Miracle-dz/UniFAR-FTUs huggingface dataset:
Personalized intra- and inter-city travel recommendation using large-scale geotags

In this paper, a geotag-based inter- and intra-city travel recommendation system that considers both the personal preference and the seasonal/temporal popularity is presented. For the inter-city recommendation, a combination of two similarity measure among users is proposed. Accurate intra-city recommendation is achieved by incorporating the seasonal and temporal information into a Markov model. The effectiveness of the proposed algorithm has been experimentally demonstrated by using more than 6 million geotags downloaded from Flickr.
Rows vs Columns for Linear Systems of Equations - Randomized Kaczmarz or Coordinate Descent?

This paper is about randomized iterative algorithms for solving a linear system of equations $X \beta = y$ in different settings. Recent interest in the topic was reignited when Strohmer and Vershynin (2009) proved the linear convergence rate of a Randomized Kaczmarz (RK) algorithm that works on the rows of $X$ (data points). Following that, Leventhal and Lewis (2010) proved the linear convergence of a Randomized Coordinate Descent (RCD) algorithm that works on the columns of $X$ (features). The aim of this paper is to simplify our understanding of these two algorithms, establish the direct relationships between them (though RK is often compared to Stochastic Gradient Descent), and examine the algorithmic commonalities or tradeoffs involved with working on rows or columns. We also discuss Kernel Ridge Regression and present a Kaczmarz-style algorithm that works on data points and having the advantage of solving the problem without ever storing or forming the Gram matrix, one of the recognized problems encountered when scaling kernelized methods.
Apparent Motion from Outside the Visual Field, Retinotopic Cortices May Register Extra-Retinal Positions

Observers made a saccade between two fixation markers while a probe was flashed sequentially at two locations on a side screen. The first probe was presented in the far periphery just within the observer's visual field. This target was extinguished and the observers made a large saccade away from the probe, which would have left it far outside the visual field if it had still been present. The second probe was then presented, displaced from the first in the same direction as the eye movement and by about the same distance as the saccade step. Because both eyes and probes shifted by similar amounts, there was little or no shift between the first and second probe positions on the retina. Nevertheless, subjects reported seeing motion corresponding to the spatial displacement not the retinal displacement. When the second probe was presented, the effective location of the first probe lay outside the visual field demonstrating that apparent motion can be seen from a location outside the visual field to a second location inside the visual field. Recent physiological results suggest that target locations are “remapped” on retinotopic representations to correct for the effects of eye movements. Our results suggest that the representations on which this remapping occurs include locations that fall beyond the limits of the retina.
Remittances and financial sector development. Lessons from the Salvadoran case

The paper takes a closer look at the benefits and limitations of “banking” remittances in the case of El Salvador, where state-owned banks followed an active policy of reaching out to the diaspora. The first part analyzes the role of different financial institutions in the Salvadoran remittance market. The second part crosses financial data with remittance data across Salvadoran municipalities. Although coverage of the banking sector is limited to larger municipalities and those with better-than-average socioeconomic indicators, empirical results show that the banking sector is more developed in terms of per capita savings and number of accounts in remittanceintensive municipalities.
Effective Greedy Inference for Graph-based Non-Projective Dependency Parsing

Exact inference in high-order graph-based non-projective dependency parsing is intractable. Hence, sophisticated approximation techniques based on algorithms such as belief propagation and dual decomposition have been employed. In contrast, we propose a simple greedy search approximation for this problem which is very intuitive and easy to implement. We implement the algorithm within the second-order TurboParser and experiment with the datasets of the CoNLL 2006 and 2007 shared task on multilingual dependency parsing. Our algorithm improves the run time of the parser by a factor of 1.43 while losing 1% in UAS on average across languages. More-over, an ensemble method exploiting the joint power of the parsers, achieves an average UAS 0.27% higher than the TurboParser.
Speed Control of Induction Motor Drive Based on Indirect Vector Control Using PI Controller

INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY Speed Control of Induction Motor Drive Based on Indirect Vector Control Using PI Controller Mr.P.Nagasekhar Reddy pnsreddy04@gmail.com Abstract The induction motors were characterized by comple x, highly non-linear and time-varying dynamics, and hence their speed control is a challenging problem in the industry. The advent of vector control techn iques has solved induction motor control problems. The vector c ntrol analysis of an induction motor allows the decoupled analysis where the torque and the flux components c an be independently controlled (just as in dc motor ). This makes the analysis easier than the per phase equivalent c ircuit. In indirect vector control scheme a current controlled voltage source inverter is considered, in which the stator phase currents serve as inputs, hence the s tator dynamics can be neglected. In recent years, the field orient ed control of induction motor drive is widely used in high performance drive system. It is due to its unique c haracteristics like high efficiency, good power fac tor and extremely rugged. This paper presents digital simul ation of indirect vector controlled based speed con trol of induction motor drive by means of PI controller usi ng MATLAB/SIMULINK.
Severe acute pancreatitis: a possible role of intramyocardial cytokine production.

CONTEXT Several mechanisms are involved in the development of the local and systemic response in acute pancreatitis. Cardiovascular system may be affected throughout the clinical course of acute pancreatitis. The aim was to evaluate local myocardial cytokine production, as well as, functional and histological myocardial alterations in severe acute pancreatitis. METHODS The animals were divided into three groups: Group 1: control; Group 2: sham; Group 3: severe acute pancreatitis. Echocardiographic assessment of cardiac function, serum levels of amylase and cytokines (TNF-α, IL-6 and IL-10), and mRNA expression of TNF-α, IL-6 and TGF-β were measured. Myocardial tissue alterations were analysed by histological examination. RESULTS The serum TNF-α and IL-10 levels were significant higher in AP 2h group. The mRNA IL-6 levels from group AP 2h were statistically higher. The mRNA TNF-α level from sham group and AP 2h were statistically lower. Significant changes in the left ventricular diameter were found in AP 2h and AP 12h groups. There were statistical changes for vacuolar degeneration, picnosis and loss of nucleus, and lymphocytes. CONCLUSION We found cardiac and histological changes compatible with the inflammatory process triggered by SAP with the promotion of local myocardial cytokine production.
The depolarization properties of powerful extragalactic radio sources as a function of cosmic epoch

We use the observed polarization properties of a sample of 26 powerful radio galaxies and radio-loud quasars to constrain the conditions in the Faraday screens local to the sources. We adopt the cosmological redshift, low-frequency radio luminosity and physical size of the large-scale radio structures as our ‘fundamental’ parameters. We find no correlation of the radio spectral index with any of the fundamental parameters. The observed rotation measure is also independent of these parameters, suggesting that most of the Faraday rotation occurs in the Galactic foreground. The difference between the rotation measures of the two lobes of an individual source, as well as the dispersion of the rotation measure, shows significant correlations with the source redshift, but not with the radio luminosity or source size. This is evidence that the small-scale structure observed in the rotation measure is caused by a Faraday screen local to the sources. The observed asymmetries between the lobes of our sources show no significant trends with each other or other source properties. Finally, we show that the commonly used model for the depolarization of synchrotron radio emission by foreground Faraday screens is inconsistent with our observations. We apply alternative models to our data and show that they require a strong increase of the dispersion of the rotation measure inside the Faraday screens with cosmological redshift. Correcting our observations with these models for redshift effects, we find a strong correlation of the depolarization measure with redshift and a significantly weaker correlation with radio luminosity. We do not find any (anti-)correlation of depolarization measure with source size. All our results are consistent with a decrease in the order of the magnetic field structure of the Faraday screen local to the sources for increasing cosmological redshift.
On quantum preimage attacks

We propose a preimage attack against cryptographic hash functions based on the speedup enabled by quantum computing. Preimage resistance is a fundamental property cryptographic hash functions must possess. The motivation behind this work relies in the lack of conventional attacks against newly introduced hash schemes such as the recently elected SHA-3 standard. The proposed algorithm consists of two parts: a classical one running in O(log2 |S|), where S represents the searched space, and a quantum part that contains the bulk of the Deutsch-Jozsa circuit. The mixed approach we follow makes use of the quantum parallelism concept to check the existence of an argument (preimage) for a given hash value (image) in the preestablished search space. For this purpose, we explain how a non-unitary measurement gate can be used to determine if S contains the target value. Our method is entirely theoretical and is based on the assumptions that a hash function can be implemented by a quantum computer and the key measurement gate we describe is physically realizable. Finally, we present how the algorithm finds a solution on S.
Three Compositional Varieties of Rare-Earth Element Ore: Eudialyte-Group Minerals from the Norra Kärr Alkaline Complex, Southern Sweden

Agpaitic nepheline syenites at the Norra Karr Alkaline Complex, southern Sweden, are rich in zirconium and rare-earth elements (REE), which are mainly accommodated in eudialyte-group minerals (EGM). Norra Karr hosts three compositionally distinct groups of EGM, which are complex zirconosilicates. Analyses of EGM by electron beam energy-dispersive (SEM-EDS) and wavelength-dispersive (WDS-EMP) X-ray microanalysis are presented and compared, complemented by whole-rock analyses. The SEM-EDS and WDS-EMP methods produce comparable results for most elements. Considering that most SEM instruments have a user-friendly EDS system, it is a useful tool for reconnaissance work in research and especially in exploration-related studies. The EGM evolved markedly from an initial Fe-rich and REE-poor, but HREE-dominated variety, to an intermediate Fe-Mn and HREE-rich one, and to a final Mn- and LREE-rich variety, which occur in rocks classified as lakarpite and grennaite. Based on the Mn/(Fe+Mn) ratios of the EGM, this trend is interpreted as a result of magmatic evolution. The threefold diversity of EGM presented in this work is much broader than has previously been documented.
Automated Policy Analysis

Static analysis of access-control policies is becoming increasingly important. Such analysis can reveal errors and vulnerabilities in the policies, as well as logical inconsistencies, unintended effects, and discrepancies between different policies or different versions of the same policy. In the process, it helps policy developers to better understand the effects of their policies. Policy analysis has typically been done by hand. For instance, when a bug is discovered and corrected, the resulting policy is manually inspected to ensure that the fix works and that it does not introduce any new problems. But when the policies are large or their logical structure non-trivial, performing such analysis manually is tedious and error-prone. In this paper we show how to automate a wide array of useful policy analyses. This is accomplished by representing policies as logical formulas in the SMT (satisfiability-modulo-theory) subset of first-order logic, and couching analysis questions as SMT problems, which are then solved by efficient off-the-shelf SMT solvers. Because SMT solvers can reason about arithmetic and inductive data types, in addition to Boolean constraints, our system can handle many policies that cannot be analyzed by existing policy engines. We describe the formulation of a number of useful analyses (consistency, completeness, and observational equivalence), and report experimental results on the efficiency of our implementation for analyzing policies of various sizes and kinds of logical structure.
Traffic organization method for emergency evacuation based on information centrality

Large-scale natural or man-made disasters have the potential to cause great loss of life, human injury and extreme property damage. Evacuation from areas at risk is often one of the most feasible strategies that can be undertaken in response to these types of disasters. Evacuating a large population in the shortest possible time is an extremely complicated and difficult task, which primarily relies on efficient method of traffic organization for emergency evacuation corridors. This paper, on the foundation of efficiency and contingency, puts forward a novel method of emergency evacuation traffic organization using information centrality of complex network theory, the characteristic of which integrates a method of emergency evacuation corridors optimization and traffic organization method of emergency evacuation corridors. In addition, the efficiency function in information centrality has been improved. The experiment results show that the proposed method has rationality and feasibility.
High Resolution SAR Images Multi-Layer Segmentation Based on Graph Partitioning

A method based on multi-scale inherited information for SAR image segmentation is proposed. This method combines image's macroscopical and microcosmical features together, introducing the traditional single scale processing technique into the dynamic changing multi-scale analyzed framework, which makes it easy to obtain image essential features. Anisotropic diffusion equation is adopted to get multi-scale images sequences. From coarser scale to finer scale inherited graph partitioning strategy is used, for coarser scale is easy to be segmented and the segmentation results can lead finer scale segmentation. The experimental results on real high resolution SAR images demonstrate the merit of proposed method. Moreover, this method can fulfill the request of different image processing task, and consists with people's cognizing process and vision process system. The request of extracting more information from SAR images is higher than ever before, especially in the filed of remote sensing with quickly development nowadays. The pixel-based methods in image processing applications like classification, target recognition, image compression are not satisfied the requirement. The object-based methods describe the space relationship among the whole and the parts well and truly, and are capable of actualizing high-level image processing and image understanding for dealing with image objects or segments. In this paper, we propose a multi-scales and multi-level inherited segmentation algorithm which is object-based analytical method for high resolution SAR images. This method includes flowing major steps. Firstly, it uses anisotropic diffusion equation to obtain the multi-scale images. Secondly, it adopts inherited graph partitioning strategy from coarser scale to finer scale, in the same time, improves the single-scale graph partitioning to multi-scale analyzed framework. Thirdly, it establishes segmentation inherited relationships of different scales through the multi- scale graph partitioning process. At last, through all scale images the target region can be extract easily. Also, this method can fulfill the request of different SAR image analysis and processing task, and consists with people's cognizing process and vision process system. II. MULTI-SCALE ANALYSIS
Graphical display of qvalue objects Description Usage

hedenfalk Gene expression dataset from Hedenfalk et al. (2001) Description The data come from the breast cancer cDNA microarray experiment of Hedenfalk et al. (2001). In the original experiment, comparison was made between 3,226 genes of two mutation types, BRCA1 (7 arrays) and BRCA2 (8 arrays). The data included here are p-values obtained from a two-sample t-test analysis on a subset of 3,170 genes, as described in Storey and Tibshirani (2003). Value hedenfalk Vector of 3,170 p-values of tests comparing BRCA1 to BRCA2.
Quantitative and Qualitative Support for Non-Functional Requirements in Stock Trading Systems

The efficient functioning of financial markets is important for growth across the world, affecting businesses, society and individuals. Stock trading, a key activity within financial markets, is undergoing major transformation fuelled by advances in information systems techniques. Our motivation is in the development of stock trading systems that are robust and are transparent to regulators, traders and the public. Specifically, the work presented in this paper focuses on the way that quality factors may be considered at the requirements phase when designing systems to support sock trading processes. We focus on three quality factors namely performance, availability and security. We introduce a modeling paradigm that extends the well-known UML Activity model to explicitly represent these three quality factors and augment this through quantitative and qualitative reasoning. The approach is exemplified through the use of a small aspect of a stock trading process, dealing with the ‘order crossing’ part, taken from the practices of an international firm.
Close-in phase-noise enhanced voltage-controlled oscillator employing parasitic V-NPN transistor in CMOS process

This paper presents a voltage-controlled oscillator (VCO) with low close-in phase noise by exploiting a parasitic vertical NPN transistor (V-NPN) as a tail current source in a 0.18-/spl mu/m CMOS process. V-NPN has an inherently low flicker noise (1/f noise) profile compared to CMOS devices. Simple dc and ac characteristics of V-NPN are measured and extracted for design convenience. The proposed VCO that used a V-NPN current source instead of nMOS is verified using a 0.18-/spl mu/m deep n-well CMOS process. Test results of the designed VCO show good figure-of-merit of -87.4 dBc/Hz, -111 dBc/Hz of phase noise at 10 kHz, and 100-kHz offsets while consuming only 540 /spl mu/W from the 1.8-V supply.
EFFICIENT VLSI ARCHITECTURE USING DIT-FFT RADIX-2 AND SPLIT RADIX FFT ALGORITHM

FFT has wide use in communication for processing the data being exchanged. Hence it is important to develop high-performance FFT architecture to meet the requirements of real time and low cost in many different systems. Efficient VLSI architecture based on Field Programmable Gate Array (FPGA) for Wireless Local Area Networks (WLAN) is presented in this paper. This paper concentrates on the development of the Fast Fourier Transform (FFT), based on Decimation-In-Time (DIT) domain, Radix-2 FFT algorithm and Split Radix FFT Algorithm and finally architectures by two different algorithms are compared for speed and device utilization. This paper concerns about design of DIT-FFT for different sized inputs using Verilog HDL as a design entity, and their Synthesis by Xilinx Synthesis Tool on Spartan kit. Among the different proposed algorithms, split-radix FFT has shown considerable improvement in terms of reducing hardware complexity of the architecture compared to radix2 and radix-4 FFT algorithms. The synthesis results show that the computation for calculating the 32-point Fast Fourier transform is efficient in terms of speed.
Combining test case generation for component and integration testing

When integrating different system components, the interaction between different features is often error prone. Typically errors occur on interruption, concurrency or disabling/enabling between different features. Test case generation for integration testing struggles with two problems: the large state space and that these critical relationships are often not explicitly modeled. The approach presented in this paper is to use task models to describe the interaction between environment and system. This restricts the possible state space to a feasible size and enables the generation of task sequences, which cover the critical interaction scenarios. These task sequences are too abstract for testing the System-Under-Test (SUT), due to missing input- and expected output behavior. To overcome the different abstraction levels, the tasks are mapped to component behavior models. Based on this mapping, task sequences can be enriched with additional information from the component models and thereby executed to test the SUT.
ACCURACY ASSESSMENT METHOD FOR WETLAND OBJECT-BASED CLASSIFICATION

The object-based classification approach needs an adaptation of the traditional accuracy assessment methodology. This paper presents a methodology that considers the inherent variability within each wetland class for the sampling size calculation based on objects and a stratified random sampling to select samples for each category. The polygons selected for validation are overlaid on the data used for classification. The analyst uses all ancillary data available to build an interpretation key which defines the labels of the polygons. The error matrix representing the whole territory could then be calculated. Finally, considering that wetland classes are not completely discrete and that the delineation is rarely categorical, fuzzy logic is used to analyze the accuracy. Decision rules are built based on class description to accept a relative level of confusion between similar classes.