Miracle-dz/UniFAR-FTUs huggingface dataset:
Rendering the Elephant: Characterizing Sensitive Networks for an Uncleared Audience

There is a need to convey information on sensitive networks and systems, specifically, those carrying classified information, to researchers lacking clearances. Sanitization or use of analogs allows for uncleared researchers to make contributions, but as detail is removed, data may become less useful. A number of approaches to feeding research with relevant data are described, including creation of realistic traffic from a national intelligence community network, and recommendations made for improving current practices
A New Community-based Algorithm for Influence Maximization in Social Network ⋆

Influence maximization is a fundamental issue to find a set of key individuals in social network such that targeting them initially will maximize the spread of influence. However, the problem of finding the most key nodes is NP-hard. It is shown that a greedy algorithm with provable approximation guarantees can give good approximation. However, it is too computationally expensive to apply in a large social network. Based on the community structure of social network, a cooperative game theoretic algorithm (CGINA) to find key nodes is proposed. In CGINA, we first detect the community structure of the social network with the topological structure and information diffusion model. Then, we will find key nodes in communities. Different from other literature, we think of the information diffusion in the whole network as a cooperative game with transferable utility. The communities of the network happen to be the players in the game. With the Shapley value in game theory, we allocate the number of key nodes for each community. In my view, the key nodes include two parts. One is composed of “bridge” nodes, which are easy to propagate information across communities, the other is composed of “influential” nodes, which can diffuse information quickly in its own community. Empirical studies on a large social network show that our algorithm is efficient and powerful.
Determinants of visitor expenditure at the Tsitsikamma National Park

The Tsitsikamma National Park is Africa’s oldest and largest marine reserve. It has considerable importance for the community and the region. In the face of declining government funding, it needs to attract more high spenders if it is to be sustainable. This requires an understanding of expenditure patterns and the determinants of Park visitors’ spending behaviour. This study investigated the socio-demographic and behavioural determinants of visitor expenditure, using visitor surveys at the Park in 2010/2011. Correlation analysis and regression analysis established the most significant determinants. The results indicated that a longer stay, a smaller travel group and obtaining information from magazines were the variables associated with higher spending. These findings provide strategic insights for marketing the Park, with the aim of achieving a greater economic impact and competitive advantage and ultimately aiding conservation efforts.
Quadratic Volatility Smiles

The paper assumes that the implied volatility of options with some given expiration is a quadratic function of the moneyness. The coefficients of this quadratic function (the smile) are time dependent and stochastic. The paper derives exposure parameters of the price of the option to the local change in each of the smile coefficients, and an approximate formula for their risk adjusted expected value. These are important in managing the exposure of the price of an option portfolio to changes in the smile coefficients.
Predictive activation for localization using minimal data-fusion in MANETs

We propose a unique localization algorithm for MANETs: the mobile infrastructure-less networks with support of static underlying wireless sensor network nodes. The algorithm has been designed with two stages for localizing the MANET. The first stage is the naive activation stage which acts as the bootstrap for the prediction stage. The predictive minimal energy consumption algorithm incorporates the information from the measured TOA (Time Of Arrival) to locate the mobile nodes. The experimental results and comparative analysis show that our system provides accurate localization of linearly moving MANET's using low power consumption of the underlying wireless sensor networks.
Geography of Knowledge-based Collaboration in a Post-communist Country: Specific Experience or Generalized Pattern?

This article addresses the role of geographical proximity for knowledge and innovation collaboration patterns in the Czech Republic and assesses the factors which determine the spatial distribution of innovation co-operation. The article uses alternative sources of empirical data to map collaboration patterns of innovating companies, research institutes and universities and to find basic regularities. By this, the article aims to fill in the gap in current research focused rather on most advanced regions by adding new knowledge from a transformation, post-communist economy. Also, it aims to shed light on the issue of the role of proximity between actors involved in collaboration in the sphere of knowledge and innovation creation which still remains rather elusive. The findings indicate that even though co-location and intra-regional knowledge and innovation collaboration exist, it cannot be regarded as a decisive characteristic. Geographical proximity is not a crucial condition in knowledge and innovation collaboration as all actors are involved to an important degree in international linkages. Yet, the role of the specific institutional context and factors at micro-level influence the innovation co-operation pattern.
Total integrated scatter from surfaces with arbitrary roughness, correlation widths, and incident angles

Abstract. Surface scatter effects from residual optical fabrication errors can severely degrade optical performance. The total integrated scatter (TIS) from a given mirror surface is determined by the ratio of the spatial frequency band-limited “relevant” root-mean-square surface roughness to the wavelength of light. For short-wavelength (extreme-ultraviolet/x-ray) applications, even state-of-the-art optical surfaces can scatter a significant fraction of the total reflected light. In this paper we first discuss how to calculate the band-limited relevant roughness from surface metrology data, then present parametric plots of the TIS for optical surfaces with arbitrary roughness, surface correlation widths, and incident angles. Surfaces with both Gaussian and ABC or K-correlation power spectral density functions have been modeled. These parametric TIS predictions provide insight that is useful in determining realistic optical fabrication tolerances necessary to satisfy specific optical performance requirements.
Blood and Dried Blood Spot Telomere Length Measurement by qPCR: Assay Considerations

Measurement of telomere length is crucial for the study of telomere maintenance and its role in molecular pathophysiology of diseases and in aging. Several methods are used to measure telomere length, the choice of which usually depends on the type and size of sample to be assayed, as well as cost and throughput considerations. The goal of this study was to investigate the factors that may influence the reliability of qPCR-based relative telomere length measurements in whole blood. Day to day intra-individual variability, types of blood anticoagulant, sample storage conditions, processing and site of blood draw were investigated. Two qPCR-based methods to measure telomere length (monoplex vs. multiplex) were also investigated and showed a strong correlation between them. Freezing and thawing of the blood and storage of the blood at 4°C for up to 4 days did not affect telomere length values. Telomere lengths in dried blood spots were significantly higher than both whole blood and peripheral mononuclear blood cells, and were highly correlated with both. We found that telomere length measurements were significantly higher in dried blood spots collected directly from fingertip prick compared to dried blood spots prepared with anticoagulated whole blood collected from the finger, and non-blotted whole blood taken from both finger and arm venipuncture. This suggests that DNA from cells blotted on paper is not equivalent to that collected from venipuncture whole blood, and caution should be taken when comparing between blood sample types.
Autonomous AU Bicycle: Self-Balancing and tracking control (AUSB2)

This paper discusses about the Autonomous AU Bicycle: Self-Balancing and tracking control (AUSB2). The system will be explained in two parts; balancing and tracking control. In the balancing part, the gyroscope and encoder are used to sense the balance position of the bicycle, the position of the flywheel. Compass, GPS and encoder are used for the tracking control. The main objective of this paper is to demonstrate the implementation methodology of the bicycle robot and the balancing and tracking control methods.
Asteroids as far-infrared photometric standards for ISOPHOT

Asteroids are used as far-IR calibrators for the imaging photopolarimeter ISOPHOT on board the Infrared Space Observatory ISO. For the 10 selected objects we compiled a large uniform database(1) of 678 individual observations, ranging from 7-2 000 mu m. A
Multiobjective Microarchitectural Floorplanning for 2-D and 3-D ICs

This paper presents the first multiobjective microarchitectural floorplanning algorithm for high-performance processors implemented in two-dimensional (2-D) and three-dimensional (3-D) ICs. The floorplanner takes a microarchitectural netlist and determines the dimension as well as the placement of the functional modules into single- or multiple-device layers while simultaneously achieving high performance and thermal reliability. The traditional design objectives such as area and wirelength are also considered. The 3-D floorplanning algorithm considers the following 3-D-specific issues: vertical overlap optimization and bonding-aware layer partitioning. The hybrid floorplanning approach combines linear programming and simulated annealing, which is shown to be very effective in obtaining high-quality solutions in a short runtime under multiobjective goals. This paper provides comprehensive experimental results on making tradeoffs among performance, thermal, area, and wirelength for both 2-D and 3-D ICs
Recognition Memory for Colored and Black-and-White Scenes in Normal and Color Deficient Observers (Dichromats)

Color deficient (dichromat) and normal observers’ recognition memory for colored and black-and-white natural scenes was evaluated through several parameters: the rate of recognition, discrimination (A’), response bias (B”D), response confidence, and the proportion of conscious recollections (Remember responses) among hits. At the encoding phase, 36 images of natural scenes were each presented for 1 sec. Half of the images were shown in color and half in black-and-white. At the recognition phase, these 36 pictures were intermixed with 36 new images. The participants’ task was to indicate whether an image had been presented or not at the encoding phase, to rate their level of confidence in his her/his response, and in the case of a positive response, to classify the response as a Remember, a Know or a Guess response. Results indicated that accuracy, response discrimination, response bias and confidence ratings were higher for colored than for black-and-white images; this advantage for colored images was similar in both groups of participants. Rates of Remember responses were not higher for colored images than for black-and-white ones, whatever the group. However, interestingly, Remember responses were significantly more often based on color information for colored than for black-and-white images in normal observers only, not in dichromats.
Training and evaluation of neural networks for multi-variate time series processing

We study the training and generalization for multi-variate time series processing. It is suggested to used a quasi-maximum likelihood approach rather than the standard sum of squared errors, thus taking dependencies among the errors of the individual time series into account. This may lead to improved generalization performance. Further, we extend the optimal brain damage pruning technique to the multi-variate case. A key ingredient is an algebraic expression for the generalization ability of a multi-variate model. The variability of the suggested techniques are successfully demonstrated in a multi-variate scenario involving the prediction of the cylinder pressure in a marine engine.
Predictors of Response to Anti-tnf-therapy among Patients with Rheumatoid Arthritis: Results from the British Society for Rheumatology Biologics Register

Background. Anti-tumour necrosis factor-(TNF-) therapies represent an important advancement in therapy for rheumatoid arthritis (RA). However, there remains a proportion of patients who do not improve despite therapy. These drugs are expensive and have the potential of serious toxicity. Therefore, it would be ideal to predict the patients who will respond, so that the use of these drugs can be targetted. Objective. To identify the clinical factors present at the start of anti-TNF-therapy that are associated with response at 6 months in patients with RA. Methods. The British Society for Rheumatology (BSR) Biologics Register collects detailed data on all patients with a rheumatic disease receiving biologic therapy in the UK. We studied all patients with RA who had started etanercept (ETA) or infliximab (INF) and had achieved a minimum 6 months follow-up by 1 October, 2004. The disease status at the baseline and at 6 months was assessed using the Disease Activity Score (DAS28). The response was classified according to the European League against Rheumatism (EULAR) improvement criteria. The effect of baseline characteristics on response was studied using multivariate ordinal logistic regression. Results. 2879 patients were included in this analysis (1267 ETA, 1612 INF). At the start of therapy, the mean age was 55 yrs, disease duration 14 yrs, baseline DAS28 6.7 and health assessment questionnaire (HAQ) 2.1. In all, 28% of ETA and 86% of INF patients were receiving methotrexate. After 6 months, 18% had a good EULAR response, of whom 9% were considered to be in remission and 50% had a moderate response. There was no overall difference in response rate between the two anti-TNF-therapies. A higher baseline HAQ score correlated with a lower response rate while a better response was associated with the current use of NSAIDs and the use of methotrexate (MTX), although the latter only reached statistical significance with ETA [OR 1.82 (95% CI 1.38–2.40)]. There was a lower response rate among current smokers, particularly in patients receiving INF [OR 0.77 (95% CI 0.60–0.99)]. Age, disease duration, rheumatoid factor and the previous number of disease-modifying antirheumatic drugs (DMARDs) did not predict response to either drug. However, females were less likely to achieve remission. Conclusions. These data support an improved outcome among patients receiving MTX in combination with anti-TNF-therapies. However, the most disabled patients were less likely to respond, despite concurrent MTX. The benefits of NSAIDs may reflect the relative absence of comorbidities in patients who …
Human Factors in Online Communities and Social Computing

The popularity of online communities is expanding. It was estimated that there were over 1.70 billion Internet users globally in 2009 (Pingdom, 2010) with one in four Internet users participating in chat rooms or online discussions (Madden and Rainie, 2003). Especially social networking sites have been exponentially increasing in population in the last few years. For example, just on the social network site Facebook, there are around 350 million users, and 50% of these users log in everyday (Pingdom, 2010). In this chapter we try to provide a synopsis of the topic of human factors for online communities and social computing by first defining online communities and computer-mediated communication (CMC). This is followed by a review of the different types of CMC, with specific categories of online communities described in more depth. The chapter concludes with a brief summary and suggestions for new directions in the area of online communities. 2 DEFINITION OF ONLINE COMMUNITIES
Pipelined adaptive IIR filter architectures using scattered and relaxed look-ahead transformations

Fine-grain pipelined architectures for adaptive infinite impulse response (AIIR) filters are presented in this paper. The AIIR filters are equation error based. The proposed architectures are developed by employing a combination of scattered look-ahead and relaxed look-ahead pipelining techniques. First, a pipelined system identification scenario is developed. Then, the scattered look-ahead technique is applied to the nonadaptive (but time-varying) recursive section. Finally, a relaxed look-ahead technique is applied to the adaptive blocks. Convergence analysis of the pipelined architectures is presented and verified via simulations. It is shown that speedups of up to 8 and more can be achieved with marginal or no degradation in performance.
on Circuit , Power and Computing Technologies [ ICCPCT ] Study of security and effectiveness of DoIP in vehicle networks

As the number of Electronic Control Unit increased in automotive system, its memory capability and functionalities have also increased in large scale. These large number of high functional Electronic Control Units (ECU) in vehicle system demand for high data rate connectivity to external network and within invehicle network. This high data rate requirement lead to the introduction of Ethernet Technology to the vehicle network system, which also provide the remote vehicle access and remote diagnostic functionalities to the vehicle network. Diagnostics over IP (DoIP) have standardized as international standard for diagnostics over IP which is documented in ISO 13400 DIS . This survey studies different technologies in vehicle network and are compared based on the data rate for diagnostics and a study of different Communication scenarios along with safety and security requirements of DoIP protocol is examined. Keywords— DoIP, AutoSAR, Diagnostics , Ethernet Diagnostics.
Incremental Adaptation of Constraint Handling Rule Derivations ?

Constraint solving in dynamic environments requires an immediate adaptation of previously evaluated solutions of constraint satisfaction problems if these problems are changed. After a change, an adapted solution is preferred which is stable, i.e. as close as possible to the original solution. A wide range of incremental constraint solving methods for dynamic (cid:12)nite domain constraint satisfaction problems are known which satisfy more or less this additional requirement. Fr(cid:127)uhwirth's Constraint Handling Rules (CHRs) are a high-level language extension to write constraint solvers. Up to now, more than 20 solvers for di(cid:11)erent kinds of constraints are available, including (cid:12)nite-domain constraints, linear equations and inequations, and set constraints. In this paper, a new general constraint solving method for dynamic constraint satisfaction problems is presented. In detail, a new incremental algorithm is presented which adapts CHR derivations after changes of the initial constraint systems (especially after constraint deletions). This algorithm guarantees optimal stability in the sense of the longest, still applicable sub-derivation. Therefore, all constraint satisfaction problems solved by a solver written in CHRs are incremental solvable in the dynamic case, too.
MULTIMODAL INTERACTION FOR SCENE BOUNDARY DETECTION

A scene boundary detection method is presented, which analy zes both aural and visual information sources and accounts for t hei inter-relations and coincidence to semantically identify v deo scenes. Audio analysis focuses on the segmentation of the audio source into three types of semantic primitives, i.e. silenc e, speech and music. Further processing on speech segments aims at loc ating speaker changing points. Video analysis attempts to segmen t th video source into shots. Results from single source segment atio are in some cases suboptimal. Audio-visual interaction ach ieves to either enhance single source findings or extract high level s emantic information. The aim of this paper is to identify semanti cally meaningful video scenes by exploiting the temporal correla tions of both sources based on the observation that semantic chang es re characterized by significant changes in both information so urces. Experimentation has been carried on several TV sequences co mposed of many different in-content scenes with plenty of com mercials in-between.
Modeling Finite-Fault Radiation from the o ) n Spectrum by

The high-frequency seismic field near the epicenter of a large earthquake is modeled by subdividing the fault plane into subelements and summing their contributions at the observation point. Each element is treated as a point source with an o92 spectral shape, where co is the angular frequency. Ground-motion contributions from the subsources are calculated using a stochastic model. Attenuation is based on simple geometric spreading in a whole space, coupled with regional anelastic attenuation (Q operator). The form of the co n spectrum with natural n follows from point shear-dislocation theory with an appropriately chosen slip time function. The seismic moment and comer frequency are the two parameters defining the point-source spectrum and must be linked to the subfanlt size to make the method complete. Two coefficients, Aa and K, provide this link. Assigning a moment to a subfault of specified size introduces the stress parameter, Ao-. The relationship between comer frequency (dislocation growth rate) and fault size is established through the coefficient K, which is inherently nonunique. These two parameters control the number of subsources and the amplitudes of high-frequency radiation, respectively. Derivation of the model from sheardislocation theory reveals the unavoidable uncertainty in assigning ogn spectrum to faults with finite size. This uncertainty can only be reduced through empirical validation. The method is verified by simulating data recorded on rock sites near epicenters of the M8.
Navigation Using Optical Flow Fields: An Application of Dominant Plane Detection

Video sequences capturing real scenes may be interpreted with respect to a dominant plane which is a planar surface covering ‘a majority’ of pixels in an image of a video sequence, i.e. that planar surface which is represented in the image by a maximum number of pixels. In this paper, we propose an algorithm for the detection of dominant planes from optical flow fields caused by camera motion in a static scene. We, in particular, intend to adopt this algorithm as a module for obstacle detection in vision-based navigation of autonomous robots. 1 Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology 2 Media Technology Division, IMIT, Chiba University 3 Software Research Division, National Institute of Informatics 4 Center for Image Technology and Robotics Tamaki Campus, The University of Auckland, Auckland, New Zealand. r.klette@citr.auckland. ac.nz You are granted permission for the non-commercial reproduction, distribution, display, and performance of this technical report in any format, BUT this permission is only for a period of 45 (forty-five) days from the most recent time that you verified that this technical report is still available from the CITR Tamaki web site under terms that include this permission. All other rights are reserved by the author(s). Navigation Using Optical Flow Fields: An Application of Dominant Plane Detection Kazuhiko Kawamoto, Daisuke Yamada, Atsushi Imiya and Reinhard Klette Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology Media Technology Division, IMIT, Chiba University Software Research Division, National Institute of Informatics CITR, University of Auckland E-mail: kawa@hrt.dis. titech.ac. jp