Miracle-dz/UniFAR-FTUs huggingface dataset:
Elliptic curve cryptography

—In 1985, Victor Miller and Neil Koblitz, independently, proposed the use of elliptic curves in public key cryptosystems, know as elliptic curve cryptography (ECC). The security of ECC is based on the intractability of the elliptic curve discrete logarithm problems (ECDLP). The key advantage of ECC over other established algorithms such as RSA or DSA is that there is no sub-logarithmic algorithm for solving the ECDLP. The lack of a sub-logarithmic algorithm results in substantially smaller key lengths, with the same security, as RSA or DSA. This makes ECC highly attractive when implemented on devices with limited resources. Elliptic curves have the potential, due to the lack of a credible attack, of replacing RSA as the algorithm of choice in public key cryptosystems. I propose to build a system that employs elliptic curves as the primary encryption algorithm. The elliptic curves will be defined over the fields F2m and Fp with an underlying arithmetic based on polynomial and optimal normal representation.
Experimental Evaluation of Analog Joint Source-Channel Coding in Indoor Environments

Recently, analog joint source-channel coding has been proposed as a means of achieving near-optimum performance for high data rates with a very low complexity. However, no experimental evaluation showing the practical feasibility of this scheme has been performed to date. In this paper, we describe a software-defined radio implementation of an analog joint source-channel coded wireless transmission system. Experimental evaluation carried out in an indoor environment making use of a wireless testbed shows that the performance perfectly matches that originally reported by simulations in Additive White Gaussian Noise (AWGN) channels for signal-to-noise ratio values below 20 dB.
Disrupting diffusion: Critical nodes in network

With the advent and proliferation of connected entities such as social, marketing, scientific and computer networks, it has become immensely important to understand and analyze the impact of one entity’s influence on another in the network. In this context, our objective is to identify a set of entities, which when made ineffective (quarantined or protected) will maximally disrupt the spread of influence in the network. We formulate and study the problem of identifying nodes whose absence can maximally disrupt propagation of information in the independent cascade model of diffusion. We present the notion of impact and characterize critical nodes based on this notion. Informally, impact of a set of nodes quantifies the necessity of the nodes in the diffusion process. We prove that the impact is monotonic. Interestingly, unlike similar formulation of critical edges in the context of Linear Threshold diffusion model, impact is neither submodular nor supermodular. Hence, we develop heuristics that rely on greedy strategy and modular or submodular approximations of impact function. We empirically evaluate our heuristics by comparing the level of disruption achieved by identifying and removing critical nodes as opposed to that achieved by removing the most influential nodes.
Design of GDI based 4-Bit Multiplier using Low Power Adder Cells

Gate Diffusion input (GDI) a new technique of designing lowpower digital combinational circuit is described. This technique allows reduction in power consumption, transistor count, propagation delay and area of digital circuits. This approach allows implementation of a wide range of complex logic functions using only two transistors. GDI proposes and compared with traditional CMOS. Comparison of GDI transistor count with CMOS is presented. Simulation result shows that the propose GDI has better performance in terms of power consumption and transistor count in compared to CMOS design. In our paper, we designed the 4*4 array multiplier based on GDI and the simulations are performed by CADENCE VIRTUOSO based on 180nm CMOS technology with the supply voltage of 0.7V.
A Layered Graphical Model for Cloud Forensic and Mission Attack Impact Analysis

Cyber-attacks on the system supporting an enterprise’s mission can impact achieving its objectives. We describe a layered graphical model as an extension of a forensic investigation in order to quantify mission impacts. Our model has three layers: the upper layer models operational tasks that constitute the mission and their inter-dependencies. The middle layer reconstructs attack scenarios from available evidence to reconstruct their inter-relationships. In cases where not all evidence is available, the lower level reconstructs potentially missing attack steps. Using the three levels of graphs constructed in these steps, we present a method to compute the impacts of attack activities on missions. We use NIST’s National Vulnerability Database’s (NVD)-Common Vulnerability Scoring System (CVSS) scores or forensic investigators’ estimates in our impact computation. We present a case study to show the utility of our model.
AIS Electronic

IT and business managers are not being given a clear guidance on what ECMS can offer and how they could benefits from these technologies. This study posits that ECMS-use is related to business process aspects, the organizational context and human factors that shapes the way organizations use the technology. With these focus in mind, this research has conducted multiple case studies in seven large organizations to understand the different ways they use ECMS. Based on the collected evidences, cross case analysis has yield interesting findings to how these organizations have been utilizing their ECMS in different ways to suit their business processes need, institutional conditions, users’ requirements and ECMS facilities available at hand. These outcomes make a significant contribution in guiding organizations to: plan intended ECMS-use, understand why their ECMS technology may be underutilized and design ways to exploit the use of these technologies.
American Society of Mechanical Engineers

This paper presents corrections for existing hydrodynamic instability based Critical Heat Flux (CHF) models in pool boiling by taking into account the effect of the viscosity, geometry and size of the liquid-vapour interface. Based on the existing literature, the Kelvin – Helmholtz theory, used by the most commonly adopted CHF models, can lead to noticeable errors when predicting the instability conditions. The errors are mainly due to the inaccuracy of the inviscid flow assumptions and the oversimplification of the interface geometry. In addition, the literature suggests the most unstable condition predicted by the Viscous Correction for Viscous Potential Flow (VCVPF) theory for the cylindrical interfaces best match the observed air column breakup conditions in water. In this paper, the most unstable instability conditions predicted by the VCVPF theory are used to correct the existing CHF models. The comparison between the existing and corrected CHF models suggests that the corrected models always predict a higher CHF value. In addition, the corrected Zuber model predicts similar CHF value to the Lienhard and Dhir model. The comparison with experimental data suggests that the correction to the Zuber model can increase its prediction accuracy in most cases, but not necessary for the Lienhard and Dhir model. When compared to experimental CHF data for boiling cryogens at different pressures, the corrected CHF models are consistently more accurate than the original CHF models.
Better Transit Routing by Exploiting Vehicle GPS Data (Research Paper)

Current public transport journey planners are mostly based on timetables, i.e., their planning assumes implicitly that all transit vehicles run on schedule. Unfortunately, unpredictable delays occur frequently which may have a negative impact on the quality of the journeys provided by timetable-based planners. In this paper, we check solutions for mitigating this problem and evaluate them empirically on the metropolitan public transportation network of Rome (Italy). We first try to assess whether the availability of dynamic information on the geo-location of transit vehicles (via GPS data) may help to improve the quality of the journeys offered by a planner. The main findings of our experiments are that GSP data provides substantial benefits for short journeys, while it does not seem to provide enough insight to improve long journeys. In particular, even with the use of GPS data, a journey planner can still be rather unreliable for long journeys, as there can be large fluctuations between the times predicted by the planner and the actual travel times incurred by passengers. As a second contribution of our work, we provide and evaluate experimentally new routing algorithms to improve the reliability of public transport journey planners.
Subjective Quality Assessment for Impaired Videos with Varying Spatial and Temporal Information I World

The new era of digital communication has brought up many challenges that network operators need to overcome. The high demand of mobile data rates require improved networks, which is a challenge for the operators in terms of maintaining the quality of experience (QoE) for their consumers. In live video transmission, there is a sheer need for live surveillance of the videos in order to maintain the quality of the network. For this purpose objective algorithms are employed to monitor the quality of the videos that are transmitted over a network. In order to test these objective algorithms, subjective quality assessment of the streamed videos is required, as the human eye is the best source of perceptual assessment. In this paper we have conducted subjective evaluation of videos with varying spatial and temporal impairments. These videos were impaired with frame freezing distortions so that the impact of frame freezing on the quality of experience could be studied. We present subjective Mean Opinion Score (MOS) for these videos that can be used for fine tuning the objective algorithms for video quality assessment. Keywords—Frame freezing, mean opinion score, objective assessment, subjective evaluation.
Improving landfill monitoring programs with the aid of geoelectrical - imaging techniques and geographical information systems

As the complexity of electrical systems on vehicles increases, so does the amount of communication. As of today communication often relies on controller area network (CAN) technology. The limitations of CAN in terms of bandwidth have begun to constitute a reason for concern within vehicle and boat industry and a change in technology is becoming more and more desirable, as proven by some major initiatives (from FlexRay to OPEN consortium). Earlier work at CPAC has shown standard Ethernet to be a possible candidate. This thesis aims to take that work further and to build a proof-of-concept, a steer-by-wire system that can be tested on a boat. This study, about how a complete Ethernet based system could be structured, revealed several challenges but showed that the construction of a functional proof of concept system was possible. The system was built using existing CAN to Ethernet converters, where the software was further developed to increase reliability and robustness. An evaluation of the use of nonstandard cables with standard Ethernet components showed that the communication was sensitive to electromagnetic disturbance, a subject which requires further study to properly determine properties such as the cost, weight and resilience of different types of cables suitable for use in Ethernet communication. Several types of connectors, from different vendors, were found to be possible alternatives when designing a system for the marine environment. A major part in the design of an Ethernet system is the choice of network topology. Different topologies give the network different properties, which must be matched with the desired properties of individual systems. The possibility to easily use off the shelf products was seen as an obvious advantage, allowing for the assembly of a working demonstrative system with cheap wireless routers, an Ethernet camera and standard Android devices.
Simulation and inference for stochastic volatility models driven by Lévy processes

We study Ornstein-Uhlenbeck stochastic processes driven by Levy processes, and extend them to more general non-Ornstein-Uhlenbeck models. In particular, we investigate the means of making the correlation structure in the volatility process more flexible. For one model, we implement a method for introducing quasi long-memory into the volatility model. We demonstrate that the models can be fitted to real share price returns data. Copyright 2007, Oxford University Press.
Quantifying economic values of coastal and marine ecosystem services and assessing their use in decision-making : applications in New Caledonia and Australia

Coastal and marine ecosystems are some of the most heavily exploited with increasing degradation. This alarming situation appeals for urgent and effective actions. The optimal balance between use and conservation of ecosystems theoretically requires all costs and benefits to be considered in decision-making, including intangible costs and benefits such as non-market use and non-use values. The broad aim of this PhD is to examine how these economic values associated with coastal and marine ecosystem services can be measured, and how the economic valuation exercise may be considered and influence management decision- making.The first analytical part of the thesis focuses on assessing non-market use and non-use values, through econometric methods. The characterization and estimation of non-use values are complex and controversial, especially when the valuation exercise is focusing on individuals who are users of the ecosystem services being considered. An original approach based on a stated preference method, namely choice experiments, is developed then empirically applied in quantifying non-market values for marine and coastal ecosystems in two areas in New Caledonia. It allows the estimation of non-use values for populations of users in an implicit way. An in-depth analysis of the individuals’ choice heuristics during the valuation exercise is also conducted, with a focus on payment non-attendance. This issue is dealt with by comparing multiple modelling approaches in terms of: (1) inferred attendance, in relation to stated attendance; (2) attendance distribution according to several socio-economic variables; and (3) welfare estimates.After noting that the potential influence of economic valuation in decision making is unclear and largely unexplored in the literature, the second major component of this PhD aims to examine if, how and to what extent the economic valuation of ecosystem services, including measures of non-market values, influence decision-making regarding coastal and marine ecosystems management in Australia. Based on two nation-wide surveys, the perceived usefulness of the economic valuation of ecosystem services by the general public and decision-makers is studied, and the reasons why decision-makers may or may not fully consider economic values are elicited. Using a multi-criteria analysis, a part of the surveys also aims at examining the relative importance of different evaluation criteria (ecological, social and economic) when assessing the consequences of a hypothetical coastal development project on commercial activities, recreational activities and marine biodiversity.
Image Segmentation Using MorphologicalOperation for Automatic Region Growing

Image Segmentation is a subset of an expansive field of Computer Vision which deals with the analysis of the spatial content of an image. It is used to detach regions from the rest of the image, in order to recognize them as objects. The key contributions of this paper are based on an algorithm and were executed step by step. Firstly Noisy Image was filtered with the help of various filters. Secondly Filtered Image was reconstructed with the help of Morphological Operations. Subsequently, Region Growing Technique was applied on reconstructed image and segmented image was implemented. Furthermore Segmented Image was divided into sub parts. Finally, Results are analyzed on three bases, firstly on the segmented noisy image and secondly on the filtered segmented image and finally on the sub parts of the noisy and filtered segmented image with four parameters such as PSNR (Peak Signal Noise to Ratio), MSE (Mean Square Error), Mean difference and Maximum difference.
Unsupervised Identification of Coherent Motion in Video

The identification and classification of motion patterns in point trajectories has been an important issue in understanding and representing dynamic scenes. This paper proposes an unsupervised approach to identify coherent motion in video. Instead of producing a spatio-temporal segmentation of the raw data, the proposed method analyzes point trajectories along the video sequence to identify sets of points that move coherently. This new way of extracting motion information from videos potentially can be used in different areas of image processing and computer vision.
Murk Removal and Object Detection in Foggy Image using CLAHE and CURVELET Transform

Images taken in poor weather conditions has a high amount of murk and haze in it. It degrades the visibility and clarity of the image. In this project, we propose the technique to enhance the murk image and to detect the object present in it. The enhancement technique used here is Contrast Limited Adaptive Histogram Equalisation (CLAHE). The enhanced image is segmented and the objects are detected using Curvelet Transform. Initially the RGB image is converted to gray scale image. The gray scale image is then filtered using median filter. The filtered image is enhanced using CLAHE. The enhanced image is segmented and the parameters such as Mean, Standard Deviation, Peak Signal to Noise Ratio, Mean Square Error are obtained and based on these parameters Curvelet Transform is applied and the objects are detected.
Visual Displays: The Continuing Investigations of the Highlighting Paradox

Visual Displays: The Continuing Investigations of the Highlighting Paradox by Frank Tamborello Previous research has suggested that making certain items visually salient, or highlighting, can speed performance in a visual search task. But designers of interfaces cannot always easily anticipate a user's target, and highlighting items other than the target can be associated with performance decrements. Three experiments were performed which demonstrated that people's performance in a visual search task is differentially sensitive to highlighting's predictiveness oftarget location. That sensitivity depends upon the proportion of instances in which highlighting actually predicts target location. A cognitive model constructed using the ACT-R architecture inferred that people evaluate and adjust their visual search behavior at a very small level of the task. TABLE OF CONTENTS INTRODUCTION . 1 EXPERIMENT 1A . 5 Method . 5 Results and Discussion . 6 EXPERIMENT 1B . 6 Method . 7 Results and Discussion . 7 EXPERIMENT 2 . 13 Method . 14 Results and Discussion . 15 THE ALGEBRAIC MODEL OF OPTIMAL VISUAL SEARCH IN A HIGHLIGHTED DISPLAY . 21 THE ACT-R MODEL . 26 GENERAL DISCUSSION . 36 REFERENCES . 38 APPENDIX A: HISTOGRAMS OF HUMAN RESPONSE TIME IN INVALID TRIALS AS A FUNCTION OF TARGET DISTANCE FROM HIGHLIGHTED ITEM . 39 APPENDIX B: HISTOGRAMS OF HUMAN AND ACT-R MODEL DATA . 72 LIST OF TABLES Table 1. Means and standard deviations for absolute slope of increasing and decreasing validity groups. Table 2. Values for PH given highlighting validity. Table 3. Production priors for the ACT-R model. 20 25 3
Usage and Usability Assessment

The first report in the new Tools for Practitioners series from the Council on Library and Information Resources, Usage and Usability Assessment: Library Practices and Concerns , targets libraries right in the navel, the selfexamination center that is. Evaluation and assessment have fueled the evolution of traditional, print-based libraries. Methodologies, such as user surveys, focus groups, and statistics gathering, have been used to collect the data needed for planning and decision making. In today’s digital environment, library resources and services are being transformed constantly, thus the assessment of usage and usability is a more formidable challenge. As noted in the preliminary text: “While libraries have excelled at assessing the development and use of their traditional collections and services, comparable assessments of online collection and services are more complicated and less well understood” (p. v). As a distinguished fellow of the Digital Library Federation (DLF) 2000–2001, Denise Troll Covey, associate university librarian of arts, archives, and technology at Carnegie Mellon University, researched library assessment practices. Over a three-month period, she surveyed twenty-four DLF member institutions, gathering data on the methods these libraries are using to assess the usage and usability of their online collections and services. The list of libraries surveyed is impressive and includes the California Digital Library, Carnegie Mellon University, Johns Hopkins University, the Library of Congress, and the New York Public Library. Using the survey findings, Covey crafts a brief yet comprehensive snapshot of current assessment methodologies. The report is organized into five sections. After a general introduction there are sections devoted to user studies and usage studies, followed by a section on how to plan and implement a research project, and general conclusions and future directions for assessment. The section on user studies describes informationgathering techniques that can be employed to identify and analyze gaps (or success ratios) in meeting users’ needs and expectations. Covey supplies an in-depth analysis of the basic methodologies:
Effects of Partial Melting on Seismic Velocity and Attenuation: A New Insight from Experiments

The effects of partial melting on seismic velocity and attenuation have long been studied by focusing on the direct effects of melt, such as the poroelastic effect. The direct effects are generally very small for a very small melt fraction. Because geochemical studies have shown that the melt fraction during partial melting is very small (∼0.1%), it is difficult to explain upper-mantle low-velocity regions by the direct effects of melt. Recent experimental studies, by using a rock analog, have captured a significant enhancement of polycrystal anelasticity just before partial melting in the absence of melt. This newly recognized effect enables us to interpret seismological and geochemical observations consistently. The new anelasticity model significantly changes the interpretation of upper-mantle seismic structures. This review summarizes the recent progress in the understanding of polycrystal anelasticity, starting from a basic knowledge of linear anelasticity.
Posterior Exploration for Computationally Intensive Forward Models

where e includes observation error as well as error due to the fact that the simulator η(x) may be systematically different from reality ζ(x) for input condition x. Our goal is to use the observed data y to make inference about the spatial input parameters x—predict x and characterize the uncertainty in the prediction for x. The likelihood L(y|x) is then specified to account for both mismatch and sampling error. We will assume zero-mean Gaussian errors so that