome these drawbacks, a Modified Self - Adaptive Plateau Histogram Equalization with Mean threshold (Modified SAPHE-M) is proposed in this paper and compared the experimental results with Histogram Equalization (HE), Self-Adaptive Plateau Histogram Equalization (SAPHE) and Modified Self-Adaptive Plateau Histogram Equalization (Modified SAPHE) by using image quality measures such as Absolute Mean Brightness Error (AMBE) and Peak-Signal to Noise Ratio (PSNR).
Design exploration of inrush current aware controller for nonvolatile processor

Leakage power consumption has become a critical limitation in the normally off low-power systems. Power gating provides a promising solution to reduce leakage energy but cannot avoid data loss. Nonvolatile processor has paved the way to achieve zero leakage power while maintaining data. However, nonvolatile processor faces severe inrush current problem when all nonvolatile memories are backed up in parallel. A large inrush current will occur and induce IR drop, which deteriorates the stability of the entire system. This paper proposes a distributed backup control architecture for nonvolatile processors to cope with the inrush current problem. Furthermore, we devise corresponding algorithms to accelerate backup operations under given maximum tolerable current constraints. The proposed techniques are evaluated on a simulation platform and a prototype chip. Experimental results demonstrate up to 26.3% reduction in backup time compared with the sequential backup strategy under the same inrush current constraint.
Overhead and Spectral Efficiency of Pilot-Assisted Interference Alignment in Time-Selective Fading Channels

The spectral efficiency achievable by interference alignment (IA) in a K-user multiple-input-multiple-output interference channel is studied in the face of time-selective continuous fading explicitly estimated through pilot-symbol observations. The robustness of IA in such operationally relevant conditions is assessed through a joint optimization of the pilot overhead and the IA update interval, which are characterized - in high-power conditions - as solutions of a fixed-point equation. Variations of the formulation are given for both frequency-division duplexing (FDD) and time-division duplexing, the former requiring explicit feedback of the fading estimates and the latter relying on fading reciprocity. For the FDD variation, analog feedback is considered. In addition to arbitrary numbers of users and antennas and arbitrary temporal fading correlation functions, the derivations accommodate forward and reverse links with asymmetric power levels.