Miracle-dz/UniFAR-FTUs huggingface dataset:
In-nimbo sandboxing

Sandboxes impose a security policy, isolating applications and their components from the rest of a system. While many sandboxing techniques exist, state of the art sandboxes generally perform their functions within the system that is being defended. As a result, when the sandbox fails or is bypassed, the security of the surrounding system can no longer be assured. We experiment with the idea of in-nimbo sandboxing, encapsulating untrusted computations away from the system we are trying to protect. The idea is to delegate computations that may be vulnerable or malicious to virtual machine instances in a cloud computing environment. This may not reduce the possibility of an in-situ sandbox compromise, but it could significantly reduce the consequences should that possibility be realized. To achieve this advantage, there are additional requirements, including: (1) A regulated channel between the local and cloud environments that supports interaction with the encapsulated application, (2) Performance design that acceptably minimizes latencies in excess of the in-situ baseline. To test the feasibility of the idea, we built an in-nimbo sandbox for Adobe Reader, an application that historically has been subject to significant attacks. We undertook a prototype deployment with PDF users in a large aerospace firm. In addition to thwarting several examples of existing PDF-based malware, we found that the added increment of latency, perhaps surprisingly, does not overly impair the user experience with respect to performance or usability.
Rough Law Separation-Reduction Based on Function S-Rough Sets

Function S-rough sets have dynamic characteristics and law characteristics. By employing function S-rough sets and law generation, this paper proposes the concepts of rough law, F-separation rough law band, f-separation law and f-reduction law. Based on these concepts above, this paper proposes the theorem of rough law separation, the composition generation theorem of rough law band, and the entire separation theorem of f-rough law. In the end, an application of rough law separation in recognizing the risk profit law is presented.
Practice of consensual BDSM and relationship satisfaction

ABSTRACT Sexual behaviors and styles that differ from that of the majority culture have been pathologized throughout history. One such category of sexual variation is BDSM (bondage-discipline/dominance-submission/sadism–masochism). Research onpsychotherapists suggests beliefs that BDSM practitioners cannot sustain healthy relationships. A growing body of literature, however, describes those who engage in BDSM activities as socially well-adjusted individuals who are no more likely to have psychological distress than the general population. This study used an online survey distributed via BDSM community websites and word-of-mouth to measure relationship satisfaction among BDSM practitioners who were in committed relationships. The Revised Dyadic Adjustment Scale (RDAS) was administered, as well as a number of demographic and BDSM participation questions about both the participants and their partners. Findings indicated participants did not score above the clinically distressed criterion cut-off on the RDAS. Additionally, data analysis compared gender and BDSM roles on RDAS scores. This yielded no statistically significant results. These results were considered in the context of the feminist critique of BDSM and family systems theory. The current study adds to previous research by examining relationship satisfaction, providing more evidence that those practicing BDSM are not significantly more pathological than the population in general.
Revisiting the Joint Transport and MAC Optimization for Wireless Ad Hoc Networks

In this paper, we revisit the optimization based control problem of wireless ad-hoc networks. Even though much work has been done so far, they are limited either in their practicality or in their efficiency. We develop another framework based on independent set and propose an implementable heuristic algorithm. Our heuristic is based on the longest queue first (LQF) policy and the neighborhood price.
An Integration of Biographical Data and Personality Research Through Sherwood Forest Empiricism: Robbing From Personality to Give to Biodata.

Archival data was used to assess the effectiveness of incorporating biodata scoring into extant personality measures. Personality and biodata theories were briefly reviewed and several commonalities were noted. Hypotheses were developed for Conscientiousness, Emotional Stability. Agreeableness, and Openness to Experience. The first three dimensions were expected to predict absenteeism and all four were expected to predict turnover, and empirical scoring was expected to increase predictive validity. Data were collected from three samples (school bus drivers, bus drivers, and law enforcement) and three different personality measures were scored using England’s (1971) vertical percent method. Results showed that two of the three samples did not produce significant correlations between personality and two criterion measures. Only the correlation between Conscientiousness and absenteeism (r = .13) for the law enforcement sample was similar to Barrick and Mount’s (1991) results. Personality profiles for high and low absenteeism employees, and stayers and leavers were compared, but the profiles did not contain the hypothesized elevations. Biodata scoring improved some correlations, but inconsistently, for law enforcement employees. Biodata scoring for this sample was most useful for predicting turnover. Correlations for the other samples were small and insignificant Whereas biodata scoring provided incremental validity over the personality scales, the results were inconsistent and therefore did not support the hypotheses. Further, profiles developed through biodata scoring diverged from those developed via personality scoring. The interpretation of biodata profiles was difficult due to possible changes in scale meaning due to scoring. The overall component of personality and biodata profiles were compared and it was shown that sometimes the biodata overall component explained incremental variance. Limitations of the study included using incumbents versus applicants, a lack of specificity of the criterion measures, and an inability to compare the results from the three samples. Future studies are needed to determine possible applicant-incumbent differences for personality and biodata measures and determine possible changes in the structure of personality tests caused by empirical scoring. These results provide
Magnon Modes and Magnon-vortex Scattering in 2d Easy-plane Ferromagnets

We calculate the magnon modes in the presence of a vortex on a circular system, combining analytical calculations in the continuum limit with a numerical diagonalization of the discrete system. The magnon modes are expressed by the S-matrix for magnon-vortex scattering, as a function of the parameters and the size of the system and for diierent boundary conditions. Certain quasi-local translational modes are identiied with the frequencies which appear in the trajectory ~ X(t) of the vortex center in recent Molecular Dynamics simulations of the full many-spin model. Using these quasi-local modes we calculate the two parameters of a 3 rd-order equation of motion for ~ X(t). This equation was recently derived by a collective variable theory and describes very well the trajectories observed in the simulations. Both parameters, the vortex mass and the factor in front of ::: ~ X, depend strongly on the boundary conditions.
Asynchronous programs with prioritized task-buffers

We consider the algorithmic analysis of asynchronous software systems as a means for building reliable software. A key challenge in designing such analyses is identifying a concurrency model which does not extraneously introduce behaviors infeasible in the actual system, does not extraneously exclude actual behaviors, and isolates the challenging features for analyses to focus on. Guided by real-world asynchronous software, we propose a concurrency model which enriches the existing serial task-buffer asynchrony model [29] with task-priorities and multiple task-buffers. Our model allows non-serial execution: tasks with higher priority preempt lower-priority tasks, and tasks drawn from distinct buffers freely interleave with one another. Modeling these features allows analysis algorithms to detect otherwise uncaught programming errors in asynchronous programs due to inter-buffer interleaving and task-interruption, while correctly ignoring false errors due to infeasible out-of-priority-order executions. Besides more precisely capturing real-world systems, our concurrency model inspires the design of a novel analysis algorithm. Given parameters K1, K2 ε N that restrict inter-buffer task interleaving and intra-buffer task reordering, we give a code-to-code translation to sequential programs, which can then be analyzed by off-the-shelf program analysis tools. For any given parameter values, the resulting sequential program encodes a subset of possible behaviors, and in the limit as both parameters approach infinity, the sequential program encodes all behaviors. We demonstrate the viability of our technique by experimenting with a prototype implementation. Our prototype is competitive with state-of-the-art concurrent program verification tools, and is able to correctly identify errors in simplified Windows device driver code, while ignoring infeasible executions.
Adapting Moments for Handwritten Kannada Kagunita Recognition

The Handwriting character recognition (HCR) for Indian Languages is an important problem where there is relatively little work has been done. In this paper, we investigate the use of moments features on Kannada Kagunita. Kannada characters are curved in nature with some kind of symmetric structure observed in the shape. This information can be best extracted as a feature if we extract moment features from the directional images. To recognize a Kagunita, we need to identify the vowel and the consonant present in the image. So we are finding 4 directional images using Gabor wavelets from the dynamically preprocessed original image. We analyze the Kagunita set and identify the regions with vowel information and consonant information and cut these portions from the preprocessed original image and form a set of cut images. We then extract moments features from them. These features are trained and tested for both vowel and Kagunita recognition on Multi Layer Perceptron with Back Propagation Neural Network. The recognition results for vowels is average 85% and consonants is 59% when tested on separate test data with moments features from directional images and cut images.
An improved multiple internal standard normalisation for drift in LA-ICP-MS measurementsPresented at the 2nd International Conference on High-resolution Sector Field ICP-MS, Vienna, Austria, September 12???15, 2001.

One of the primary factors limiting precision in LA-ICP-MS measurements is the instrument fluctuation. To overcome this limitation one usually employs a normalisation based on a single internal standard. This article reports a new approach for the normalisation of LA-ICP-MS measurements, based on multiple internal standards. The novelty of the approach is that it (i) takes into account the measurement uncertainties, (ii) generates uncertainty bounds on the normalized measurements and (iii) allows one to check and dismiss the mass dependency of the normalisation procedure. As a result, it is shown that the improvement in normalisation factor increases proportionally to the square root of the number of internal standards (e.g., the use of two internal standards leads to a decrease of the standard deviation by 30%, three to 42% and four up to 50% compared with the classical normalisation). This is illustrated on the NIST 610 standard with a 266 nm UV LA-ICP-MS. An extra advantage of the use of multiple internal standards is that it allows the detection of artifacts in the measurements (internal quality check).
Chapter 1 ON THE FUNDAMENTAL RELATIONSHIP BETWEEN THE ACHIEVABLE CAPACITY AND DELAY IN MOBILE WIRELESS NETWORKS

In this work, we establish the fundamental relationship between the achievable capacity and delay in mobile wireless networks. Under an i.i. d. mobility model, we first obtain the following upper bound on the achievable capacity given a delay constraint. For a mobile wireless network with n nodes, if the per-bit-averaged mean delay is bounded by D̄, then the upper bound on the per-node capacity is on the order of 3 q D̄ n log n. By studying the conditions under which the upper bound is tight, we are able to identify the optimal values of several key scheduling parameters. We then develop a scheduling scheme that can almost achieve the upper bound (up to a logarithmic factor). This suggests that the upper bound is tight. Our scheduling scheme also achieves a provably larger per-node capacity than schemes reported in previous works. In particular, when the delay is bounded by a constant, our scheduling scheme achieves a per-node capacity that is inversely proportional to the cube root of n (up to a logarithmic factor). This implies that, for the i.i. d. mobility model, mobility improves the achievable capacity of static wireless networks, even with constant delays! Finally, the insight drawn from the upper bound allows us to identify limiting factors in existing scheduling schemes. These results present a relatively com∗This work has been partially supported by the NSF grants ANI-0207728, EIA-0130599 and the Indiana 21st Century Fund for Wireless Networks. 2 plete picture of the achievable capacity-delay tradeoffs under different settings.
Adaptive variable density sampling based on Knapsack problem for fast MRI

This paper presents a novel heuristic approach to generate a variable density sampling (VDS) pattern for fast MRI data acquisition, based on the principle of Knapsack problem. MR images are known to exhibit weak sparsity in Fourier domain. This sparsity has been exploited to devise faster k-space sampling schemes by acquiring lesser samples while using Compressed Sensing reconstruction techniques to reconstruct high quality MR images. The entire range of distribution of the magnitude of fc-space is divided into fixed/variable bin widths and draw samples from these bins according to a cost criterion satisfying the undersampling factor. This will facilitate sampling the k-space coefficients by preserving the energy content for the desired undersampling factor and do away with the deterministic central region sampling resulting in a VDS method with a correlation to the magnitude spectrum of the reference image scan. Knapsack principle is used to select the relevant bins. The method is also devoid of parameter tuning, yielding significant good results at both the lower and higher under sampling ratios.
A Proposal for a Common Infrastructure for Process and Product Models

This paper presents an infrastructure for process and product models where structural coupling plays a central role. It begins with two sections that introduce process and product models. Then the third section describes the components of a common infrastructure. This is a domain model engine that relies on some powerful metaphors. We describe these metaphors with a few software patterns. The ideas contained here stem from two existing frameworks, one for telecommunications billing [JA] and the other for insurance systems [JO].
The Effectiveness of Traditional and Open Relation Extraction for the Slot Filling Task at TAC 2011

Our goal in this paper is to investigate the effectiveness of relation extraction techniques for the slot-filling task. We discuss two relation extraction systems. YRES follows the traditional paradigm in relation extraction, where a system takes advantage of available examples for each relation to be extracted. On the other hand, SONEX follows the open relation extraction paradigm, where the relations to be extracted are assumed to be unknown a priori. In particular, SONEX applies clustering techniques to identify relations in an unsupervised way. The results of our submissions show that the performances of the two systems are fairly similar.
An Improved Bound on the List Error Probability and List Distance Properties

List decoding of binary block codes for the additive white Gaussian noise (AWGN) channel is considered. The output of a list decoder is a list of the most likely codewords, that is, the signal points closest to the received signal in the Euclidean-metric sense. A decoding error occurs when the transmitted codeword is not on this list. It is shown that the list error probability is fully described by the so-called list configuration matrix, which is the Gram matrix obtained from the signal vectors forming the list. The worst case list configuration matrix determines the minimum list distance of the code, which is a generalization of the minimum distance to the case of list decoding. Some properties of the list configuration matrix are studied and their connections to the list distance are established. These results are further exploited to obtain a new upper bound on the list error probability, which is tighter than the previously known bounds. This bound is derived by combining the techniques for obtaining the tangential union bound with an improved bound on the error probability for a given list. The results are illustrated by examples.
Implicit treatment of substrate and power-ground losses in return-limited inductance extraction

Full-wave analysis, based on rigorous solution of the differential or integral form of Maxwell's equations, is too slow for all but the smallest designs. Traditional on-chip extraction engines are, therefore, being pushed to extract inductance and provide accurate high frequency interconnect modelling while maintaining computational efficiency and capacity. This paper describes further accuracy-improving enhancements to the commercial full-chip RLCK extraction engine, Assura RLCX, based on the return-limited inductance formulation. Specifically, we incorporate substrate losses due to eddy currents and power-ground losses while, based on design-driven assumptions, avoiding explicit extraction of the power-ground and substrate. Results are validated on small testcases where comparison with full-wave solutions is practical.
Visualizing Interactions in Program Executions

Implementing, validating, modifying, or reengineering an object-oriented system requires an understanding of the object and class interactions which occur as a program executes. This work seeks to identify, visualize, and analyze interactions in object-oriented program executions as a means for examining and understanding dynamic behavior. We have discovered recurring interaction scenarios in program executions that can be used as abstractions in the understanding process, and have developed a means for identifying these interaction patterns. Our visualizations focus on supporting design recovery, validation, and reengineering tasks, and can be applied to both object-oriented and procedural programs.
Increasing Awareness in Collaborative Authoring through Edit Profiling

Awareness of the activities of other users and also document evolution is an important part of collaborative authoring. We introduce the concept of an editing profile that can be used to maintain and visualise measures of the changes made across a document by different users in both synchronous and asynchronous collaborative editing. It provides a simple means of making users aware of ¿hot areas¿ and also who is or has been active in various parts of the document, as well as a quick access point into parts of the document that have been changed. The profile can be adapted to display the most relevant information based on both user preference and situation.
Planning aircraft taxiing trajectories via a multi-ojective immune optimisation

Airport operations include departure sequencing, arrival sequencing, gate/stand allocation and ground movements (taxiing). During the past few decades, air traffic at major airports has been significantly increased and is expected to be so in the near future, which imposes a high requirement for more efficient cooperation across all airport operations. A very important element of this is an accurate estimation of the ground movement, which serves as a link to other operations. Previous researches have been concentrated on the estimation of aircraft taxi time. However, such a concept should be stretched more than just predicting time. It should also be able to estimate the associated cost, e.g. fuel burn, for it to achieve such an expected time. Hence, in this paper, an immune inspired multi-objective optimisation method is employed to investigate such trade-offs for different segments along taxiways, which leads to a set of different taxiing trajectories for each segment. Each of these trajectories, on the one hand, provides an estimation of aircraft taxi time, and on the other hand, has great potential to be integrated into the optimal taxiway routing and scheduling process in a bid to find out the optimal taxiing not only in terms of reducing total taxi time but also in terms of lowering fuel consumption.
What have I just done? Anchoring, self-knowledge, and judgments of recent behavior

Can numerical anchors influence people’s judgments of their own recent behavior? We investigate this question in a series of six studies. In Study 1, subjects’ judgments of how many anagrams they were given assimilated to numerical anchors. Subjects’ judgments of how many math problems they correctly solved and how many stairs they had just walked up were also influenced by numerical anchors (Studies 2A and 3A), and this occurred even when the anchors were extreme and nonsensical (Studies 2B and 3B). Thus, our first five studies showed that anchors can affect people’s judgments of their own recent behavior. Finally, in Study 4, we tested the hypothesis that self-knowledge, despite not eliminating anchoring effects, does still attenuate anchoring. However, we found no evidence that self-knowledge reduced anchoring: subjects’ judgments of their own recent behavior and subjects’ judgments of other people’s recent behavior were equally influenced by anchors. We discuss implications of these findings for research on domain knowledge and anchoring, as well as for research on the malleability of memory.
Improved GVF external force based on modified normal flow

Active contours are one of the most successful image segmentation methods in image processing and computer vision field. Their main limitations are high noise sensitivity and poor capture range from the target object. One of the most promising approaches for solving these limitations is the gradient vector flow (GVF). However, GVF still has improving space in converging to concavities and noise robustness. Here we propose a novel GVF external force based on modified normal flow for improving contour performance. This novel external force field is insensitive to noises and may converge to concavities. We compared the proposed method with other methods by synthetic images and real medical images. Experimental results illustrated that the proposed method had achieved more accurate segmentation for noise robustness and concavity convergence.