Miracle-dz/UniFAR-FTUs huggingface dataset:
A reduced-rank approach to adaptive linearly constrained minimum variance beamforming based on joint iterative optimization of adaptive filters

This paper presents a low-complexity reduced-rank approach to adaptive linearly constrained minimum variance (LCMV) beamforming. The proposed reduced-rank scheme is based on a constrained joint iterative optimization of adaptive filters according to the minimum variance criterion. The constrained joint iterative optimization procedure adjusts the parameters of a bank of full-rank adaptive filters that forms the projection matrix and an adaptive reduced-rank filter that operates at the output of the bank of filters. We describe LCMV expressions for the design of the projection matrix and the reduced-rank filter and low-complexity stochastic gradient adaptive algorithms for their efficient implementation. Simulations for a beamforming application show that the proposed scheme outperforms in convergence and tracking the state-of-the-art existing reduced-rank schemes with significantly lower complexity.
Human Protein Function Prediction from Sequence Derived Features using See5

Drug Discovery is a tedious process and involves lot of iterations and different processes for the final approval. The pres ent work focus on prediction of molecular class of an unknown protein. The sequence data is taken from HPRD (Human Protein Reference Database) and then the different features are explored for each molecular sequence using various online tools. The decision tree was constructed based on training data of 55 sequences and test data of 29 sequences from different type of molecular classes. See5 based on C5 decision tree is used to obtain the results. Continuous data involving the values of sequence derived features for different sequences is given as input. Different advanced options and combinations are tried out of which decision tree powered with boosting and winnowing give the maximum accuracy of 30% for the data under consideration. If the continuous data set for 25 sequences is taken then the accuracy comes out to be 64% with the same technique.
Learning styles and learning spaces: A review of the multidisciplinary application of experiential learning theory in higher education

Using the concept of learning style and learning space to describe the interface between learners and the learning environment in higher education, in this chapter we review studies addressing how learning style information and the experiential learning model have been applied to improve teaching and learning in sixteen different academic fields and professions. Studies suggest that experiential learning affords educators a way to design and implement teaching and learning strategies conducive to creating a learning environment beneficial for both faculty and students with possibilities for institutional wide dissemination of its core principles and practices. Drawing from the findings generated from the studies, we propose guiding principles for creating growth promoting learning spaces throughout higher education.
Dynamic query scheduling in data integration systems

Execution plans produced by traditional query optimizers for data integration queries may yield poor performance for several reasons. The cost estimates may be inaccurate, the memory available at run-time may be insufficient, or data delivery rate can be unpredictable. We address the problem of unpredictable data arrival rate. We propose to dynamically schedule queries in order to deal with irregular data delivery rate and gracefully adapt to the available memory. Our approach performs careful step-by-step scheduling of several query fragments and processes these fragments based on data arrivals. We describe a performance evaluation that shows important performance gains in several configurations.
A two-threshold fall detection algorithm for reducing false alarms

Wireless health monitoring can be used in health care for the aged to support independent living, either at home or in sheltered housing, for as long as possible. The most important single monitoring need with respect to security and well-being of the elderly is fall detection. In this paper, a two-threshold MATLAB-algorithm for fall detection is described. The algorithm uses mainly tri-axial accelerometer and tri-axial gyroscope data measured from the waist to distinguish between fall, possible fall, and activity of daily living (ADL). The decision between fall and possible fall is done by the posture information from the waist- and ankle-worn devices ten seconds after the fall impact. By categorizing falls into these two sub-categories, an alarm is generated only in serious falls, thus leading to low false alarm rate. The impact itself is detected as the total sum vector magnitudes of both the acceleration and angular velocity exceeds their fixed thresholds. With this method, the sensitivity of the algorithm is 95.6% with the set of 68 recorded fall events. Specificity is 99.6% with the set of 231 measured ADL movements. It is further shown that the use of two thresholds gives better results than just one threshold.
Assessing the Regional Economic Impacts of Defense Activities: A Survey of Methods

Defense activities exercised in a specific region may alter the region's economic performances. An accurate assessment of the potential economic impacts of defense activities within a specific area is therefore a valuable undertaking, especially for regional planners who may want to prepare for changes. The variety in the methodological landscape, counting, among others, input-output models, economic base models, Keynesian regional multipliers, fixed-effects estimators, and casestudy approaches inspired by geography, sociology, or political science may pose a dilemma. In this paper, we detail the historical and theoretical background of each method, as well as select exemplary cases where these methods were successfully or inappropriately applied. By examining old and 'new' methods based on the extant literature in regional economics, we aim to construct a methodological typology that could be extremely valuable to all stakeholders.
Automatic accident detection using topic models

Automatic accident detection is one of the most important tasks for an intelligent transportation system (ITS). In this paper, a new framework for automated traffic accident recognition using topic models is proposed. This framework uses a set of visual features and automatically discovers the motion patterns in traffic scenes. Then, using these learned motion patterns, occurrence of an accident could be detected by various abnormality measures. Results on real video sequences collected from Tehran traffic control center confirm the effectiveness and the applicability of the proposed framework.
A method of detecting interaction between breeding cows from time-series bird's eye pictures of pasture

Breeding cows are known to engage in sociality, in which they interact and form groups. This paper proposes a method of detecting the interaction between breeding cows from time-series pictures of pastures by a similar image retrieval method using a Bag of Visual Words. We divided the interaction detection into three tasks: detecting a pair of cows in an interaction, pinpointing the time and the place that the interaction was observed and identifying its type. This paper focuses on the identifying task. In the proposed method, a similar image retrieval method is used to classify the interaction, and the information from the states of preceding and succeeding the interaction is considered to improve the accuracy of the interaction classification. The effectiveness of the proposed method was confirmed experimentally.
Hyoscine-N-Butyl-Bromide-Induced Hypotension and Myocardial Ischemia

Hyoscine N-butyl bromide, also known as scopolamine, is a type of antimuscarinic agent. This drug is associated with numerous common side effects, including abdominal fullness, constipation, urinary retention, blurred vision, skin flushing, tachycardia, decreased sweating, and salivation. The most unfavorable side effect is hemodynamic instability. In the present case, hypotension and acute myocardial infarction developed after intravenous hyoscine injection as a premedication therapy for colonoscopy. It was difficult to differentiate the cause-effect relationship between myocardial infarction and hypotension. Because both conditions were present under drug effects, we considered 2 possible diagnoses. One was coronary spasm with cardiogenic shock, and the other was myocardial ischemic sequela due to shock status. The latter diagnosis was confirmed after a series of examinations.
Global mapping of the electrically conductive lower mantle

It is known that the electrical conductivity of the Earth's mantle increases to about 1 S/m at depths between 500 and 1000 km. This increase could equally well be ascribed to thermally activated conduction or to enhanced conductivity in high pressure mineral phases. Thermal activation would produce a smooth conductivity profile while conductivity as- sociated with abrupt phase changes would also vary abruptly. Unfortunately, geomagnetic data alone cannot distinguish be- tween these two models. However, under the assumption that the variation is indeed abrupt, we seek the best estimate for the depth to a conductivity jump. A peak in the geomagnetic spec- trum around a period of 27 days produces an electromagnetic response at this period with least uncertainty and least bias associated with breakdown of an assumed p0 source-field ge- ometry. Fitting such data using a simple two-parameter model of a buried conducting sphere, we estimate a conductivity of 1.184-0.10 S/m at a depth of 6504-20 km. The coincidence of this result with estimated depths to the 660 km seismic discon- tinuity provides independent support for the hypothesis that the observed abrupt change in the elasticity of the mantle is also accompanied by an equally abrupt change in the electrical conductivity. Both physical properties are presumably associ- ated with a mineral transition from an olivine-dominated upper
Working Paper / Document de travail 2008-28 The Welfare Implications of Fiscal Dominance

Bank of Canada working papers are theoretical or empirical works-in-progress on subjects in economics and finance. The views expressed in this paper are those of the authors. No responsibility for them should be attributed to the Bank of Canada. Abstract This paper studies the interdependence between fiscal and monetary policy in a DSGE model with sticky prices and non-zero trend inflation. We characterize the fiscal and monetary policies by a rule whereby a given fraction k of the government debt must be backed by the discounted value of current and future primary surpluses. The remaining fraction of debt is backed by seigniorage revenues. When k = 1, there is no fiscal dominance, since the fiscal authority backs all debt and accommodates (independent) monetary policy, by adjusting current or future primary surpluses to satisfy the government's intertemporal budget constraint. If k = 0, all debt is backed by the monetary authority and there is complete fiscal dominance. A continuum of possibilities lies between these two polar cases. We numerically show that: 1) the degree of fiscal dominance, as measured by (1 – k), is positively related to trend inflation, and 2) when prices are sticky, k has significant effects on the business cycle dynamics. The model is estimated using Bayesian techniques. Estimates of k imply a high degree of fiscal dominance in both Mexico and South Korea, but almost no fiscal dominance in Canada and the U.S. The country-specific estimates of the structural parameters are used in a second-order approximation of the equilibrium around the deterministic steady-state to evaluate the welfare costs of fiscal dominance. Results suggest significant welfare losses for countries with high degrees of fiscal dominance. Résumé Les auteurs étudient l'interdépendance des politiques budgétaire et monétaire au moyen d'un modèle d'équilibre général dynamique et stochastique à prix rigides et taux d'inflation tendanciel non nul. Les politiques en question sont caractérisées par une règle selon laquelle une fraction k de la dette publique doit être garantie par la valeur actualisée des excédents primaires présents et futurs, et la fraction restante par les revenus de seigneuriage. Il n'y a aucune prépondérance budgétaire lorsque k = 1, car les autorités budgétaires garantissent l'ensemble de la dette et s'adaptent à la politique monétaire (indépendante) en modifiant les excédents primaires présents ou futurs, de façon à tenir compte de la contrainte budgétaire intertemporelle de l'État. Lorsque k = 0, l'ensemble de la dette se …
An assessment of the Nam Pehchan computer program for the identification of names of south Asian ethnic origin.

BACKGROUND An assessment was made of the usefulness and accuracy of a computer program for the identification of the south Asian population through the classification of names on a disease register. METHODS The computer program, Nam Pehchan, was used to classify names as either south Asian or non south Asian. The results were compared with a reference standard, which combined use of the program with visual inspection. The latter was facilitated by a computer-generated dictionary of common non south Asian names. The data set consisted of 356,555 cases of incident cancer (ICD9: 140-208) registered between 1990 and 1992 by Thames, Trent, West Midlands and Yorkshire cancer registries. RESULTS Nam Pehchan classified 5506 cases as south Asian. Visual inspection identified 2024 false positives (36.8 per cent of all cases identified as south Asian by Nam Pehchan) and 363 false negatives (9.5 per cent of those identified by the reference standard). Compared with the reference standard, Nam Pehchan had a sensitivity of 90.5 per cent and a positive predictive value of 63.2 per cent. CONCLUSION The Nam Pehchan program quickly identified a high proportion of the names classified as south Asian by the reference standard, but the high false positive rate means that the program alone is not an adequate single strategy. The time-consuming process of inspection of program negatives for large data sets can be substantially reduced by comparison with dictionaries of common non south Asian names.
Black carbon ageing in the Canadian Centre for Climate modelling and analysis atmospheric general circulation model

Abstract. Black carbon (BC) particles in the atmosphere have important impacts on climate. The amount of BC in the atmosphere must be carefully quantified to allow evaluation of the climate effects of this type of aerosol. In this study, we present the treatment of BC aerosol in the developmental version of the 4th generation Canadian Centre for Climate modelling and analysis (CCCma) atmospheric general circulation model (AGCM). The focus of this work is on the conversion of insoluble BC to soluble/mixed BC by physical and chemical ageing. Physical processes include the condensation of sulphuric and nitric acid onto the BC aerosol, and coagulation with more soluble aerosols such as sulphates and nitrates. Chemical processes that may age the BC aerosol include the oxidation of organic coatings by ozone. Four separate parameterizations of the ageing process are compared to a control simulation that assumes no ageing occurs. These simulations use 1) an exponential decay with a fixed 24h half-life, 2) a condensation and coagulation scheme, 3) an oxidative scheme, and 4) a linear combination of the latter two ageing treatments. Global BC burdens are 2.15, 0.15, 0.11, 0.21, and 0.11TgC for the control run, and four ageing schemes, respectively. The BC lifetimes are 98.1, 6.6, 5.0, 9.5, and 4.9 days, respectively. The sensitivity of modelled BC burdens, and concentrations to the factor of two uncertainty in the emissions inventory is shown to be greater than the sensitivity to the parameterization used to represent the BC ageing, except for the oxidation based parameterization. A computationally efficient parameterization that represents the processes of condensation, coagulation, and oxidation is shown to simulate BC ageing well in the CCCma AGCM. As opposed to the globally fixed ageing time scale, this treatment of BC ageing is responsive to varying atmospheric composition.
Fe b 20 03 KUNS-1817 YITP-02-73 TAUP-2719-02 hep-th / 0212314 December 2002 Holographic Renormalization Group

The holographic renormalization group (RG) is reviewed in a self-contained manner. The holographic RG is based on the idea that the radial coordinate of a space-time with asymptotically AdS geometry can be identified with the RG flow parameter of the boundary field theory. After briefly discussing basic aspects of the AdS/CFT correspondence, we explain how the notion of the holographic RG comes out in the AdS/CFT correspondence. We formulate the holographic RG based on the Hamilton-Jacobi equations for bulk systems of gravity and scalar fields, as was introduced by de Boer, Verlinde and Verlinde. We then show that the equations can be solved with a derivative expansion by carefully extracting local counterterms from the generating functional of the boundary field theory. The calculational methods to obtain the Weyl anomaly and scaling dimensions are presented and applied to the RG flow from the N = 4 SYM to an N = 1 superconformal fixed point discovered by Leigh and Strassler. We further discuss a relation between the holographic RG and the noncritical string theory, and show that the structure of the holographic RG should persist beyond the supergravity approximation as a consequence of the renormalizability of the nonlinear σ model action of noncritical strings. As a check, we investigate the holographic RG structure of higher-derivative gravity systems, and show that such systems can also be analyzed based on the Hamilton-Jacobi equations, and that the behaviour of bulk fields are determined solely by their boundary values. We also point out that higher-derivative gravity systems give rise to new multicritical points in the parameter space of the boundary field theories. E-mail: fukuma@gauge.scphys. kyoto-u.ac. jp E-mail: matsu@yukawa.kyoto-u.ac. jp E-mail: tsakai@post.tau.ac.il
An object following method based on computational geometry and PTAM for UAV in unknown environments

This paper introduces an object following method based on the computational geometry and PTAM for Unmanned Aerial Vehicle(UAV) in unknown environments. Since the object is easy to move out of the field of view(FOV) of the camera, and it is difficult to make it back to the field of camera view just by relative attitude control, we propose a novel solution to re-find the object based on the visual simultaneous localization and mapping (SLAM) results by PTAM. We use a pad as the object which includes a letter H surrounded by a circle. We can get the 3D position of the center of the circle in camera coordinate system using the computational geometry. When the object moves out of the FOV of the camera, the Kalman filter is used to predict the object velocity, so the pad can be searched effectively. We demonstrate that the ambiguity of the pad's localization has little impact on object following through experiments. The experimental results also validate the effectiveness and efficiency of the proposed method.
Shared Address Space I/O: A Novel I/O Approach for System-on-a-Chip Networking

For real-time system -on-a-chip (SoC) network applications, high-speed and lowlatency network I/O is the key to achieve predictable execution and high performance. Existing network I/O approaches are either not directly suited to SoC applications, or too complicated and expensive. This paper introduces a novel approach, referred to as shared address space I/O , for real-time SoC network applications. This approach facilitates build ing of heterogeneous multiprocessor systems with application intensive processors (main processor) and I/O intensive processors (I/O processor), where network I/O processing can be offloaded to a specialized I/O processor. With the shared address space I/O approach, in such a system, communication and synchronization between main and I/O processors can be implemented with a shared address space. This approach is realized through Atalanta, a heterogeneous real-time SoC operating system we have developed. In this paper, we demonstrate that shared address space I/O can provide high-speed and low-latency network I/O for SoC network applications.
Novel Combination Markers for Predicting Survival in Patients with Muscle Invasive Bladder Cancer: USP18 and DGCR2

We performed gene expression profiling in bladder cancer patients to identify cancer-specific survival-related genes in muscle invasive bladder cancer (MIBC) patients. Sixty-two patients with MIBC were selected as the original cohort and another 118 MIBC patients were chosen as a validation cohort. The expression of USP18, DGCR2, and ZNF699 genes were measured and we analyzed the association between gene signatures and survival. USP18 and DGCR2, were significantly correlated to cancer-specific death (P=0.020, P=0.007, respectively). Cancer-specific survival in the low USP18 or DGCR2 expression group was significantly longer than the high expression group (P=0.018, P=0.006, respectively). In multivariate Cox regression analysis, a combination of USP18 and DGCR2 mRNA expression levels were significant risk factors for cancer-specific death (HR, 2.106; CI, 1.043-4.254, P=0.038). Overall survival and cancer-specific survival rates in the low-combination group were significantly longer than those in the high-expression group (P=0.001, both). In conclusion, decreased expressions of USP18 and DGCR2 were significantly associated with longer cancer-specific survival, and also the combination of two genes was correlated to a longer survival for MIBC patients. Thus, the combination of USP18 and DGCR2 expression was shown to be a reliable prognostic marker for cancer-specific survival in MIBC. Graphical Abstract
Cluster-Based Collaborative Filtering for Sign Prediction in Social Networks with Positive and Negative Links

Social network analysis and mining get ever-increasingly important in recent years, which is mainly due to the availability of large datasets and advances in computing systems. A class of social networks is those with positive and negative links. In such networks, a positive link indicates friendship (or trust), whereas links with a negative sign correspond to enmity (or distrust). Predicting the sign of the links in these networks is an important issue and has many applications, such as friendship recommendation and identifying malicious nodes in the network. In this manuscript, we proposed a new method for sign prediction in networks with positive and negative links. Our algorithm is based first on clustering the network into a number of clusters and then applying a collaborative filtering algorithm. The clusters are such that the number of intra-cluster negative links and inter-cluster positive links are minimal, that is, the clusters are socially balanced as much as possible (a signed graph is socially balanced if it can be divided into clusters with all positive links inside the clusters and all negative links between them). We then used similarity between the clusters (based on the links between them) in a collaborative filtering algorithm. Our experiments on a number of real datasets showed that the proposed method outperformed previous methods, including those based on social balance and status theories and one based on a machine learning framework (logistic regression in this work).