Miracle-dz/UniFAR-FTUs huggingface dataset:
Robust and E cient Sharing of RSA FunctionsRosario

We present two eecient protocols which implement robust threshold RSA signature schemes, where the power to sign is shared by N players such that any subset of T or more signers can collaborate to produce a valid RSA signature on any given message, but no subset of fewer than T corrupted players can forge a signature. Our protocols are robust in the sense that the correct signature is computed even if up to T ? 1 players behave in arbitrarily malicious way during the signature protocol. This in particular includes the cases of players that refuse to participate or that introduce erroneous values into the computation. Our robust protocols achieve optimal resiliency as they can tolerate up to (N ? 1)=2 faults, and their eeciency is comparable to the eeciency of the underlying threshold RSA signature scheme. Robust threshold signature schemes have very important applications, since they provide increased security and availability for a signing server (e.g. a certiication authority or an electronic cash provider). Solutions for the case of the RSA signature scheme are especially important because of its widespread use. In addition, these techniques apply to shared RSA decryption as well and, in consequence, to key escrow schemes based on RSA. Our schemes are based on some interesting extensions that we devised for the information checking protocol of T. Rabin and Ben-Or Rab94, RB89], and the undeniable signature work initiated by Chaum and van Antwerpen CA89]. These extensions have some attractive properties, and hence are of independent interest.
Distributed mapping with privacy and communication constraints: Lightweight algorithms and object-based models

We consider the following problem: a team of robots is deployed in an unknown environment and it has to collaboratively build a map of the area without a reliable infrastructure for communication. The backbone for modern mapping techniques is pose graph optimization, which estimates the trajectory of the robots, from which the map can be easily built. The first contribution of this paper is a set of distributed algorithms for pose graph optimization: rather than sending all sensor data to a remote sensor fusion server, the robots exchange very partial and noisy information to reach an agreement on the pose graph configuration. Our approach can be considered as a distributed implementation of a two-stage approach that already exists, where we use the Successive Over-Relaxation and the Jacobi Over-Relaxation as workhorses to split the computation among the robots. We also provide conditions under which the proposed distributed protocols converge to the solution of the centralized two-stage approach. As a second contribution, we extend the proposed distributed algorithms to work with the object-based map models. The use of object-based models avoids the exchange of raw sensor measurements (e.g. point clouds or RGB-D data) further reducing the communication burden. Our third contribution is an extensive experimental evaluation of the proposed techniques, including tests in realistic Gazebo simulations and field experiments in a military test facility. Abundant experimental evidence suggests that one of the proposed algorithms (the Distributed Gauss–Seidel method) has excellent performance. The Distributed Gauss–Seidel method requires minimal information exchange, has an anytime flavor, scales well to large teams (we demonstrate mapping with a team of 50 robots), is robust to noise, and is easy to implement. Our field tests show that the combined use of our distributed algorithms and object-based models reduces the communication requirements by several orders of magnitude and enables distributed mapping with large teams of robots in real-world problems. The source code is available for download at https://cognitiverobotics.github. io/distributed-mapper/
Is Health Care Expenditure Really a Luxury Good? Re-Assessment and New Evidence Based on OECD Data

The aim of the paper is to present new evidence on the relationship between income and health expenditure allowing for (i) substitution and complementary relationships between private and public health expenditure, (ii) presence of structural breaks in the dependent variables, and (iii) presence of heterogeneous institutional setting (country-specific health systems). Our results show that income elasticity is quite sensitive to the inclusion of technology variables and to health system heterogeneity, that complementary and substitution relationships play an important role in determining public and private health expenditure and, finally, that public and private health expenditures are both related with a cyclical indicator of economic activity.
Socially Embedded Prediction Markets

We propose a model of prediction markets where participants are biased according to their social relationships. We relax the standard assumption of complete rationality and adopt an arguably more realistic model where agents are disproportionally influenced by their neighbors in a social network. We conduct extensive agent-based simulations of our model. We find that prices in prediction markets remain accurate even when participants are biased and irrational. Moreover, accuracy is robust to changes in many factors, including how individuals are motivated to participate in the market, the way that individuals use public information, individual utility functions, the topology of the social network, and the strength of social influences. Our model can explain the high volume of trade often observed in speculative markets that is hard or impossible to explain under standard market rationality assumptions. Our model can also explain the documented ability of prediction markets to succeed even in the face of biased and irrational participants.
Towards Time-Discounted Influence Maximization

The classical influence maximization (IM) problem in social networks does not distinguish between whether a campaign gets viral in a week or in a year. From the practical standpoint, however, campaigns for a new technology or an upcoming movie must be spread as quickly as possible, otherwise they will be obsolete. To this end, we formulate and investigate the novel problem of maximizing the time-discounted influence spread in a social network, that is, the campaigner is interested in both "when" and "how likely" a user would be influenced. In particular, we assume that the campaigner has a utility function which monotonically decreases with the time required for a user to get influenced, since the activation of the seed nodes. The problem that we solve in this paper is to maximize the expected aggregated value of this utility function over all network users. This is a novel and relevant problem that, surprisingly, has not been studied before. Time-discounted influence maximization (TDIM), being a generalization of the classical IM, still remains NP-hard. However, our main contribution is to prove the sub-modularity of the objective function for any monotonically decreasing function of time, under a variety of influence cascading models, e.g., the independent cascade, linear threshold, and maximum influence arborescence models, thereby designing approximate algorithms with theoretical performance guarantees. We also illustrate that the existing optimization techniques (e.g., CELF) for influence maximization are more efficient over TDIM. Our experimental results demonstrate the effectiveness of our solutions over several baselines including the classical influence maximization algorithms.
Solving Distributed Constraint Optimization Problems Using Ranks

We present a variation of the classical Distributed Stochastic Algorithm (DSA), a local iterative best-response algorithm for Distributed Constraint Optimization Problems (DCOPs). We introduce weights for the agents, which influence their behaviour. We model DCOPs as graph processing problems, where the variables are represented as vertices and the constraints as edges. This enables us to create the Ranked DSA (RDSA), where the choice of the new state is influenced by the vertex rank as computed by a modified Page Rank algorithm. We experimentally show that this leads to a better speed of convergence to Nash Equilibria. Furthermore, we explore the trade-off space between average utility and convergence to Nash Equilibria, by using algorithms that switch between the DSA and RDSA strategies and by using heterogeneous graphs, with vertices using strategies in different proportions.
Social media and the world of work : A strategic approach to employees’ participation in social media

Purpose – The purpose of this paper is to explore the risks and benefits of employees’ social media use for an organization's reputation, and delivers suggestions for a strategic management approach. Design/methodology/approach – The findings of this research paper are based on a comprehensive literature review and supported by a leading practice example. Findings – Through social media, employees function as powerful brand ambassadors who shape reputation with everything they do and say online. This requires a strategic management approach to employees’ social media use, including research, internet access at the workplace, a strong commitment from the C-suite, the establishment of social media teams, the implementation of guidelines and policies, training and education, integration, as well as goal setting and measurement. These eight key steps will help communications professionals to better prevent the risks and leverage the benefits of their employees’ participation in the social web. Originality/val.
PATENTS : DO OWNERS GAIN / SUSTAIN COMPETITIVE ADVANTAGE ? Valuing IT Opportunities

The importance of information systems (IS) and information technology (IT) as strategic business tools has been widely acknowledged by both practitioners and academics. Hence, researchers have long been interested in the business value of IT and its influence on gaining and sustaining competitive advantage. Many claim that IT is subject to easy duplication and lack of protection and therefore sustained competitive advantage from IT is not a reality. However, other researchers have been able to show that the strategic use of IT applications can lead to longer term superior performance. Business method patents could be the missing link between the strategic use of IT and sustained competitive advantage. These patents have become much more valuable and enforceable in recent years providing protection for the patent owner that has not been considered by academicians. In this study, 40 patenting firms were matched with 40 nonpatenting competitors and their performance was compared in order to explore patentprotected IT-enabled sustained competitive advantage. The ownership of business method patents was not found to be a significant contributor to competitive advantage. However, patent-owning firms that were able to gain an initial performance improvement were more likely to maintain that advantage over time.
Privacy-preserving virtual machine checkpointing mechanism

Virtual machines (VMs) have been widely adopted in cloud platforms to improve server consolidation and reduce operating costs. VM checkpointing is used to capture a persistent snapshot of a running VM and to later restore the VM to a previous state. Although VM checkpointing eases system administration, such as in recovering from a VM crash or undoing a previous VM activity, it can also increase the risk of exposing users’ confidential data. This is because the checkpoint may store a VM’s physical memory pages and disk contents that contain confidential data such as clear text passwords and credit card numbers. This paper presents the design and implementation of SPARC, a Security and Privacy AwaRe virtual machine Checkpointing mechanism. SPARC enables users to selectively exclude users’ confidential data within a VM from being checkpointed. We describe the design challenges in effectively tracking and excluding process-specific memory and disk contents from the checkpoint file for a VM running on the com.
Exercising real options: the case of voluntary liquidations

This paper presents a theoretical and empirical model of voluntary liquidation. Using the insight from real options literature, we examine the rationale and optimality of US corporate voluntary liquidations for 1990-2000. We test the key predictions from the optimal option exercise boundary. OLS regressions suggest that both the interest effect and the variance effect are at work. However, it seems that performance variability is the key to liquidation decision. We therefore conclude that real options models have explanatory power.
A New Segmentation Method for Lung HRCT Images

Image segmentation plays a crucial role in many medical imaging applications by automating or facilitating the delineation of anatomical structures and other regions of interest. The aim of this paper is to develop an accurate and reliable method for segmentation of lung HRCT images using a pixel-based approach. The proposed method combines traditional concepts, such as global-threshold segmentation, mathematical morphology, edge detection and noise reduction, with new ideas, such as performing geometrical computations to achieve the defined ROIs. Two different approaches are proposed and tested on 100 computed-tomography images. Noise tolerance of the algorithm is calculated considering several parameters and objective criteria. In addition, the image segmentation results were visually validated by radiologists.
A high-efficiency cross-coupled charge pump for flash memories

This paper presents a new cross-coupled charge pump structure which generates 2Vdd output and applies to flash memory. Compared with conventional structures, the novel scheme has lower ripple voltage, and higher efficiency. These advantages were achieved by employing the methods of reducing power loss effectively. The proposed charge pump was fabricated with TSMC 0. 18µm CMOS process. By the simulation of HSPICE, it shows that the new scheme could operate at a supply voltage as low as 0.9V with the maximum efficiency of 91.82%.
Fast Mode Decision Algorithm for Spatial and Coarse Grain Quality Scalable Video Coding

In the current Scalable Video Coding (SVC) Extension of the H.264/AVC standard, an exhaustive search method is employed to achieve the optimal Rate-Distortion (RD) cost, but it results in an extremely heavy computational burden. In this paper, an improved fast mode decision algorithm is proposed for spatial and Coarse Grain Quality (CGS) scalable video coding. It makes use of the mode correlation between the base layer and the enhancement layer as well as the mode correlations between Macroblocks (MBs) in spatial neighborhood. Specifically, the prediction mode candidates include the mode predicted from the co-located MB in the base layer, the best modes of spatial neighboring MBs, and the SKIP mode. Combined with an early termination check and a refinement search, the coding complexity can be reduced while preserving good quality. From the experimental results, the proposed method can reduce the total encoding time by up to 52.25% with negligible quality degradation.
The first UAV-based P- and X-band interferometric SAR system

In this paper we present the design overview of the UAV-based P- (repeat-pass) and X-band (single-pass) interferometric SAR system of OrbiSat, Brazil. The main objective is to built a compact and flexible InSAR system capable of performing accurate topographic survey and differential interferometry. To our knowledge, this is the first UAV-based In-SAR system with such characteristics, multi-band and fixed-baseline (X-band), to be projected. The status, and some main project results and solution are described and depicted.
A Two-Stage Incremental Annotation Approach to Constructing a Network Informal Language Corpus

Network Informal Language (NIL) refers to the special human language widely used in the community of digital network chat via platforms such as chat rooms/tools, mobile phone short message services (SMS), bulletin board systems (BBS), emails, etc. NIL holds anomalous characteristics in forming words, phrases, and non-alphabetical characters. This makes it difficult to handle NIL text by conventional natural language processing (NLP) tools. Previous research reveals that knowledge based methods perform less effectively in processing unseen NIL expressions. This motivates us to construct an annotated NIL corpus which is used specially to develop and evaluate techniques for extraction and normalization of NIL expressions. A two-stage incremental annotation approach is proposed in this paper to construct a NIL corpus with minimal human involvement. Several experiments are conducted which reveal that the efficiency of corpus annotation can be improved greatly with this approach.
Discovering hotspots: A placement strategy for Wi-Fi based trajectory monitoring within buildings

In the last decade, Wi-Fi based trajectory monitoring has gathered high interest in the scientific and commercial world, due to the increased usage of Wi-Fi capable mobile devices. A lot of work can be found where monitor nodes are placed in an area of interest capturing Wi-Fi signals from passing phones. However, the deployment of such nodes is often inefficient, expressed by a low ratio between monitored trajectories and the amount of installed nodes. Hence, finding an optimal setting of node positions is an essential and challenging task. In this paper, a systematic solution for this variant of the NP-hard art gallery problem is investigated. The idea is to set monitor nodes only on places (hotspots), where most of the human paths can be tracked. For the discovery of such hotspots, three novel approaches are presented working on simulated user traces based on an extended pathway mobility model, and a given plant layout. The results of each approach are evaluated in terms of quality for Wi-Fi based trajectory monitoring using different parameters and settings. The evaluation indicates that the proposed methods show different potentials and limitations. Overall, they return a reliable setting of hotspots compared to a completely random selection of an equal amount of node positions and, thus, they serve as a systematic and sophisticated placement strategy.
Foundations of public economics: Contents

Preface and acknowledgments Notation Part I. Scope and Limitations: 1. Introduction 2. Social objectives and direct decision making 3. Market decentralization 4. Market decentralization 4. Theory of collective goods Part II. Decision Making in a Mixed Economy: 5. Planning mechanisms 6. Models of a mixed economy 7. Government budgeting and fiscal decentralization 8. Public pricing and optimal-commodity taxation Part III. First-Order Project Analysis: 9. Decompositions and general theory of second best 10. Principles of shadow pricing 11. Local public goods 12. Intertemporal contexts with uncertainty 13. Identifying shadow values: hedonic methods and capitalization Part IV. Evaluating Large Projects: 14. search for exact measures 15. Surplus approximations 16. Practical methods for large-project evaluation 17. Peak-load problem Epilog References Author index Subject index.
Diversity benefits in 60 GHz VCN wireless architecture

This paper gives comprehensive description of a broadband communication system using the 60 GHz frequency band. We describe the channel and its inherent problems such as interference situations and body shadowing. We introduce the use of Virtual Frequency Networks and multiple receiving antennas in order to solve these problems resulting in an overlapping cellular architecture. We explain how the diversity of the channel can be used to increase reliability and performance. Finally, we simulate the link performance of a VCN using two receiving antennas for a set of OFDM parameters.
Adaptive and resilient systems for emergency response

Events of recent years have brought to light the difficulties involved in responding to major emergencies, particularly with respect to the on-site coordination of the many responding agencies. This paper presents an overview of the work being conducted by a team within National ICT Australia (NICTA) on rapidly deployable, resilient and adaptive networks and applications for emergency response. Our work is focused on creating reconfigurable, selfhealing hybrid wireless mesh networks and enabling context-aware applications for emergency response teams that can be deployed over such networks. BIOGRAPHY: Dr Ricky Robinson is a researcher in the SAFE Networks work package of the Smart Applications for Emergencies (SAFE) Project at NICTA’s Queensland Research Laboratory. He is conducting research into context-aware systems, and self-configuring and selfhealing networks, with an aim to applying the research outcomes to the domain of emergency
Growth expectations and financial performance of small businesses:evidence from Latvia

By applying regulatory focus theory, this paper investigates the impact of both initial confidence and of exactness of growth expectations on subsequent financial performance of the small firms. Drawing on the unique data set based on the repeated survey design, we make one of the first attempts to explore the complexity of this relationship empirically. Overall the findings suggest that controlling for other relevant factors, including actual growth, the entrepreneurs having higher growth expectations perform significantly better later on in terms of profitability. In addition, education has a strong modifying effect: the impact of high growth expectations on subsequent profit performance is stronger for entrepreneurs with lower level of education.
Finite element assessment of block-augmented total knee arthroplasty

Loosening and migration of tibial prostheses have been identified as causes of early total knee replacement (TKR) failure. The problem is made more complex when defects occur in the proximal tibia compromising fixation and alignment. Clinical studies using metal augments have shown these to be an alternative to other means of defect treatment. Finite element (FE) analysis can be used to identify regions that may be prone to loosening and migration. In the current work, 3D FE models of TKR uncontained type-2 defects treated with block augments have been constructed and analysed. It has been shown that a metal augment is the most suitable. The use of bone cement (PMMA) to fill proximal defects is not considered suitable as stresses carried by the cement block exceed those of the fatigue limit of bone cement. It has been shown that the stresses in the proximal cancellous bone of block-augmented models are significantly below levels likely to cause damage due to overloading. Furthermore, the use of stem extensions has been shown to reduce the cancellous bone stresses in the proximal region thus increasing the likelihood of bone resorption. Given this, it is recommended that stem extensions are not required unless necessary to mitigate some other problem.
Economic Transition in Vietnam

I. The development of foreign trade and aid since 1960: foreign trade and aid in the development of a market economy reform of the foreign trade system. II. The development of unofficial trade and aid 1976-1996: introduction commercial links with the Soviet Union and Eastern Europe goods sent by overseas Vietnamese to their relatives the intershop system VOSCO goods cross-border trade between Vietnam and Laos trade across the Cambodian border cross-border trade with China sales of goods and services to foreigners international payments. III. Conclusion: past, present and future.