Miracle-dz/UniFAR-FTUs huggingface dataset:
‘Ultra Large-Scale FFT Processing on Graphics Processor Arrays’

Graphics Processor Unit (GPU) technology has been shown well-suited to efficient Fast Fourier Transform (FFT) processing. An illustrative example is the NVIDIA CUFFT library providing capability for GPU-based 1D/2D/3D FFT computations at sample sizes ranging up to 8 × 10 6 . In this paper, a processing model and software architecture are described by which GPU-based FFT computations may be further scaled in both size and speed. In essence, the Ultra Large Scale FFT (ULSFFT) butterfly graph is restructured based upon adoption of preexisting FFT kernels as RADIX N Butterfly components (‘N-Flys’) to which ancillary phase-factor and address-shuffle operators are appended. A supercomputer-styled scatter-gather processing model is employed based upon a parallel schedule by which N-fly instances are mapped and queued at multi-GPU Array (GPA) and cluster interfaces. In this manner, FFT sample size is rendered independent of GPU resource constraints. CPU/GPU process pipelining enables optimization of effective parallelization based upon asynchronous work-unit transactions at the GPA/API interface. GPU instruction pipeline reuse is also employed to further amortize I/O transaction overhead. A characteristic 1 × 10 9 full-complex, RADIX 1024 ULSFFT design benchmark is then presented and discussed.
Partition Testing versus Random Testing: the Innuence of Uncertainty

| The paper compares partition testing and random testing on the assumption that program failure rates are not known with certainty before testing and are therefore modeled by random variables. It is shown that under uncertainty, partition testing compares more favorably to random testing than suggested by prior investigations concerning the deterministic case: the restriction to failure rates that are known with certainty systematically favors random testing. In particular, we generalize a result by Weyuker and Jeng stating equal fault detection probabilities for partition testing and random testing in the case where the failure rates in the subdomains deened by the partition are equal. It turns out that for independent random failure rates with equal expectation, the case above is a boundary case (the worst case for partition testing), and the fault detection probability of partition testing can be up to k times higher than that of random testing, where k is the number of subdomains. Also in a related model for dependent failure rates, partition testing turns out to be consistently better than random testing. The dominance can also be veriied for the expected (weighted) number of detected faults as an alternative comparison criterion.
Effective Image Fusion Rules Of Multi-scale Image Decomposition

Image fusion rule is the key that influences the quality of image fusion which is a primary branch of multi-sensor information fusion. This paper proposes a fusion rule based on the combination of PCA and consistency checking and applies it to multi-scale image fusion algorithm. The method applies the PCA method to the approximation image decomposed by multi-scale and adopts "select max" on detail image, the consistency of which is later checked with fusion decision. The proposed rule overcomes the instability and incontinuity of information occurring in the image fusion decomposed by multi-scale before. The experimental results show that better than the traditional rules, this method can effectively improve the quality of multi-sensor image fusion, and is especially applicable to images fusion of different sensors.
MODELLING APPROACHES IN THE EARLY PHASES OF INFORMATION SYSTEMS DEVELOPMENT

Modelling the real life plays a significant role in Information Systems Development (ISD). There are several approaches that can be utilized, with different emphases on methods and notations. Some of them are well-known, like the traditional process modelling approach, while some newer ones are not widely known, like the Activity Driven Approach. In this paper we study modelling approaches in the early phases of ISD with two dimensions – the scope (technical – social) and the degree of structure – and create a map of modelling approaches. Traditional process modelling, socio-technical and Activity Driven approaches are located on the map in order to provide an overview of the approaches and their relations with each other.
Erim Report Series Research in Management Erim Report Series Reference Number Ers-2000-16-lis Managing Knowledge in a Distributed Decision Making Context: the Way Forward for Decision Support Systems Bibliographic Data and Classifications

This paper considers the role of electronic communication in the creation and distribution of knowledge, and in particular, the creation and sharing of personalised knowledge. Personalised knowledge or " intellectual capital " is perhaps a least understood but most important asset of modern organisations. This paper reveals the creation and sharing of personalised knowledge in a network organisation. The network organisation investigated in this paper relies on electronic communication in a distributed decision making context to leverage the skills and intellect of its key professionals. This paper investigates electronic group meetings that take place on this electronic social space to analyse key processes of knowledge creation. Implications for managing distributed personalised knowledge are discussed and conclusions drawn with respect to the key decision support systems functionalities required for managing knowledge in situations where decision making is distributed and takes place on an electronic social space.
Prevention of diabetic nephropathy with enalapril in normotensive diabetics with microalbuminuria.

STUDY OBJECTIVE--To assess the effectiveness of inhibition of angiotensin converting enzyme in preventing diabetic nephropathy. DESIGN--Randomised follow up study of normotensive diabetics with persistent microalbuminuria (30-300 mg/24 hours) treated with enalapril or its matched placebo for one year. Double blind for first six months, single blind for last six months. SETTING--Diabetic clinic in tertiary referral centre. PATIENTS--Treatment group and placebo group each comprised 10 normotensive diabetics with persistent microalbuminuria. INTERVENTIONS--Treatment group was given enalapril 20 mg daily and controls matched placebo. Patients were given antihypertensive treatment after one year. END POINT--Albumin excretion, arterial pressure, and renal function. MAIN RESULTS--In last three months of trial three of 10 patients taking placebo had diabetic nephropathy (albumin excretion greater than 300 mg/24 hours). No patients taking enalapril developed nephropathy and five showed normal albumin excretion (less than 30 mg/24 hours) (p = 0.005, Mann-Whitney test). Mean arterial pressure was reduced by enalapril throughout study (p less than 0.005) but increased linearly with placebo (p less than 0.05). Albumin excretion decreased linearly with enalapril but not placebo. An increase in albumin excretion with placebo was positively related to the increase in mean arterial pressure (r = 0.709, p less than 0.05, Spearman's rank test). With enalapril total renal resistances and fractional albumin clearances improved progressively (time effect, p = 0.0001). CONCLUSION--Inhibition of angiotensin converting enzyme prevents development of nephropathy in normotensive diabetics with persistent microalbuminuria. This may be due to reduction in intraglomerular pressure and to prevention of increased systemic blood pressure. Future studies should compare long term effects of inhibitors of converting enzyme with other antihypertensive drugs.
The Co-evolution of Trading Strategies in A Multi-agent Based Simulated Stock Market Through the Integration of Individual Learning and Social Learning

In this paper we present a multi-agent based model of a simulated stock market within which active stock traders are modelled as heterogeneous adaptive artificial agents. We employ the approach of integrating individual learning and social learning to co-evolve these artificial agents with the aim of evolving successful trading strategies. The proposed model was tested on the British Petroleum (BP.L) share from the LSE (London Stock Exchange). Throughout the experiment we see successful trading strategies emerge among the artificial traders. These artificial agents also demonstrate rich dynamic learning behaviours during the simulation. On average, 80% of the artificial stock traders were able to trade using successful trading strategies which brings the investors higher returns compared to a baseline buyand-hold strategy.
Fountain codes design for asynchronous multi-relay system

For asynchronous transmission, the scheme with fountain codes is more attractive. In multi-relay system, each relay encodes with fountain codes and transmits encoded packets independently. A practical family of Raptor codes is proposed, which combines flexible pre-code with short-length LT codes. Simulation results show that the transmission scheme with our proposed fountain codes can achieve better performance at same overhead, and need less overhead at same performance.
Capacity of cognitive radio under outage constraint with partial channel knowledge

This paper considers a cognitive radio network where a secondary user (SU) shares the same narrow spectrum band that is originally licensed to the primary user (PU) as long as the interference caused by the SU to the latter is below a prescribed threshold. At the SU, channel state information (CSI) is used to regulate the SU transmit power to limit the interference. In this respect, we assume only partial CSI is available to the SU, and investigate the SU ergodic capacity under the PU outage loss constraint as well as the peak/average transmit power constraint in Rayleigh fading channels. In particular, we derive the optimal power allocation to achieve the SU ergodic capacity, and further obtain closed-form expressions for the ergodic capacity. Numerical simulations are also given to corroborate our theoretical results.
GRAIN ALIGNMENT IN OMC1 AS DEDUCED FROM OBSERVED LARGE CIRCULAR POLARIZATION

The properties of polarization in scattered light by aligned ellipsoidal grains are investigated with the Fredholm integral equation method and the T-matrix method, and the results are applied to the observed circular polarization in OMC1. We assume that the grains are composed of silicates and are ellipsoidal (oblate, prolate, or triaxial ellipsoid) in shape with a typical axial ratio of 2:1. The angular dependence of circular polarization pc on directions of incident and scattered light is investigated with spherical harmonics and associated Legendre polynomials. The degree of circular polarization pc also depends on the Rayleigh reduction factor R, which is a measure of imperfect alignment. We find that pc is approximately proportional to R for grains with |m|xeq ≲ 3 − 5, where xeq is the dimensionless size parameter and m is the refractive index of the grain. Models that include those grains can explain the observed large circular polarization in the near-infrared, ≈15%, in the southeast region of the BN object in OMC1, if the directions of incidence and scattering of light is optimal, and if grain alignment is strong, i.e., R ≳ 0.5. Such a strong alignment cannot be explained by the Davis–Greenstein mechanism; we prefer instead an alternative mechanism driven by radiative torques. If the grains are mixed with silicates and ice, the degree of circular polarization pc decreases in the 3 μm ice feature, while that of linear polarization increases. This wavelength dependence is different from that predicted in a process of dichroic extinction.
Strategic search from long-term memory: An examination of semantic and autobiographical recall

Searching long-term memory is theoretically driven by both directed (search strategies) and random components. In the current study we conducted four experiments evaluating strategic search in semantic and autobiographical memory. Participants were required to generate either exemplars from the category of animals or the names of their friends for several minutes. Self-reported strategies suggested that participants typically relied on visualization strategies for both tasks and were less likely to rely on ordered strategies (e.g., alphabetic search). When participants were instructed to use particular strategies, the visualization strategy resulted in the highest levels of performance and the most efficient search, whereas ordered strategies resulted in the lowest levels of performance and fairly inefficient search. These results are consistent with the notion that retrieval from long-term memory is driven, in part, by search strategies employed by the individual, and that one particularly efficient strategy is to visualize various situational contexts that one has experienced in the past in order to constrain the search and generate the desired information.
TrustRings in mobile wireless network settings

Trust in mobile wireless networks introduces new challenges in addition to the traditional notions of Trust for infrastructure networks. Mobile, wireless and dynamic network settings diversify Trust research in multiple ways. Unfortunately, traditional security concepts, such as Public Key Infrastructures, are not accurate to protect sensitive communication in these special network environments. In this work, we focus on Trust establishment and calculation in mobile wireless networks, which includes Mobile Ad-Hoc Networks known as MANETs. We present our idea of TrustRings which is used to calculate Trust-Values for entities in mobile wireless networks. Our model is based on an egocentric network view which is combined with the location and the distance between communicating devices.
Habit : Leveraging Human Mobility and Social Network for Efficient Content Dissemination in MANETs

Digital content (e.g., music, photos, videos) has become very easy to create and disseminate, thanks to the widespread success of powerful, networked handheld devices. As the volume of content being produced is increasing dramatically, it becomes crucial to be able to filter irrelevant information as early as possible; this is to avoid both network congestion and end-user overload. In order to achieve these goals, this paper proposes Habit, a novel cross-layered approach to content dissemination for mobile ad-hoc networks that leverages information about nodes’ colocation (physical layer) and their social network (application layer). More precisely, the regularity of users’ colocation is learned based on historical colocation observations; also, the users’ social network (or ‘network of interest’) is dynamically propagated during periods of colocation; finally, these distinct pieces of information are locally combined and used to compute the paths that content should follow, in a way that maximises both precision (i.e., nodes receive only content they are interested in) and recall (i.e., all relevant content is received by interested nodes). We demonstrate the effectiveness of the approach by means of simulation using a large set of real world traces.
A Cost Framework Specification for Software Product Lines Scenarios

A large number of software organizations are adopting the software product line approach in their reuse program. One fundamental factor to evaluate cost-benefit of this approach is the practical use of cost models to estimate ROI to a family of products. This paper describes the state of art of cost models for software product lines, presenting the models evolution on the last decade. This work makes a summary of basic reuse cost models and addresses the use of reuse scenarios for ROI estimation. At the end, a framework for ROI estimation in product lines is specified through the definition of a Cost Configuration Model.
Achieving Usability through Software Architecture

Abstract : In this report, we present an approach to improving the usability of software systems by means of software architectural decisions. We identify specific connections between aspects of usability, such as the ability to "undo," and software architecture. We also formulate each aspect of usability as a scenario with a characteristic stimulus and response. For every scenario, we provide an architecture pattern that implements its aspect of usability. We then organize the usability scenarios by category. One category presents the benefits of these aspects of usability to users or their organizations. A second category presents the architecture mechanisms that directly relate to the aspects of usability. Finally, we present a matrix that correlates these two categories with the general scenarios that apply to them.
Target-Specific IPSC Kinetics Promote Temporal Processing in Auditory Parallel Pathways

The acoustic environment contains biologically relevant information on timescales from microseconds to tens of seconds. The auditory brainstem nuclei process this temporal information through parallel pathways that originate in the cochlear nucleus from different classes of cells. Although the roles of ion channels and excitatory synapses in temporal processing have been well studied, the contribution of inhibition is less well understood. Here, we show in CBA/CaJ mice that the two major projection neurons of the ventral cochlear nucleus, the bushy and T-stellate cells, receive glycinergic inhibition with different synaptic conductance time courses. Bushy cells, which provide precisely timed spike trains used in sound localization and pitch identification, receive slow inhibitory inputs. In contrast, T-stellate cells, which encode slower envelope information, receive inhibition that is eightfold faster. Both types of inhibition improved the precision of spike timing but engage different cellular mechanisms and operate on different timescales. Computer models reveal that slow IPSCs in bushy cells can improve spike timing on the scale of tens of microseconds. Although fast and slow IPSCs in T-stellate cells improve spike timing on the scale of milliseconds, only fast IPSCs can enhance the detection of narrowband acoustic signals in a complex background. Our results suggest that target-specific IPSC kinetics are critical for the segregated parallel processing of temporal information from the sensory environment.
A Structural Equation Modelling Analysis of the Relationships between Perceived Occupational Stress, Burnout, and Teacher Resilience

Challenged with the task of effectively performing a wide range of roles and obligations in their work, teachers have one of the most stress-provoking professions. Very much related to teacher stress and role complexity, teacher burnout can be considered as a professional dilemma, which may happen for every teacher during his/her career. This study aimed to investigate the intercorrelations of teaching context, perceived occupational stress, and burnout with the mediating role of teacher resilience among Iranian EFL teachers. To this end, validated versions of four questionnaires were administered to 400 Iranian EFL teachers. The collected data were analyzed via Structural Equation Modeling. The results showed that lack of supervisory support as a dimension of teaching context can affect teachers’ occupational stress more than other dimensions. Moreover, significant positive relationships were found between teachers’ occupational stress and their burnout level. There were also significant negative relationships between teacher resilience and their occupational stress and burnout. It can be stated that teacher resilience has a mediatory role considering the relationship between occupational stress and burnout in that it reduces occupational stress and results in reduction of burnout.
Ranking for Social Semantic Media

This diploma thesis is devoted to the ranking of results returned by search engines. We present a State of the Art which covers the ranking for various datatypes, including the Web, XML, RDF, and folksonomies. For every datatype the calculation of a popularity score as well as the computing of a content score is presented. For most datatypes we also discuss the relevance of two objects to each other. This is especially of interest for RDF data. The purpose of this State of the Art is to provide a decent understanding of the technologies in ranking that exist, so based on that it is easier to either come up with an enhanced ranking algorithm or use the technologies provided here as a basis for developing new algorithms for new datatypes. In particular, to the best of our knowledge there is apparently no ranking scheme available for Social Semantic Wikis, which have both semantic annotations as well as structured data. We provide some suggestions for developing such a new algorithm in the section Conclusion and future work.
Incremental relevance feedback for information filtering

We use data from the TREC routing experiments to explore how relevance feedback can be applied incrementally-using a few judged documents each tim~to achieve results that are as good as if the feedback occurred in one paas. We show that relatively few judgments are needed to get highquality results. We also demonstrate methods that reduce the amount of information archived from past judged documents without adversely tiecting effectiveness. A novel simulation shows that such techniques are useful for handling long-standing queries with drifting notions of relevance.
Unified Analysis of Finite Element Methods for Problems with Moving Boundaries

We present a unified analysis of finite element methods for problems with prescribed moving boundaries. In particular, we study an abstract parabolic problem posed on a moving domain with prescribed evolution, discretized in space with a finite element space that is associated with a moving mesh that conforms to the domain at all times. The moving mesh is assumed to evolve smoothly in time, except perhaps at a finite number of remeshing times where the solution is transferred between finite element spaces via a projection. A key result of our analysis is an abstract estimate for the $L^2$-norm of the error between the exact and semidiscrete solutions at a fixed positive time, expressed in terms of the total variation in time of a quantity that measures the difference between the exact solution at time $t$ and its elliptic projection onto the finite element space at time $t$. Specializing the abstract estimate to particular choices of the mesh motion strategy, finite element space, and projector leads to e.