Miracle-dz/UniFAR-FTUs huggingface dataset:
An Efficient Algorithm for Outlier Detection in High Dimensional Real Databases

Detecting outlier patterns in data has been an important res ea ch topic in statistics, data mining and machine learning commu nities for many years. Research in identifying effective solution s to this problem have several interesting applications in a myr iad of domains ranging from data cleaning to financial fraud detect ion and from network intrusion detection to clinical diagnosis of d iseases. Among the different algorithms, statistical (parametric) approaches and distance-based outlier detection are the most popular i n use. The former is well grounded but often has difficulty scaling t o large and high dimensional data. The latter is relatively ef fici nt and empirically found to be effective on a number of domains b ut scalability is still an issue in spite of a fair bit of researc h on the topic. To address this limitation, in this work, we propose Atalaia , n efficient and scalable distance-based algorithm for detect ing outliers in large high dimensional databases. Central to our al gorithm is a fast strategy to estimate the unusualnessof a record within the database and use a rank-ordered approach to evaluate record s. Our algorithm partitions the database and ranks the objects tha t are candidates to be an outlier, reducing significantly the number o f comparisons among objects. We evaluate different ranking heur istics in a comprehensive set of real and synthetic databases. Furt her, Atalaia also handles heterogeneous databases, i.e, those c ontaining both categorical and continuous attributes. The result s show that our algorithm outperforms by up to 73% the state-of-the -art distance-based outlier detection algorithm.
Virtual typing by people with tetraplegia using a self-calibrating intracortical brain-computer interface

Individuals with tetraplegia are able to type self-paced for hours across multiple days using a self-calibrating point-and-click intracortical brain-computer interface. Prolonged typing with refined BCI The fact that the brain can be hooked up to a computer to allow paralyzed individuals to type is already a technological feat. But, these so-called brain-computer interface technologies can be tiring and burdensome for users, requiring frequent disruptions for recalibration when the decoded neural signals change. Jarosiewicz and colleagues therefore combined three calibration methods—retrospective target interference, velocity bias correction, and adaptive tracking of neural features—for seamless typing and stable neural control. This combination allowed two individuals with tetraplegia and with cortical microelectrode arrays to compose long texts at their own paces, with no need to interrupt typing for recalibration. Brain-computer interfaces (BCIs) promise to restore independence for people with severe motor disabilities by translating decoded neural activity directly into the control of a computer. However, recorded neural signals are not stationary (that is, can change over time), degrading the quality of decoding. Requiring users to pause what they are doing whenever signals change to perform decoder recalibration routines is time-consuming and impractical for everyday use of BCIs. We demonstrate that signal nonstationarity in an intracortical BCI can be mitigated automatically in software, enabling long periods (hours to days) of self-paced point-and-click typing by people with tetraplegia, without degradation in neural control. Three key innovations were included in our approach: tracking the statistics of the neural activity during self-timed pauses in neural control, velocity bias correction during neural control, and periodically recalibrating the decoder using data acquired during typing by mapping neural activity to movement intentions that are inferred retrospectively based on the user’s self-selected targets. These methods, which can be extended to a variety of neurally controlled applications, advance the potential for intracortical BCIs to help restore independent communication and assistive device control for people with paralysis.
Equity Price Dynamics in Thin Emerging Markets of Central and Eastern Europe

This paper investigates the apparent co-movement of equity prices in the Czech Republic, Hungary and Poland. The main underlying force moving stock prices in these countries is argued to be the inflow and outflow of foreign capital. Since the inflow of foreign investment to these markets is an unobservable variable, it is modelled as a two- state Markov chain. This latent variable is driving the stock returns process and makes it switch from a high growth regime to a depression regime, or vice versa. In such a framework, the stock return process comes from a mixture of two normal distributions with different means. This is modelled using the vector Markov switching method of Hamilton (1989, 1990). The estimated process shows significant correlation with a number of data series on global capital flows. The paper applies the Hamilton technique to the new dataset and, most importantly, it builds an empirical model for the stock returns of the `thin' emerging markets of Central and Eastern Europe.
Parallel scale space construction using SIMD hypercube

This paper proposes parallel scale space construction of Scale Invariant Feature Transform (SIFT) using SIMD hypercube. The parallel SIFT approach is used for iris feature extraction. The input iris images and Gaussian filters are mapped to each processor in the hypercube and convolution takes place in each processor concurrently. The time complexity of parallel algorithm is O(N2) whereas sequential algorithm performs with complexity of O(lsN2), where l is the number of octaves, s is the number of Gaussian scale levels within an octave for N2 sized iris image.
A Hybrid Technique for De-interlacing Based on Motion Compensation Reliability

Although motion compensated interpolation (MCI) improves the vertical resolution of de-interlaced frames effectively, it often introduces serious defects like feathering artifacts. In this paper, we propose an arbitration rule between MCI and intra-field interpolation for de-interlacing to avoid the motion compensation artifacts (MCAs) produced by erroneous MCI. In the proposed deinterlacing method, we check the MCI results by using the proposed MCA detection method and decide whether the MCI results are reliable or not. And then, we use the reliability of MCI results to combine two de-interlacing methods. The proposed arbitration method is more elaborate than conventional methods since we directly detect the artifacts in MCI results and the reliability of MCI results is used as one of the important factors of the proposed arbitration weights. Experimental results show that the proposed method achieves better image quality than the conventional methods in terms of both subjective and objective measures.
Many-to-one contagion of economic growth rate across trade credit network of firms

We propose a novel approach and an empirical procedure to test direct contagion of growth rate in a trade credit network of firms. Our hypotheses are that the use of trade credit contributes to contagion (from many customers to a single supplier - "many to one" contagion) and amplification (through their interaction with the macrocopic variables, such as interest rate) of growth rate. In this paper we test the contagion hypothesis, measuring empirically the mesoscopic "many-to-one" effect. The effect of amplification has been dealt with in another paper. Our empirical analysis is based on the delayed payments between trading partners across many different industrial sectors, intermediated by a large Italian bank during the year 2007. The data is used to create a weighted and directed trade credit network. Assuming that the linkages are static, we look at the dynamics of the nodes/firms. On the ratio of the 2007 trade credit in Sales and Purchases items on the profit and loss statements, we estimate the trade credit in 2006 and 2008. Applying the "many to one" approach we compare such predicted growth of trade (demand) aggregated per supplier, and compare it with the real growth of Sales of the supplier. We analyze the correlation of these two growth rates over two yearly periods, 2007/2006 and 2008/2007, and in this way we test our contagion hypotheses. We could not find strong correlations between the predicted and the actual growth rates. We provide an evidence of contagion only in restricted sub-groups of our network, and not in the whole network. We do find a strong macroscopic effect of the crisis, indicated by a coincident negative drift in the growth of sales of nearly all the firms in our sample.
Regionalisation and rural development in England

This is a study of the discourses of regionalisation and rural development in England. The thesis examines the impact of New Labour‟s period of regionalisation from 1997 to 2008 on the policy and practice of rural development. A Foucauldian inspired discourse analysis reveals the patterns of power relations between national, regional and local actors, networks and governance structures, contributing to our understanding of political change. Regionalisation has resulted in changes both to rural policy and the practices of governing. Previous studies have emphasised the contrast between the rhetoric of devolution and the extent to which the state retains control by extending its power to the devolved scale. A framework of four discourses combines these contrasting notions to form four discourses of the region – “participatory development”, “administrative regionalism”, “participatory regionalism” and “regional autonomy”. Non-government actors express their choices, captured in three discourses of response – “buying into regionalism, “reluctant regionalism” and “local autonomy” – highlighting the complexity of regional/local power relations. The discourses illustrate regional difference and shed light on how and why divergence has taken place. The research was conducted through documentary analysis, and interviews in two case study regions of the North West and East of England. The discourses are drawn from the language of rural actors in each region. Employment as a rural development practitioner gave the researcher „insider‟ knowledge and understanding, whilst the discipline of an academic and reflexive approach aided an „outsider‟ view, with both identities contributing to the research. The research found some differences between English regions and between regional government agencies, as a consequence of devolution. Nevertheless, the discursive practices centre on realising state plans. Furthermore, regionalisation restricts the choices available to the local level, compromising capacity building and participation in rural development, long recognised by researchers as critical aspects of successful rural development. Local plans were formulated on the basis of a generic, homogenous territory, marking a fundamental change from previous territorial rural programmes.
Profit-Based Caching for Information-centric Network

In-network caching as one of the primary components for ICN (information-centric network) has attracted more and more attentions. In this paper, we present a profit-based caching for ICN. The profit value for the content arriving on a router is determined by request popularity, distance to content source, content size and content duration, etc. The content duration is considered as an important factor in methodology to avoid the error caused by storing the overdue contents, which is the main difference from existing caching scheme. A 0-1 ILP (integer linear programming) is used to formulate whether to cache the coming content or not and eviction objects simultaneously. Also, a near-optimal heuristic algorithm is proposed to find profit-efficient cache decision, which can be quickly deployed. The analytical and simulation results show our profit-based caching scheme can attain a better network profit compare to Least Frequently used (LFU), and totally avoids caching withdrawing contents.
On the Modelling of Prosodic Cues in Synthetic Speech: What Are the Effects on Perceived Uncertainty and Naturalness?

In this paper we present work on the modelling of uncertainty by means of prosodic cues in an articulatory speech synthesizer. Our stimuli are embedded into short dialogues in question-answering situations in a human-machine scenario. The answers of the robot vary with respect to the intended level of (un)certainty, the independent variables are intonation (rising vs. falling) and filler (absent vs. present). We perform a perception study in order to test the relative impact of the prosodic cues of uncertainty on the perception of uncertainty and also of naturalness. Our data indicate that the cues of uncertainty are additive. If both prosodic cues of uncertainty are present, the perceived level of uncertainty is higher as opposed to the deactivation of a single cue. Regarding the relative contribution of intonation vs. filler our results do not show a significant difference between judgments. Moreover, the correlation between the judgment of uncertainty and of naturalness is not significant.
A low cost polyimide based metal oxide film RH sensor

A simple flexible metal oxide (γ-Al2O3) film based parallel plate capacitive humidity sensor has been fabricated by sol-gel method on UPILEX-S polyimide substrate for measuring relative humidity (RH). The important features of the sensor are easy to fabricate, no shorting problem, highly flexible, bulk producible and can be integrated with signal conditioning unit. The characteristics of the sensor have been studied with humidity in the range of 5 to 85 % RH. The measured sensitivity of the sensor is 4.044 pF/% RH The sensor output is found to be highly stable and reproducible up to 0.4% The response and recovery time are 244s and 159s respectively.
MEAN VARIANCE PREFERENCES, EXPECTATIONS FORMATION, AND THE DYNAMICS OF RANDOM ASSET PRICES

This paper analyzes the dynamics of an explicit random process of prices and price expectations of finitely many assets in an economy with overlapping generations of heterogeneous consumers. They maximize expected utility with respect to subjective transition probabilities defined by Markov kernels which describe the forecasting behavior of agents. Given such forecasting rules (predictors) and an exogenous process of dividends, the evolution of equilibrium asset prices and expectations is described by a random dynamical system in the sense of Arnold (1998) . The paper investigates the long‐run behavior (stationary solutions) by proving the existence and stability of random fixed points for mean‐variance preferences under various predictors, including unbiased predictions, and adaptive, as well as OLS forecasting. An explicit characterization of rational expectations solutions is given, providing a full dynamic characterization of asset price processes for the classical CAPM in the case of stationary OLG economies. Numerical simulations are used to compare the performance of the different predictors under an AR(1) dividend process.
Direct Accessible Filter Using Succinct Data Structure for Packet Filtering

Packet filtering is a function to determine whether a packet is allowed to forward or not by applying rules to a packet. Filtering packets can improve security and performance. Linear search is the simplest and a storage-efficient algorithm. The time to filter a packet grows linearly with the number of rules. If an action list which stores actions (allow or drop) for all manner of packet headers is pre-computed from a rule set, routers can filter a packet in constant time. The list is called Direct Accessible Filter (DAF) in this paper. However, DAF requires large storage. This paper proposes DAF using succinct data structures which are low storage requirement and support fast query. We apply succinct representation techniques to DAF and aim at low storage requirement. Theoretical and experimental results show that DAF using succinct data structure enjoys low storage requirement and constant search speed.
B2b, old economy businesses and the role of quality: part 2 – the more complex possibilities

This paper explores the impact of the Internet on the business transactions of organisations. Three main impacts – globalisation, customisation, and customer demand solutions – are examined. It is argued that the medium and large old economy companies will be most affected by transactions within the new economy, and this leads to both problems and possibilities. The paper has identified three major ways in which these old economy companies are attempting to integrate the new economy as a development of their current business – treating the Net as an extension of their normal service, using the Net to expand and improve their current co‐makership relationship with suppliers, and a step‐back‐and‐reflect approach to assess how the Internet might affect their business.
Chronotherapy with low-dose modified-release prednisone for the management of rheumatoid arthritis: a review

To date, rheumatoid arthritis (RA) remains a debilitating, life-threatening disease. One major concern is morning symptoms (MS), as they considerably impair the patients’ quality of life and ability to work. MS change in a circadian fashion, resembling the fluctuations of inflammatory cytokines such as interleukin-6, whose levels are higher in RA patients compared to healthy donors. Conversely, serum levels of the potent anti-inflammatory glucocorticoid cortisol are similar to that of healthy subjects, suggesting an imbalance that sustains a pro-inflammatory state. From a therapeutic point of view, administering synthetic glucocorticoids (GCs) to RA patients represents an optimal strategy to provide for the inadequate levels of cortisol. Indeed, due to their high efficacy in RA, GCs remain a cornerstone more than 60 years after their first introduction, and despite the development of a wide range of targeted agents. However, to improve safety, low-dose GCs have been introduced, that have demonstrated high efficacy in reducing disease activity, radiological progression, and improving patients’ signs and symptoms especially in early RA when added to conventional disease-modifying antirheumatic drugs. A further improvement has been provided by the development of modified-release prednisone, which, by taking advantage of the circadian fluctuations of inflammatory cytokines, cortisol and MS, is given at bedtime to be released approximately 4 hours later. Several studies have already demonstrated the efficacy of this agent on disease activity, MS, and quality of life in the setting of established RA. Moreover, preliminary studies have shown that this new formulation not only has no impact on the adrenal function, but likely improves it. This review is a comprehensive, updated summary of the current evidence on the use of GCs in RA, with focus on the efficacy and safety of low-dose prednisone and modified-release prednisone, the latter representing a rational, cost-effective, and tailored approach to maximize the benefit/risk ratio in RA patients.
Doppler radar and postprocessing techniques for small area surveillance

In this paper the use of Doppler signatures for human motion detection is presented. This can be of interest during search and rescue missions where visibility can be poor or even absent. Human movements give rise to specific Doppler frequencies. Their corresponding speeds can be exploited for recognition and can be visualized by means of reassigned spectrograms. A simulation tool is developed and validated by measurements. Scenarios with increasing complexity are treated.
Mutational Pathways, Resistance Profile, and Side Effects of Cyanovirin Relative to Human Immunodeficiency Virus Type 1 Strains with N-Glycan Deletions in Their gp120 Envelopes

ABSTRACT Limited data are available on the genotypic and phenotypic resistance profile of the α-(1-2)mannose oligomer-specific prokaryotic lectin cyanovirin (CV-N). Therefore, a more systematic investigation was carried out to obtain a better view of the interaction between CV-N and human immunodeficiency virus type 1 (HIV-1) gp120. When HIV-1-infected CEM cell cultures were exposed to CV-N in a dose-escalating manner, a total of eight different amino acid mutations exclusively located at N-glycosylation sites in the envelope surface gp120 were observed. Six of the eight mutations resulted in the deletion of high-mannose type N-glycans (i.e., at amino acid positions 230, 332, 339, 386, 392, and 448). Two mutations (i.e., at position 136 and 160) deleted a complex type N-glycan in the variable V1/V2 domain of gp120. The level of phenotypic resistance of the mutated virus strains against CV-N generally correlated with the number of glycan deletions in gp120, although deletion of the glycans at N-230, N-392, and N-448 generally afforded a more pronounced CV-N resistance than other N-glycan deletions. However, the extent of the decrease of antiviral activity of CV-N against the mutated virus strains was markedly less pronounced than observed for α(1-3)- and α(1-6)-mannose-specific plant lectins Hippeastrum hybrid agglutinin (HHA) and Galanthus nivalis agglutinin (GNA), which points to the existence of a higher genetic barrier for CV-N. This is in agreement with a more consistent suppression of a wider variety of HIV-1 clades by CV-N than by HHA and GNA. Whereas the antiviral and in vitro antiproliferative activity of CV-N can be efficiently reversed by mannan, the pronounced mitogenic activity of CV-N on peripheral blood mononuclear cells was unaffected by mannan, indicating that some of the observed side effects of CV-N are unrelated to its carbohydrate specificity/activity.
Curbing cyber-crime and Enhancing e-commerce security with Digital Forensics

The explosion in the e-commerce industry which has been necessitated by the growth and advance expansion of Information technology and its related facilities in recent years have been met with adverse security issues consequently affecting the industry and the entire online activities. This paper exams the prevailing security threats e-commerce is facing which is predominantly known as cyber-crime and how computer related technology and facilities such as digital forensics tools can be adopted extensively to ensure security in online related business activities. This paper investigated the risk, damage and the cost cyber-crime poses to individuals and organizations when they become victims. As it is obvious transacting business online as well as all related online activities has become inherent in our everyday life. The paper also comprehensively elucidate on some of the cyber-crime activities that are posing serious threat to the security of E-commerce. Amazon and eBay were used as the case of study in relation to respondents who patronizes these renowned e-commerce sites for various transactions. Keywords: E-commerce Security,Cyber-Crime,digital forensics, Network forensics, Network security, Online transactions, Identity theft, hacking.
Optimal controller placement in Software Defined Networks (SDN) using a non-zero-sum game

In this paper, we discuss optimal controller placement for Software Defined Networks (SDN) and propose a non-zero-sum game based distributed technique. Our proposed technique is a simple and low-complexity solution which runs in real-time. This can be implemented as an optimization engine at each SDN controller. The optimization engine at each controller computes a payoff function and compares its own payoff value with that of neighbors and takes appropriate decisions such that either new controllers should be added, or existing controllers should be deleted or offloading should be performed between controllers dynamically. We have conducted extensive simulations and verified the usability of the proposed scheme. We also propose a deployment framework which can be implemented using OpenFlow enabled platforms. Use of this technique not only can improve Quality of Services (QoS - minimum packet drops and delay) but also can save cost of deployment and operation.