Miracle-dz/UniFAR-FTUs huggingface dataset:
Accurate memory signatures and synthetic address traces for HPC applications

Though the performance of many scientific codes is dominated by memory behavior, our ability to describe, capture, compare, and recreate that behavior is quite limited. This inability underlies much of the complexity in the field of performance analysis: it is fundamentally difficult to relate benchmarks and applications or use realistic workloads to guide system design and procurement. An observable, reproducible, and machine-independent memory characterization is needed. The Chameleon framework is a software suite that includes tools to capture a concise, machine-independent memory signature from any application and produce synthetic memory address traces that mimic that signature. By simultaneously modeling both spatial and temporal locality, Chameleon produces uniquely accurate, general-purpose synthetic traces. Our results demonstrate that the cache hit rates generated by each synthetic trace are nearly identical to those of the application it targets on dozens of memory hierarchies representing many of today's commercial offerings. We apply the framework to high-performance computing (HPC) by leveraging sampling techniques to capture the memory signatures of full-scale, parallel applications with only a 5x slowdown. The overall result is therefore a concise, observable, and machine-independent representation of the memory requirements of full-scale applications that can be tractably captured and accurately mimicked.
Depth Restoration via Joint Training of a Global Regression Model and CNNs

[1] Bredies, Kunisch and Pock. Total Generalized Variation, SIAM Journal on Imaging Sciences, 3(3):492-526, 2012 [2] Ferstl, Reinbacher, Ranftl, Ruther and Bischof. Image Guided Depth Upsampling using Anisotropic Total Generalized Variation, ICCV, 2013 [3} Kunisch and Pock. A Bilevel Optimization Approach for Parameter Learning in Variational Models. SIAM Journal on Imaging Sciences, 6(2):938-983, 2013 [4] Martull, Peris and Fukui. Realistic CG Stereo Image Dataset with Ground Truth Disparity Maps. ICPRW, 2012 [5] Ranftl and Pock. A Deep Variational Model for Image Segmentation, GCPR, 2014 References
Seven‐year safety and efficacy of the unrestricted use of drug‐eluting stents in saphenous vein bypass grafts

Objectives: The aim was to investigate the 7‐year clinical outcomes of patients treated with either drug‐eluting stents (DES) or bare‐metal stents (BMS) for saphenous vein graft disease (SVG). Background: Atherosclerotic disease in SVG has several peculiarities which make it difficult to extrapolate outcomes of the use of DES as compared to BMS, from outcomes observed in native coronary arteries. To date no long‐term safety and efficacy results for DES in SVG have been published. Methods: Between January, 2000 and December, 2005 a total of 250 consecutive patients with saphenous vein graft disease were sequentially treated with DES (either sirolimus‐ or paclitaxel‐eluting stents) or with BMS. Yearly follow‐up was performed. Results: At 87 months (7.25 years), a total of 101 patients died (58 [46%] in the BMS group and 43 [42%] in the DES group, P‐value= 0.4). There was no significant difference in the combined endpoint mortality or myocardial infarction. Cumulative target vessel revascularisation (TVR) was higher in the BMS group compared to the DES group (41% vs. 29%, respectively; adjusted hazard ratio [HR] 0.63, 95% confidence interval [CI]: 0.39–1.0). The cumulative incidence of major adverse cardiac events was 73% vs. 68% in the BMS and DES groups, respectively (adjusted HR 0.93, 95% CI: 0.67–1.3). Conclusions: In the present study, the unrestricted use of DES for SVG lesions appeared safe and effective up to 7.25 years‐ and the use of DES resulted in a clinically relevant lower rate of TVR. © 2011 Wiley Periodicals, Inc.
Improvement of Generalization Ability of Kernel-Based Fisher Discriminant Analysis for Recognition of Japanese Sign Language Hand Pastures, "Yubi-Moji", Using K-means Method

Clustering of the training data using K-means method improved the generalization ability of kernel-based Fisher discriminant analysis. In this study, Gaussian type kernel function was used. The proposed method is applied to the vision-based recognition of the 41 Japanese Sign Language (JSL) static hand postures, which express part of the Japanese syllabary. The reflective near-infrared light method was used with few burdens for a hand postures hand postures in which the outline were similar cannot be discriminated, or a hand had to be colored. In this study, the reflective near-infrared light method without a cumbersome glove-like device is applied to the recognition of the 41 JSL static hand postures. After preprocessing for the raw data, feature vector was extracted by K-means method and Gaussian type kernel function [5]. For classification of 41 postures of 4 subjects, linear discriminant analysis (LDA) was used. expressioner compared with the conventional methods. The image data obtained by this 2 Manual Japanese Syllabary,
Robust visual tracking via adaptive forest

In this paper, we address the visual object tracking problem in the so-called “Tracking-by-Detection” framework, which forms a dominating trend for target tracking recently. Combining ideas from random forest and multiple instance learning, we propose a novel online ensemble classifier selection procedure to conduct the tracking task. The proposed algorithm has been tested on several challenging image sequences. Experimental results validate the effectiveness of the proposed tracking method.
Patient Satisfaction and Perceived Success with a Telephonic Health Coaching Program: The Natural Experiments for Translation in Diabetes (NEXT-D) Study, Northern California, 2011

Introduction Health coaching can improve lifestyle behaviors known to prevent or manage chronic conditions such as diabetes. However, little is known about the patient experience with telephonic coaching programs in real-world care settings. We examined patient satisfaction, patient’s perceived success in achieving program goals, and the patient-level correlates of these outcomes in a voluntary telephonic coaching program at a large integrated health care delivery system in northern California. Methods Kaiser Permanente Northern California patients who participated in a telephonic coaching program in 2011 were sent a cross-sectional survey about their satisfaction with health coaching and perceived success with program goals. We examined associations with patient characteristics. Results The survey response rate was 34%; analyses were based on the 32% who completed the survey. Of those who had completed 2 or more sessions (n = 232 [52%]), most reported being satisfied (70%) or neutral (20%) with the program, and 71% would recommend health coaching. Healthy weight, healthful eating, and physical activity were the most common topics discussed (88%). Adjusting for demographic characteristics, 73% of those who had 2 or more sessions reported that health coaching helped achieve their weight-related goal. Outcomes were positively correlated with patient activation but not consistently correlated with patient demographic characteristics. Conclusion Levels of satisfaction and perceived success with telephonic health coaching provided by a health plan were high and positively correlated with the number of sessions completed and patient activation. Voluntary telephonic health coaching programs should promote retention and assess patients’ activation levels.
Self-consistent Green's function embedding for advanced electronic structure methods based on a dynamical mean-field concept

We present an embedding scheme for periodic systems that facilitates the treatment of the physically important part (here a unit cell or a supercell) with advanced electronic structure methods, that are computationally too expensive for periodic systems. The rest of the periodic system is treated with computationally less demanding approaches, e.g., Kohn-Sham density-functional theory, in a self-consistent manner. Our scheme is based on the concept of dynamical mean-field theory formulated in terms of Green’s functions. Our real-space dynamical mean-fieldembeddingschemefeaturestwonestedDysonequations,onefortheembedded clusterandanotherfor the periodic surrounding. The total energy is computed from the resulting Green’s functions. The performance of our schemeis demonstratedbytreating theembedded regionwith hybridfunctionals andmany-body perturbation theoryintheGWapproachforsimplebulksystems.Thetotalenergyandthedensityofstatesconvergerapidlywith respect to the computational parameters and approach their bulk limit with increasing cluster (i.e., computational supercell) size.
Electrospinning of Core-Shell Fibers for Drug Release Systems

Electrospinning is a promising method for the fabrication of fibers used for drug release system, due the ease of operation of the electrospinning process and the high surface to volume ratio, high loading capacity and high encapsulation efficiency of the obtained fibers. In this study release of tetracycline hydrochloride (TCH) from both monolithic and core-shell electrospun fibers of poly-lactic acid (PLA), poly-caprolactone (PCL) and their blend were studied. It was found that the drug release from the fibers depended on their composition. Core-shell fibers were designed with PCL and TCH in the core and with blends (PCL/PLA) of varying composition in the shell. A varying initial burst release was observed when the composition of the shell was varied. This illustrates that the burst release might be tunable which can be advantageous for many applications.
A close-to-capacity dirty paper coding scheme

The "writing on dirty paper"-channel model offers an information-theoretic framework for precoding techniques for canceling arbitrary interference known at the transmitter. It indicates that lossless precoding is theoretically possible at any signal-to-noise ratio (SNR), and thus dirty-paper coding may serve as a basic building block in both single-user and multiuser communication systems. We design an end-to-end coding realization of a system materializing a significant portion of the promised gains. We employ multidimensional quantization based on trellis shaping at the transmitter. Coset decoding is implemented at the receiver using "virtual bits. " Combined with iterative decoding of capacity-approaching codes we achieve an improvement of 2dB over the best scalar quantization scheme. Code design is done using the EXIT chart technique.
Non-linear Registration using a Finite Element Method

An automated method to register Medical Images is presented in this work. This new technique employs an iterative w arping scheme and is performed, either over fully pixel information or using geometrical features such as ridges. The warp at each iteration is given by a n umberof local Finite Element transformations which p r o vide a non-linear global warp. Results show that this technique can be applied satisfactorily to images with a severe level of distortions.
Adaptive rank-aware query optimization in relational databases

Rank-aware query processing has emerged as a key requirement in modern applications. In these applications, efficient and adaptive evaluation of top-k queries is an integral part of the application semantics. In this article, we introduce a rank-aware query optimization framework that fully integrates rank-join operators into relational query engines. The framework is based on extending the System R dynamic programming algorithm in both enumeration and pruning. We define ranking as an interesting physical property that triggers the generation of rank-aware query plans. Unlike traditional join operators, optimizing for rank-join operators depends on estimating the input cardinality of these operators. We introduce a probabilistic model for estimating the input cardinality, and hence the cost of a rank-join operator. To our knowledge, this is the first effort in estimating the needed input size for optimal rank aggregation algorithms. Costing ranking plans is key to the full integration of rank-join operators in real-world query processing engines.Since optimal execution strategies picked by static query optimizers lose their optimality due to estimation errors and unexpected changes in the computing environment, we introduce several adaptive execution strategies for top-k queries that respond to these unexpected changes and costing errors. Our reactive reoptimization techniques change the execution plan at runtime to significantly enhance the performance of running queries. Since top-k query plans are usually pipelined and maintain a complex ranking state, altering the execution strategy of a running ranking query is an important and challenging task.We conduct an extensive experimental study to evaluate the performance of the proposed framework. The experimental results are twofold: (1) we show the effectiveness of our cost-based approach of integrating ranking plans in dynamic programming cost-based optimizers; and (2) we show a significant speedup (up to 300%) when using our adaptive execution of ranking plans over the state-of-the-art mid-query reoptimization strategies.
OpenEAR — Introducing the munich open-source emotion and affect recognition toolkit

Various open-source toolkits exist for speech recognition and speech processing. These toolkits have brought a great benefit to the research community, i.e. speeding up research. Yet, no such freely available toolkit exists for automatic affect recognition from speech. We herein introduce a novel open-source affect and emotion recognition engine, which integrates all necessary components in one highly efficient software package. The components include audio recording and audio file reading, state-of-the-art paralinguistic feature extraction and plugable classification modules. In this paper we introduce the engine and extensive baseline results. Pre-trained models for four affect recognition tasks are included in the openEAR distribution. The engine is tailored for multi-threaded, incremental on-line processing of live input in real-time, however it can also be used for batch processing of databases.
Complications of Translabyrinthine Vs. Suboccipital Approach for Acoustic Tumor Surgery

This study presents the operative results of surgeons with experience in both the translabyrinthine and suboccipital approaches to acoustic tumor removal for the purpose of resolving some of the controversy among centers favoring one approach over the other. The subjects were 171 patients with acoustic tumors who were treated at Virginia Mason Clinic from 1975 to 1986. The translabyrinthine approach was used in 64% of cases, the suboccipital approach in 35%, and the middle fossa approach in 1%. There were minor differences in morbidity and mortality between approaches. These data did not favor one approach over another. In an exploratory analysis, we found that the morbidity with a planned two-stage translabyrinthine-suboccipital removal was greater than the morbidity with a one-stage removal.
The effect of a change in the dose of trimegestone on the pattern of bleeding in estrogen-treated post-menopausal women: 6 month extension of a dose-ranging study.

BACKGROUND Abnormal bleeding pattern is one major reason for non-compliance with hormone replacement therapy (HRT) in post-menopausal women. We have previously documented that the dose of trimegestone is the main determinant of the pattern of bleeding in women treated with estradiol (E(2)) and sequential combined trimegestone administered in four doses. The objectives of this study were to test the effect of changing the dose of trimegestone and the duration of treatment on the pattern of bleeding in these women who then entered a 6 month extension phase where a single dose of trimegestone was given sequentially combined with E(2). METHODS The menstrual diaries of 134 post-menopausal women who completed a dose-ranging study of trimegestone and then entered a 6 month extension phase were analysed. In the 6 month extension study, all women were given one dose of trimegestone (0.25 mg) in a sequential fashion (day 15-28) combined with continuous E(2) (2 mg/day). RESULTS Women who had received trimegestone 0.25 mg/day during the first 6 months experienced no change in the bleeding pattern in the 6 month extension. Women who had been treated with 0.5 mg/day dose experienced earlier onset, and more prolonged bleeding (P < 0.0001) following the change to 0.25 mg/day. Women who previously received trimegestone doses of 0.05 and 0.1 mg experienced a later onset of bleeding, which was lighter and of shorter duration (P < 0.001) during the extension phase as compared with the first 6 months. CONCLUSION The dose of trimegestone, and not the duration of treatment, appears to be the important determinant of the pattern of bleeding in post-menopausal women on this HRT regimen.
PMI Matrix Approximations with Applications to Neural Language Modeling

The negative sampling (NEG) objective function, used in word2vec, is a simplification of the Noise Contrastive Estimation (NCE) method. NEG was found to be highly effective in learning continuous word representations. However, unlike NCE, it was considered inapplicable for the purpose of learning the parameters of a language model. In this study, we refute this assertion by providing a principled derivation for NEG-based language modeling, founded on a novel analysis of a low-dimensional approximation of the matrix of pointwise mutual information between the contexts and the predicted words. The obtained language modeling is closely related to NCE language models but is based on a simplified objective function. We thus provide a unified formulation for two main language processing tasks, namely word embedding and language modeling, based on the NEG objective function. Experimental results on two popular language modeling benchmarks show comparable perplexity results, with a small advantage to NEG over NCE.
Interactex: an integrated development environment for smart textiles

Construction kits and development environments have dramatically reduced the time and expertise required for the development of physical interactive devices. The field of smart textiles, however, still lacks of established tools that support their development. In this paper, we introduce Interactex, a visual programming environment specifically designed for smart textiles. Interactex supports different activities related to smart textile development, including application development, testing and circuit design. Interactex's visual programming semantics span across mobile phone and smart textile enabling users to take advantage of capabilities present on both devices without writing source code. We also provide evidence from two user studies that Interactex lowers entrance barrier to smart textile development and facilitates rapid prototyping of smart textiles.
Enhancing 3 D Face Recognition based PCA by using Rough Set Theory

Face recognition is a biometric authentication method that has become more and more relevant in the recent years. From being too inaccurate, it is becoming a more mature technology deployed in large scale systems like the new Visa Information System, etc. Sophisticated commercial systems have been developed that achieve high recognition rates. The proposed method of 3D facial recognition based on Rough set technique. In this paper PCA (Principal Component Analysis) approach has been used to reduce Feature vector, for selection of feature have been used the concept of Rough set approach that can be based on the minimal description length principle and tuning methods of parameters of the approximation spaces to obtain high quality classifiers. Finally, Classification of face applied by using Euclidean Distance (ED) and displaying the result to show efficiency and accuracy of proposed method. General Terms Pattern recognition, Principle component analysis PCA, Eigenfaces, Rough set theory, Euclidean distance.
Decomposition Analysis of Factor Cost Shares: The Case of Greek Agriculture

Abstract An alternative version of decomposition analysis, based on factor cost shares rather than input demand functions, is presented and applied to Greek agriculture. Decomposition analysis shows that most of the changes in factor cost shares during the period from 1973 to 1989 are attributed to technical change and factor substitution, while the role of the scale effect is small, except that of fertilizer. The decomposition analysis results are then used to analyze the implications of Greece's fertilizer and feed subsidy removal, which took place in 1990.
New Methods for Determining the Thermophysical and Hydraulical Properties of Unconsolidated Rocks

The heat conductivity and diffusivity as well as the hydraulic properties of unconsolidated rocks are important parameters to quantify the conductive and convective heat transfer in the subsurface. Depending on the type and way of installation of an underground heat exchanger system the involved soil undergoes compaction, change in saturation e.g. The most soil properties will be changed somehow, just the grain size distribution remains constant. In the operation phase the temperature and saturation are variable in time and space. The change in the ratios of the gas phase and water phase in the subsoil affects the themo-physical performance. The hydraulic conductivity of soils is a non-linear function on the water content. The heat capacity of unconsolidated rocks can be calculated from the heat capacities of the individual components and their volume fractions. In contrast, there is no linear dependence of the thermal conductivity and the water content. Established computational models provide approximations for the thermal conductivity as a function of water content and other constraints such as temperature. However, for the additional determination of convective transport behavior, the unsaturated hydraulic conductivity and water retention function, largely dependent on the tortuosity of the pore space, have to be determined simultaneously. Here, for the integrated study of soil mechanics, hydraulic and geothermal properties of unconsolidated rocks, a heat and temperature conductivity meter has been developed and patented. The device allows measurements of samples either under constant pressure of up to 7.6 Mpa which means soil compaction can be varied stepwise or it can be driven at a constant sample volume. The treatment temperatures of the soil samples can be varied from -10 to +80 ° C. Additionally to the parameters such as temperature, pressure, volume and water content, the capillary tension is recorded during the measurement. For the simultaneous study of water transport characteristics and the unsaturated conductivity of undisturbed unconsolidated rock samples, an evaporation test has been developed. It is equipped with a full-space line source to determine the thermal conductivity. This allows the simultaneous measurement of thermal conductivity, water retention characteristics and hydraulic conductivity of a soil sample up to the air entry point of the ceramic tensiometer cap (approx. -780 hPa). The functionality of the equipment and methods has been validated and the devices were used for soil investigation in numerous projects. Determination of the design parameters of shallow geothermal systems and of the heat transfer of burried cables is thepurpose of the methods presented in this study. The data compile mathematical models for the thermo-physical parameters of soils. A mathematical function for calculating the thermal conductivity in dependence of the capillary tension is introduced here and the test results of geotechnical and geothermal soil parameters of sand, clay and silt are presented.