Miracle-dz/UniFAR-FTUs huggingface dataset:
A R ECOMMENDER SYSTEM SENSITIVE TO INTRANSITIVE CHOICE AND PREFERENCE REVERSALS

One of the basic foundations for many recommender systems is the assumption of preference consistency and transitivity of choice. In this paper we challenge this assumption and argue that it should be revised. We also provide a method by which recommender systems can estimate preference reversals and choice intransitivity. Our general approach is to incorporate variants of choice-behavior such that recommender systems incorporate decision-sensitive factors within choice-sets that tend to influence decision making. After establishing why recommender systems ought to consider preference reversal phenomena, we provide a high-level outline of a mechanism for automatically discovering and predicting preference reversals. Thereafter we show how the discovered or predicted preference reversals can help in generating choice sets that 1) are better for the users all things considered (by being in line with their general preferences as exhibited over time) and 2) help users make better decisions.
About the correspondences of points between N images

We analyze the correspondence of points between an arbitrary number of images, from an algebraic and geometric point of view. We use the formalism of the Grassmann-Cayley algebra as the simplest way to make both geometric and algebraic statements in a very synthetic and effective way (i.e. allowing actual computation if needed). We propose a systematic way to describe the algebraic relations which are satisfied by the coordinates of the images of a 3D point. They are of three types: bilinear relations arising when we consider pairs of images among the N and which are the well-known epipolar constraints, trilinear relations arising when we consider triples of images among the N, and quadrilinear relations arising when we consider four-tuples of images among the N. Moreover, we show how two trilinear relations imply the bilinear ones (i.e. the epipolar constraints). We also show how these trilinear constraints can be used to predict the image coordinates of a point in a third image, given the coordinates of the images in the other two images, even in cases where the prediction by the epipolar constraints fails (points in the trifocal plane, or optical centers aligned). Finally, we show that the quadrilinear relations are in the ideal generated by the bilinearities and trilinearities, and do not bring in any new information. This completes the algebraic description of correspondence between any number of cameras.
Sparse recovery via Orthogonal Least-Squares under presence of Noise

We consider the Orthogonal Least-Squares (OLS) algorithm for the recovery of a $m$-dimensional $k$-sparse signal from a low number of noisy linear measurements. The Exact Recovery Condition (ERC) in bounded noisy scenario is established for OLS under certain condition on nonzero elements of the signal. The new result also improves the existing guarantees for Orthogonal Matching Pursuit (OMP) algorithm. In addition, This framework is employed to provide probabilistic guarantees for the case that the coefficient matrix is drawn at random according to Gaussian or Bernoulli distribution where we exploit some concentration properties. It is shown that under certain conditions, OLS recovers the true support in $k$ iterations with high probability. This in turn demonstrates that ${\cal O}\left(k\log m\right)$ measurements is sufficient for exact recovery of sparse signals via OLS.
Antigenic Peptides Capable of Inducing Specific Antibodies for Detection of the Major Alterations Found in Type 2B Von Willebrand Disease

Von Willebrand disease (VWD) is an inherited hemorrhagic disorder promoted by either quantitative or qualitative defects of the von Willebrand factor (VWF). The disease represents the most common human coagulopathy afflicting 1.3% of the population. Qualitative defects are subdivided into four subtypes and classified according to the molecular dysfunction of the VWF. The differential diagnosis of the VWD is a difficult task, relying on a panel of tests aimed to assess the plasma levels and function of the VWF. Here, we propose biochemical approaches for the identification of structural variants of the VWF. A bioinformatic analysis was conducted to design seven peptides among which three were representatives of specific amino acid sequences belonging to normal VWF and four encompassed sequences found in the most common VWD subtype 2B. These peptides were used to immunize mice, after which, peptide-specific immunoglobulins were purified. This resulted in four Ig preparations capable of detecting alterations in the subtype 2B VWD plus additional three antibody fractions targeting the normal VWF. The panel of antibodies could serve many applications among them (1) assessment of VWF: antigen interaction, (2) VWF multimer analysis, and (3) production of monoclonal antibodies against VWF for therapeutic purposes as in thrombotic thrombocytopenic purpura.
A scalable BIST architecture for delay faults

We present a scalable BIST (Built-In Self Test) architecture that provides a tunable trade-off between on-chip area demand and test execution time for delay fault testing. So, the architecture can meet test execution time requirements, area requirements, or any target in between. Experiments show the scalability of our approach, e.g., that considerably shorter test execution time can be achieved by storing only a few additional input vectors of the BIST architecture. The gain of test execution time possible with the proposed method ranges from a factor of 2 up to a factor of more than 800000.
Where Teachers Learn Through Work and Students Work to Learn: An Empirically Informed Report on Two Examples of Educational Innovations From a German School

This empirically informed report presents two innovative approaches to learning through work and working to learn from a secondary school in Germany, with both the school and its innovative development having received the German School Award. In one approach, the school's leadership team deployed the new "Challenges" school project for students' comprehensive educational development. In the other, the school initiated the possibility for teachers to gain practical experience outside the school by working full-time. In addition to their teaching duties, teachers can now work for a limited period in the private sector, thereby gaining valuable experience by shaping their professional stances and influencing their approaches to their students in everyday school life. This empirically informed report is based on desk research complemented by qualitative data gathered during a site visit. These data shall give a deeper understanding of how innovative actions initiated by the school leadership team can contribute to change within an educational system towards advanced teacher learning and transformative school development to achieve better student success.
Energy efficient Echo-Hiding extraction method based on fine grain intermittent power control

We propose a low power extraction method of Echo-Hiding audio steganography. Our intermittent power control strategy enables to reduce the active time of devices including processor, ADC, and sensors. Our strategy consists of two features; majority-rule extraction method reduces the active time during extraction, and intermittent watermark detection enables the devices to be almost powered off in the environment without watermarked audio. In the experiments, our method reduced the active time of the processor and ADC to 60-70%. Also, in the environment without watermarked audio, our method was able to reduce 99% of the active time.
Traces of molecular disease mechanisms on microarrays

Gene expression profiling using micro-arrays is a modern approach for molecular diagnostics. In clinical micro-array studies, researchers aim to predict disease type, survival, or treatment response using gene expression profiles. In this process, they encounter a series of obstacles and pitfalls. This chapter reviews fundamental issues from machine learning and recommends a procedure for the computational aspects of a clinical micro-array study.
Radiative Accelerations for Evolutionary Model Calculations

Monochromatic opacities from the OPAL database have been used to calculate radiative accelerations for the 21 included chemical species. The 104 frequencies used are sufficient to calculate the radiative accelerations of many elements for T > 105 K, using frequency sampling. This temperature limit is higher for less abundant elements. As the abundances of Fe, He, or O are varied, the radiative acceleration of other elements changes, since abundant elements modify the frequency dependence of the radiative flux and the Rosseland opacity. Accurate radiative accelerations for a given element can only be obtained by allowing the abundances of the species that contribute most to the Rosseland opacity to vary during the evolution and recalculating the radiative accelerations and the Rosseland opacity during the evolution. There are physical phenomena that cannot be included in the calculations if one uses only the OPAL data. For instance, one should correct for the momentum given to the electron in a photoionization. Such effects are evaluated using atomic data from Opacity Project, and correction factors are given.
Attribution of Responsibility and Blame Regarding a Man-made Disaster: #FlintWaterCrisis

Attribution of responsibility and blame are important topics in political science especially as individuals tend to think of political issues in terms of questions of responsibility, and as blame carries far more weight in voting behavior than that of credit. However, surprisingly, there is a paucity of studies on the attribution of responsibility and blame in the field of disaster research. The Flint water crisis is a story of government failure at all levels. By studying microblog posts about it, we understand how citizens assign responsibility and blame regarding such a man-made disaster online. We form hypotheses based on social scientific theories in disaster research and then operationalize them on unobtrusive, observational social media data. In particular, we investigate the following phenomena: the source for blame; the partisan predisposition; the concerned geographies; and the contagion of complaining. This paper adds to the sociology of disasters research by exploiting a new, rarely used data source (the social web), and by employing new computational methods (such as sentiment analysis and retrospective cohort study design) on this new form of data. In this regard, this work should be seen as the first step toward drawing more challenging inferences on the sociology of disasters from "big social data".
Self-Calibration Method Based on Surface Micromaching of Light Transceiver Focal Plane for Optical Camera

In remote sensing photogrammetric applications, inner orientation parameter (IOP) calibration of remote sensing camera is a prerequisite for determining image position. However, achieving such a calibration without temporal and spatial limitations remains a crucial but unresolved issue to date. The accuracy of IOP calibration methods of a remote sensing camera determines the performance of image positioning. In this paper, we propose a high-accuracy self-calibration method without temporal and spatial limitations for remote sensing cameras. Our method is based on an auto-collimating dichroic filter combined with a surface micromachining (SM) point-source focal plane. The proposed method can autonomously complete IOP calibration without the need of outside reference targets. The SM procedure is used to manufacture a light transceiver focal plane, which integrates with point sources, a splitter, and a complementary metal oxide semiconductor sensor. A dichroic filter is used to fabricate an auto-collimation light reflection element. The dichroic filter, splitter, and SM point-source focal plane are integrated into a camera to perform an integrated self-calibration. Experimental measurements confirm the effectiveness and convenience of the proposed method. Moreover, the method can achieve micrometer-level precision and can satisfactorily complete real-time calibration without temporal or spatial limitations.
Blind Decision-Feedback Equalization of Shallow Water Acoustic Channels

In this paper, blind receivers for signals transmitted through shallow water are proposed. After having introduced the used modulation scheme and its favorable properties, three different blind receiver structures are studied. The first processing step in all cases is explicit non-data-aided timing recovery. Then, blind adaptive-decision feedback equalization and phase recovery is performed. The adaptive setting of the nonlinear equalizer is attained by using the constant modulus algorithm for the feed-forward section and various strategies for the feedback section. All structures have been successfully tested with measured shallow water data gathered during the ROBLINKS 1999 sea trial. The obtained results suggest that blind decision-feedback equalization is possible and may speed up convergence compared to linear CMA.
Normalized Aspect Ratio (W/L)

1 PROBLEM 1 Based on [1], design equations for a saturated MOSFET using ACM model are given by: f D m T i I ng    1 1 2  (1) S D f I I i  (2) L W nC I T ox S. 2 2    (3)   1 1 2. 2 2    f T T i L f   (4)   4 1 1) (    f T SAT DS i V  (5) 1 1 1.    f T ox m i C g L W   (6) According to these equations, (W/L), f T , and power consumption can be plotted as a function of inversion level (i f). The normalized plots generated using MATLAB are shown in Fig. 1. f max is another important parameter of a technology. It can be presented as a function of f T as shown below:
Detection of coordinated attacks using alert correlation model

Alerts correlation techniques have been widely used to provide intelligent and stateful detection methodologies. This is to understand attack steps and predict the expected sequence of events. However, most of the proposed systems are based on rule-based mechanisms which are tedious and error prone. Other methods are based on statistical modeling; these are unable to identify causal relationships between the events. In this paper, an improved “requires/provides” model is presented which established a cooperation between statistical and knowledge-based model, to achieve higher detection rate with the minimal false positives. A knowledge-based model with vulnerability and extensional conditions provide manageable and meaningful attack graphs. The proposed model has been implemented in real-time and has successfully generated security events on establishing a correlation between attack signatures. The system has been evaluated to detect one of the most serious multi-stage attacks in cyber crime - Botnet. Zeus Botnet is analyzed within the realm of simulated malicious activities normally used by cyber criminals.
Haptic display for virtual reality: progress and challenges

Abstract Immersion, interaction, and imagination are three features of virtual reality (VR). Existing VR systems possess fairly realistic visual and auditory feedbacks, and however, are poor with haptic feedback, by means of which human can perceive the physical world via abundant haptic properties. Haptic display is an interface aiming to enable bilateral signal communications between human and computer, and thus to greatly enhance the immersion and interaction of VR systems. This paper surveys the paradigm shift of haptic display occurred in the past 30 years, which is classified into three stages, including desktop haptics, surface haptics, and wearable haptics. The driving forces, key technologies and typical applications in each stage are critically reviewed. Toward the future high-fidelity VR interaction, research challenges are highlighted concerning handheld haptic device, multimodal haptic device, and high fidelity haptic rendering. In the end, the importance of understanding human haptic perception for designing effective haptic devices is addressed.
Towards the Understanding of Interaction in Information Visualization

Over the past few years the web has been responsible for the rise in popularity of visualizations and it seems that interactive or playable visualizations have become more popular and end up standing out more. The use of interactivity and animation has been extensively discussed in information visualization research, but there has been some controversy in relation to its benefits. Additionally, there is still little empirical evidence about its efficacy in terms of improving understanding of the data and there is few research that points out guidelines of how to incorporate it successfully and that proves that playable visualizations are indeed more enjoyable and popular among users. In order to guide future research on the actual benefits of interactivity in visualization it is important to understand what types of interactivity are currently being used in the field and to have a framework to help discuss and evaluate interaction techniques. After conducting an extensive review of popular visualizations and their interactive capabilities, we propose eleven categories of interaction techniques: filtering, selecting, abstract/elaborate, overview and explore, connect/relate, history, extraction of features, reconfigure, encode, participation/collaboration, and gamification.
Epidemiology , diagnosis and control of swine diseases

Introduction Admittedly, the title of this lecture is not particularly original or thought provoking. For many years the Howard Dunne Memorial Lecture has touched topics that were not necessarily related directly or totally to what veterinarians were academically formed to do, or have to deal with on a day to day basis. The idea I believe was to make sure that we would keep our eyes open on what might come in the future, and how it would affect our work and positioning within the swine industry. In this respect this year’s lecture will be a bit different since it is completely centered on a more traditional or basic area of our work. I was told that the 2004 AASV annual meeting would focus on ‘bugs and diseases’, and this is what this lecture will be all about. It is naturally impossible to adequately cover the epidemiology, diagnosis and control of all swine diseases in a short document. However, it is possible to illustrate some of the points that I would like to make in this paper by using specific diseases and situations as examples. It is my hope that a few of the ideas, data and facts that will be discussed in the following lines may, in a very modest way, stimulate constructive discussions within our membership.
An advective mechanism for deep chlorophyll maxima formation in southern Drake Passage

We observe surface and subsurface fluorescence‐derived chlorophyll maxima in southern Drake Passage during austral summer. Backscatter measurements indicate that the deep chlorophyll maxima (DCMs) are also deep biomass maxima, and euphotic depth estimates show that they lie below the euphotic layer. Subsurface, offshore and near‐surface, onshore features lie along the same isopycnal, suggesting advective generation of DCMs. Temperature measurements indicate a warming of surface waters throughout austral summer, capping the winter water (WW) layer and increasing off‐shelf stratification in this isopycnal layer. The outcrop position of the WW isopycnal layer shifts onshore, into a surface phytoplankton bloom. A lateral potential vorticity (PV) gradient develops, such that a down‐gradient PV flux is consistent with offshore, along‐isopycnal tracer transport. Model results are consistent with this mechanism. Subduction of chlorophyll and biomass along isopycnals represents a biological term not observed by surface satellite measurements which may contribute significantly to the strength of the biological pump in this region.
A 3D CFD Modelling Study of a Diesel Oil Evaporation Device Operating in the Stabilized Cool Flame Regime

Diesel fuel is used in a variety of technological applications due to its high energy density and ease of distribution and storage. Motivated by the need to use novel fuel utilization techniques, such as porous burners and fuel cells, which have to be fed with a gaseous fuel, a Diesel fuel evaporation device, operating in the “Stabilized Cool Flame” (SCF) regime, is numerically investigated. In this device, a thermo-chemically stable lowtemperature oxidative environment is developed, which produces a well-mixed, heated air-fuel vapour gaseous mixture that can be subsequently fed either to premixed combustion systems or fuel reformer devices for fuel cell applications. In this work, the ANSYS CFX 11.0 CFD code is used to simulate the three-dimensional, turbulent, twophase, multi-component and reacting flow-field, developed in a SCF evaporation device. An innovative modelling approach, based on the fitting parameter concept, has been developed in order to simulate cool flame reactions. The model, based on p.
A Training Assistant Tool for the Automated Visual Inspection System

This thesis considers the problem of assisting a human user setting up an automated Visual Inspection (VI) system. The VI system uses a stationary camera on an automobile assembly line to inspect cars as they pass by. The inspection process is intended to identify when parts have been missed or incorrect parts have been assembled. The result is reported to a human working on the assembly line who then can take corrective actions. As originally developed, the system requires a setup phase in which the human user places the camera and records a video of at least 30 minutes length to use for training the system. Training includes specifying regions of cars passing by that are to be inspected. After deployment of a number of systems, it was learned that users could benefit from being provided guidance in best practices to delineate training data. It was also learned that users could benefit from simple visual feedback to ascertain whether or not an inspection problem was suitable for a VI system or if the problem was too challenging. This thesis describes a few methods and a new software tool intended to address this need.
Diverging temperature responses of CO2 assimilation and plant development explain the overall effect of temperature on biomass accumulation in wheat leaves and grains

Under rising temperature, the rate of any developmental process increased with temperature more rapidly than that of CO2 assimilation. We found that this discrepancy, summarised by the CO2 assimilation rate per unit of plant development, could explain the observed reductions in biomass accumulation in leaves and grain under high temperatures. This simple model describes the effects of night and day temperature equally well, and offers a simple framework for describing the effects of temperature on plant growth, without any supplementary effect of rising night temperatures.
An Improved Item-based Collaborative Filtering Algorithm Based on Clustering Method

Item-based collaborative filtering recommendation algorithm is one of the most widely used recommendation algorithm, which is widely used in many recommendation systems. But there are some drawbacks when used in large e-business systems. The existing traditional algorithms can’t perform well when the item space changes; on the other side, the performance of the recommendation system will go down as the items increase into a large amount. An improved collaborative filtering recommendation algorithm based on dynamic item clustering method was proposed in the paper. A similitude threshold model was introduced to divide the item space into clusters dynamically. Experiment states that using dynamic item clustering method can satisfy the requirement of increasing amount users and consumers in large e-business systems. The improved collaborative filtering recommendation algorithm performs relatively good recommendation with less resource consumption.