Miracle-dz/UniFAR-FTUs huggingface dataset:
Sparse binary matrices as efficient associative memories

Associative memories are widely used devices which can be viewed as universal error-correcting decoders. Employing error-correcting code principles in these devices has allowed to greatly enhance their performance. In this paper we reintroduce a neural-based model using the formalism of linear algebra and extend its functionality, originally limited to erasure retrieval, to handle approximate inputs. In order to perform the retrieval, we use an iterative algorithm that provably converges. We then analyze the performance of the associative memory under the assumption of connection independence. We support our theoretical results with numerical simulations.
of the BUSINESS AND HEALTH ADMINISTRATION ASSOCIATION CHICAGO , IL March 23-25 , 2011

As Electronic Medical Records (EMR) Systems increase in popularity among medical facilities, so will the questions surrounding their ability to have an effect on productivity. With any business, increased productivity generally means greater revenues, and medical facilities are no different. If a medical facility is looking to implement an EMR system, they should be aware, not only of what the system can offer, but the different ways that it can affect productivity.In this study, data was collected from local medical facilities to see what kind of effect implementing an EMR system has on their productivity. Productivity was based on four variables: filing time, labor hours spent entering charges, accuracy of entering charges, and revenues. Monthly data was collected on each variable and each facility was asked to obtain six months of data before the system was implemented and six months of data after the system was implemented. Although no significant differences were found between the months before the system was implemented and the months following the implementation, this doesn‘t mean that these systems have a negative effect on productivity.
Constraining the Cosmological Density of Compact Objects with the Long-Term Variability of Quasars

Most of the matter in the Universe appears to be in some form which does not emit or absorb light. While evidence for the existence of this dark matter has accumulated over the last seventy years, its nature remains elusive. In this thesis, quasars and low surface brightness galaxies (LSBGs) are used to investigate the properties of the dark matter. Quasars are extremely bright light sources which can be seen over vast distances. These cosmic beacons may be used to constrain dark matter in the form of low-mass, compact objects along the line of sight, as such objects are expected to induce brightness fluctuations in quasars through gravitational microlensing effects. Using a numerical microlensing model, we demonstrate that the uncertainty in the typical size of the optical continuum-emitting region in quasars represents the main obstacle in this procedure. We also show that, contrary to claims in the literature, microlensing fails to explain the observed long-term optical variability of quasars. Here, quasar distances are inferred from their redshifts, which are assumed to stem from the expansion of the Universe. Some astronomers do however defend the view that quasar redshifts could have a different origin. A number of potential methods for falsifying claims of such non-cosmological redshifts are proposed. As the ratio of dark to luminous matter is known to be unusually high in LSBGs, these objects have become the prime targets for probing dark matter halos around galaxies. Here, we use spectral evolutionary models to constrain the properties of the stellar populations in a class of unusually blue LSBGs. Using rotation curve data obtained at the ESO Very Large Telescope, we also investigate the density profiles of their dark halos. We find our measurements to be inconsistent with the predictions of the currently favoured cold dark matter scenario.
A New Current Probe with a Wide Bandwidth

We present a new isolated current probe for power applications based on a Hall sensor as well as on a Rogowski coil. Employing these two sensors allows to eliminate the integrator circuit needed for the Rogowski signal. With this new probe DC currents as well as current transients with di/dt's of several kA/us can be measured.
A hybrid feature selection method for high-dimensional data

Feature selection is one of the important preprocessing steps in analyzing high dimensional datasets. In this paper, first the ensemble of three different filter ranking methods including: Information Gain (IG), ReliefF and F-score are used to reduce the dimension of datasets. Afterward, reduced data are utilized as inputs of the meta-heuristic algorithm, Improved Binary Gravitational Search Algorithm (IBGSA), for selecting optimal subset of features with highest classification accuracy rate. In order to evaluate the proposed method, it is applied to several high-dimension standard datasets and the results in terms of classification accuracy and feature reduction rate are presented. The experimental results confirm the capability of the proposed algorithm.
Modified Principal Curves Based Fingerprint Minutiae Extraction and Pseudo Minutiae Detection

It is difficult but crucial for minutiae extraction and pseudo minutiae deletion of low quality fingerprint images in auto fingerprint identification systems. Traditional methods based on thinning images or gray-level images are, however, susceptible to noise. Reference 14 indicated that principal curves based fingerprint minutiae extraction was feasible to overcome the drawback, but the extended polygonal line (EPL) principal curves algorithm used in the paper extracted the principal curves ineffectively. As the fingerprint data sets are usually large, the original EPL principal curves algorithm is time-consuming. Meanwhile, scattered fingerprint data lead to the deviation of fingerprint skeleton. In this paper, the algorithm is modified, and a fingerprint minutiae extraction and pseudo minutiae detection method based on principal curves is proposed. Experimental results show that the modified EPL principal curves algorithm outperforms the original EPL algorithm both in efficiency and quality, and the proposed minutiae extraction method outperforms the methods proposed by Miao under noise conditions.
The Impact of L2 Learning on Working Memory: A Case of Iranian Intermediate EFL Learners

The impact, effect and agreement of working memory on second language learning has received some attention in L2 research. However, there seems to be a massive gap regarding the reverse, i.e. the effect of second language learning on working memory. Cognitive advantages of learning a second language are presumed to derive from the requirement to continuously control the activation of lexical representations from the non-target language in a way that they have no interference with the ongoing language processing (Green, 1998). The present study draws on one of the most prominent models for working memory put forward by Baddeley and Hitch (1974). This study attempts to assess the impact of learning a second language on the aforementioned components of the participants' short term memory. For the sake of the study, 48 participants (aged14-16 at the beginning of the study) were selected out of which 24 had just started attending English language classes in Zabansara Language Institute and the other half had been studying English in the same institute for 3 years in Astaneh, Guilan. The instruments employed were the Non-word test, the digit span test, the questionnaire based on Wechsler Adult Intelligence Scale; WAIS (1930) and Corsi Block Tapping –Test (1970) to assess the short term memory of the participants with different language learning backgrounds. The statistical analyses of the results provide evidence in support of the effect of background of learning English as a second language on the improvement of short term memory.
A reappraisal for the digital era

This article suggests that the Chicago School’s use of ecological metaphors has much to offer scholars interested in the complexities of the contemporary media environment. The article opens by considering how the use of ecological metaphors enabled the Chicago School to build an empirical and progressive approach to the study of human forms of organization. It then traces how the use of ecological metaphors has evolved in subsequent scholarship on media and communications. It examines the interest of media ecology scholars in the environment created by technologies, and discusses how proponents of actor network theory have expanded the view of networked actors to encompass technologies, objects and human agents. The article subsequently traces a more recent proliferation of ecological metaphors as a way of understanding globalized and networked media practices. This approach, in turn, enables the reconfiguration of questions around the relationship between media, democracy and citizenship. The paper ultimately suggests that the use of ecological approaches enables scholars to pay attention to the complexities of networked interactions in communities that are geographically bounded but globally connected. This, in turn, points the continued importance of grounded, nitty-gritty empirical work tracing the variety of communicative practices within particular communities, and the ways in which these practices are shaped by relationships between a variety of actors within and beyond these communities.
Structural studies on induced antibodies with defined idiotypic specificities. IX. Framework differences in the heavy- and light-chain- variable regions of monoclonal anti-p-azophenylarsonate antibodies from A/J mice differing with respect to a cross-reactive idiotype

Amino terminal amino acid sequence analyses have been performed on the heavy and light chains of induced monoclonal antibodies with specificity for the hapten p-azophenylarsonate. Four of the eight antibodies react with conventional antisera to the previously described A/J anti-arsonate cross-reactive idiotype (CRI). Of the 16 chains analyzed, all but one contain sequence differences in their first framework segment (residues 1-30) that distinguish them from the heavy- and light-chain sequences found in anti-arsonate antibodies isolated from A/J serum or ascites fluid. The presence of such framework differences appears to be independent of whether or not the hybridoma antibodies bear the CRI. In spite of the framework substitutions, all four of the CRI-positive hybridoma antibodies have variable (V)-region frameworks that are very similar to each other and to the CRI-positive molecules found in A/J serum. Two of the four CRI-negative molecules are also structurally similar to the serum antibodies. Two others, however, are strikingly different from any serum anti-arsonate antibody thus far described and appear to reflect a completely separate repertoire of anti-arsonate antibodies in the A/J MOUSE. In addition, serological analyses with an anti-idiotypic antiserum generated against a CRI-positive hybridoma product suggest that each monoclonal antibody may possess individual antigenic specificities different from the determinant(s) detected with the conventional rabbit anti-CRI. The consistent appearance of framework substitutions in what has been thought to be a homogeneous antibody population has important implications for our understanding of the generation of antibody diversity and for the precise chemical definition of an idiotype.
InSide: Interactive Sketching for Image Database Exploration

We propose an interactive sketching tool for exploring image database, called InSide. Our main contribution is a new solution of interactive image exploration that dynamically adapts to users' sketching and provides mixed feedback. A position-aware matching approach is proposed for InSide in order to support translation-free sketch searching. Based on demonstrated results, our method outperforms state-of-the-art approaches in aspects of user interface and matching results.
Enabling high-speed turbo-decoding through concurrent interleaving

Turbo-codes are among the most advanced channel coding schemes and are already part of the 3rd generation wireless communication standards. Future applications, however, will have a demand for higher throughput than the currently targeted 2 Mbit/s, leading to a need for highly parallelized architectures for turbo-decoding. Those where until now nearly infeasible because the component decoders are separated by interleavers, which form a bottleneck between them. This paper presents for the first time architectures that perform concurrent instead of sequential interleaving, thus widening the interleaver bottleneck and enabling parallelized high-speed turbo-decoders. As no limitations on the interleaver design are implied, standard compliant turbo-decoders for high throughput are now feasible. Optimizations for high degrees of parallelization are derived, applied, and validated using our simulated and synthesized register transfer level model. Thus, a whole design space is provided instead of just a single architecture.
Dispatch of mobile sensors in the presence of Obstacles Using Modified Dijkstra Algorithm

A hybrid wireless sensor network consists of both static sensor and mobile sensor nodes. Static sensors monitor the environment and report events occurring in the sensing field. Mobile sensors are then dispatched to visit these event locations to conduct more advanced analysis. The sensing field may contain obstacles. A big challenge is how to dispatch the mobile sensor to the event location without colliding with any obstacles and mobile sensor should reach the event location in a shortest path. Therefore the objective of the paper is to dispatch the mobile sensor to the event location in a shortest collisionfree path. This paper gives a modified dijkstra’s algorithm to dispatch mobile sensor from its position to the event location. Our solution proposes a simple way to dispatch the mobile sensor to the event location in the presence of obstacle with modified dijkstra’s algorithm. This paper contributes in defining a more general and easiest dispatch solution in the presence of obstacles.
Stress-induced plasticity of GABAergic inhibition

GABAergic neurotransmission is highly plastic, undergoing dynamic alterations in response to changes in the environment, such as following both acute and chronic stress. Stress-induced plasticity of GABAergic inhibition is thought to contribute to changes in neuronal excitability associated with stress, which is particularly relevant for stress-related disorders and seizure susceptibility. Here we review the literature demonstrating several mechanisms altering GABAergic inhibition associated with stress, including brain region-specific alterations in GABAA receptor (GABAAR) subunit expression, changes in chloride homeostasis, and plasticity at GABAergic synapses. Alterations in the expression of specific GABAAR subunits have been documented in multiple brain regions associated with acute or chronic stress. In addition, recent work demonstrates stress-induced alterations in GABAergic inhibition resulting from plasticity in intracellular chloride levels. Acute and chronic stress-induced dephosphorylation and downregulation of the K+/Cl− co-transporter, KCC2, has been implicated in compromising GABAergic control of corticotropin-releasing hormone (CRH) neurons necessary for mounting the physiological response to stress. Acute stress also unmasks the capacity for both long-term potentiation and long-term depression, in distinct temporal windows, at GABAergic synapses on parvocellular neuroendocrine cells (PNCs) in the paraventricular nucleus (PVN) of the hypothalamus. This review highlights the complexity in the plasticity of GABAergic neurotransmission associated with stress and the relationship to neuronal excitability, including alterations in GABAAR expression, synaptic plasticity at GABAergic synapses, and changes in chloride homeostasis.
Molecular Recognition of PTS-1 Cargo Proteins by Pex5p: Implications for Protein Mistargeting in Primary Hyperoxaluria

Peroxisomal biogenesis and function critically depends on the import of cytosolic proteins carrying a PTS1 sequence into this organelle upon interaction with the peroxin Pex5p. Recent structural studies have provided important insights into the molecular recognition of cargo proteins by Pex5p. Peroxisomal import is a key feature in the pathogenesis of primary hyperoxaluria type 1 (PH1), where alanine:glyoxylate aminotransferase (AGT) undergoes mitochondrial mistargeting in about a third of patients. Here, we study the molecular recognition of PTS1 cargo proteins by Pex5p using oligopeptides and AGT variants bearing different natural PTS1 sequences, and employing an array of biophysical, computational and cell biology techniques. Changes in affinity for Pex5p (spanning over 3–4 orders of magnitude) reflect different thermodynamic signatures, but overall bury similar amounts of molecular surface. Structure/energetic analyses provide information on the contribution of ancillary regions and the conformational changes induced in Pex5p and the PTS1 cargo upon complex formation. Pex5p stability in vitro is enhanced upon cargo binding according to their binding affinities. Moreover, we provide evidence that the rational modulation of the AGT: Pex5p binding affinity might be useful tools to investigate mistargeting and misfolding in PH1 by pulling the folding equilibria towards the native and peroxisomal import competent state.
Parallel sorting on Intel Single-Chip Cloud computer

The Single-Chip Cloud Computer (SCC) is an experimental processor created by Intel Labs. It comprises 48 x86 cores linked by an on-chip high performance network, as well as four DDR3 memory controllers to access an off-chip main memory of up to 64GiB. This work evaluates the performance of the SCC when accessing the off-chip memory. The focus of this study is not on taxing the bare hardware. Instead, we are interested in the performance of applications that run on the Linux operating system and use the SCC as it is provided. We see that the per-core read memory bandwidth is largely independent of the number of cores accessing the memory simultaneously, but that the write memory access performance drops when more cores write simultaneously to the memory. In addition, the global and per-core memory bandwidth, both writing and reading, depends strongly on the memory access pattern.
Graduated Response Policy and the Behavior of Digital Pirates: Evidence from the French Three-Strike (Hadopi) Law

Most developed countries have tried to restrain digital piracy by strengthening laws against copyright infringement. In 2009, France implemented the Hadopi law. Under this law individuals receive a warning the first two times they are detected illegally sharing content through peer to peer (P2P) networks. Legal action is only taken when a third violation is detected. We analyze the impact of this law on individual behavior. Our theoretical model of illegal behavior under a graduated response law predicts that the perceived probability of detection has no impact on the decision to initially engage in digital piracy, but may reduce the intensity of illegal file sharing by those who do pirate. We test the theory using survey data from French Internet users. Our econometric results indicate that the law has no substantial deterrent effect. In addition, we find evidence that individuals who are better informed about the law and piracy alternatives substitute away from monitored P2P networks and illegally access content through unmonitored channels.
Developing Software Bug Prediction Models Using Various Software Metrics as the Bug Indicators

The bug prediction effectiveness reasonably contributes towards enhancing quality of software. Bug indicators contribute significantly in determining the bug prediction approaches and help in achieving software reliability. Various comparative research studies have indicated that Depth of Inheritance (DIT), Weighted Method per Class (WMC), Coupling between Objects (CBO) and Lines of Code (LoC) have significantly established themselves as reliable bug indicators for comprehensive bug predictions. The researchers have carried out a quantitative research and have developed prediction models using above bug indicators as models input and have applied these models on open source projects (Camel and Ant). During this research, the results demonstrates that there is significant correlation between size oriented metrics (bug indicators) such as DIT, WMC, CBO, LoC and bugs. Overall, DIT takes dominance in achieving better impact on predicting bugs than WMC, CBO and LoC. The outcomes of the present research study would be of significance to software quality practitioners worldwide and would help them in prioritizing the efforts involved in bug prediction.
A Scalable, Portal-Based Interface for Managing Applications in Interactive Workspaces

Iconic interfaces have been used to enable users to visually manage applications in interactive workspaces. However, current implementations do not scale for larger numbers of applications and do not allow users to maintain adequate awareness of collaborator activities. Following an iterative design process and building on our previous work, we developed a new iconic interface called SEAPort. Our new interface uses zooming and animation-based interactions to improve scalability and uses application icons and thumbnails to improve awareness. Results from a user study validate these claims. The interaction techniques are applicable to the broader class of iconic and portal-based interfaces. ACM Classification: H.5. 2 User Interfaces, H.5. 3.b Collaborative Computing, C.3. h Ubiquitous Computing.
Writer dependent online handwriting generation with Bayesian network

In this paper, we propose a method to generate writer dependent (WD) handwritings. We modelled the shape of character both globally and locally with probabilistic relationships between character components. Then writer independent (WI) model was trained with lots of data. Once WI model was built, the model was adapted to a training example to maximize likelihood of the example by minimization of squared error between model and instance. The experimental results of WI numeral character generation showed that global shape consistencies and variabilities of local shape were preserved. The relationships from WI model were still valid in WD models by proposed adaptation technique so that we could generate natural-looking writer specific handwritings.
Multispecialist System for 3D Scene Analysis

This paper presents a scene analysis system, called MESSIE, in a 3D robotic context. It is a blackboard based multispecialist system. The basic architecture of MESSIE has been extended to meet the requirements of a vision reasoning system for a robotic platform and to generalize the application domain of our previous works 7, 4, 3, 5]. In the rst part, we present the system architecture and the models of objects , scene and sensors and the diierent interpretation and detection strategies. After, we present current experiments on indoor scene interpretation and an interpretation running example using constrained low-level feature extraction mechanism to improve low-level processing results.