Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance Evaluation of One Dimensional Systolic Array for FFT Processor

A new approach for the systolic implementation of FFT algorithms is presented, the proposed approach is based on the fundamental principle of 1-dimensional DFT can be decomposed efficiently with less number of twiddle values and also the computation burden involved with multipliers is reduced considerably, the FFT can be computed efficiently with 1-D systolic array, the essence of 1D systolic array is to have efficient computation with less twiddles, the proposed systolic array does not require any preloading of input data and it produces output data at boundary PES. No networks for intermediate spectrum transposition between constituent I-dimensional transforms are required: therefore the entire processing is fully pipelined. This approach also has significant advantages over existing architectures in reduced complexity with Wallace tree adder and Booth multiplier
Towards a Complete View of the Certificate Ecosystem

The HTTPS certificate ecosystem has been of great interest to the measurement and security communities. Without any ground truth, researchers have attempted to study this PKI from a variety of fragmented perspectives, including passively monitored networks, scans of the popular domains or the IPv4 address space, search engines such as Censys, and Certificate Transparency (CT) logs. In this work, we comparatively analyze all these perspectives. We find that aggregated CT logs and Censys snapshots have many properties that complement each other, and that together they encompass over 99% of all certificates found by any of these techniques. However, they still miss 1.5% of certificates observed in a crawl of all domains in . com, . net, and . org. We go on to illustrate how this combined perspective affects results from previous studies. In light of these findings, we have worked with the operators of Censys to incorporate CT log data into its results going forward, and we recommend that future HTTPS measurement adopt this new vantage.
Resource provisioning for cloud computing

In resource provisioning for cloud computing, an important issue is how resources may be allocated to an application mix such that the service level agreements (SLAs) of all applications are met. A performance model with two interactive job classes is used to determine the smallest number of servers required to meet the SLAs of both classes. For each class, the SLA is specified by the relationship: Prob [response time ≤ x] ≥ y. Two server allocation strategies are considered: shared allocation (SA) and dedicated allocation (DA). For the case of FCFS scheduling, analytic results for response time distribution are used to develop a heuristic algorithm that determines an allocation strategy (SA or DA) that requires the smallest number of servers. The effectiveness of this algorithm is evaluated over a range of operating conditions. The performance of SA with non-FCFS scheduling is also investigated. Among the scheduling disciplines considered, a new discipline called probability dependent priority is found to have the best performance in terms of requiring the smallest number of servers.
Enhanced Cardiac Perception Is Associated With Increased Susceptibility to Framing Effects

Previous studies suggest in line with dual process models that interoceptive skills affect controlled decisions via automatic or implicit processing. The "framing effect" is considered to capture implicit effects of task-irrelevant emotional stimuli on decision-making. We hypothesized that cardiac awareness, as a measure of interoceptive skills, is positively associated with susceptibility to the framing effect. Forty volunteers performed a risky-choice framing task in which the effect of loss versus gain frames on decisions based on identical information was assessed. The results show a positive association between cardiac awareness and the framing effect, accounting for 24% of the variance in the framing effect. These findings demonstrate that good interoceptive skills are linked to poorer performance in risky choices based on ambivalent information when implicit bias is induced by task-irrelevant emotional information. These findings support a dual process perspective on decision-making and suggest that interoceptive skills mediate effects of implicit bias on decisions.
Object Persistence in 3 D for Home Robots

This paper proposes a practical method to achieve object persistence – that is, a memory of the objects that have previously been discovered by a system, along with a way to update this memory as objects move. Our approach creates and maintains an object representation that includes 3D location, pose, semantic label, and appearance from multiple viewpoints. We employ a change-based attention operator which allows for efficient re-recognition of moved objects without wasted computation on stationary items. Our global model incrementally learns object appearances and which allows for increasingly successful persistence tracking as more time is spent in the environment. Our results demonstrate that the system is able to successfully maintain its model as objects in a cluttered kitchen area are moved during a series of days.
SINGLE ROW FACILITY LAYOUT PROBLEM USING AN IMPERIALIST COMPETITIVE ALGORITHM

In this paper, a novel metaheuristic algorithm named imperialist competitive algorithm (ICA) is employed to solve the single row facility layout problem (SRFLP). SRFLP is known as NP-hard and involves arranging a number of facilities on a straight line to minimize transportation costs among the facilities. ICA starts with an initial population of countries (solutions) which are classified as Imperialist and Colony. Each colony in the initial population is assigned to an imperialist respectively. An imperialist and its corresponding colonies construct an Empire. ICA proceeds through three main components, namely, assimilation inside each empire, imperialistic competition among empires and elimination of powerless empires. ICA converges to local optima when there is only one empire left. Details of applying ICA to SRFLP are elaborated and the quality of ICA is evaluated on a number of SRFLP instances (30 small-size instances and 20 large-size instances) from the literature. For small-size instances with known optimal solutions, ICA was able to find all the optimal solutions. In addition, for large-size instances with no proven optimal solutions, ICA succeeded in improving 8 previously known best solutions.
An Evaluation of Job Scheduling Strategies for Divisible Loads on Grid Platforms

In this paper we study distributed job scheduling in grid environments when each job is a DL application . The scheduling goal is to minimize the average steady-state job turnaround time. In this context, we identify in which regimes classes of scheduling strategies are efﬁcient, namely for which platforms and which communication to computation ratios. We also quantify what level of global information about the platform is required for efﬁcient scheduling. All our ﬁndings are obtained via simulation of wide ranges of application and platform scenarios. Our most signiﬁcant ﬁndings are that the use of grid information is only necessary at high workload, and that at high workload using dynamic information improves performance by around 10% when compared to using static information.
Piecewise Polynomial Functions and the Fast Fourier Transform

Piecewise polynomial functions are frequently used to approximate functions that exhibit complex behavior across a variety of scales. We investigate the use of nonuniform FFT (NUFFT) approaches to quickly and accurately evaluate the first several Fourier series coefficents of piecewise linear functions, and propose a new NUFFT approach that provides quick convergence at relatively low cost.
A new worm exploiting IPv4-IPv6 dual-stack networks

It is commonly believed that the IPv6 protocol can provide good protection against network worms due to its huge address space. However, it is proved to be incorrect by our study on the new "dual-stack worm" which can spread in IPv4-IPv6 dual-stack networks. It is found in this paper that the dual-stack worm can collect the IPv6 addresses of all running hosts on the link-local quickly and effectively, which may result in accelerated worm spreading on the IPv6 link-locals. This worm applies a two-level scanning mechanism to find its targets in dual-stack networks, which is investigated by exploring its similarity to the self-replicating behaviors of biological viruses. Based on the ideas of classifying the population into different species or patches, we categorized all vulnerable hosts into two species and separated all dual-stack hosts into several patches to model the propagation of this worm by differential equations. Simulation is performed to validate the worm propagation model and to study the propagation of the worm in various dual-stack networks with different patch parameters. The simulation results show that the worm is able to spread much faster in IPv4-IPv6 dual-stack network than that in the pure IPv4 Internet. It is also noted that the dual-stack links may influence the propagation of the worm in the Internet
Complex, Dynamic Combination of Physical, Chemical and Nutritional Variables Controls Spatio-Temporal Variation of Sandy Beach Community Structure

Sandy beach ecological theory states that physical features of the beach control macrobenthic community structure on all but the most dissipative beaches. However, few studies have simultaneously evaluated the relative importance of physical, chemical and biological factors as potential explanatory variables for meso-scale spatio-temporal patterns of intertidal community structure in these systems. Here, we investigate macroinfaunal community structure of a micro-tidal sandy beach that is located on an oligotrophic subtropical coast and is influenced by seasonal estuarine input. We repeatedly sampled biological and environmental variables at a series of beach transects arranged at increasing distances from the estuary mouth. Sampling took place over a period of five months, corresponding with the transition between the dry and wet season. This allowed assessment of biological-physical relationships across chemical and nutritional gradients associated with a range of estuarine inputs. Physical, chemical, and biological response variables, as well as measures of community structure, showed significant spatio-temporal patterns. In general, bivariate relationships between biological and environmental variables were rare and weak. However, multivariate correlation approaches identified a variety of environmental variables (i.e., sampling session, the C∶N ratio of particulate organic matter, dissolved inorganic nutrient concentrations, various size fractions of photopigment concentrations, salinity and, to a lesser extent, beach width and sediment kurtosis) that either alone or combined provided significant explanatory power for spatio-temporal patterns of macroinfaunal community structure. Overall, these results showed that the macrobenthic community on Mtunzini Beach was not structured primarily by physical factors, but instead by a complex and dynamic blend of nutritional, chemical and physical drivers. This emphasises the need to recognise ocean-exposed sandy beaches as functional ecosystems in their own right.
Investigation of Weakly Supervised Learning for Semantic Role Labeling

In this paper, we investigate the possibility of the weakly supervised learning for Semantic Role Labeling. First, we attempt to achieve feature splitting which is the base constraint of co-training, and examine if co-training works for the task of Semantic Role Labeling. We also examine the possibility of self-training which uses the identical features with co-training, and compare the performance of co-training and self-training. From the experiments, we found some interesting points about Semantic Role Labeling task and the weakly supervised learning. As far as we know, this is the first experiment to apply weakly supervised learning to Semantic Role Labeling and the experimental results show that Semantic Role Labeling can be successfully done by weakly supervised learning.
Motivation for or from bilingual education? A comparative study of learner views in the Netherlands

ABSTRACT Content and Language Integrated Learning (CLIL) has been said to increase not only foreign language proficiency but also learner motivation (Coyle, D., P. Hood, and D. Marsh. 2010. CLIL: Content and Language Integrated Learning. Cambridge: Cambridge University Press). In contexts where CLIL is elective, however, the question can be raised as to whether its motivational effects can be distinguished from the pre-existing motivation that may have influenced the learner’s choice of educational route. The current study examined motivational differences between learners in Dutch-English bilingual and mainstream education. The aim was to establish whether the learner groups were differently motivated and whether their motivation appeared to be diachronically related to their chosen educational format. 581 learners in the first three years of general secondary education completed a questionnaire exploring their views on (language) learning. Results were analysed in terms of differences between bilingual and mainstream learners and across year-groups. Learners in bilingual education displayed more motivation in nearly all of the areas examined. There was little evidence, however, of this being a result of exposure to bilingual education, reinforcing the idea that motivation may be inherent to this group of CLIL learners.
Grid-based Histogram of Oriented Optical Flow for analyzing movements on video data

Detection and recognition of object movements in a video is one of the research topics that are popular today. For the purposes of the analysis of the object movements in the video, the direction of movement is the important feature. In this study, we proposed a new method for determining the direction of movement using Histogram of Oriented Optical Flow (HOOF). We extract it locally at every N-by-N grid, not the entire frame. Direction movement is determined based on the value of HOOF on every grid. We classify the direction of movement in each grid into 12 directions. We use a video from UMN datasets for testing the proposed method. The experiment results show the value of False Positive Per Grid (FPPG) is 28.32%, and False Negative Per Grid (FNPG) is 4.08%. It proved that the use of Grid-based HOOF for analyzing movements on video data is good enough and can be improved in the future studies.
Neuro Modelling of Flexible Plate Structure Rig for Development of Active Vibration Control Algorithm

This paper presents an investigation into the performance of system identification using Backpropagation Multi-layer Perceptron Neural Networks algorithm for identification of a flexible plate system. Details of the implementation and the experimental studies are given and analyzed in the paper. The input-output data of the system were first acquired through the experimental studies using National Instrumentation (NI) data acquisition system. A sinusoidal force was then applied to excite the flexible plate and the dynamic response of the system was investigated. A linear parametric model of the system is developed using Recursive Least Square (RLS). Furthermore, a non-parametric model of the system is developed using Multi-layer Perceptron Neural Networks (MLP-NN). Later a comparative performance of the approaches used is presented and discussed. Finally, the validity of the obtained model was investigated using correlation tests.
Concurrent bandwidth aggregation over wireless networks

Mobile client platforms have emerged with the ability to access and utilize multiple wireless networks concurrently. Aggregation can be performed using wireless modems on one device or cooperatively across devices within wireless proximity of each other. This paper explores various concurrent bandwidth aggregation schemes. The aggregation can be achieved on the application-layer, transport layer like MultipathTCP, or on layers below IP such as the RLC layer. These schemes are compared. In general, aggregation on the lower layer is closer to the client device and easier to adapt to the varying channel and loading conditions. However, lower layer aggregation needs more changes to wireless access stratum infrastructure. Aggregation above the IP layer is simpler to implement. A feasibility study of MultipathTCP aggregation over multiple WWANs is presented.
Research on Replica Strategy in Cloud Storage System

Most cloud storage system uses replica technology to ensure data reliability and improve data access efficiency. But in current file system, there are some problems such as the fixed number of replica and replica placement may cause load imbalance. In order to solve these problems, introducing a dynamic replica adjustment strategy and replica placement algorithm, this strategy can dynamic adjust the number of replica along with the change of heat of access and access response time. When placing a replica, in order to make the access efficiency is the highest, propose a replica placement algorithm based on transmission cost, which is select the best place of access efficient is most in placement a replica. Finally, experimental results show the effectiveness of the strategy.
Developing an Extended Task Framework for Exploratory Data Analysis Along the Structure of Time

Exploratory data analysis of time-oriented data is an important goal that Visual Analytics has to tackle. When users from real-world domains are asked about time-oriented tasks, they often refer to the unique structure of time (e.g., calendars, primitives, etc.). Several task frameworks have been developed, but none of them combines a complete, systematic approach with explicit attention to the structure of time. To fill this gap, we aim for complementing an established task framework with a rule set that explicitly models the structure of time for tasks. This rule set allows to consistently formulate tasks for evaluating time-oriented data analysis methods.
Ieee Transactions on Image Processing the Finite Ridgelet Transform for Image Representation

— The ridgelet transform (Candès and Donoho, 1999) was introduced as a sparse expansion for functions on continuous spaces that are smooth away from discontinu-ities along lines. In this paper, we propose an orthonormal version of the ridgelet transform for discrete and finite-size images. Our construction uses the finite Radon transform (FRAT) (Bolker, 1987; Matúš and Flusser, 1993) as a building block. To overcome the periodization effect of a finite transform, we introduce a novel ordering of the FRAT coefficients. Taking the one-dimensional wavelet transform on the projections of the FRAT in a special way results in the finite ridgelet transform (FRIT), which is invertible, non-redundant, and computed via fast algorithms. Furthermore , our construction leads to a family of directional and orthonormal bases for images. Numerical results show that the FRIT is more effective than the wavelet transform in approximating and denoising images with straight edges.
Priors in Web Search

The invention provides generally a method and system for selecting an element of a computer generated drawing model graphically represented on a computer screen wherein each selectable element of the model occupies a position in a hierarchical tree describing the model. A pointer can be used to specify a position on the screen and pre-selecting an element on an axis extending from the position of the pointer along a predetermined direction such that the direction is not in the plane of the screen. Pre-selection can be moved from a first position on the hierarchical tree to a second position on the hierarchical tree in response to activation of an arrow mechanism. Full selection can be accomplished by activating a selection mechanism.
Large-Eddy Simulation of Ship Flows with Wall-Layer Models on Cartesian Grids

The recent development of CFDShip-Iowa Version 6, a high-performance, high-fidelity Cartesian grid solver for computational ship hydrodynamics, is presented. First, a wall function approach has been introduced for wall-layer modeling based on the immersed boundary method and the one-equation Spalart-Allmaras turbulence model. Second, in order to develop more advanced wall-layer modeling schemes, an orthogonal curvilinear grid solver based on the Cartesian grid solver has been implemented and tested. Third, a coupled level set volume-of-fluid method has been developed to substantially improve the volume conservation properties of the interface tracking/ capturing schemes. In addition, fluid-structure interactions for ship motions in the framework of current Cartesian grid solver are also discussed. Finally, domain decomposition using MPI in all three directions has been included, parallel I/O becomes fully functional, and a new high-performance Poisson solver has been implemented. A series of cases ranging from the NACA0024 hydrofoil, Wigley hull, surface combatant DTMB model 5512, bow waves by a wedge, and surface-piercing circular cylinder, etc., have been carried out to validate the accuracy and demonstrate the scalability of the current method. Results including wave field patterns, velocity fields are successfully compared with experimental data and other computational results.
Analysis of a winter regional haze event and its formation mechanism in the North China Plain

Abstract. A regional haze episode occurred in the Beijing, Tianjin and Hebei province (BTH) area in the North China Plain (NCP) from 16 to 19 January 2010. Data were collected and analyzed during the time frame of 14 through 23 January 2010 to include the haze event. The increase of secondary inorganic pollutants (SO 4 2− , NO 3 − , NH 4 + ) in PM 2.5 was observed simultaneously at four sites, especially in the plain area of the BTH, which could be identified as a common characteristic of pollution haze in east China. The sulfate and nitrate in PM 2.5 were mainly formed through the heterogeneous reaction process in the urban area. The organic matter (OM) increased more significantly at the Chengde (CD) site than the other three sites in the plain area. The secondary organic aerosols only existed during haze days at CD but in both haze and non-haze days at the other three sites, which suggested the greater regional impact of secondary formation process during the haze episode. The secondary formation of aerosol was one important formation mechanism of haze. The strong temperature inversion and descending air motions in the planetary boundary layer (PBL) allowed pollutants to accumulate in a shallow layer. The weak surface wind speed produced high pollutants concentration within source regions. The accumulation of pollutants was one main factor in the haze formation. The enhanced southwest wind in the last period of this episode transported pollutants to the downwind area and expanded the regional scope of the haze.
Email filtering based on supervised learning and mutual information feature selection

Electronic mail is one of today's most important ways to communicate and transfer information. Because of fast delivery and easy to access, it is used almost in every aspect of communication in work and life. However, the increase in email users has resulted in a dramatic increase in spam emails during the past few years. In this paper, we propose an email-filtering approach that is based on supervised classifier and mutual information. The proposed model has the advantage of combining machine supervised learning with feature selection. Term frequency (TF) is presented to assign relevance weights to words of each email class. We conduct experiments to compare between six different classifiers. Results show that the proposed approach has high performance in terms of precision, recall and accuracy performance measures.