Miracle-dz/UniFAR-FTUs huggingface dataset:
Linear mesh deformation with snake constraint

Recently, the mesh deformation commonly requires not only geometric details of surface, skeleton and volume of the mesh to be preserved as much as possible, but also the interactive operation time is as quick as possible. The geometric details of surface can be preserved perfectly by the gradient domain technique, as the same time the computation consumed is the linear. However, how to integrate the skeleton and volume characteristics preservation into the linear gradient domain technique, is still a special challenge. In this paper, we incorporate the Snake constraint with the ldquoLaplacian coordinatesrdquo gradient domain technique on mesh deformation. The Snake constraint maintains the main skeleton and volume characteristics of the mesh, meanwhile, it is a linear constraint. So the main computation involved in the deformation is a solution of a linear energy minimization problem. We demonstrate our deformation algorithm with a variety of examples, showing that the deformation operation is geometric details, skeleton and volume preserved and real-time interactive.
Aerobic metabolism underlies complexity and capacity

The evolution of biological complexity beyond single‐celled organisms was linked temporally with the development of an oxygen atmosphere. Functionally, this linkage can be attributed to oxygen ranking high in both abundance and electronegativity amongst the stable elements of the universe. That is, reduction of oxygen provides for close to the largest possible transfer of energy for each electron transfer reaction. This suggests the general hypothesis that the steep thermodynamic gradient of an oxygen environment was permissive for the development of multicellular complexity. A corollary of this hypothesis is that aerobic metabolism underwrites complex biological function mechanistically at all levels of organization. The strong contemporary functional association of aerobic metabolism with both physical capacity and health is presumably a product of the integral role of oxygen in our evolutionary history. Here we provide arguments from thermodynamics, evolution, metabolic network analysis, clinical observations and animal models that are in accord with the centrality of oxygen in biology.
SpikeNav: Using Stylus Tilt in Three-Dimensional Navigation

We propose a new method for 3D navigation using a commodity stylus and tablet already in common use among 3D artists. SpikeNav exploits tilt sensitivity to provide a mo re direct interaction style. Conceptually the stylus is turned i nto a spike which the user can jab into the model by contact with the tablet; moving the stylus drags the model around and tilting it rotates it naturally, making the stylus a temporary ha ndle for integral direct manipulation. Pressure triggers a m ode switch between rotating and dollying along the view direction with tilt, conceptually using the stylus as a lever inst ead.
Query by outlines: a new paradigm to help manage programs

We propose a new paradigm to query information about programs, namely query by outlines. This paradigm relies on an outlining model that conceptually describe units of code according to the computations they perform. Outlines are automatically constructed by our system PRISME for C and Lisp programs. Currently, both our model and our system are restricted to loops.QBO is a prototype tool that implements the query by outline paradigm. It proposes to browse the loops of a program directly through their outline, and allows to restrict these loops to browse with queries expressed as constraints on the outlines. Thus it enables to answer questions such as "where is this variable modified? ", "where is this kind of computation performed? ", or "are there many places where this computation is performed? ". In this paper, we sketch our outlining model, introduce QBO and argue that query by outline is a helpful paradigm to manage programs.
The Eigenmode Transmission Coupled with Space-Time Codes in Adaptive Power Allocation MIMO Systems

Summary For the wireless communication systems coupled with multiple transmit receive antennas and orthogonal frequency-division multiplexing (OFDM), data sub-streams can be directed along orthogonal modes of channels, when spatial channel information is known at transmitters. These eigenmodes are generally obtained by the singular value decomposition (SVD) of spatial channel fading matrix at every carrier, but they could not be directly used to steer data symbols encoded by space-time codes, as they ignore the effects of space-time diversity gains on data symbols. For the MIMO OFDM systems with universal space-time codes and correspondent least-squared decoders, we present a novel eigenmode transmission according to the SVD of equivalent channel matrix. With these novel eigenmodes, data symbols encoded by space-time codes can be steered to these eigenmodes similar to MIMO wireless communication systems with single-carrier transmission. Moreover, the relations among different code-rate space-time codes, system capacity and number of eigenmodes are respectively analyzed and evaluated by numerical simulation. Furthermore, an improved water-filling scheme is also proposed for determining the optimal transmit powers for orthogonal eigenmodes. The classical water-filling strategy is firstly adopted to determine the optimal power allocation and correspondent bit numbers for every Eigenmode, followed by a residual power reallocation to further determine the additional bit numbers carried by every eigenmode. Compared with classical water-filling schemes, it can also obtain larger throughputs via residual power allocation. Numerical simulation results indicate that the improved water-filling scheme can obtain good tradeoff with respect to throughputs and complexity, with comparison to classical water-filling schemes and greedy algorithms respectively.
Swarming Scalable Content Delivery for the Masses

Due to the high cost of a Content Distribution Network, most Internet users are not able to scalably deliver content to large audiences. In this paper we study swarming, a scalable and economic content delivery mechanism that combines peer-to-peer networking with parallel download. First, we define a swarming architecture that generalizes the basic delivery mechanism in popular swarming protocols such as Gnutella and BitTorrent. We then conduct a comprehensive performance study of swarming delivery, using a variety of workloads. Our results show that swarming scales with offered load up to several orders of magnitude beyond what a basic web server can manage. Most impressively, swarming enables a web server to gracefully cope with a flash crowd, with minimal effect on client performance. During the course of our study we illustrate the benefits and limitations of a basic swarming protocol and identify several key opportunities for performance improvements.
Bone Marrow-Derived Endothelial Progenitors Expressing Delta-Like 4 (Dll4) Regulate Tumor Angiogenesis

Neo-blood vessel growth (angiogenesis), which may involve the activation of pre-existing endothelial cells (EC) and/or the recruitment of bone marrow-derived vascular precursor cells (BM-VPC), is essential for tumor growth. Molecularly, besides the well established roles for Vascular endothelial growth factor (VEGF), recent findings show the Notch signalling pathway, in particular the ligand Delta-like 4 (Dll4), is also essential for adequate tumor angiogenesis; Dll4 inhibition results in impaired, non-functional, angiogenesis and reduced tumor growth. However, the role of BM-VPC in the setting of Notch pathway modulation was not addressed and is the subject of the present report. Here we show that SDF-1 and VEGF, which are produced by tumors, increase Dll4 expression on recruited BM-VPC. Mechanistically, BM-VPC activated, in a Dll4-dependent manner, a transcriptional program on mature EC suggestive of EC activation and stabilization. BM-VPC induced ICAM-2 and Fibronectin expression on EC, an effect that was blocked by a Dll4-specific neutralizing antibody. In vivo, transplantation of BM-VPC with decreased Dll4 into tumor-bearing mice resulted in the formation of microvessels with decreased pericyte coverage and reduced fibronectin expression. Consequently, transplantation of BM-VPC with decreased Dll4 resulted in impaired tumor angiogenesis, increased tumor hypoxia and apoptosis, and decreased tumor growth. Taken together, our data suggests that Dll4 expression by BM-VPC affects their communication with tumor vessel endothelial cells, thereby modulating tumor angiogenesis by affecting vascular stability.
Null values in data base management a denotational semantics approach

We start with a very brief description of the many-valued logic approach to the formal treatment of null values in data bases and show some problems that are encountered. In the second part of the paper we present our approach, based on the Denotational Semantics Theory. An informal introduction to the theory is given and then the relational model is described in terms of the theory. Query evaluations are defined as continuous functions and several examples are presented. The formalization in the framework of Denotational Semantics allows for a better understanding of the semantic problems with null values. It also gives flexibility for alternatives in acceptable semantic interpretations. We conclude with a presentation of an algorithm for the evaluation of simple queries. This algorithm uses symbolic manipulations and it is more economical than the strict application of the definition of query evaluations.
The Application of Agent-Based Information Push Technology in Mobile Learning

Mobile learning (m-learning) is attracting much attention with the convenience of the anytime-and-anywhere learning. However, information dissemination to the huge numbers of mobile learners using a peer-to-peer channel arouses network bandwidth consumption and the heavy load on the servers. In this paper, we propose an agent-based information push technology in the m-learning system. The system architecture, agent-based push model and the division of the functional modules are described in detail.
Network Coding Theorem for Dynamic Communication Networks

A symbolic approach to communication networks, where the topology of the underlying network is contained in a set of formal terms, was recently introduced. The so-called min-cut of a term set represents its number of degrees of freedom. For any assignment of function symbols, its dispersion measures the amount of information sent to the destinations and its Renyi entropies measure the amount of information that can be inferred about the input from the outputs. It was proved that the maximum dispersion and the maximum Renyi entropy of order less than one asymptotically reach the min-cut of the term set. In this paper, we first generalize the term set framework for multi-user communications and state a multi-user version of the dispersion (and Renyi entropy) theorem. We then model dynamic networks as a collection of term sets and the possible demands of users via a utility function. We apply the multi-user theorem to derive a general principle for many-to-many cast communications in dynamic multi-user networks. In general, we show that if each user's demand can be satisfied locally, then all the demands can be satisfied globally.
The Swedish parental benefit and its effects on childbearing : - An empirical study of whether raised compensation levels within the parental benefit cause increased probabilities of having children

In this study I analyze the Swedish parental benefit system focusing on a certain component, the basic level, and its effects on childbearing. The basic level consists of a fixed monetary amount given to parents. The compensation level was raised three times between 2002 and 2004, which would, according to economic theories, imply increased incentives for having children. I use longitudinal data of women in fertile age between 1993 and 2005. Applying a difference-in-differences model on comparison groups based on region of birth I conclude that the policy changes probably did not cause increased probabilities of having children.
Rodosvisor — An ARINC 653 quasi-compliant hypervisor: CPU, memory and I/O virtualization

This paper presents a novel hypervisor engineered for aerospace applications using an object oriented approach embodying time and space partitioning (TSP) on a PowerPC core embedded in a FPGA, for the NetworkCentric core avionics [1] - an architecture of cooperating components and managed by a real-time operating system to implement dependable computing and targeting simplicity. To support partitioned IMA [2]software architectures our hypervisor adapted to the aerospace application domain the Popek and Goldberg's [3] fidelity, efficiency and resource control virtualization requirements by extending them with additional ones like timing determinism, reactivity and improved dependability. A distinctive feature of the hypervisor is its I/O device virtualization approach that guarantees real-time performance and small trusted computing base.
A Cost-Effective UHF RFID Tag for Transmission of Generic Sensor Data in Wireless Sensor Networks

The use of RF identification (RFID) technology for the automatic transmission of physical parameters in wireless sensor networks paves the way to a large class of attractive applications ranging from healthcare to automotive, diagnostic systems, robotics, and many others. Nevertheless, although some RFID tags capable to transmit sensor-like information are already on the market, only a limited number of sensors, such as those for temperature or pressure measurement, can be easily miniaturized and embedded in the RFID chip. The integration of more complex sensors, in fact, appears to be complicated and extremely expensive. In this paper, a cost-effective general-purpose multi-ID tag is proposed. It can be connected to generic sensors, regardless of the actual measured value, and it is capable to transmit, when interrogated by a standard RFID reader, a proper combination of ID codes that univocally codifies the sensor measured value. The functionalities of this device have been extensively validated under stressing conditions and the capability to transmit whatever kind of sensor data has been demonstrated.
My Google Glass Sees Your Passwords! (Black Hat USA 2014 White paper)

In this white paper, we introduce a novel computer vision based attack that automatically discloses inputs on a touch enabled device while the adversary cannot see any text or popup in a video of the victim tapping on the touch screen. We carefully analyze the shadow formation around the ﬁngertip and apply optical ﬂow, Deformable Part-based Model (DPM) based object detector, k-means clustering, and other computer vision techniques to automatically locate the touched points. Planar homography is then applied to map the estimated touched points to a reference image of software keyboard keys. Our work is substantially different from existing research efforts on blind recognition of touch inputs. We target passcodes/passwords where no language model can be applied to correctly estimate touched keys. We are interested in scenarios such as conferences and similar gathering places where a Google Glass, webcam, or smartphone can be used for stealthy attacks. Extensive experiments are performed to demonstrate the impact of this attack.
Neutralizing Viruses in Suspensions by Copper Oxide-Based Filters

ABSTRACT We report the capacity of copper oxide-containing filters to reduce infectious titers of a panel of viruses spiked into culture media. Enveloped, nonenveloped, RNA, and DNA viruses were affected, suggesting the possibility of using copper oxide-containing devices to deactivate a wide spectrum of infectious viruses found in filterable suspensions.
Robot Audition from the Viewpoint of Computational Auditory Scene Analysis

We have been engaged in research on computational auditory scene analysis to attain sophisticated robot/computer human interaction by manipulating real-world sound signals. The objective of our research is the understanding of an arbitrary sound mixture including music and environmental sounds as well as voiced speech, obtained by robot's ears (microphones) embedded on the robot. Three main issues in computational auditory scene analysis are sound source localization, separation, and recognition of separated sounds for a mixture of speech signals as well as polyphonic music signals. The Missing Feature Theory (MFT) approach integrates sound source separation and automatic speech recognition by generating missing feature masks. This robot audition system has been successfully ported to three kinds of robots, SIG2, Robovie R2 and Honda ASIMO. A robot recognizes three simultaneous speeches such as placing a meal order or a referee for Rock- Paper-Scissors Sound Games with a delay of less than 2 seconds. The real-time beat tracking system is also developed for robot audition. A robot hears music, understands and predicts its musical beats to behave in accordance with the beat times in real-time.
Subword Partition based Data Driven Clock Gating Scheme for Low Power VLSI Design

low power optimization has been major concern in VLSI design from last two decades. The work presented here analyzes various clock gating based power optimization techniques in the context of digital signal processing applications. The clock gating based techniques with architecture level optimization possibilities are discussed. A novel method for data specific clock gating based on subword partition is developed and same is verified on Transposed FIR filter structure. The generic VHDL models of subword datapath based FIR architectures are used along with Xilinx Vivado power and performance analysis tools for validation. The results show power optimization upto 47% for narrowband input signal conditions on Virtex-6 Lx240T FPGA. The research shows a promising direction of power optimization technique, which can be used for wide range of signal processing applications.
Minimum description length (MDL) regularization for online learning

An approach inspired by the Minimum Description Length (MDL) principle is proposed for adaptively selecting features during online learning based on their usefulness in improving the objective. The approach eliminates noisy or useless features from the optimization process, leading to improved loss. Several algorithmic variations on the approach are presented. They are based on using a Bayesian mixture in each of the dimensions of the feature space. By utilizing the MDL principle, the mixture reduces the dimensionality of the feature space to its subspace with the lowest loss. Bounds on the loss, derived, show that the loss for that subspace is essentially achieved. The approach can be tuned for trading o between model size and the loss incurred. Empirical results on large scale real-world systems demonstrate how it improves such tradeos. Huge model size reductions can be achieved with no loss in performance relative to standard techniques, while moderate loss improvements (translating to large regret improvements) are achieved with moderate size reductions. The results also demonstrate that overtting is eliminated by this approach.
Combining Linguistics with statistics for multiword term extraction: a fruitfull association?

The acquisition of multiword terms from large text collections is a fundamental issue in the context of Information Retrieval. Indeed, their identification leads to improvements in the indexing process and allows guiding the user in his search for information. In this paper, we present an original methodology that allows extracting multiword terms by either (1) exclusively considering statistical word regularities or by (2) combining word statistics with endogenously acquired linguistic information. For that purpose, we conjugate a new association measure called the Mutual Expectation with a new acquisition process called the LocalMaxs. On one hand, the Mutual Expectation, based on the concept of Normalised Expectation, evaluates the degree of cohesiveness that links together all the textual units contained in an n-gram (i.e. ∀n, n ≥ 2). On the other hand, the LocalMaxs retrieves the candidate terms from the set of all the valued n-grams by evidencing local maxima of association measure values. Finally, we compare the results obtained by applying the methodology over a raw Portuguese text with the results reached by combining word statistics with linguistic information endogenously acquired from the same corpus previously tagged.
Exploring the Role of Information Systems Resources in Dynamic Environments

This study seeks to understand the role of information systems (IS) resources in dynamic environments. To date, 30 interviews have been conducted with senior managers in charge of online retail commerce operations. The results appear to challenge the research literature both in terms of the composition of IS resources and the role that they play in sustained competitiveness. This paper describes preliminary results from the first phase of a multi-phase study on how IS resources affect the firm.
THE IMPORTANCE OF DETECTING BOUNDARIES IN MUSIC STRUCTURE ANNOTATION

This document summarizes our submission to the MIREX 2012 1 Structural Segmentation task 2 and provides pointers to the relevant papers explaining the details of such submission. The method we follow is rooted on first detecting segment boundaries [3] and matching the found segments by state-of-the-art music alignment/similarity algorithms afterwards [4]. In fact, the rationale is that if structure or segment boundaries are sufficiently accurately placed, then the task of structure annotation can be easily solved by employing standard tools for music matching (e.g. [1, 5]). Hence the title of this extended abstract. Our method starts with the extraction of pitch class profile (PCP) features (also called chromas, cf. [1]). Contiguous PCPs are then joined to form delay coordinate vectors, and a recurrence plot (RP) is constructed (an RP can be thought of as a thresholded self-similarity matrix, cf. [2]). Next, structure features (SF) are obtained by transforming the RP into a time-lag matrix and convolving this with a two-dimensional Gaussian kernel [3]. The differences between consecutive SFs yields a novelty curve whose peaks generally correspond to structural boundaries. Once structural segment boundaries are delimited, we cross compare all possible segments using the previously computed RP, similarly to what is done in music version identification [5] or in audio matching [1]. This process yields all pairwise similarities between segments. Finally, we apply a recursive matrix multiplication process to decide if these similarities are large enough to classify two segments as being the same or not [4]. For the complete explanation of our method we refer to [3] and [4]. The former is focused on SFs and the latter explains the entire method in detail. [Briefly comment on the results]
Rough Set Based Approximations of Classes in the OWL Ontology of Places in Poland (extended abstract)

The main goal of our research is to build the ontology of places in Poland covering a variety of aspects of places, mainly administrative and socio-economic. The ontology is being implemented using the OWL 2 Web Ontology Language. In the created OWL ontology, we can distinguish two kinds of classes, primary classes exactly de ned in the ontology as well as secondary classes de ned over the ontology on the basis of primary classes and properties of individuals considered in the ontology. We show how to use rough sets to approximate secondary classes by means of primary classes in the created ontology. Rough set approximations enable us to extract some useful knowledge about places.