Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Passive Ankle and Knee Joint Motions on the Length of Fascicle and Tendon of the Medial Gastrocnemius Muscle

The purpose of this study was to investigate the effects of passive ankle and knee joint motions on the length of fascicle and tendon of the gastrocnemius muscle. The ankle joint was passively moved from maximal dorsiflexed position to maximal plantar flexed position, while the knee joint was fixed at 0° (fully extended position). Also, the knee joint was passively extended from 90° to 0°, while the ankle joint was fixed at 0° (neutral position). In each test condition, lengths of fascicle and external tendon of the medial gastrocnemius were measured by ultrasonography. The length of external tendon was significantly changed by the ankle joint motion, but not by the knee joint motion. This demonstrates that the length of the external tendon distal to the muscle belly is influenced only by the angle changes of the joint distal to the gastrocnemius muscle. The change in fascicle length during the knee joint motion was significantly larger than during the ankle joint motion in spite of a similar length change of total muscle-tendon complex between the two motions. This demonstrates that fascicles located proximally to the external tendon are more influenced by the angle changes of the joint proximal to the gastrocnemius muscle. These results reveal that angle changes of each joint located in the proximal and distal parts of a biarticular muscle have different effects on the length of fascicle and external tendon.
Sparc64 VIIIfx: A New-Generation Octocore Processor for Petascale Computing

The Sparc64 VIIIfx eight-core processor, developed for use in petascale computing systems, runs at speeds of up to 2 GHz and achieves a peak performance of 128 gigaflops while consuming as little as 58 watts of power. Sparc64 VIIIfx realizes a six-fold improvement in performance per watt over previous generation Sparc64 processors.
The SARC Architecture

The SARC architecture is composed of multiple processor types and a set of user-managed direct memory access (DMA) engines that let the runtime scheduler overlap data transfer and computation. The runtime system automatically allocates tasks on the heterogeneous cores and schedules the data transfers through the DMA engines. SARC's programming model supports various highly parallel applications, with matching support from specialized accelerator processors.
A Configurable and Strong RAS Solution for Die-Stacked DRAM Caches

The resiliency problem of die-stacked memory will become important because of its lack of serviceability. This article details how to provide practical and cost-effective reliability, availability, and serviceability support for die-stacked DRAM cache architectures. The proposed approach can provide varying levels of protection, from fine-grained single-bit upsets to coarser-grained faults within the constraints of commodity non-error-correcting code DRAM stacks.
Always-on Vision Processing Unit for Mobile Applications

Myriad 2 is a multicore, always-on system on chip that supports computational imaging and visual awareness for mobile, wearable, and embedded applications. The vision processing unit incorporates parallelism, instruction set architecture, and microarchitectural features to provide highly sustainable performance efficiency across a range of computational-Imaging and computer vision applications, including those with low latency requirements on the order of milliseconds.
Designing Efficient Heterogeneous Memory Architectures

Recent packaging technologies that enable DRAM chips to be stacked inside the processor package or on top of the processor chip can lower DRAM energy-per-bit costs, provide wider interfaces, and offer higher bandwidth. However, these technologies are limited in capacity and come at a higher price than traditional off-package memories, requiring system designers to balance price, performance, and capacity tradeoffs. The most obvious means to achieve this balance is to employ both on- and off-package memory in a heterogeneous memory architecture. However, designers must then decide whether to deploy the on-package memory as an additional cache-hierarchy level (controlled by hardware or software) or as a memory peer to the off-package DRAM in a NUMA configuration. This article presents a model and analysis of energy, bandwidth, and latency for current and emerging DRAM technologies that enable an exploration of memory hierarchies combining heterogeneous memory technologies with different attributes. The analysis shows that the gap between on- and off-package DRAM technologies is narrower than what is found between cache layers in traditional memory hierarchies. As a result, heterogeneous memory caches must achieve very high hit rates or risk degrading both system energy and bandwidth efficiency.
Nonlinear induced disturbance rejection in inertial stabilization systems

A frequent problem in inertial stabilization control systems is the rejection of disturbances associated with moving components. Very often such disturbances are nonlinear and time varying. A prime example is the relative motion of components within a gimbal; in this case, nonlinear bearing friction induces a destabilizing torque from base motion to the component being stabilized. This paper presents a linear quadratic Gaussian algorithm, based on a simple first-order linear stochastic differential equation, for estimating and compensating in real time a particular class of disturbances that can be modeled as a plus or minus unknown slowly changing random value which is characterized by nonlinear Coulomb friction. Results of computer simulations testing the control algorithm are presented along with actual measurements from a laboratory brassboard system. The results reveal a noteworthy improvement in disturbance rejection as compared with a conventional PI controller with notch filters.
Exploiting Interposer Technologies to Disintegrate and Reintegrate Multicore Processors

Silicon interposers enable the integration of multiple stacks of in-package memory to provide higher bandwidth or lower energy for memory accesses. Once the interposer has been paid for, there are new opportunities to exploit the interposer. In this article, the authors exploit the interposer to "disintegrate" a multicore CPU chip into smaller chips that collectively cost less to manufacture than a single large chip. They study the performance-cost tradeoffs of interposer-based, multichip, multicore systems and propose new interposer network-on-chip (NoC) organizations to mitigate the performance challenges while preserving the cost benefits. Although this article focuses on NoC support for disintegrated systems, it paves the way for a range of new research problems in interposer-based disintegrated systems.
A stochastic model of speech incorporating hierarchical nonstationarity

The concept of two-level (global and local) hierarchical nonstationarity is introduced to describe the elastic and dynamic nature of the speech signal. A doubly stochastic process model is developed to implement this concept. In the model, the global nonstationarity is embodied through an underlying Markov chain that governs evolution of the parameters in a set of output stochastic processes. The local nonstationarity is realized by utilizing state-conditioned, time-varying first- and second-order statistics in the output data-generation process models. For potential uses in automatic uncovering of relationally invariant properties from the speech signal and in speech recognition, the local nonstationarity is represented in a parametric form. Preliminary experiments on fitting the models to speech data demonstrate superior performances of the proposed model to several traditional types of hidden Markov models. >
Automatic parsing of TV soccer programs

While automatic parsing of general video images are difficult or nearly impossible, parsing a specific type of video image can be achieved if the video structure can be explicitly identified and its model can be constructed. The paper presents ongoing work on using domain knowledge to parse content of soccer video programs. The proposed system can classify a sequence of soccer frames into various play categories, such as shot at left goal, top left corner kick play in right penalty area, in midfield, etc, based on a priori model comprising four major components: a soccer court, a ball, the players and the motion vectors. Approaches in applying the model for parsing soccer programs are presented in detail. Experimental results are included to evaluate the performance of the system.
Statistical recovery of wideband speech from narrowband speech

We present an algorithm to generate wideband speech from a narrow band version of the same. The main body of the algorithm is a statistical recovery function (SRF), which predicts the highband spectrum based solely on the narrowband spectrum. The performance of the algorithm has been measured both in terms of spectral distortion and spectral signal-to-noise ratio (SNR). We obtained a 3 dB gain in SNR for the reconstructed wideband speech as compared to the narrowband speech. >
Deleted strategy for MMI-based HMM training

We apply the maximum mutual information (MMI) criterion to discriminative training of hidden Markov model (HMM) parameters. In contrast to the conventional MMI training approach, we adopt the cross-validatory strategy with which the parameters are estimated on a part and assessed on the other parts of the training data. For this purpose, we propose the deleted MMI training method, which performs cross-validatory parameter updating while maintaining the converging behavior of the conventional MMI-based algorithm. The proposed method is compared to the conventional MMI approach in classification of artificial data and in speaker-independent continuous speech recognition, and shows better performance.
Improving performance of spectral subtraction in speech recognition using a model for additive noise

Addresses the problem of speech recognition with signals corrupted by additive noise at moderate signal-to-noise ratio (SNR). A model for additive noise is presented and used to compute the uncertainty about the hidden clean signal so as to weight the estimation provided by spectral subtraction. Weighted dynamic time warping (DTW) and Viterbi (HMM) algorithms are tested, and the results show that weighting the information along the signal can substantially increase the performance of spectral subtraction, an easily implemented technique, even with a poor estimation for noise and without using any information about the speaker. It is also shown that the weighting procedure can reduce the error rate when cepstral mean normalization is also used to cancel the convolutional noise.
Sports video analysis

Summary form only given. Techniques of computer and Internet are developing very fast, and users want to access their interested multimedia information from anywhere at anytime by using their most convenient digital equipments. Sports video always appeals to large audiences, and it becomes an important problem to automatically extracting useful semantic information from sports video to facilitate user's accessing requirements. Therefore, sports video analysis has emerged as a hot research point in multimedia area recently due to its high commercial potentials. This talk gives an introduction on technologies and prototypes of sports video analysis and enhancement that include object detection and tracking, scene analysis, event detection and highlight summarization, as well as 3D virtual sports event reconstruction. In the processing of sports video, playfield, player, ball, overlay text and jersey number are detected in the object level. Video scenes with the same semantic meaning are categorized together by using supervised classification and unsupervised clustering algorithms. Solutions of event detection and highlight ranking by using multi-model information are employed in the highlight extraction level, which is one of the most important goals in sports video analysis. 3D virtual cartoon from broadcast soccer video are generated by applying both computer vision and computer graphics techniques. These results can be used to intelligently adapt, enhance and personalize the multimedia content to meet users' preferences and network/device environments.
Rate-proportional servers: a design methodology for fair queueing algorithms

Generalized processor sharing (GPS) has been considered as an ideal scheduling discipline based on its end-to-end delay bounds and fairness properties. Until recently, emulation of GPS in a packet server has been regarded as the ideal means of designing a packet-level scheduling algorithm to obtain low delay bounds and bounded unfairness. Strict emulation of GPS, as required in the weighted fair queueing (WFQ) scheduler, however, incurs a time-complexity of O(N) where N is the number of sessions sharing the link. Efforts in the past to simplify the implementation of WFQ, such as self-clocked fair queueing (SCFQ), have resulted in degrading its isolation properties, thus affecting the delay bound. We present a methodology for the design of scheduling algorithms that provide the same end-to-end delay bound as that of WFQ and bounded unfairness without the complexity of GPS emulation. The resulting class of algorithms, called rate-proportional servers (RPSs), are based on isolating scheduler properties that give rise to ideal delay and fairness behavior. Network designers can use this methodology to construct efficient fair-queueing algorithms, balancing their fairness with implementation complexity.
Mediterranean Diet Inversely Associated With the Incidence of Metabolic Syndrome

There is some evidence of the beneficial role of food patterns and lifestyles on metabolic syndrome (1,2). The Mediterranean food pattern (MFP) has acquired an emerging role in cardiovascular epidemiology (3). It is characterized by a high consumption of fruits, vegetables, legumes, grains, moderate alcohol intake, a moderate-to-low consumption of dairy products and meats/meat products, and a high monounsaturated–to–saturated fat ratio. Although some cross-sectional studies have suggested that the MFP (or some of its components) may reduce the incidence of the metabolic syndrome (1,4), there are no prospective studies assessing this association. Our aim was to prospectively assess the relationship between adherence to the MFP and the subsequent development of metabolic syndrome in the Seguimiento Universidad de Navarra (SUN) dynamic cohort, composed of Spanish university graduates followed up for 6 years (5). The SUN Study uses methodology similar to that of large American cohorts (6), but recruitment is permanently open (it is designed as a dynamic cohort). Baseline assessment of participants consists of a self-administered questionnaire sent by postal mail, gathering information on lifestyle factors and including a 136-item validated food frequency questionnaire (7). Biennially mailed follow-up questionnaires are used to collect a wide variety of information about diet, lifestyle, and medical conditions (5). Among the 18,000 graduates currently participating in the SUN cohort, 5,360 members were recruited …
A GUI software design model and its runtime architecture for digital AV applications

In the field of digital AV equipment, the size of embedded software for the implementation of the graphical user interface (GUI) has increased. Also, as a remote controller is used as an input device, a GUI different from that of a computer using a mouse is required. We propose an example of applying the MVC model for GUI software design intended for remote controller operation, an efficient runtime architecture in line with this design model, and development tools. We also evaluated the improvement of software productivity when using this design model and its runtime architecture.
Comparison of two‐point discrimination testing devices

In order to provide hand therapists and physicians with information regarding instruments for testing two‐point discrimination we evaluated 20 noninjured and 18 nerve‐injured patients using the three‐prong Aesthesiometer™, a paper clip, and a Disk‐Criminator™. Two‐point discrimination was tested by means of a randomized order for the two different discrimination tests and the three different testing devices. The measurement for either moving or static two‐point discrimination, when obtained with the three‐prong Aesthesiometer™, was consistently less sensitive than with the Disk‐Criminator™, and the correlation coefficient was the least between these two testing devices. The Disk‐Criminator™ measurement had the smallest standard deviation among the three testing devices. In terms of desirability of the testing device tip geometry, translation of interprong distance to numerical rating scale, and facility of alternating between one‐ and two‐prong testing techniques, the paper clip was judged to be the least favorable and the Disk‐Criminator™ to be the most favorable test device.
Evolutionary design of fuzzy rule base for nonlinear system modeling and control

In designing fuzzy models and controllers, we encounter a major difficulty in the identification of an optimized fuzzy rule base, which is traditionally achieved by a tedious trial-and-error process. The paper presents an approach to the evolutionary design of an optimal fuzzy rule base for modeling and control. Evolutionary programming is used to simultaneously evolve the structure and the parameter of fuzzy rule base for a given task. To check the effectiveness of the suggested approach, four numerical examples are examined. The performance of the identified fuzzy rule bases is demonstrated.
Fuzzy modeling of client preference from large data sets: an application to target selection in direct marketing

Advances in computational methods have led, in the world of financial services, to huge databases of client and market information. In the past decade, various computational intelligence techniques have been applied in mining this data for obtaining knowledge and in-depth information about the clients and the markets. The paper discusses the application of fuzzy clustering in target selection from large databases for direct marketing purposes. Actual data from the campaigns of a large financial services provider are used as a test case. The results obtained with the fuzzy clustering approach are compared with those resulting from the current practice of using statistical tools for target selection.
Color image watermarking based on a color visual model

To locate the right places for embedding watermark signals, and to set the proper strength of the embedded watermark signal is a critical problem for obtaining a robust and transparent watermark in color images. In this paper, a color visual model and the associated watermarking scheme are proposed for solving this problem. The visual model can estimate the profile of error visibility thresholds for each wavelet subband in each color channel of the host image, by which groups of perceptually significant wavelet coefficients are located for watermark embedding and the quantizer step sizes for quantization index modulation can be appropriately determined. Simulation results show that robust watermarks can be attained while retaining high image quality.
Combining deep learning and unsupervised clustering to improve scene recognition performance

Deep Neural Networks (DNN) are now the state-of-the-art for many image and object recognition tasks, as illustrated by their performance on standard benchmarks. The success of DNNs is attributed to their ability to learn rich mid-level image representations, as opposed to hand-designed low-level features used in other image analysis methods. Typically a large dataset of unlabeled images is used for unsupervised feature learning, and then standard classifiers are trained on the features extracted from the images in a labeled set. In this paper, we show that clustering the images using the features from the DNN allows more accurate per-cluster classifiers to be learned, which improves the overall classification accuracy. We demonstrate the effectiveness of our approach on a scene recognition task.
Cancerogenesis in colorectal neoplasms: Evidence from early onset colorectal cancer

Objective: Majority of colorectal cancers (CRC) happen via two distinct mechanisms of genomic instability: chromosomal and microsatellite instability. The proportion to which colorectal cancers belong to these pathways is well addressed in literature. However, there is much paucity and controversy regarding this proportion in early onset CRC; therefore, in the present study, major proteins involved in chromosomal and microsatellite instability pathways were determined in 104 early-onset CRC specimens. Materials and Methods: Outcome measures comprised expression of 4 mismatch repair (MMR) proteins (MLH1, MSH2, MSH6, PMS2), and two representative proteins of chromosomal instability pathway (P53 and β-catenin), which were determined by immunohistochemistry. Results: Twenty-nine cases (27.9%) had loss of expression of MMR proteins, of which 17 belonged to MutSα pathway and 12 to MutLα. Four tumors had solitary loss of PMS2. Tumors with abnormal MMR status were more likely to be right sided, and occurred mainly in familial setting ( P P Conclusions: Taken together, our study demonstrated that loss of expression of MMR proteins happens more frequently in early-onset CRC, and on the contrary, the role of CIN pathway is less highlighted at the same time. Moreover, because of its ability to track the losses of expression of PMS2, IHC is recommended for determining the eligibility of mutation analysis of MMR genes, especially in younger ages.
Energy Minimization Using Multiple Supply Voltages

We present a dynamic programming technique for solving the multiple supply voltage scheduling problem in both non-pipelined and functionally pipelined data-paths. The scheduling problem refers to the assignment of a supply voltage level to each operation in a data ow graph so as to minimize the average energy consumption for given computation time or throughput constraints or both. The energy model is accurate and accounts for the input pattern dependencies, re-convergent fanout induced dependencies, and the energy cost of level shifters. Experimental results show that using four supply voltage levels on a number of standard benchmarks, an average energy saving of 53% (with a computation time constraint of 1.5 times the critical path delay) can be obtained compared to using one xed supply voltage level.
Bridging the semantic gap with computational media aesthetics

C ontent processing and analysis research in multimedia systems has one central objective: develop technologies that help sift and easily access useful nuggets of information from media data streams. A fundamental need exists to analyze, cull, and categorize information automatically and systematically from media data and to manage and exploit it effectively despite rapidly accumulating digital media collections. However, user expectations of such systems are far from being met, despite continued research for nearly a decade. Currently, only simple, generic, low-level content metadata is made available from analysis. This metadata isn’t always useful because it deals primarily with representing the perceived content rather than the semantics of it. In the last few years, we’ve seen much attention given to the semantic gap problem in automatic content annotation systems. The semantic gap is the gulf between the rich meaning and interpretation that users expect systems to associate with their queries for searching and browsing media and the shallow, lowlevel features (content descriptions) that the systems actually compute. For more information on this dilemma, see Smeulders et al.,1 who discuss the problem at length and lament that while “the user seeks semantic similarity, the database can only provide similarity on data processing. ”