Miracle-dz/UniFAR-FTUs huggingface dataset:
A Signature Scheme Associated with Universal Re-signcryption

Today, with increasing deversity of network technologies, people have been likely to be interested in anonymity. The attacker might threaten anonymity of senders and receivers by confirming linkability between their sessions. Recently, Golle et al. proposed the re-encryption scheme applicable to Mix, called Universal Re-encryption. In this scheme, a ciphertext is supposed to be re-encrypted without public information corresponding to it. Moreover, only a subject that re-enctypts a ciphertext can know the correspondence of original ciphertext and it, and the computational complexity to break the unlinkability property is equal to the semantic secrecy. In this paper, we consider and improve the Universal Re-encryption scheme, and propose a scheme that can verify who transmit the message by adding the property of signature.
Combining Storytelling Tradition and Pervasive Gaming

In recent years storytelling has gone through various attempts of renaissance, thanks to a recreational storytelling revivalist movement, which has not been largely successful. Pervasive gaming is an all-encompassing branch in gaming and has the potential to reach a large amount of people. Moreover, it provides a way to mix modern society with age-old traditions like storytelling. This paper describes the development of a small scale pervasive game embedding at the same time social and improvisational features and the use of this game by amateur storytellers. The game, Props, aims to take storytelling from oblivion to modern urban environments.
A Speaker Identification System for Video Content Analysis

Recently, more literatures proposed to apply audio content analysis techniques in content-based video parsing. This paper presents our current works on a speaker identification system for video content analysis. The system is different from normal ones in the following aspects: firstly, soundtrack extracted from video stream includes not only silence and speech, but also music and environmental sound; secondly, the number of speakers in video content are uncertain; thirdly, the presence of noise in the video can significantly deteriorate system performance. According to these considerations, our speaker identification system involves such basic parts: audio classification and segmentation using rule and support vector machine (SVM) based classifier; speech clustering using spectral clustering technique and speaker identification based on Gaussian mixture model (GMM); speech enhancement based on spectral subtraction. Experiments are carried on a database extracted from news, conversation and movie videos. The obtained results confirm the validity of the proposed system architecture.
Fine‐scale genetic structure and its consequence in breeding aggregations of a passerine bird

The pattern of fine‐scale genetic structure in a population may reflect current biological processes of the species, such as natal dispersal, the breeding system and demography. We investigated the spatial distribution of nests and fine‐scale genetic structure during two breeding seasons in a population of a weakly territorial, flock‐living passerine bird, the vinous‐throated parrotbill, Paradoxornis webbianus. Nest distribution was clustered. There were two peaks of egg laying within each breeding season, and spatial clustering of nests was more extreme during the second peak after controlling for breeding density. The patterns of genetic structure during the breeding season varied with parental sex and season. Genetic structure occurred during the second laying peak: males breeding within 200 m of one another at this time were significantly more closely related than males breeding farther apart. However, no apparent genetic structure was detected in males during the first laying peak or among females in either laying peak. These results reveal male‐oriented kin affiliation during part of the breeding season in this species. Furthermore, juvenile recruitment into the winter flocks was positively related to this increased relatedness among males via kin affiliation. This study implies that fine‐scale genetic structure during the breeding season could be a factor determining individual fitness and may play an important role in our understanding of the evolution of social systems.
Development platform for parallel image processing

This paper describes a development distributed platform with client-server architecture that allows developing parallel primary image processing on a cluster with variable number of workstations. The principles of the software and hardware architecture of this platform are presented underlining the versatility and the capacity of adaptation to a specific application. Experimental results show that for a realistic image processing application performances are accurate and consequently the core of the architecture forms a powerful basis for automatic parallelization of a wide range of image processing software.
Throughput-Optimal Load Balancing for Intra Datacenter Networks

Traffic load-balancing in datacenters alleviates hot spots and improves network utilization. In this paper, a stable in-network load-balancing algorithm is developed in the setting of software-defined networking. A control plane configures a data plane over successive intervals of time. While the MaxWeight algorithm can be applied in this setting and offers certain throughput optimality properties, its bang-bang control structure rewards single flows on each interval and prohibits link-capacity sharing. This paper develops a new algorithm that is throughput-optimal and allows link-capacity sharing, leading to low queue occupancy. The algorithm deliberately imitates weighted fair queueing, which provides fairness and graceful interaction with TCP traffic. Inspired by insights from the analysis, a heuristic improvement is also developed to operate with practical switches and TCP flows. Simulations from a network simulator shows that the algorithm outperforms the widely-used equal-cost multipath (ECMP) technique.
Extending anisotropic operators to recover smooth shapes q

Anisotropic differential operators are widely used in image enhancement processes. Recently, their property of smoothly extending functions to the whole image domain has begun to be exploited. Strong ellipticity of differential operators is a requirement that ensures existence of a unique solution. This condition is too restrictive for operators designed to extend image level sets: their own functionality implies that they should restrict to some vector field. The diffusion tensor that defines the diffusion operator links anisotropic processes with Riemmanian manifolds. In this context, degeneracy implies restricting diffusion to the varieties generated by the vector fields of positive eigenvalues, provided that an integrability condition is satisfied. We will use that any smooth vector field fulfills this integrability requirement to design line connection algorithms for contour completion. As application we present a segmenting strategy that assures convergent snakes whatever the geometry of the object to be modelled is. 2004 Elsevier Inc. All rights reserved.
The cross-convolution method for interpreting SKS splitting observations, with application to one and two-layer anisotropic earth models

We present a new method for determining anisotropic earth models using observations of split shear waves (such as SKS). The method consists of first constructing two time-series, x(t) and y(t), that contain information concerning both the observed seismograms and a hypothetical earth model, and then varying the earth model so as to minimize the misfit. e(t) = x(t) - y(t). The time-series are defined by the rules, x(t) = h p r e (m, t)* V o b s (t) and y(t) = v p r e (m, t)*H o b s (t), where V o b s (t) and H o b s (t) are the observed radial-horizontal and tangential-horizontal component seismograms, respectively, v p r e (m, t) and h p r e (m, t) are the radial-horizontal and tangential-horizontal impulse responses, respectively, predicted by some earth model, m, and * denotes convolution. The best-fitting earth model is the one that minimizes ∥e(t)∥ 2 with respect to m, where ∥. ∥ is an amplitude-normalized L 2 norm. This definition of misfit is insensitive to the source wavelet, and thus eliminates that unknown quantity from the problem. We show that this method yields estimates of one-layer splitting parameters that are very similar to those achieved through traditional means, but that unlike those traditional methods it can be applied to more complicated models (e.g. multilayer anisotropy) without recourse to approximate 'apparent splitting' parameters. We apply the method to synthetic SKS pulses generated for two-layer anisotropic earth models, and show that it can successfully recover information concerning both layers. We then apply the method to SKS and PKS data from Pinon Flat, California (PFO) on the San Andreas fault. This station has been studied previously by Ozalaybey & Savage, Liu et al. and Polet & Kanamori, who provide two-layer solutions based on modelling of the azimuthal variation of apparent splitting parameters. Our results are broadly consistent with theirs, but provide additional information concerning the statistical significance of the two-layer solution. By this measure, none of the published two-layer solutions is significantly better than a one-layer solution, although all fit the waveform data better than the best-fitting one-layer solution. This result is consistent with the interpretations of Ozalaybey & Savage and Liu et al., who provide similar assessments of their two-layer solutions. The fact that neither our one-layer nor two-layer solutions does very well at reducing the overall misfit strongly suggests that some process other than two-layer anisotropy is affecting SKS and PKS waveforms at PFO.
Fast Pedestrian Detection with Laser and Image Data Fusion

In this paper, we proposed a pedestrian detection system based on laser and image data fusion. The high speed of laser data based location and precise of image based classification are fully explored. First, laser scanner point data is clustered into segments, each of which implies a pedestrian candidate. Then, the segments are projected to the image domain to form regions of interest (ROI) on the image, given camera calibration parameters. Finally two SVM classifiers on Histogram of Oriented Gradient (HOG) features are used to precisely locate pedestrians on the ROI. Experiments report over 30 times higher speed than the state-of-the-art method and a comparable detection rate.
Finding Versus Fixing: Self‐Monitoring for Readers Who Struggle

This article explains how teachers can understand, notice, and supportively respond to readers who struggle with self-monitoring during text reading. The unique strategic processing demands for readers who struggle support the argument that teaching children to find and notice errors is different than fixing a word, or getting it right. Three critical attributes of teaching for self-monitoring based on the important works of Peter Johnston and Marie Clay are put forth: teacher observation and hypothesizing, noticing and naming, and teaching for strategic activity and agency. Teaching examples provide a frame for critical attributes to guide professional conversations around self-monitoring.
Improving Mac OS X security through gray box fuzzing technique

The kernel is the core of any operating system, and its security is of vital importance. A vulnerability, in any of its parts, compromises the whole system security model. Unprivileged users that find such vulnerabilities can easily crash the attacked system, or obtain administration privileges. In this paper we propose LynxFuzzer, a framework to test kernel extensions, i.e., the dynamically loadable components of Mac OS X kernel. To overcome the challenges posed by interacting with kernel-level software, LynxFuzzer includes a bare-metal hardware-assisted hypervisor, that allows to seamlessly inspect the state of a running kernel and its components. We implemented and evaluated LynxFuzzer on Mac OS X Mountain Lion and we obtained unexpected results: we indivuated 6 bugs in 17 kernel extensions we tested, thus proving the usefulness and effectiveness of our framework.
Minimum Coverage Hypersphere Based Category-Separability Criterion and Feature Selection

There is still a problem, lack of enough generalization ability, with existing feature selection methods. To solve this problem, a supervised feature selection method base on support vector machine is proposed in view of generalization ability of support vector machine for small sample set and ability of processing high-dimensional data of kernel function. The new method introduces the category-separability criterion in terms of minimum coverage hypersphere of samples, and uses the criterion as the feature assessment index to feature sorting and feature selection. The experimental results show that this method can obtain a reasonable feature sorting, eliminate unrelated feature in the data set effectively.
Coordination at different stages of the product design process

This paper addresses the following question: how does the coordination challenge faced by managers change over the life of time bound projects such as product design. We use coordination structure, an approach to modeling organizational situations that highlights concurrent responsibility interdependencies rather than the more traditional task interdependencies. We explain coordination structure and use it to capture the responsibility interdependencies in a sample of complex system design projects drawn from two different organizations. We use this data: to illustrate the differences possible in the responsibility interdependencies that can exist within design projects from different organizations and at different project key points; to identify a set of four basic modules, or groupings, of responsibility interdependencies useful for modeling design organizations; and to generate a set of testable hypotheses on how the coordination challenge faced by project managers can vary between organizations and over project key points.
Extracting Attributes and Synonymous Attributes from Online Encyclopedias

In this paper, we present an approach that extracts attributes of open-domain named entities for the Chinese language. The approach contains two steps. The first step consists in an unsupervised technique which captures high frequency attributes from online encyclopedias. The second step discovers uncommon attributes with low frequency. Lastly, an integrated framework is proposed to obtain attributes and their synonymous attributes simultaneously. Experimental results show that the proposed approach boosts the coverage of extracted attributes without losing the precision.
Overview of an Interprocedural Automatic Parallelization System

We present an overview of our interprocedural analysis system, which applies the program analysis required for parallelization across procedure boundaries. We discuss the issues we addressed to e(cid:14)ciently obtain precise results in the interprocedural setting. We present the analysis required for parallelization, illustrated with an excerpt from a Fortran benchmark program. By integrating a comprehensive suite of interprocedural analyses, we have built a system that is much more e(cid:11)ective at locating parallelism in scienti(cid:12)c benchmarks than earlier interprocedural systems.
Deception in Authorship Attribution

Deception in Authorship Attribution Sadia Afroz Advisor: Rachel Greenstadt, PhD In digital forensics, questions often arise about the authors of documents: their identity, demographic background, and whether they can be linked to other documents. The field of stylometry uses linguistic features and machine learning techniques to answer these questions. While stylometry techniques can identify authors with high accuracy in non-adversarial scenarios, their accuracy is reduced to random guessing when faced with authors who intentionally obfuscate their writing style or attempt to imitate that of another author. Most authorship attribution methods were not evaluated in challenging real-world datasets with foreign language and unconventional spelling (e.g. l33tsp3ak). In this thesis we explore the performance of authorship attribution methods in adversarial settings where authors take measures to hide their identity by changing their writing style and by creating multiple identities. We show that using a large feature set, it is possible to distinguish regular documents from deceptive documents with high accuracy and present an analysis of linguistic features that can be modified to hide writing style. We show how to adapt regular authorship attribution to difficult datasets such as leaked underground forum and present a method for detecting multiple identities of authors. We demonstrate the utility of our approach with a case study that includes applying our technique to an underground forum and manual analysis to validate the results, enabling the discovery of previously undetected multiple accounts.
Top management toolbox for managing corporate IT

process involving such activities as identifying promising application targets, deciding the application’s posture (defensive or offensive) and mode of use (internal or external), and assessing the application’s associated risk of system failure and financial loss. One practical conclusion for strategic systems is that planning for them is intertwined with an organization’s business strategy, so cooperation between IS managers and non-IS managers is critical for their implementation. In many organizations, general and functional managers—with law, finance, accounting, marketing, or even engineering backgrounds—are not familiar with the latest technology. This raises a barrier to communication that limits their ability to determine risk before deciding whether to go ahead with a project or how to control large projects during their development life cycles. Two examples illustrate how it can lead to disastrous results: Bank of America. Development of a system to support the bank’s management of trust accounts was budgeted at $25 million and scheduled to take two years to complete. The result was to be the MasterNet system, with online updating and automated generation of monthly statements. Instead, completion took five years at a total cost of $80 million— and was still rejected by its target users because it created accounting problems and suffered from slow response times and communication and disk drive problems. Many of the bank’s employees were laid off during development, and the bank’s reputation was severely damaged. Some major banking customers even lost confidence in the bank; the total number of institutional accounts dropped from 800 to 700, and assets under management shrank from $38 billion to $34 billion [1, 2]. In 1995, seven years after the project’s failure, the bank’s management sold its institutional trusts and securities services division, which still needed a major technology investment to position itself to compete against the enormous institutions that dominate the field of institutional trust banking. However, because of the bank’s flawed history in implementing technology to support corporate trust businesses, the bank’s executives decided it
Multi-Layer Mechanical Model of Glagov Remodeling in Coronary Arteries: Differences between In-Vivo and Ex-Vivo Measurements

When blood vessels undergo remodeling because of the buildup of atherosclerotic plaque, it is thought that they first undergo compensatory or outward remodeling, followed by inward remodeling: the lumen area stays roughly constant or increases slightly and then decreases rapidly. The second phase of remodeling is supposed to start after the plaque burden exceeds about 40%. These changes in the vessel were first observed by S. Glagov who examined cross-sections of coronary arteries at different stages of the disease. In this paper, we use a mathematical model based on growth and elasticity theory to verify the main aspects of Glagov’s result. However, both our model and curve-fitting to the data suggest that the critical stenosis is around 20% rather than 40%. Our model and data from the PROSPECT trial also show that Glagov remodeling is qualitatively different depending on whether measurements are taken ex-vivo or in-vivo. Our results suggest that the first outward phase of “Glagov remodeling” is largely absent for in-vivo measurements: that is, the lumen area always decreases as plaque builds up. We advocate that care must be taken when infering how in-vivo vessels remodel from ex-vivo data.
Forest Disturbances and Regrowth Assessment Using ALOS PALSAR Data from 2007 to 2010 in Vietnam, Cambodia and Lao PDR

This paper aims to develop a new methodology for monitoring forest disturbances and regrowth using ALOS PALSAR data in tropical regions. In the study, forest disturbances and regrowth were assessed between 2007 and 2010 in Vietnam, Cambodia and Lao People’s Democratic Republic. The deforestation rate in Vietnam has been among the highest in the tropics in the last few decades, and those in Cambodia and Lao are increasing rapidly. L-band ALOS PALSAR mosaic data were used for the detection of forest disturbances and regrowth, because L-band SAR intensities are sensitive to forest aboveground biomass loss. The methodology used here combines SAR data processing, which is particularly suited for change detection, forest detection and forest disturbances and regrowth detection using expectation maximization, which is closely related to fuzzy logic. A reliable training and testing database has been derived using AVNIR-2 and Google Earth images for calibration and validation. Efforts were made to apply masking areas that are likely to show different SAR backscatter temporal behaviors from the forests considered in the study, including mangroves, inundated forests, post-flooding or irrigated croplands and water bodies, as well as sloping areas and urban areas. The resulting forest disturbances and regrowth map (25-m resolution) indicates disturbance rates of −1.07% in Vietnam, −1.22% in Cambodia and −0.94% in Lao between 2007 and 2010, with corresponding aboveground biomass losses of 60.7 Tg, 59.2 Tg and 83.8 Tg , respectively. It is expected that the method, relying on free of charge data (ALOS and ALOS2 mosaics), can be applied widely in the tropics.
Learning meanings for sentences

Consider an English sentence of length n, say “Cats like to chase mice” with n = 5. Suppose that we are given a binary tree representing the syntactic structure of the sentence. Each word is a leaf node of the tree, and there are n− 1 internal nodes. Each internal node covers a phrase of two or more consecutive words. We will associate a column vector in R with each node, to represent the meaning of the corresponding phrase. A typical value for the dimensionality d is 100. The meaning of each word is initialized to be a random vector in R. This means that we create a fixed lexicon containing a random vector for each word. Each random vector is generated independently from a Gaussian of dimension d with mean zero and diagonal covariance matrix σI . Each time the same word is used in any sentence, the same vector is used as its meaning. The meaning of a phrase is a function of the meanings of its two components. This is called a compositional approach to semantics. Let the node k have children i and j, whose meanings are xi and xj . The meaning of node k is