Miracle-dz/UniFAR-FTUs huggingface dataset:
Thin plate regression splines

Summary. I discuss the production of low rank smoothers for d ≥ 1 dimensional data, which can be fitted by regression or penalized regression methods. The smoothers are constructed by a simple transformation and truncation of the basis that arises from the solution of the thin plate spline smoothing problem and are optimal in the sense that the truncation is designed to result in the minimum possible perturbation of the thin plate spline smoothing problem given the dimension of the basis used to construct the smoother. By making use of Lanczos iteration the basis change and truncation are computationally efficient. The smoothers allow the use of approximate thin plate spline models with large data sets, avoid the problems that are associated with ‘knot placement’ that usually complicate modelling with regression splines or penalized regression splines, provide a sensible way of modelling interaction terms in generalized additive models, provide low rank approximations to generalized smoothing spline models, appropriate for use with large data sets, provide a means for incorporating smooth functions of more than one variable into non‐linear models and improve the computational efficiency of penalized likelihood models incorporating thin plate splines. Given that the approach produces spline‐like models with a sparse basis, it also provides a natural way of incorporating unpenalized spline‐like terms in linear and generalized linear models, and these can be treated just like any other model terms from the point of view of model selection, inference and diagnostics.
Novel presentation attack detection algorithm for face recognition system: Application to 3D face mask attack

The face biometric systems are highly vulnerable for the presentation attack that can be carried out by presenting a photo or video or even a 3D mask. In this paper, we present a novel Presentation Attack Detection (PAD) algorithm that can accurately detect and mitigate the 3D mask attacks on a face recognition system. The proposed scheme extracts both local and global features from the captured face image. The local features employed in this work corresponds to the eye (periocular) and nose region that are expected to provide clue on the presence of the mask. In addition, we also capture the micro-texture variation as a global feature using Binarized Statistical Image Features (BSIF). We then train a linear Support Vector Machine (SVM) independently on these two features whose scores are fused using the weighted sum rule before making the decision about a real face or an artefact. Extensive experiments are carried out on the public 3D mask database 3DMAD that shows the superiority of the proposed scheme with an outstanding performance of HTER = 0.03%.
DESIGN OF MIMO SYSTEM WITH ENHANCED PERFORMANCE

The next generation of broadband wireless communication system is expected to provide user with wireless multimedia services such as high-speed internet access, wireless television and mobile television. Multiple input and multiple output (MIMO) can be a solution for such demands. In MIMO systems, multiple antennas at both transmitter & receiver and diversity techniques can be used to reduce multi-path fading and interference. But transmit diversity scheme are growing increasingly popular as they promise high data rate transmission over wireless fading channels in both the uplink and downlink while putting the diversity burden on the base station and the coding schemes like space time block coding and space time trellis coding are explored, out of which space time block codes provide full diversity with no coding gain and space time trellis coding provides full diversity and coding gain with complex receivers. This paper presents the design of a MIMO system which takes advantage of both these coding schemes.
An empirical comparison of social, collaborative filtering, and hybrid recommenders

In the Social Web, a number of diverse recommendation approaches have been proposed to exploit the user generated contents available in the Web, such as rating, tagging, and social networking information. In general, these approaches naturally require the availability of a wide amount of these user preferences. This may represent an important limitation for real applications, and may be somewhat unnoticed in studies focusing on overall precision, in which a failure to produce recommendations gets blurred when averaging the obtained results or, even worse, is just not accounted for, as users with no recommendations are typically excluded from the performance calculations. In this article, we propose a coverage metric that uncovers and compensates for the incompleteness of performance evaluations based only on precision. We use this metric together with precision metrics in an empirical comparison of several social, collaborative filtering, and hybrid recommenders. The obtained results show that a better balance between precision and coverage can be achieved by combining social-based filtering (high accuracy, low coverage) and collaborative filtering (low accuracy, high coverage) recommendation techniques. We thus explore several hybrid recommendation approaches to balance this trade-off. In particular, we compare, on the one hand, techniques integrating collaborative and social information into a single model, and on the other, linear combinations of recommenders. For the last approach, we also propose a novel strategy to dynamically adjust the weight of each recommender on a user-basis, utilizing graph measures as indicators of the target user's connectedness and relevance in a social network.
An Advanced Deburring and Chamfering System

A second-generation automated deburring cell is currently under development at the National Institute of Standards and Technology. This cell will be capable of automatically generating, from part geometry and machining information, a series of robot paths for deburring aerospace parts made from superalloys. In order to compensate for the inaccuracy of robots when following computed coordinates, an actively-controlled end effector will be used to precisely position a rotary file in response to forces sensed at the part edge.
A NALYSIS OF THE D YNAMICS OF R EASONING T ASKS : I NTRODUCTION 1 Part C Chapter 1 Analysis of the Dynamics of Complex Reasoning Tasks : Introduction

Within specific domains such as in medicine, humans perform complex tasks that require both knowledge of the domain and knowledge of how to reason to solve a specific type of problem. For example, to perform diagnosis knowledge is needed that connects diseases (causes, often not directly observable) to symptoms or test results (observable consequences). In addition, a reasoning method is needed to perform in a systematic manner the type of reasoning required, for example a specific diagnostic reasoning method. Another example is the domain of industrial product development, and the design task within this domain, which can be a quite complex type of reasoning task involving reasoning about the requirements imposed on a new product to be developed, and reasoning about possibilities to satisfy these requirements. The analysis of such complex reasoning tasks is addressed from a generic perspective in the literature on task analysis (also including protocol analysis) and on reasoning within Cognitive Psychology. Furthermore, within Artificial Intelligence, reasoning tasks are addressed in the literature on knowledge engineering (also including knowledge acquisition and knowledge modelling) and (automated) reasoning. Moreover, literature can be found on the analysis of reasoning tasks dedicated to specific domains or tasks, such as ‘AI in Medicine’, ‘AI and Law’, ‘Design Studies’, or ‘AI in Design’.
Multi-Policy Dialogue Management

We present a new approach to dialogue management based on the use of multiple, inter-connected policies. Instead of capturing the complexity of the interaction in a single large policy, the dialogue manager operates with a collection of small local policies combined concurrently and hierarchically. The meta-control of these policies relies on an activation vector updated before and after each turn.
Accurate Quadrifocal Tracking for Robust 3D Visual Odometry

This paper describes a new image-based approach to tracking the 6DOF trajectory of a stereo camera pair using a corresponding reference image pairs instead of explicit 3D feature reconstruction of the scene. A dense minimisation approach is employed which directly uses all grey-scale information available within the stereo pair (or stereo region) leading to very robust and precise results. Metric 3D structure constraints are imposed by consistently warping corresponding stereo images to generate novel viewpoints at each stereo acquisition. An iterative non-linear trajectory estimation approach is formulated based on a quadrifocal relationship between the image intensities within adjacent views of the stereo pair. A robust M-estimation technique is used to reject outliers corresponding to moving objects within the scene or other outliers such as occlusions and illumination changes. The technique is applied to recovering the trajectory of a moving vehicle in long and difficult sequences of images.
Approaches to Exploring Category Information for Question Retrieval in Community Question-Answer Archives

Community Question Answering (CQA) is a popular type of service where users ask questions and where answers are obtained from other users or from historical question-answer pairs. CQA archives contain large volumes of questions organized into a hierarchy of categories. As an essential function of CQA services, question retrieval in a CQA archive aims to retrieve historical question-answer pairs that are relevant to a query question. This article presents several new approaches to exploiting the category information of questions for improving the performance of question retrieval, and it applies these approaches to existing question retrieval models, including a state-of-the-art question retrieval model. Experiments conducted on real CQA data demonstrate that the proposed techniques are effective and efficient and are capable of outperforming a variety of baseline methods significantly.
Differential Fault Analysis of MICKEY-128 2.0

This paper presents a differential fault analysis of the MICKEY-128 2.0 stream cipher, one of the finalist of eStream project. The current attack works on MICKEY-128 2.0 with 320 state register-bits and requires 480 number of random single bit faults to break it. Till date, only two fault attacks against MICKEY family are available in literature, one attack on MICKEY-128 and another on MICKEY 2.0. The attack on MICKEY-128 with same 320 register bits required 640 number of faults whereas the other attack on MICKEY 2.0 with 200 state register bits required $2^{16.7} number of faults. To the best of our knowledge the current attack gives the best performance with respect to the number of faults to be induced against the highest version of MICKEY, MICKEY-128 2.0.
STRATEGY-PROOF AND EFFICIENT SCHEDULING

I construct a class of strategy-proof and Pareto efficient fair division mechanisms among players with dichotomous preferences. This class of mechanisms offer a flexible platform to allocate a continuum of heterogeneous goods according to various distributional objectives such as envy-freeness or arbitrary guaranteed shares of reported demand. The characterization of the strategy-proofness of the mechanisms also serves as a sufficient condition for the non-inferiority of consumer’s demand subject to arbitrary submodular ceilings on quantities supplied with fixed prices.
Representation dimension of artin algebras

Auslander has shown that an algebra is of finite representation type, that is, it admits only finitely many indecomposable modules up to isomorphism, if and only if its representation dimension is at most 2. We will give a proof of this fact in Section 1 as Corollary 1.9. This led Auslander to the expectation, “that this notion gives a reasonable way of measuring how far an artin algebra is from being of finite representation type. ” [1, III.5, lines 2, 3]
Medical Record Semantic Analysis Based on Weighted LDA

Latent Dirichlet allocation (LDA) and other modified topic models have become the prevalent tools for semantic analysis and text data mining. With the rapid development of the medical information, large amount of data has been accumulated in the form of text, while most of which recording in a confused structure. Based on LDA, this paper proposes a revised approach, which enlightens an idea of weighting. This paper also demonstrates the desirable performance of the modified method, thus yields the proof of its effectiveness.
Power-Aware Minimum NBTI Vector Selection Using a Linear Programming Approach

Transistor aging is a major reliability concern for nanoscale CMOS technology that can significantly reduce the operation lifetime of very large-scale integration chips. Negative bias temperature instability (NBTI) is a major contributor to transistor aging that affects pMOS transistors. On the other hand, leakage power is becoming a dominant factor of the total power with successive technology scaling. Since the input combinations applied to a logic core have a significant impact on both NBTI and leakage power, input vector control can be used to optimize both phenomena during idle cycles. In this paper, we present an efficient input vector selection technique based on linear programming for cooptimizing the NBTI-induced delay degradation and leakage power consumption during standby mode. Since the NBTI-induced delay degradation and leakage power are not affected by the input vector in the same direction, we provide a pareto curve based on both phenomena. A suitable point from such a pareto curve is chosen based on circuit conditions and requirements during runtime.
Stupid File Systems Are Better

File systems were originally designed for hosts with only one disk. Over the past 20 years, a number of increasingly complicated changes have optimized the performance of file systems on a single disk. Over the same time, storage systems have advanced on their own, separated from file systems by the narrow block interface. Storage systems have increasingly employed parallelism and virtualization. Parallelism seeks to increase throughput and strengthen fault-tolerance. Virtualization employs additional levels of data addressing indirection to improve system flexibility and lower administration costs. Do the optimizations of file systems make sense for current storage systems? In this paper, I show that the performance of a current advanced local file system is sensitive to the virtualization parameters of its storage system. Sometimes random block layout outperforms smart file system layout. In addition, random block layout stabilizes performance across several virtualization parameters. This approach has the advantage of immunizing file systems to changes in their underlying storage systems.
Inducing Metric Violations in Human Similarity Judgements

Attempting to model human categorization and similarity judgements is both a very interesting but also an exceedingly difficult challenge. Some of the difficulty arises because of conflicting evidence whether human categorization and similarity judgements should or should not be modelled as to operate on a mental representation that is essentially metric. Intuitively, this has a strong appeal as it would allow (dis)similarity to be represented geometrically as distance in some internal space. Here we show how a single stimulus, carefully constructed in a psychophysical experiment, introduces l2 violations in what used to be an internal similarity space that could be adequately modelled as Euclidean. We term this one influential data point a conflictual judgement. We present an algorithm of how to analyse such data and how to identify the crucial point. Thus there may not be a strict dichotomy between either a metric or a non-metric internal space but rather degrees to which potentially large subsets of stimuli are represented metrically with a small subset causing a global violation of metricity.
Point cloud data enhancement based on homomorphic filter

Point cloud data of complex product with small changes of surface has narrow data range, high spatial relativity and smooth data change. It is not sensitive to feature extraction and shape recognition. Homomorphic filter is introduced into point cloud data enhancement. Point cloud data reflecting the product shape and spacial relationship is divided into the low frequency part and the high frequency part. Spatial location change has little effect on the low frequency part. The high frequency part changes greatly with spatial location characteristics of the object itself. Homomorphic filter is designed to reduce the low frequency part and enhance high-frequency part. Point cloud data enhancement based on homomorphic filter is proposed. Example shows point cloud data enhancement based on homomorphic filter can convert non uniform distribution point cloud data to uniform distribution point cloud data, improving the contrast of point cloud data.
Larval Performance in the Context of Ecological Diversification and Speciation in Lycaeides Butterflies

The role of ecology in diversification has been widely investigated, though few groups have been studied in enough detail to allow comparisons of different ecological traits that potentially contribute to reproductive isolation. We investigated larval performance within a species complex of Lycaeides butterflies. Caterpillars from seven populations were reared on five host plants, asking if host-specific, adaptive larval traits exist. We found large differences in performance across plants and fewer differences among populations. The patterns of performance are complex and suggest both conserved traits (i.e., plant effects across populations) and more recent dynamics of local adaptation, in particular for L. melissa that has colonized an exotic host. We did not find a relationship between oviposition preference and larval performance, suggesting that preference did not evolve to match performance. Finally, we put larval performance within the context of several other traits that might contribute to ecologically based reproductive isolation in the Lycaeides complex. This larger context, involving multiple ecological and behavioral traits, highlights the complexity of ecological diversification and emphasizes the need for detailed studies on the strength of putative barriers to gene flow in order to fully understand the process of ecological speciation.
TREEPSI: tree based energy efficient protocol for sensor information

Limited battery powers of sensor nodes demand routing protocol for sensor network that consume minimum possible amount of energy and hence give longer life to the system. In a sensor network, sensor nodes are the potential source of information and they need to send their sensed/collected information to a remote base station (BS)/Sink. Generally, it needs a fixed amount of energy to receive one bit of information and an additional amount of energy to transmit the same. This additional amount depends on the transmission range. So, if all nodes transmit directly to the BS, then they will quickly deplete their energy. Therefore, a multi-hop routing protocol is needed to give longer life of the network. LEACH (aW. Heinzelman et al., 2000) (aW. Heinzelman et al., 2000) is an elegant energy efficient protocol where clusters are formed to fuse data before transmission to base station. By randomizing the cluster heads chosen to transmit to the base station, LEACH achieves a factor of 8 improvements over direct transmission, as measured in terms of nodes longevity. PEGASIS (aS. Lindsey and C. Raghavendra, 2001, 2002) is a chain based protocol that is an improvement over LEACH. In PEGASIS, each node communicates only with a close neighbor and takes turns in transmitting to the base station, thus reducing the amount of energy spent per round. It performs better than LEACH by about 100 - 300% for different network sizes and topologies. In this paper, we propose TREEPSI (tree based energy efficient protocol for sensor information) which gives up to 30% better performance (in terms of energy efficiency) than PEGASIS
Arabidopsis Tic40 Expression in Tobacco Chloroplasts Results in Massive Proliferation of the Inner Envelope Membrane and Upregulation of Associated Proteins

The chloroplast inner envelope membrane (IM) plays essential roles in lipid synthesis, metabolite transport, and cellular signaling in plants. We have targeted a model nucleus-encoded IM protein from Arabidopsis thaliana, pre-Tic40-His, by relocating its expression from the nucleus to the chloroplast genome. Pre-Tic40-His was properly targeted, processed, and inserted. It attained correct topology and was folded and assembled into a TIC complex, where it accounted for up to 15% of the total chloroplast protein. These results confirm the existence of a novel pathway for protein targeting to the IM. Tic40-His overexpression resulted in a massive proliferation of the IM (up to 19 layers in electron micrographs) without significant effects on plant growth or reproduction. Consistent with IM proliferation, the expression levels of other endogenous IM proteins (IEP37, PPT, Tic110) were significantly (10-fold) upregulated but those of outer envelope membrane (Toc159), stromal (hsp93, cpn60), or thylakoid (LHCP, OE23) proteins were not increased, suggesting retrograde signal transduction between chloroplast and nuclear genomes to increase lipid and protein components for accommodation of increased accumulation of Tic40. This study opens the door for understanding the regulation of membrane biogenesis within the organelle and the utilization of transgenic chloroplasts as bioreactors for hyperaccumulation of membrane proteins for biotechnological applications.
Modeling multidimensional databases

The authors propose a data model and a few algebraic operations that provide semantic foundation to multidimensional databases. The distinguishing feature of the proposed model is the symmetric treatment not only of all dimensions but also measures. The model provides support for multiple hierarchies along each dimension and support for ad hoc aggregates. The proposed operators are composable, reorderable, and closed in application. These operators are also minimal in the sense that none can be expressed in terms of others nor can any one be dropped without sacrificing functionality. They make possible the declarative specification and optimization of multidimensional database queries that are currently specified operationally. The operators have been designed to be translated to SQL and can be implemented either on top of a relational database system or within a special purpose multidimensional database engine. In effect, they provide an algebraic application programming interface (API) that allows the separation of the front end from the back end. Finally, the proposed model provides a framework in which to study multidimensional databases and opens several new research problems.