Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimization Framework for Learning a Hierarchical Shape Vocabulary for Object Class Detection

This paper proposes a stochastic optimization framework for unsupervised learning of a hierarchical vocabulary of object shape intended for object class detection. We build on the approach by [6], which has two drawbacks: 1. ) learning is performed strictly bottom-up; and 2. ) the selection of vocabulary shapes is done solely on their frequency of appearance. This makes the method prone to overfitting of certain parts of object shape while losing the more discriminative shape information. The idea of this paper is to cast the vocabulary learning into an optimization framework that iteratively improves the hierarchy as a whole. Optimization is two-fold: one that learns and selects the vocabulary of shapes at each layer in a bottom-up phase and the other that extends/improves it by top-down feedback from the higher layers. The algorithm then loops between the two learning stages several times. We have evaluated the proposed learning approach for object class detection on 11 diverse object classes taken from the standard recognition data sets. Compared to the original approach [6], we obtain a 3 times more compact vocabulary, a 2:5 times faster inference, and a 10% higher detection performance at the expense of 5 times longer training time (25min vs 5min). The approach attains a competitive detection performance with respect to the current state-of-the-art at both, faster inference as well as shorter training times.
Renormalization in Self-Consistent Approximation schemes at Finite Temperature III: Global Symmetries

We investigate the symmetry properties for Baym's $\ensuremath{\Phi}$-derivable schemes. We show that in general the solutions of the dynamical equations of motion, derived from approximations of the $\ensuremath{\Phi}$ functional, do not satisfy the Ward-Takahashi identities of the symmetry of the underlying classical action, although the conservation laws for the expectation values of the corresponding Noether currents are satisfied exactly for the approximation. Further we prove that one can define an effective action functional in terms of the self-consistent propagators which is invariant under the operation of the same symmetry group representation as the classical action. The requirements for this theorem to hold true are the same as for perturbative approximations: The symmetry has to be realized linearly on the fields and it must be free of anomalies; i.e., there should exist a symmetry-conserving regularization scheme. In addition, if the theory is renormalizable in Dyson's narrow sense, it can be renormalized with counterterms which do not violate the symmetry.
Ignorability for categorical data

We study the problem of ignorability in likelihood-based inference from incomplete categorical data. Two versions of the coarsened at random assumption (car) are distinguished, their compatibility with the parameter distinctness assumption is investigated and several conditions for ignorability that do not require an extra parameter distinctness assumption are established. It is shown that car assumptions have quite different implications depending on whether the underlying complete-data model is saturated or parametric. In the latter case. car assumptions can become inconsistent with observed data.
Implementation of 3t dram using adiabatic logic for ultra low power applications

Adiabatic logic circuits in weak inversion region or sub threshold region is calculated in deepness for the first time in the reporting to make great improvement in ultra low power circuit design. Adiabatic Logic circuits are operated with an oscillating power supply. The sub-threshold adiabatic logic for VLSI circuits based on power delay product. The voltage scaling method was used to reduce the power consumption. The sub threshold adiabatic units can save significant energy compared with a logically equivalent static CMOS implementation. The 8T static random access memory was designed and also improved both read and write stability in sub threshold region for ultra low power applications. The propose scheme uses a 3T gain cell (GC) dynamic random access memory (DRAM) bit cell that operates with a single-supply voltage and provides more write capability to the predictable GC structures. The propose GC is operated from a single supply voltage, eliminating the boosted voltages. The propose circuit is targeted at low power energy efficient applications. In the propose scheme area will be reduced as compared with the 8T static random access memory. By using TINA and MICROWIND simulator the power consumption and area will be reduced.
Scheduling and Optimizing Stream Programs on Multicore Machines by Exploiting High-Level Abstractions

Real-time streaming of HD movies and TV via YouTube, Netflix, Apple TV and Xbox Live is gaining popularity. Stream programs often consume considerable amounts of energy due to their compute-intensive nature. Making stream programs energy-efficient is important, especially for energy-constrained computing devices such as mobile phones and tablets. The first part of this thesis focuses on exploiting the popular Synchronous Dataflow (SDF) high-level abstraction of stream programs to design adaptive stream programs for energy reduction on multicore machines. Observing that IO rates of stream programs can vary at runtime, we seek to make stream programs adaptive by transforming their internal structures to adapt required occupied computing resources, e.g., cores and memory, to workload changes at runtime. Our experiments show that adapting stream programs to IO rate changes can lead to significant energy reduction. In addition, we also show that the modularity and static attributes of stream programs' abstraction not only help map stream programs on multicore machines more easily but also enable energy-efficient routing schemes of high-bandwidth stream traffic on the interconnection fabric, such as networks on-chip.While SDF abstractions can help optimize stream programs on multicore machines, SDF is more suitable for describing stream data-intensive computations such as FFT, DCT, and FIR and so on. Modern stream operations such as MPEG2 or MP3 encoders/decoders are often more sophisticated and composed of multiple such computations. Enabling operation synchronization between different such computations with different semantics leads to the need for control messaging. We extend previous work on control messaging and give a formal definition for control message latency via the semantics of information wavefronts. This control-operation-integrated SDF (COSDF) is able to model sophisticated stream programs more precisely. However, the conventional scheduling method developed for SDF is not sufficient to schedule COSDF applications. To schedule COSDF applications, we develop a scheduling method using dependency graphs and applying a periodic graph theory, based on reduced dependency graphs (RDG). This RDG scheduling method also helps extract parallelism of stream programs. The more precise abstraction of COSDF is expected to help synthesize and generate sophisticated stream programs more efficiently.Although the SDF modularity property also improves programmability, it can come at a price of efficiency when SDF models are not compiled and run using model-based design environments. However, compiling large SDF models to mitigate the inefficiency can be prohibitive in the situations where even a small change in a model may lead to large recompilation overhead. We tackle the problem by proposing a method for incrementally compiling large SDF models that faithfully captures the executions of original SDF models to avoid potential artificial deadlocks of a naive compilation method.
A Restricted Poincar&#233; Map for Determining Exponentially Stable Periodic Orbits in Systems with Impulse Effects: Application to Bipedal Robots

Systems with impulse effects form a special class of hybrid systems that consist of an ordinary, time-invariant differential equation (ODE), a co-dimension one switching surface, and a re-initialization rule. The exponential stability of a periodic orbit in a C1-nonlinear systems with impulse effects can be studied by linearizing the Poincaré return map around a fixed point and evaluating its eigenvalues. However, in feedback design-where one may be employing an iterative technique to shape the periodic orbit subject to it being exponentially stable—recomputing and re-linearizing the Poincaré return map at each iteration can be very cumbersome. For a non- linear system with impulse effects that possesses an invariant hybrid subsystem and the transversal dynamics is sufficiently exponentially fast, it is shown that exponential stability of a periodic orbit can be determined on the basis of the restricted Poincaré map, that is, the Poincaré return map associated with the invariant subsystem. The result is illustrated on a walking gait for an underactuated planar bipedal robot.
Capital Investments and Stock Returns

Abstract Firms that substantially increase capital investments subsequently achieve negative benchmark-adjusted returns. The negative abnormal capital investment/return relation is shown to be stronger for firms that have greater investment discretion, i.e., firms with higher cash flows and lower debt ratios, and is shown to be significant only in time periods when hostile takeovers were less prevalent. These observations are consistent with the hypothesis that investors tend to underreact to the empire building implications of increased investment expenditures. Although firms that increase capital investments tend to have high past returns and often issue equity, the negative abnormal capital investment/return relation is independent of the previously documented long-term return reversal and secondary equity issue anomalies.
Adaptive Capacity Sharing through Probabilistic Controlled Placement

As capacity demands vary among simultaneously executed threads in chip multiprocessors, dynamically managing cache resources according to the run-time demands is effective to improve L2 cache performance. Differed from existing dynamic cache management schemes based on LRU replacement policy, we propose an adaptive capacity sharing mechanism based on a global reuse replacement policy. This mechanism adopts decoupled tag and data arrays, and partitions the data arrays into private and shared regions. Capacity sharing is accomplished by determining whether to place the incoming data into the private data region or into the shared data region, which is controlled by probabilities. Our mechanism includes: (1) A VMON monitor to predict run-time capacity demands. (2) A PCS algorithm to determine the probabilities. (3) A probabilistic controlled placement scheme to enforce capacity sharing. We evaluated our mechanism with a full system simulation of an 8-core CMP and used parallel programs from PARSEC benchmark suite. We found that with the same total L2 cache capacity, our mechanism exceeds the conventional private cache managed by LRU policy, the private cache without sharing managed by reuse replacement policy, and an existing adaptive sharing scheme based on LRU policy.
Path Relinking Scheme for the Max-Cut Problem within Global Equilibrium Search

In this paper, the potential of the path relinking method for the maximum cut problem is investigated. This method is embedded within global equilibrium search to utilize the set of high quality solutions provided by the latter. The computational experiment on a set of standard benchmark problems is provided to study the proposed approach. The empirical experiments reveal that the large sizes of the elite set lead to restart distribution of the running times, i.e., the algorithm can be accelerated by simply removing all of the accumulated data set P and re-initiating its execution after a certain number of elite solutions is obtained.
Designing View Maintenance Algorithm in Data Warehousing Environment

A data warehouse stores materialized views generated from the underlying source data. Materialized views are used to speed up query processing on large amounts of data. These views need to be maintained in response to updates in the source data. This is often done, for reasons of efficiency, using incremental techniques rather than recomputing the view from scratch. In this paper we investigate the problem of incremental maintenance of materialized views in data warehouses. We consider views defined by relational algebraic operators and aggregate functions. We show that a materialized view can be maintained without accessing the view itself by materializing and maintaining additional relations. These relations are derived from the intermediate results of the view computation. We first give an algorithm for determining what additional relations need to be materialized in order to maintain a materialized view incrementally. We then propose an efficient incremental algorithm for updating the materialized view (and the additional relations) based on the optimized operator tree used for evaluating the view as a query. One important feature of our algorithm is that it derives the ‘exact change’ to every materialized additional relation, including the materialized view, without accessing the view itself. This feature is important to ensure the correctness of the update to views defined by aggregate functions. Also, this is important in active database applications where triggers are fired by updates to the view. We also show that our incremental maintenance technique can be extended to make the view (and the additional relations) self-maintainable by materializing some ‘selected’ source data.
Midregional Proadrenomedullin Improves Risk Stratification beyond Surgical Risk Scores in Patients Undergoing Transcatheter Aortic Valve Replacement

Background Conventional surgical risk scores lack accuracy in risk stratification of patients undergoing transcatheter aortic valve replacement (TAVR). Elevated levels of midregional proadrenomedullin (MR-proADM) levels are associated with adverse outcome not only in patients with manifest chronic disease states, but also in the general population. Objectives We investigated the predictive value of MR-proADM for mortality in an unselected contemporary TAVR population. Methods We prospectively included 153 patients suffering from severe aortic stenosis who underwent TAVR from September 2013 to August 2014. This population was compared to an external validation cohort of 205 patients with severe aortic stenosis undergoing TAVR. The primary endpoint was all cause mortality. Results During a median follow-up of 258 days, 17 out of 153 patients who underwent TAVR died (11%). Patients with MR-proADM levels above the 75th percentile (≥ 1.3 nmol/l) had higher mortality (31% vs. 4%, HR 8.9, 95% CI 3.0–26.0, P < 0.01), whereas patients with EuroSCORE II scores above the 75th percentile (> 6.8) only showed a trend towards higher mortality (18% vs. 9%, HR 2.1, 95% CI 0.8–5.6, P = 0.13). The Harrell’s C-statistic was 0.58 (95% CI 0.45–0.82) for the EuroSCORE II, and consideration of baseline MR-proADM levels significantly improved discrimination (AUC = 0.84, 95% CI 0.71–0.92, P = 0.01). In bivariate analysis adjusted for EuroSCORE II, MR-proADM levels ≥1.3 nmol/l persisted as an independent predictor of mortality (HR 9.9, 95% CI (3.1–31.3), P <0.01) and improved the model’s net reclassification index (0.89, 95% CI (0.28–1.59). These results were confirmed in the independent validation cohort. Conclusions Our study identified MR-proADM as a novel predictor of mortality in patients undergoing TAVR. In the future, MR-proADM should be added to the commonly used EuroSCORE II for better risk stratification of patients suffering from severe aortic stenosis.
Channel Analysis for an OFDM-MISO Train Communications System Using Different Antennas

For the design of an OFDM train communications system it is essential to characterise and consider the channel parameters. The transmission channel of a high-speed train scenario is frequency selective as well as time variant. Thus, delay spread and Doppler spread are investigated as crucial parameters for the OFDM system performance. Using a ray-tracing tool realistic impulse responses of the transmission channels are simulated. The investigated system includes three base stations operating in common frequency mode along a railway track and one mobile station situated on a high-speed train. For the mobile station different antenna patterns are included in the simulation model. The results are compared and assessed with respect to delay spread, Doppler spread and receive power. When using directional antennas a distinct reduction in Doppler spread is achieved.
Reduction of implant RF heating through modification of transmit coil electric field

In this work, we demonstrate the possibility to modify the electric‐field distribution of a radio frequency (RF) coil to generate electric field‐free zones in the body without significantly altering the transmit sensitivity. Because implant heating is directly related to the electric‐field distribution, implant‐friendly RF transmit coils can be obtained by this approach. We propose a linear birdcage transmit coil with a zero electric‐field plane as an example of such implant‐friendly coils. When the zero electric‐field plane coincides with the implant position, implant heating is reduced, as we demonstrated by the phantom experiments. By feeding RF pulses with identical phases and shapes but different amplitudes to the two orthogonal ports of the coil, the position of the zero electric‐field plane can also be adjusted. Although implant heating is reduced with this method, a linear birdcage coil results in a whole‐volume average specific absorption rate that is twice that of a quadrature birdcage coil. To solve this issue, we propose alternative methods to design implant‐friendly RF coils with optimized electromagnetic fields and reduced whole‐volume average specific absorption rate. With these methods, the transmit field was modified to reduce RF heating of implants and obtain uniform transmit sensitivity. Magn Reson Med, 2011. © 2010 Wiley‐Liss, Inc.
Monetary Policy in the New Neoclassical Synthesis: A Primer

This primer provides an understanding of the mechanics and objectives of monetary policy using a benchmark new neoclassical synthesis (NNS) macromodel. The NNS model incorporates classical features such as a real business cycle (RBC) core, and Keynesian features such as monopolistically competitive firms and costly price adjustment. Price stability maximizes welfare in the benchmark NNS model because it keeps output at its potential defined as the outcome of an imperfectly competitive RBC model with a constant markup of price over marginal cost.
Synthesized lengthening of function words - The fuzzy boundary between fluency and disfluency

As [1]’s model of speech production suggests, speakers sense upcoming difficulties and can correct them before uttering. A reasonable strategy to bridge resulting gaps is to prolong the words in the articulatory buffer [2]. This often buys enough time to correct the issue, resulting in standalone disfluent lengthening, after which fluency is resumed [3]. In case of more severe difficulties, the lengthening may be followed by other disfluencies such as silent or filled pauses or repetitions. Similar hesitation strategies might be useful in automatic speech production, e.g. for spoken dialogue systems that interact with human users and typically face a variety of challenges in natural language understanding and generation. Lengthening is an ambivalent phenomenon in speech that seems to be located at the fuzzy boundary between fluency and disfluency. It regularly occurs before phrase boundaries [4][5] and besides constitutes a common hesitation disfluency. Some disfluencies consist of lengthening [3] only, and some lengthenings appear so subtle that they pass unnoticed [6][7]. We assume that these characteristics of lengthening make it a key component in spoken dialogue systems that are capable of producing disfluencies, as they enable to buy a variable amount of time whilst being unobtrusive to the listener [6]. It is not yet known, however, how much synthetic lengthening is acceptable and how lengthening influences the user’s interaction with the system. To address these issues, this study tests the effects of step-wise increases of synthesized lengthening on user ratings and interaction speed.
Belief propagation for minimum weight many-to-one matchings in the random complete graph

In a complete bipartite graph with vertex sets of cardinalities $n$ and $n^\prime$, assign random weights from exponential distribution with mean 1, independently to each edge. We show that, as $n\rightarrow\infty$, with $n^\prime=\lceil n/\alpha\rceil$ for any fixed $\alpha>1$, the minimum weight of many-to-one matchings converges to a constant (depending on $\alpha$). Many-to-one matching arises as an optimization step in an algorithm for genome sequencing and as a measure of distance between finite sets. We prove that a belief propagation (BP) algorithm converges asymptotically to the optimal solution. We use the objective method of Aldous to prove our results. We build on previous works on minimum weight matching and minimum weight edge cover problems to extend the objective method and to further the applicability of belief propagation to random combinatorial optimization problems.
Arc-Length Constraint-Based Surface Deformation Using Energy-Minimum Optimization

Deformation of 3D objects is an important problem in many application domains, such as geometric modeling, computer graphics and computer-aided design. In this paper, we propose a method for deformation of 3D objects with arc-length constraints. We convert the curve into the polyline. Then we build the energy function of the polyline. Based on the minimum energy curve method, the curve on the mesh is deformed with arc-length constraints and multi-points constraints. The test results show that the proposed method has good performance. Compared to the other method, shape preserving of the curve is better. Finally, we use this method for the deformation of the 3D mannequin model.
A unified framework for semantic shot representation of sports video

The development of mid-level shot description helps to bridge the gap between low-level feature and high-level semantics in video indexing and analysis. In this paper, we present a unified framework for semantic shot representation in field-ball sports genres, in which a video shot is characterized via three essential properties, namely, camera shot size, subject in a scene and video production technology. The three properties clearly represent the primary factors of a shot, and provide a unified viewpoint of semantic shot definition. Based on this framework, we design an effective architecture for semantic shot management comprising three main components as: 1) flexible shot clustering and retrieval by adjusting the weights of three properties according to different requirements; 2) semantics based video temporal segmentation for further event recognition; and 3) comprehensive sports video semantics analysis. Extensive experiments on soccer, basketball and tennis demonstrate the effectiveness and validity of this framework.
A reduction from LWE problem to dihedral coset problem

Learning with Errors (LWE) problems are the foundations for numerous applications in lattice-based cryptography and are provably as hard as approximate lattice problems in the worst case. Here we present a reduction from LWE problem to dihedral coset problem(DCP). We present a quantum algorithm to generate the input of the two point problem which hides the solution of LWE. We then give a new reduction from two point problem to dihedral coset problem on D_{{{({n^{13}})}^{n\log n}}}. Our reduction implicate that any algorithm solves DCP in subexponential time would lead a quantum algorithm for LWE.