Miracle-dz/UniFAR-FTUs huggingface dataset:
A Computationally Efficient Framework for 3D Warping Technique

Image-based rendering (IBR) techniques produce realistic-looking 3D graphics at a relatively low cost. The 3D image warping technique is particularly appropriate for such an implementation, because it requires a relatively small input data set. In this paper, we propose a computationally efficient framework for 3D image warping technique. This includes a function that maps the visible points in a reference image to their correct positions in any desired view. The mapping of reference image to desired image is determined by the center-of-projection and pinhole-camera model of the two images and by a generalized disparity value associated with each point in the reference image. In the proposed approach, we perform the restructuring of warping order cases and utilize scan line coherency to do this mapping efficient. Through experimental results it has been proved that the proposed technique is computationally better than the existing 3D warping technique.
A cost-optimal service selection approach for collaborative workflow execution in clouds

Today, there has been a strong demand of distributed collaboration in design and manufacturing, due to the acceleration of economic globalization and the popularity of virtual enterprises (VE) model. Because of the characteristics of cloud computing, such as elasticity and on-demand computing, it is promising to deploy and execute collaborative workflows that contain multiple tasks and services such as Computer-Aided Design (CAD) software components on cloud resources for supporting collaboration across enterprises. Specifically, how to cost-effectively select appropriate services to execute workflows within deadlines while without violating multiple constraints becomes an important issue. In this paper, through investigating the practical requirements of collaborative design workflow, we first formulate the issue of the cost-optimal cloud service selection for collaborative workflow executions as a multi-dimensional optimization problem with multiple constraints. Then we propose an effective approach based on genetic algorithms to address this problem for obtaining near-optimal solutions. Based on workload data derived from real-world systems, we conduct experiments which show that our approach outperforms traditional greedy algorithms in finding better solutions and it also provides real-time performance guarantees in real-world cloud computing environments.
Managing the death of close others: Evidence of higher valuing of ingroup identity in young adults who have experienced the death of a close other

Abstract The death of a close other (DOCO) is perhaps the most difficult experience that people endure. According to terror management theory (TMT), people manage the potentially terrorizing awareness of their mortality by immersing in cultural worldviews that allow them to feel like valuable members of a meaningful universe who may have some existence or trace after death. Although TMT has potential implications for understanding how people cope with DOCO, few studies have examined this possibility. We report results from four studies showing that, in line with TMT, students who experienced DOCO reported stronger valuing of their identification with their in-groups, which in turn was associated with higher levels of self-esteem. These findings shed new light on the social-psychological dynamics of DOCO.
Fitting the Term-structure in Stamp 8.10 2 Term Structure

In the Summer of 2008 we have upgraded STAMP to version 8.10 which is the current release version. The new items in version 8.10 are re lativ ly small. The forecasting dialog allows the forecasting of the unobserve d components as well as the future observations. More importantly, various erro rs have been removed from the program and some improvements have been introduced . Most notably, the batch facilities have improved and some bugs in the routi nes for models with explanatory variables and intervention variables have bee n solved. Finally, the automatic outlier and break detection procedure has been op timized further. for the professional use of state space methods in econometr ic, statistical and general time series analysis. The state space form provides an unified representation of a wide range of linear Gaussian time series models inc uding autoregressive moving average (ARMA) models, time-varying regression mod els, dynamic linear models and unobserved components time series models. St ate space methods are used in many different fields including forecasting, sig nal extraction, seasonal adjustment, business cycle analysis, macroeconomic model s, option pricing, financial analysis based volatility, interest rate term-str uctures (yield curve) and many more. To emphasize the powerful options available in STAMP 8.10, we would like to present a multivariate analysis of the interest rate term st ucture in this OxMetrics Newsletter.
Improving Performance in Sub-Block Caches with Optimized Replacement Policies

Recent advances in computer processor design have led to the introduction of sub-blocking to cache architectures. Sub-block caches reduce the tag area and power overhead in caches without reducing the effective cache size by using fewer tags to index the full data RAM array. In spite of achieving reduced area and power overhead, sub-block caches suffer performance degradation due to cache trashing. This occurs when a wider cache line (super-block), made up of multiple valid cache lines (sub-blocks), is replaced or evicted when only a sub-block is to be allocated into the wider super-block. To address this problem, we propose cache replacement policies as they relate specifically to sub-block caches. We propose new replacement policies that are tuned for sub-block caches by adding more intelligence based on the valid state of individual sub-blocks of a super-block. We also investigate the effect of using a few level-0 registers to bypass a few level-1 cache pipe stages on sub-block cache performance. To evaluate the performance improvement offered by our proposed replacement policies and the use of level-0 registers, we developed a sub-block cache simulator based on the Simplescalar toolset for single-core evaluations and the Sniper Simulator for multicore evaluations. We show that, with minimal architectural updates to existing conventional cache replacement policies, we are able to improve level-1 cache hit rates by up to 4.17% using our proposed policies alone on SPEC2006 benchmarks and up to 14% in shared level-2 caches using multicore benchmark suites: PARSEC and SPLASH2.
Increasing Trends in the Excess Comovement of Commodity Prices

We investigate how the excess comovement of commodity prices, that is, the correlation in commodity returns after filtering out common fundamental shocks, has changed over the past three decades by developing the smooth-transition dynamic conditional correlation model that can capture long-run trends and short-run dynamics of correlation simultaneously. Using data from 1983 to 2011, we find that significant increasing longrun trends in excess comovement have appeared since around 2000. We confirm that these increasing trends are neither an artifact of the financial crisis after the bankruptcy of Lehman Brothers in September 2008 nor the time-varying sensitivities of commodity returns to common fundamental shocks. Moreover, we find that no significant increasing trends exist in the excess comovement among off-index commodities and that the surge of global demand alone cannot explain the increasing trends. These findings provide additional evidence for the timing and scope of the recent increasing commodity-return correlations that suggest the influence of the financialization of commodity markets starting around 2000.
A Fuzzy Cognitive Map for Identifying User Satisfaction from Smartphones

Fuzzy Cognitive Map (FCM) is an efficient knowledge representation and reasoning method, which is based on human knowledge and experience. In this work, a FCM model is constructed to represent users' perceptions of satisfaction from Information Technology (IT) products, such as smart phones. A set of key factors, related with smart phone characteristics and functionalities, was first derived from the literature to construct the FCM model. Then, a questionnaire was disseminated to a number of randomly selected (current/potential) smart phone users. Users' preferences were converted into fuzzy numbers representing the degree of satisfaction, as it was expressed by individual users, from each corresponding factor. Strengths of causal relationships between factors were specified by calculating similarities/dissimilarities between these fuzzy numbers. The produced FCM indicates the smart phone functionalities and trade-offs which influence more the perceived user satisfaction.
Muscle Co-Contraction Modulates Damping and Joint Stability in a Three-Link Biomechanical Limb

Computational models of neuromotor control require forward models of limb movement that can replicate the natural relationships between muscle activation and joint dynamics without the burdens of excessive anatomical detail. We present a model of a three-link biomechanical limb that emphasizes the dynamics of limb movement within a simplified two-dimensional framework. Muscle co-contraction effects were incorporated into the model by flanking each joint with a pair of antagonist muscles that may be activated independently. Muscle co-contraction is known to alter the damping and stiffness of limb joints without altering net joint torque. Idealized muscle actuators were implemented using the Voigt muscle model which incorporates the parallel elasticity of muscle and tendon but omits series elasticity. The natural force-length-velocity relationships of contractile muscle tissue were incorporated into the actuators using ideal mathematical forms. Numerical stability analysis confirmed that co-contraction of these simplified actuators increased damping in the biomechanical limb consistent with observations of human motor control. Dynamic changes in joint stiffness were excluded by the omission of series elasticity. The analysis also revealed the unexpected finding that distinct stable (bistable) equilibrium positions can co-exist under identical levels of muscle co-contraction. We map the conditions under which bistability arises and prove analytically that monostability (equifinality) is guaranteed when the antagonist muscles are identical. Lastly we verify these analytic findings in the full biomechanical limb model.
An improved amplify-and-forward strategy for user cooperation channels

A new amplify-and-forward (AAF) strategy is proposed for user cooperation channels. Differing from the previously reported ones in which users either send independent signals, i.e., Azarian's AAF, or do not directly send information to the base station, i.e., Laneman's AAF, the proposed AAF strategy allows users to send signals that are correlated with the previously transmitted signals. The achievable rate region is presented. Numerical results show that the proposed AAF outperforms the traditional AAF, and can provide a larger achievable rate region than the full duplex decode and forward (DAF) relaying strategy and the full duplex estimate and forward (EAF) relaying strategy under certain conditions.
Identification of regulatory elements using a feature selection method

MOTIVATION Many methods have been described to identify regulatory motifs in the transcription control regions of genes that exhibit similar patterns of gene expression across a variety of experimental conditions. Here we focus on a single experimental condition, and utilize gene expression data to identify sequence motifs associated with genes that are activated under this experimental condition. We use a linear model with two-way interactions to model gene expression as a function of sequence features (words) present in presumptive transcription control regions. The most relevant features are selected by a feature selection method called stepwise selection with monte carlo cross validation. We apply this method to a publicly available dataset of the yeast Saccharomyces cerevisiae, focussing on the 800 basepairs immediately upstream of each gene's translation start site (the upstream control region (UCR)). RESULTS We successfully identify regulatory motifs that are known to be active under the experimental conditions analyzed, and find additional significant sequences that may represent novel regulatory motifs. We also discuss a complementary method that utilizes gene expression data from a single microarray experiment and allows averaging over variety of experimental conditions as an alternative to motif finding methods that act on clusters of co-expressed genes. AVAILABILITY The software is available upon request from the first author or may be downloaded from http://www.stat.berkeley.edu/~sunduz. CONTACT keles@stat.berkeley.edu
Multi-swarm particle swarm optimization based on mixed search behavior

The paper develops a Multi-swarm particle swarm optimization (MPSO) to overcome the premature convergence problem. MPSO takes advantage of multiple sub-swarms with mixed search behavior to maintain the swarm diversity, and introduces cooperative mechanism to prompt the information exchange among sub-swarms. Moreover, MPSO adopts an adaptive reinitializing strategy guided by swarm diversity, which can contribute to the global convergence of the algorithm. Through the mixed local search behavior modes, the cooperative search and the reinitializing strategy guided by swarm diversity, MPSO can maintain appropriate diversity and keep the balance of local search and global search validly. The proposed MPSO was applied to some well-known benchmarks. The experimental results show MPSO is a robust global optimization technique for the complex multimodal functions.
Towards a Software Integration Framework in Product Collaborative Design Environment

To meet the enterprises requirements of product collaborative design and optimization, an adaptive integration software framework was established. Through the requirements analysis of product interdisciplinary development, the six-layered functional structure of the framework was put forward. Key technologies of adaptive software integrated were also addressed. The multidisciplinary design and optimization environment was analyzed. Design process modeling and task execution was represented for group cooperation environment. Data multi-views consistency and knowledge process management was resolved in the interdisciplinary product collaborative design. The service-of-design oriented and adaptive integrated software framework can effectively realize cross-platform and scalable application tools integration, design resources sharing and data interoperability for product collaborative design.
Evaluation of training methods for conditioning of fuzzy based maintainability metric

The software maintainability can be ensured by carefully control of its software development process. An early measurement of maintainability starting from design phase is always desirable to produce maintainable software. Some of the researchers have tried to use soft computing techniques to measure maintainability. In spite of their reported validations, these models are not calibrated and no attention has been paid to evaluate and improve the stability of these methods. An attempt has been made in this paper to evaluate and compare several methodologies for improving the numerical stability of a fuzzy logic based maintainability metrics system. Tuning of fuzzy system parameters is carried out using genetic algorithm with system condition number as objective function for optimization. A number of alternates are considered, in which training data sets are generated using different methods and these sets are used to evaluate objective functions in GA and accordingly fuzzy parameters are tuned. In order to show the advantage of such stability improvement, real projects' maintainability data is used and our study indicates that fuzzy model performance gets increased after conditioning.
Determining factors in acceptance of ICT by the university faculty in their teaching practice

Information Communications Technology (ICT) has, little by little, infiltrated educational environments but without reaching the expectations of it's stakeholders. For this reason, the objective of this study is to determine the factors that influence the use and acceptance of ICT within the faculty of the Universidad Nacional de Chimborazo in their teaching practice. A quantitative approach was taken with a non-experimental, cross-sectional design of a correlational and descriptive nature. For this study, an instrument made up of 50 items, themselves divided into 10 dimensions (technological, pedagogical, techno-pedagogical, axiological, academic management, perception of usefulness, ease of use, intent of use, frequency of use and enabling conditions) was applied to a sample of 178 professors. The results obtained show that the Digital Competences and the Institutional Support have a significantly positive impact both in perception of usefulness and perception of ease of use. The principal conclusion shows the importance of Digital Competences that the faculty should have in order to use and accept ICT in their teaching practice.
A corpus-based approach to comparative evaluation of statistical term association measures

Statistical association measures have been widely applied in information retrieval research, usually employing a clustering of documents or terms on the basis of their relationships. Applications of the association measures for term clustering include automatic thesaurus construction and query expansion. This research evaluates the similarity of six association measures by comparing the relationship and behavior they demonstrate in various analyses of a test corpus. Analysis techniques include comparisons of highly ranked term pairs and term clusters, analyses of the correlation among the association measures using Pearson's correlation coefficient and MDS mapping, and an analysis of the impact of a term frequency on the association values by means of z-score. The major findings of the study are as follows: First, the most similar association measures are mutual information and Yule's coefficient of colligation Y, whereas cosine and Jaccard coefficients, as well as χ2 statistic and likelihood ratio, demonstrate quite similar behavior for terms with high frequency. Second, among all the measures, the χ2 statistic is the least affected by the frequency of terms. Third, although cosine and Jaccard coefficients tend to emphasize high frequency terms, mutual information and Yule's Y seem to overestimate rare terms.
Construction of the system framework of Spatial Data Warehouse in Internet of Things environments

In the era of the Internet of Things (IOT), the information world and the entity world are gradually integrated. Thus, the ways that people obtain, transmit, store, update and analyze information are also undergoing profound change. These changes will undoubtedly bring some new challenges to the traditional Spatial Data Warehouse (SDW) system. Based on the analysis of the technical characteristics of IOT and its potential application trends which combine IOT technology with geographic information, firstly, we proposed an architecture solution for the Spatial Data Warehouse system in IOT environments (SDWIT). Secondly, the SDWIT system was constructed which supported by the architecture solution. In this paper, the data source layer, the data processing layer, the data storage layer and the application analysis layer of the SDWIT system are designed in detail. Together, the four layers achieve the collection, transmission, storage and update for the real-time or near real-time information of perceived entities. Thus, the SDWIT system realizes data integration and data fusion for the Abstract Data Type Data (ADTD) and Entity Perception Data (EPD), and improves the ability of data analysis and data mining. At the same time, it also ensures the interchange and process between person and person, person and things, things and things, and utilizes the integration advantage to compensate for some deficiencies of the traditional SDW system. Finally, in the view of technology integration application of IOT technology fusing with GPS, Virtual Reality and Mobile GIS, a next generation innovation application mode of IOT under the support of the SDWIT system was briefly discussed.
In-situ multi-view multi-scattering stochastic tomography

To recover the three dimensional (3D) volumetric matter distribution in an object, the object is imaged from multiple directions and locations. Using these images, tomographic computations seek the distribution. When scattering is significant and under constrained irradiance, tomography must explicitly account for off-axis scattering. Furthermore, tomographic recovery must function when imaging is done in-situ, as occurs in medical imaging and ground-based atmospheric sensing. We formulate tomography that handles arbitrary orders of scattering, using a Monte-Carlo model. The model is highly parallelizable in our formulation. This can enable large scale rendering and recovery of volumetric scenes having a large number of variables. We solve stability and conditioning problems that stem from radiative transfer modeling in-situ.
A Nonnegative Subspace Approach for Packet Loss Concealment

This paper presents a nonnegative subspace approach for packet loss concealment problem. The magnitude spectrogram of speech signal is projected onto nonnegative subspace using nonnegative matrix factorization algorithm. Consequently, packet loss concealment problem is transformed to linear interpolation of the projective coefficients in nonnegative subspace. Simulation examples, objective tests show that packet loss concealment in the nonnegative subspace results in improved perceptual quality of speech compared to popular packet loss concealment algorithms. Streszczenie. Zaprezentowano metode subprzestrzeni dla rozwiązania problemu straty pakietu. Spektrogram amplitudowy sygnalu mowy . jest poddawany projekcji do nieujemnej podprzestrzeni przy wykorzystaniu macierzy faktoryzacji. W rezultacie problem staje sie mozliwy do liniowej interpolacji. Osiągnieto dostrzegalną poprawe jakości przetwarzania sygnalu mowy. (Metoda nieujemnej podprzestrzeni stosowana w przypadku straty pakietu)
Antiobesity Effect of Eicosapentaenoic Acid in High-Fat/High-Sucrose Diet–Induced Obesity

OBJECTIVE Given the pleiotropic effect of eicosapentaenoic acid (EPA), it is interesting to know whether EPA is capable of improving obesity. Here we examined the anti-obesity effect of EPA in mice with two distinct models of obesity. RESEARCH DESIGN AND METHODS Male C57BL/6J mice were fed a high-fat/high-sucrose diet (25.0% [w/w] fat, 32.5% [w/w] sucrose) (HF/HS group) or a high-fat diet (38.1% [w/w] fat, 8.5% [w/w] sucrose) (HF group) for 4–20 weeks. A total of 5% EPA was administered by partially substituting EPA for fat in the HF/HS + EPA and HF + EPA groups. RESULTS Both the HF/HS and HF groups similarly developed obesity. EPA treatment strongly suppresses body weight gain and obesity-related hyperglycemia and hyperinsulinemia in HF/HS-fed mice (HF/HS + EPA group), where hepatic triglyceride content and lipogenic enzymes are increased. There is no appreciable effect of EPA on body weight in HF-fed mice (HF + EPA group) without enhanced expression of hepatic lipogenic enzymes. Moreover, EPA is capable of reducing hepatic triglyceride secretion and changing VLDL fatty acid composition in the HF/HS group. By indirect calorimetry analysis, we also found that EPA is capable of increasing energy consumption in the HF/HS + EPA group. CONCLUSIONS This study is the first demonstration that the anti-obesity effect of EPA in HF/HS-induced obesity is associated with the suppression of hepatic lipogenesis and steatosis. Because the metabolic syndrome is often associated with hepatic lipogenesis and steatosis, the data suggest that EPA is suited for treatment of the metabolic syndrome.