Miracle-dz/UniFAR-FTUs huggingface dataset:
Contagion in S. E. Asia Measuring Stock Market Co-Movement

This paper utilizes two different approaches to examine whether there is a contagion among South East Asian economies. According to the cross-market correlation analysis, there is a contagion between Thailand, Indonesia and Philippines and market co-movements which simply cannot be explained by the fundamental linkages between these economies. A contagion is also detected by the cointegration analysis. The long-run relationship among South East Asian countries and Japan significantly changed after July 1997. Both impulse response analysis and variance decomposition confirm the changes in market co-movements. The findings suggest that multinational investment managers may need to re-design their strategies for South East Asia consistent with Tang's advise [2001]. A quick move by IMF approving Philippines' request for an extension of its Extended Fund Facility (EFF), Chieng Mei initiative on foreign exchanged swapped and others proposed by Chaipravat and Bhanich Supapol [2000] under ASEAN commission and massive financial packages to Thailand and Indonesia are among justifiable measures supported by our empirical evidence.
International Conference on Intelligent and Advanced Systems 2007 Improved Dynamic Ant Colony System ( DACS ) on symmetric Traveling Salesman Problem ( TSP )

Ants are a fascinating creature that demonstrates a capability of finding food and bring it back to their nest. Their ability as a colony to find paths or routes to the food sources has inspired the development of an algorithm namely Ant Colony System (ACS). The principle of cooperation has been the backbone in these algorithmic developments. However, observing the behavior of a single ant can provide an added value to the principle. Ants communicate to each other through a chemical substance called pheromone. Manipulating and empowering this substance is the trivial factor in finding the best solution. However, without considering the experiences of individuals would contribute a complete waste of available knowledge. Having the concepts of a single ant trying to reconstruct or reconnect the paths that was previously laid by its colony when a certain obstacle placed on its normal paths has added another level of pheromone updates. Thus, this new level of pheromone updates which manipulating and empowering the searching experiences of individual ants can improve the current ACS algorithm. Traveling Salesman Problem (TSP) was used as a case study to show the capability of the algorithm in order to find the best solution in terms of the shortest distance. At the end of this paper, we presented an experimental result on a benchmark data to show how it could improve the fundamental of ACS algorithm.
Purposive hidden-object game (P-HOG) towards imperceptible human computation

This demonstration presents a novel purposive web game on iOS to collect object locations, named Purposive Hidden-Object-Game(P-HOG). Having sufficient training images with known object locations is crucial for many multimedia tasks. P-HOG imperceptibly embeds localizing objects into the gaming process so that P-HOG preserves attractiveness to common players. During the game, players need to localize both automatically inserted known items and unknown objects (which are aimed to localize) to gain scores. The unknown objects are indicated by the refined user-provided tags from photo sharing websites. The difficulty mainly lies in how to insert known items naturally and thus preserve the game's playability. The P-HOG can be applied for constructing a large database, which contains located objects and may benefit general learning-based algorithms for multimedia tasks. The comprehensive experiments shows that P-HOG appeals to general players and can easily perform quality control, and hence effective for collecting massive object locations with high accuracy.
Electromagnetic Inverse Scattering of Axially Moving Cylindrical Targets

Electromagnetic inverse scattering techniques are considered to reconstruct the permittivity and the velocity profiles of axially moving cylindrical targets. Two approaches are proposed. One of these is based on a two-step procedure. It is shown that it provides good approximations of the profiles to be reconstructed in a very efficient way, when the peak velocity is small with respect to the speed of light in vacuum. These features are obtained by neglecting the movement in the first step, which is devoted to the reconstruction of the geometric and dielectric properties of the cylindrical targets. The second approach is more classical and is defined as a global optimization problem. It is shown that the two procedures are in some way complementary in the sense that, when the two-step procedure can be applied, it is by far the best, with the general procedure giving large errors; vice versa, the two-step procedure is in trouble when the other one gives good results. In carrying out this analysis, some estimates on the effects of the movement on the scattered field components are deduced in the limit as the peak velocity goes to zero.
The Effects of a Negative Income Tax on School Performance: Results of an Experiment.

This paper analyzes the impact of a negative income tax experiment on the school performance of children in grades 4 through 10. The results indicate that the experimental program led to an increase in the average reading achievement of children in grades 4 through 6. This improved performance can be explained at least in part by the effect of the program on family income. No beneficial effects of the NIT program were observed for older children.
Modeling Unknown Web Attacks in Network Anomaly Detection

Due to the unknown Web attacks are hardly be detected and the early warning and response mechanism cannot be established, many of intrusion detection systems (IDSs) are only effective in detecting known Web attacks and cannot evaluate the risk of Web service. In order to conquer these limitations and inspired by immune principles, this paper presents an immune-based active defense model for Web attacks which is on the basis of the clone selection and hyper-mutation. Therefore, the immune learning algorithm and the attack detection mechanism are given. The risk of Web attacks is quantitatively analyzed on the relationship between the antibody concentration and the state of an illness in biological immune system (BIS). Theoretical analysis and experimental evaluation demonstrate that the model is more suitable for detecting unknown attacks, and provides an active defense mechanism for detecting network anomalies.
Mining Dynamic Networks : The Importance of Pre-processing on Downstream Analytics

Dynamic networks are becoming ubiquitous and the analysis of these is becoming increasingly important to better understand the processes by which they evolve over time. Various recent work in this space have looked at how to detect communities, how to model adding/removing nodes and edges, and how to model how nodes change roles over time. In this paper, we look at a different aspect of dynamic networks: assuming we can identify and track a community over time, can we predict larger evolutionary events such as whether it is about to merge with another community or split or dissolve. Further, can we predict at a node-level whether nodes are about to leave the community. We here provide an initial exploration of how different settings for network extraction from observed time-stamped links impact community detection and performance of machine learning. We show on two data sets that changing these parameters have drastic impact on the consistency and stability of communities found.
Clinical Pharmacology: Advances and Applications Dovepress Systematic Review and Network Meta-analysis of Stroke Prevention Treatments in Patients with Atrial Fibrillation

you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms Background: In the last 4 years, four novel oral anticoagulants have been developed as alternatives to warfarin and antiplatelet agents for stroke prevention in atrial fibrillation (AF) patients. The objective of this review was to estimate the comparative effectiveness of all antithrombotic treatments for AF patients. Randomized controlled trials of AF patients were selected if they compared at least two of the following: placebo, aspirin, aspirin and clopidogrel combination therapy, adjusted-dose warfarin (target international normalized ratio 2.0–3.0), dabigatran, rivaroxaban, apixaban, and edoxaban. Bayesian network meta-analyses were conducted for outcomes of interest (all stroke, ischemic stroke, myocardial infarction, overall mortality, major bleeding, and intracranial hemorrhage). Results: Based on 16 randomized controlled trials of 96,826 patients, all oral anticoagulants were more effective than antiplatelet agents at reducing the risk of ischemic stroke and all strokes. Compared to warfarin, dabigatran 150 mg (rate ratio 0.65, 95% credible interval 0.52–0.82) and apixaban (rate ratio 0.82, 95% credible interval 0.69–0.97) reduced the risk of all strokes. Dabigatran 150 mg was also more effective than warfarin at reducing ischemic stroke risk (rate ratio 0.76, 95% credible interval 0.59–0.99). Aspirin, apixaban, dabigatran 110 mg, and edoxaban were associated with less major bleeding than warfarin. Conclusion: All oral anticoagulants reduce the risk of stroke in AF patients. Some novel oral anticoagulants are associated with a lower stroke and/or major bleeding risk than warfarin. In addition to the safety and effectiveness of drug therapy, as reported in this study, individual treatment recommendations should also consider the patient's underlying stroke and bleeding risk profile.
Development of a piezo‐actuated micro‐teleoperation system for cell manipulation

Intracytoplasmic sperm injection (ICSI) requires long training and has low success rates, primarily due to poor control over the injection force. Making force feedback available to the operator will improve the success rate of the injection task. A macro–micro‐teleoperation system bridges the gap between the task performed at the micro‐level and the macroscopic movements of the operator. The teleoperation slave manipulator should accurately position a needle to precisely penetrate a cell membrane. Piezoelectric actuators are widely used in micromanipulation applications; however, hysteresis non‐linearity limits the accuracy of these actuators.
The CCM Based Implementation of the Parallel Variant of BiCG Algorithm Suitable for Massively Parallel Computing

The paper presents the implementation of a method for solving the large sparse non-symmetric linear system on the CCM class parallel machine. The method is an adaptation of the well-known biconjugate gradient algorithm. The equations solved results from the FEM based computations of the 3D electromagnetic field with a motion taken into account
Targeted Disruption of Decorin Leads to Abnormal Collagen Fibril Morphology and Skin Fragility

Decorin is a member of the expanding group of widely distributed small leucine-rich proteoglycans that are expected to play important functions in tissue assembly. We report that mice harboring a targeted disruption of the decorin gene are viable but have fragile skin with markedly reduced tensile strength. Ultrastructural analysis revealed abnormal collagen morphology in skin and tendon, with coarser and irregular fiber outlines. Quantitative scanning transmission EM of individual collagen fibrils showed abrupt increases and decreases in mass along their axes, thereby accounting for the irregular outlines and size variability observed in cross-sections. The data indicate uncontrolled lateral fusion of collagen fibrils in the decorindeficient mice and provide an explanation for the reduced tensile strength of the skin. These findings demonstrate a fundamental role for decorin in regulating collagen fiber formation in vivo.
The Impact of Organizational Culture on Process Innovation

Process innovation is vital, but paradoxical, requiring flexibility and empowerment, as well as control and efficiency. Increasingly, literatures stress organizational culture as a key to process innovation. Yet culture remains an intricate, amorphous phenomenon. In this article, we explore how organizational supportive culture – impact a particular process innovation, the implementation of advanced manufacturing technology. The study first examines how flexibility and control value profiles influence plant performance. We then discuss the role of value congruence, whether managers and operators perceive similar organizational values, and the impact of value-practice interactions.
Exploring the pathway structure of metabolism: decomposition into subnetworks and application to Mycoplasma pneumoniae

MOTIVATION Reconstructing and analyzing the metabolic map of microorganisms is an important challenge in bioinformatics. Pathway analysis of large metabolic networks meets with the problem of combinatorial explosion of pathways. Therefore, appropriate algorithms for an automated decomposition of these networks into smaller subsystems are needed. RESULTS A decomposition algorithm for metabolic networks based on the local connectivity of metabolites is presented. Interrelations of this algorithm with alternative methods proposed in the literature and the theory of small world networks are discussed. The applicability of our method is illustrated by an analysis of the metabolism of Mycoplasma pneumoniae, which is an organism of considerable medical interest. The decomposition gives rise to 19 subnetworks. Three of these are here discussed in biochemical terms: arginine degradation, the tetrahydrofolate system, and nucleotide metabolism. The interrelations of pathway analysis of biochemical networks with Petri net theory are outlined.
Practical Prediction of Inductive Generalization by the Method of Random Falsifiability

The relationship between learner capacity and generalization, established by Vapnik’s uniform convergence framework, suggests a remarkably simple validation procedure: reject the inductive hypothesis if the learning algorithm can also store the training examples with random labels. We study the properties of this apparently coarse estimator, which can be considered as the simplest possible capacity control method. First, the method is theoretically derived, under reasonable assumptions, from the uniform convergence requisites for generalization. Then, exhaustive experiments are performed on synthetic and natural data. Finally, we characterize the kind of learning situations in which the validation method is appropriate. We also discuss some implications with respect to the theoretical limits of pure induction. In summary, we will show that the method of random falsifiability is a satisfactory qualitative generalization predictor for learning machines with controllable capacity that try to minimize the empirical error. It is especially useful in adverse situations in which the problem distribution and the properties of the learning machine (e.g. its VC dimension) are unknown and additional test examples are not available.
Discrete Time Block Control for a Double Fed Induction Generator Coupled to a Wind Turbine Emulator in the Presence of Grid Faults

– In this paper, the authors propose a scheme to react to grid faults. This is based on block control technique using sliding modes. For normal operation the electric torque and the reactive power are controlled; when the fault is incepted the electric torque and the stator current are controlled. The wind turbine is emulated by a DC motor, which is controlled using a discrete time block controller which includes sliding modes. The applicability of the proposed scheme is tested via simulation.
A Human-Health Risk Assessment for West Nile Virus and Insecticides Used in Mosquito Management

West Nile virus (WNV) has been a major public health concern in North America since 1999, when the first outbreak in the Western Hemisphere occurred in New York City. As a result of this ongoing disease outbreak, management of mosquitoes that vector WNV throughout the United States and Canada has necessitated using insecticides in areas where they traditionally have not been used or have been used less frequently. This has resulted in concerns by the public about the risks from insecticide use. The objective of this study was to use reasonable worst-case risk assessment methodologies to evaluate human-health risks for WNV and the insecticides most commonly used to control adult mosquitoes. We evaluated documented health effects from WNV infection and determined potential population risks based on reported frequencies. We determined potential acute (1-day) and subchronic (90-day) multiroute residential exposures from each insecticide for several human subgroups during a WNV disease outbreak scenario. We then compared potential insecticide exposures to toxicologic and regulatory effect levels. Risk quotients (RQs, the ratio of exposure to toxicologic effect) were < 1.0 for all subgroups. Acute RQs ranged from 0.0004 to 0.4726, and subchronic RQs ranged from 0.00014 to 0.2074. Results from our risk assessment and the current weight of scientific evidence indicate that human-health risks from residential exposure to mosquito insecticides are low and are not likely to exceed levels of concern. Further, our results indicate that, based on human-health criteria, the risks from WNV exceed the risks from exposure to mosquito insecticides.
International Journal of Video&image Processing and Network Security Multiple Degree Reduction of Interval Dp Curves

— Fixed DP curve is a recent representation of the polynomial curves, proposed by Delgado and Pena in 2003. They introduced a new curve representation with linear computational complexity. An algorithmic approach to degree reduction of interval DP curve is presented in this paper. The four fixed Kharitonov's polynomials (four fixed DP curves) associated with the original interval DP curve are obtained. These four fixed DP curves are transformed into four fixed Bezier curves. The degree of the four fixed Bezier curves is reduced based on the matrix representations of the degree reduction process. The process of degree reduction times are applied to the four fixed Bezier curves of degree to obtain the four fixed Bezier curves of degree without changing their shapes. The four fixed reduced Bezier curves are converted into DP curves of the same degree. Finally the reduced interval DP control points are obtained from the four fixed reduced DP control points. An illustrative example is included in order to demonstrate the effectiveness of the proposed method.
Optimal number of users in zero-forcing based multiuser MIMO systems with large number of antennas

The optimal number of users achieving the maximum sum throughput is analyzed in zero-forcing (ZF) based multiuser multiple-input multiple-output (MIMO) systems with a large number of base station (BS) antennas. By utilizing deterministic ergodic sum rates for the ZF-beamforming (ZF-BF) and ZF-receiver (ZF-R) with a large number of BS antennas [1], [2], we can obtain the ergodic sum throughputs for the ZF-BF and ZF-R for the uplink and downlink frame structures, respectively. Then, we can also formulate and solve the optimization problems maximizing the ergodic sum throughputs with respect to the number of users. This paper shows that the approximate downlink sum throughput for the ZF-BF is a concave function and the approximate uplink sum throughput for the ZF-R is also a concave function in a feasible range with respect to the number of users. The simulation results verify the analyses and show that the derived numbersof users provide the maximum sum throughputs for the ZF-BF as well as ZF-R in multiuser MIMO systems with a large number of BS antennas.
A Sales Forecasting Model Based on Internal Organizational Variables

In this paper we develop a sales forecasting model for a small sized business unit focused on exports. Through a choice of internal explanatory variables in the organization we develop an econometric sales forecasting method, and compare its outputs with simpler univariate forecasting techniques in use at the organization. We show that the econometric technique produces a better fit to observable data, allowing for sensible statistical inference, and adds explanatory features not accessible to the simpler extrapolation techniques, by integrating quantitative variables accounting for relevant management decisions.
Experiments on Selection of Pre-processing Method for Performance Augmentation of Classifier

Business and Research organizations are continuously generating huge amount of high dimensional data. They need to analyze this data in real-time with minimum cost. Data pre-processing techniques in combination with dimensionality reduction techniques are widely used by researchers to improve the quality of data and reduce the time, cost required to analyze the data. But standard methods are not available to select the combination of data pre-processing and feature selection techniques. This paper presents a novel method for selecting combination of pre-processing and feature selection method. Experimental results are provided to support the efficiency of proposed mechanism.
Rate-distortion performance in coding bandlimited sources by sampling and dithered quantization

The rate-distortion characteristics of a scheme for encoding continuous-time band limited stationary sources, with a prescribed band, is considered. In this coding procedure the input is sampled at Nyquist's rate or faster, the samples undergo dithered uniform or lattice quantization, using subtractive dither, and the quantizer output is entropy-coded, The rate-distortion performance, and the tradeoff between the sampling rate and the quantization accuracy is investigated, utilizing the observation that the coding scheme is equivalent to an additive noise channel. It is shown that the mean-square error of the scheme is fixed as long as the product of the sampling period and the quantizer second moment is kept constant, while for a fixed distortion the coding rate generally increases when the sampling rate exceeds the Nyquist rate. Finally, as the lattice quantizer dimension becomes large, the equivalent additive noise channel of the scheme tends to be white Gaussian, and both the rate and the distortion performance become invariant to the sampling rate. >
Fast Queries Over Heterogeneous Data Through Engine Customization

Industry and academia are continuously becoming more data-driven and data-intensive, relying on the analysis of a wide variety of heterogeneous datasets to gain insights. The different data models and formats pose a significant challenge on performing analysis over a combination of diverse datasets. Serving all queries using a single, general-purpose query engine is slow. On the other hand, using a specialized engine for each heterogeneous dataset increases complexity: queries touching a combination of datasets require an integration layer over the different engines. This paper presents a system design that natively supports heterogeneous data formats and also minimizes query execution times. For multi-format support, the design uses an expressive query algebra which enables operations over various data models. For minimal execution times, it uses a code generation mechanism to mimic the system and storage most appropriate to answer a query fast. We validate our design by building Proteus, a query engine which natively supports queries over CSV, JSON, and relational binary data, and which specializes itself to each query, dataset, and workload via code generation. Proteus outperforms state-of-the-art open-source and commercial systems on both synthetic and real-world workloads without being tied to a single data model or format, all while exposing users to a single query interface.