Miracle-dz/UniFAR-FTUs huggingface dataset:
Real Time Information Extraction from Microblog

This paper present the participation of Information Retrieval Lab(IR LAB DA-IICT Gandhinagar) in FIRE 2016 Microblog Track. The main objective of the track is to identify Information Retrieval methodologies to retrieve important information from Twitter posted during the disasters. We have submitted two runs for this track. In the first run, daiict irlab 1, we have expanded topic term using Word2vec model trained by the tweet corpus provided by the organizer. Relevance score between tweet and corpus are calculated by Okapi BM25 model. Precision@20 ,primary metric, for this run, is 0.3143. In the second run,daiict irlab 2, we have set different weight for original term and expanded topic term, we achieve precision@20 around 0.30.
Smart grid traffic modeling and scheduling using 3GPP LTE for efficient communication with reduced RAN delays

There has been a dramatic improvisation in communication technologies during the last two decades. This in turn has evolved as a great source of strength to ideas regarding implementation of smart grids. This paper has three basic emphasis areas. At first, it presents a smart grid top to down hierarchy tree based traffic model by considering the different types of information carrying traffic travelling between multiple nodes of a smart grid. This is done by analyzing the multiple functions performed by a smart grid. After that 3GPP LTE is addressed as the most promising communication backbone for smart grid environment. Its performance has been analyzed in terms of high data rates, improved coverage and reduced Scheduling and Transmission delays. In the end, a priority based queuing technique for smart grid traffic is proposed by categorizing the smart grid traffic into different classes with each class representing a different type of information/data. This results in reducing the queuing delays of traffic at end and intermediate nodes. It has been shown through results that the proposed traffic modeling, scheduling and queuing result in reduced Random Access Network (RAN) delays.
Occluder Shadows for Fast Walkthroughs of Urban Environments

This paper describes a new algorithm that employs image‐based rendering for fast occlusion culling in complex urban environments. It exploits graphics hardware to render and automatically combine a relatively large set of occluders. The algorithm is fast to calculate and therefore also useful for scenes of moderate complexity and walkthroughs with over 20 frames per second. Occlusion is calculated dynamically and does not rely on any visibility precalculation or occluder preselection. Speed‐ups of one order of magnitude can be obtained.
JPEG2000: the new still picture compression standard

This paper presents an overview of the upcoming JPEG2000 still picture compression standard. JPEG2000 is not only intended to provide rate-distortion and subjective image quality performance superior to existing JPEG standard, but to also provide functionality that the current JPEG standard can either not address efficiently nor address at all. Lossless and lossy compression, encoding of very large images, progressive transmission by pixel accuracy and by resolution, robustness to the presence of bit-errors and region-of-interest coding, are some representative examples of its features.
Joint transmitter-receiver optimization for multiple input multiple output (MIMO) systems

Multiple transmit (Tx) and multiple receive (Rx) antenna systems, referred to as multiple input multiple output (MIMO) systems, have been proposed to achieve higher data rates in wireless communication systems. In this paper, we investigate joint optimization of transmitter and receiver for MIMO system when the channel information is available at both transmitter and receiver. We discuss the problem of designing Tx and Rx filter based on minimum bit error probability criterion. We first derive the optimum Tx and Rx filters for the special case of two input data symbols. Based on this optimum filter, we propose a Tx and Rx filter optimization for the general case of input data symbols. The performance of the proposed Tx and Rx filters is compared with that of the conventional minimum mean-squared error (MMSE) filter. Performance analysis shows that the proposed filter provides significant improvement over the MMSE filter in bit error probability.
Functions of Positive Emotions: Gratitude as a Motivator of Self-Improvement and Positive Change

Positive emotions are highly valued and frequently sought. Beyond just being pleasant, however, positive emotions may also lead to long-term benefits in important domains, including work, physical health, and interpersonal relationships. Research thus far has focused on the broader functions of positive emotions. According to the broaden-and-build theory, positive emotions expand people’s thought–action repertoires and allow them to build psychological, intellectual, and social resources. New evidence suggests that positive emotions—particularly gratitude—may also play a role in motivating individuals to engage in positive behaviors leading to self-improvement. We propose and offer supportive evidence that expressing gratitude leads people to muster effort to improve themselves via increases in connectedness, elevation, humility, and specific negative states including indebtedness.
Spivak and Rivera Cusicanqui on the Dilemmas of Representation in Postcolonial and Decolonial Feminisms

Abstract:Gayatri Spivak and Silvia Rivera Cusicanqui writings are regularly and justifiably cited in reference to postcolonial and decolonial feminisms. Both grapple with the thorny matter of representing subalternity and indigeneity, not only in Eurocentric scholarship, but also by migrant and diasporic academics and national elites. In this commentary, I foreground how Spivak and Rivera Cusicanqui's persistent critiques of representation are imperative because they further postcolonial and decolonial feminist scholarship and call for dialogues between them. Such dialogues entail reaching across linguistic, historical, geographical, political, and theoretical boundaries to establish anti-colonial alliances.
Enhancing low light images using near infrared flash images

In low light environment, photographs taken with a high ISO setting suffer from significant noise. In this paper, we propose to use a near infrared (NIR) flash image, instead of a normal visible flash image, to enhance its corresponding noisy visible image. We build a hybrid camera system to take an visible image and its NIR counterpart simultaneously. We introduce a new method to denoise an visible image and enhance its details using its corresponding NIR flash image. Experimental results show the superiority of our method compared with previous image denoising and detail enhancement methods.
Shitstorms, bobler eller sagsorienterede offentligheder? Digitale metoder og kontroverser på sociale medier

Kontroversen om planerne for en betalingsring i Kobenhavn afstedkom blandt andet en raekke sider pa Facebook. Eksemplet er ikke enestaende: Sociale medier laegger i disse ar ofte brugerflade til folkelige protester og kontroverser. Sociologien har med digitale metoder faet en raekke vaerktojer til at indsamle data om dem. Flere af de digitale teknikker er formet af et teoretisk udgangspunkt hos Bruno Latour. Artiklen undersoger, hvilke metodiske retningslinjer der folger af en Latour-inspireret forstaelse af politik og demokrati. Forst afsoges Latours inspirationskilder i den amerikanske pragmatisme. Dernaest diskuteres Noortje Marres’ bud pa konsekvenserne for digitale metoder. Endelig analyseres betalingsringskontroversen for at give et eksempel pa en undersogelse med digitale metoder, der tager udgangspunkt i ideen om demokratisk offentlighed som noget, der opstar i anledning af konkrete problematiske sager. Analysen bygger pa 4.500 posts og kommentarer fra syv forskellige Facebook-sider om betalingsringen, der opsummeres i en co-wordvisualisering. Artiklen fremforer, at et Latour-inspireret fokus pa sagsorienterede offentligheder tilbyder et interessant alternativ til affejende begreber som shitstorms og ekkokamre, og diskuterer de metodiske udfordringer, som tilgangen medforer for digitale metoder. ENGELSK ABSTRACT Andreas Birkbak: Shit storms, bubbles or issue publics? Digital methods and controversies on social media The controversy around plans to introduce congestion charges in Copenhagen included a number of protest pages on Facebook. This is not unique since social media are often used for popular protests these days. With the rise of digital methods, sociology has obtained a number of tools for collecting data about such protests. Several of the digital techniques are inspired by the work of Bruno Latour. This article investigates the methodological challenges that arise from a Latour-inspired understanding of politics and democracy. First, Latour’s inspiration from American pragmatism is explored. Next, Noortje Marres’s arguments about the consequences for digital methods are discussed. Finally, the congestion charge controversy is analyzed in order to provide an example of an inquiry with digital methods that is based on the idea that publics emerge in relation to problematic issues. The analysis is based on 4,500 posts and comments from seven different Facebook pages about the congestion charge controversy. The article argues that a Latour-inspired focus on issue-oriented publics offers an interesting alternative to sweeping concepts like shit storms and echo chambers, and explores the methodological challenges that the approach entails for digital methods. Keywords: Digital methods, Facebook, publics, controversy, Latour, congestion charges
Medieval Affects Now

Medievalists are uniquely qualified to intervene in what has been called “the affective turn” in contemporary cultural theory (Clough and Halley 2007). That is because, as scholars working across history, literature, and religious studies are aware, the Middle Ages saw the rise of a distinctive form of devotion, which was characterized by corporeal intensity and which was widespread among those who had less access to traditional religion, notably women (“Affective Piety”, Wikipedia 2016). 1 For too long, however, what has been described as “affective piety” has been treated as a literary genre, a social phenomenon, or a religious trend. Affect has been treated as one, especially visible part of medieval devotional life.
Non-Gaussianity of the density distribution in accelerating universes: II. N-body simulations

We explore the possibility of putting constraints on dark energy models with the statistical property of large scale structure in the non-linear region. In particular, we investigate the w dependence of the non-Gaussianity of the smoothed density distribution generated by the non-linear dynamics. In order to follow the non-linear evolution of the density fluctuations, we apply N-body simulations based on a P3M scheme. We show that the relative difference between the non-Gaussianity of the w = −0.8 model and that of the w = −1.0 model is 0.67% (skewness) and 1.2% (kurtosis) for R = 8h−1 Mpc. We also calculate the corresponding quantities for R = 2h−1 Mpc, 3.0% (skewness) and 4.5% (kurtosis), and the difference turns out to be greater, even though the non-linearity on this scale is so strong that the complex physical processes of galaxy formation affect the galaxy distribution. From this, we expect it to turn out that the difference can be tested by all sky galaxy surveys with the help of mock catalogues created by selection functions, which suggests that non-Gaussianity of the density distribution may potentially play an important role in extracting information on dark energy.
Investigation of diversity techniques considering receiver structure in MIMO systems

This paper examines receiving antenna selection (RAS) and receiving antenna combination (RAC) techniques from the viewpoint of receiver structure with the aim of improving bit error rate (BER) performance for receivers in MIMO (multi-input multi-output) systems. We assume two receiver structures. One is a structure for controlling gain in received signals centrally for all receiving antennas (CC receiver). The other is a structure for controlling gain in received signals individually in each receiving antenna (CI receiver). We show that a CC receiver can obtain good BER performance when utilizing RAS/RAC techniques using the channel matrix eigenvalue (RAS/RAC-E). Additionally, we consider RAS/RAC techniques using the phase of the channel component (RAS/RAC-PC) and received power (RAS/RAC-RP) in a CI receiver. We then simulate BER performance when employing the proposed RAS-PC and RAS-RP techniques under Rayleigh fading channels. The results clearly show that the RAS/RAC-PC techniques are able to obtain good BER performance for a CI receiver.
A Scheme for Partial Disclosure of Transaction Log

SUMMARY To investigate cyber-criminals, Police sometimes asks Administrator of a computer system to disclose the whole transaction log. Administrator, however, wants to protect the privacy of innocent users. This paper presents a solution for the disclosure/privacy problem of transaction log. In this scheme, Police can search over the encrypted records of the transaction log by keywords. The administrator discloses only the records which include the keyword, but nothing more. Police can verify that the ad
Modeling Dynamic Systems with Efficient Ensembles of Process-Based Models

Ensembles are a well established machine learning paradigm, leading to accurate and robust models, predominantly applied to predictive modeling tasks. Ensemble models comprise a finite set of diverse predictive models whose combined output is expected to yield an improved predictive performance as compared to an individual model. In this paper, we propose a new method for learning ensembles of process-based models of dynamic systems. The process-based modeling paradigm employs domain-specific knowledge to automatically learn models of dynamic systems from time-series observational data. Previous work has shown that ensembles based on sampling observational data (i.e., bagging and boosting), significantly improve predictive performance of process-based models. However, this improvement comes at the cost of a substantial increase of the computational time needed for learning. To address this problem, the paper proposes a method that aims at efficiently learning ensembles of process-based models, while maintaining their accurate long-term predictive performance. This is achieved by constructing ensembles with sampling domain-specific knowledge instead of sampling data. We apply the proposed method to and evaluate its performance on a set of problems of automated predictive modeling in three lake ecosystems using a library of process-based knowledge for modeling population dynamics. The experimental results identify the optimal design decisions regarding the learning algorithm. The results also show that the proposed ensembles yield significantly more accurate predictions of population dynamics as compared to individual process-based models. Finally, while their predictive performance is comparable to the one of ensembles obtained with the state-of-the-art methods of bagging and boosting, they are substantially more efficient.
Title Gene expression patterns in human liver cancers

Hepatocellular carcinoma (HCC) is a leading cause of death worldwide. Using cDNA microarrays to characterize patterns of gene expression in HCC, we found consistent differences between the expression patterns in HCC compared with those seen in nontumor liver tissues. The expression patterns in HCC were also readily distinguished from those associated with tumors metastatic to liver. The global gene expression patterns intrinsic to each tumor were sufficiently distinctive that multiple tumor nodules from the same patient could usually be recognized and distinguished from all the others in the large sample set on the basis of their gene expression patterns alone. The distinctive gene expression patterns are characteristic of the tumors and not the patient; the expression programs seen in clonally independent tumor nodules in the same patient were no more similar than those in tumors from different patients. Moreover, clonally related tumor masses that showed distinct expression profiles were also distinguished by genotypic differences. Some features of the gene expression patterns were associated with specific phenotypic and genotypic characteristics of the tumors, including growth rate, vascular invasion, and p53 over-expression.
Haptics-enabled teleoperation for robot-assisted tumor localization

This paper focuses on the problem of incorporating haptics-enabled teleoperation in minimally invasive tumor localization. Since the stiffness of a tumor is higher than that of the surrounding tissue, it can be identified as a hard nodule when palpated. Using a Tactile Sensing Instrument (TSI) developed at CSTAR, the distributed pressure profiles along the contacting surface can be measured during remote tissue palpation. The tumor can be detected by using a visualization software that creates a color contour map based on the magnitude of the pressure over the palpated area. The accuracy of this method depends on the uniformity of the force applied to the tissue. A haptics-enabled teleoperation system provides the surgeon with the opportunity to feel the interaction force between the instrument and tissue during Minimally Invasive Surgery (MIS). The objective of this research was to assess the feasibility of combining force feedback with tactile feedback in order to increase the overall performance of tumor localization. The teleoperation system used in this work consists of a Mitsubishi PA10 robot as the slave that is remotely controlled (over a dedicated network) through a 7 Degree-Of-Freedom (DOF) haptic interface. A two-channel architecture, along with hybrid impedance control was utilized to form a bilateral teleoperation system in which the master is under force control and the slave is under position control. The experimental results confirm the effectiveness of using force feedback in robot-assisted tactile sensing for tumor detection.
Considering Security and Quality of Service in SLS to Improve Policy-Based Management of Multimedia Services

This paper proposes to improve policy-based management by integrating security parameters into the service level specification (SLS). Integrating those parameters in the QoS part of the service level agreement (SLA) specification is of particular importance for multimedia services requiring security since QoS is negotiated when the multimedia service is deployed. Security mechanisms need to be negotiated at that time when sensible multimedia information is exchanged. In this paper we show that including security parameters in SLA specification improves the negotiation and deployment of security and QoS policies for multimedia services. The parameters this paper proposes to integrate have the advantage to be understandable by end-users and service providers.
Factor Analysis and Construction of the Acceptance of Couple Violence Scale

ABSTRACT We examined the construction for a modified Acceptance of Couple Violence (ACV) scale administered to lesbian, gay, bisexual, transgender, and queer college students (N = 266) measuring intimate partner violence. We ran an exploratory and confirmatory factor analysis; results identified 1 factor for the instrument explaining 76% of the variance in scores for all items.
Statistically controlled opportunistic resource block sharing for femto cell networks

In this paper, we propose an efficient interference management technique which controls the number of resource blocks (or subcarriers) shared with other cells based on statistical interference levels among cells. The proposed technique tries to maximize average throughput of a femto cell user under a constraint on non-real time control of a femto cell network while guaranteeing a target throughput value of a macro cell user. In our proposed scheme, femto cells opportunistically use resource blocks allocated to other cellsif the required average user throughputis not attained with the primarily allocated resource blocks. The proposed method is similar to the underlay approach in cognitive radio systems, but resource block sharing among cells is statistically controlled. For the statistical control, a femto cell sever constructs a table storing average mutual interference among cells and periodically updates the table. This statistical approach fully satisfies the constraint of non-real time control for femto cell networks. Our simulation results show that the proposed scheme achieves higher average femto user throughput than conventional frequency reuse schemes for time varying number of users.
Hough-based object detection with grouped features

Hough-based voting approaches have been successfully applied to object detection. While these methods can be efficiently implemented by random forests, they estimate the probability for an object hypothesis independently for each feature. In this work, we address this problem by grouping features in a local neighborhood to obtain a better estimate of the probability. To this end, we propose oblique classification-regression forests that combine features of different trees. We further investigate the benefit of combining independent and grouped features and evaluate the approach on RGB and RGB-D datasets.
Sparse coding based VLAD for efficient image retrieval

Representing images and videos in the form of compact codes has emerged as an important research interest in the vision community, in the context of web scale image/video search. Recently proposed Vector of Locally Aggregated Descriptors (VLAD), has been shown to outperform the existing retrieval techniques, while giving a desired compact representation. VLAD aggregates the local features of an image in the feature space. In this paper, we propose to represent the local features extracted from an image, as sparse codes over an over-complete dictionary, which is obtained by K-SVD based dictionary training algorithm. The proposed VLAD aggregates the residuals in the space of these sparse codes, to obtain a compact representation for the image. Experiments are performed over the `Holidays' database using SIFT features. The performance of the proposed method is compared with the original VLAD. The 4% increment in the mean average precision (mAP) indicates the better retrieval performance of the proposed sparse coding based VLAD.
Seasonal and spatial variability of surface ozone over China: contributions from background and domestic pollution

Abstract. Both observations and a 3-D chemical transport model suggest that surface ozone over populated eastern China features a summertime trough and that the month when surface ozone peaks differs by latitude and region. Source-receptor analysis is used to quantify the contributions of background ozone and Chinese anthropogenic emissions on this variability. Annual mean background ozone over China shows a spatial gradient from 55 ppbv in the northwest to 20 ppbv in the southeast, corresponding with changes in topography and ozone lifetime. Pollution background ozone (annual mean of 12.6 ppbv) shows a minimum in the summer and maximum in the spring. On the monthly-mean basis, Chinese pollution ozone (CPO) has a peak of 20–25 ppbv in June north of the Yangtze River and in October south of it, which explains the peaks of surface ozone in these months. The summertime trough in surface ozone over eastern China can be explained by the decrease of background ozone from spring to summer (by −15 ppbv regionally averaged over eastern China). Tagged simulations suggest that long-range transport of ozone from northern mid-latitude continents (including Europe and North America) reaches a minimum in the summer, whereas ozone from Southeast Asia exhibits a maximum in the summer over eastern China. This contrast in seasonality provides clear evidence that the seasonal switch in monsoonal wind patterns plays a significant role in determining the seasonality of background ozone over China.