Miracle-dz/UniFAR-FTUs huggingface dataset:
Systems Modelling for Economic Analyses of Security Investments: A Case Study in Identity and Access Management

Identity and Access Management (IAM) is a key issue for systems security managers such as CISOs. More specifically, it is a difficult problem to understand how different investments in people, process, and technology affect the intended security outcomes. We position this problem within the framework of optimal control models in macroeconomics, and use a process model to understand the dynamics of the utility of possible trade-offs between investment, access, and security incidents (breaches). A utility function is used to express the security manager's IAM preferences, and the functional behaviour of its components is described via a process model. Executing our process model as Monte Carlo simulations, we illustrate the behaviour of the utility function for varying levels of investment and threat, and so provide the beginnings of a decision-support tool for systems security managers.
Rating support interfaces to improve user experience and recommender accuracy

One of the challenges for recommender systems is that users struggle to accurately map their internal preferences to external measures of quality such as ratings. We study two methods for supporting the mapping process: (i) reminding the user of characteristics of items by providing personalized tags and (ii) relating rating decisions to prior rating decisions using exemplars. In our study, we introduce interfaces that provide these methods of support. We also present a set of methodologies to evaluate the efficacy of the new interfaces via a user experiment. Our results suggest that presenting exemplars during the rating process helps users rate more consistently, and increases the quality of the data.
Rapport with Virtual Agents: What Do Human Social Cues and Personality Explain?

Rapport has been recognized as an important aspect of relationship building. While rapport in the context of human-human interaction has been widely studied, how it can be established and maintained in human-agent interaction has been studied only recently. Our study investigates how social cues and personality of a human interacting with an agent can be used for automatic prediction of rapport in this context. We conduct experiments with two emotional virtual agents. Alongside the audio-visual data, we also collect human personality measures and two measures of rapport: self-reported rapport and rapport judged by observers. The social cues, such as turn-taking patterns and facial expressions are extracted from audio-visual data. Our results show that the most significant cues that infer the rapport judgments are the number of turn-taking cues and pauses. We also find that some of the significant social cues related to rapport are similar to those reported in previous psychology literature. We also confirm previous findings on how human personality plays an important role in perceiving the interaction with agents—people who score high in extraversion and agreeableness report higher rapport with both agents. Finally, the rapport prediction results suggest that automatic analysis of social phenomena in human-agent interaction could be a feasible method for agent evaluation.
Persistent neural activity in auditory cortex is related to auditory working memory in humans and nonhuman primates

Working memory is the cognitive capacity of short-term storage of information for goal-directed behaviors. Where and how this capacity is implemented in the brain are unresolved questions. We show that auditory cortex stores information by persistent changes of neural activity. We separated activity related to working memory from activity related to other mental processes by having humans and monkeys perform different tasks with varying working memory demands on the same sound sequences. Working memory was reflected in the spiking activity of individual neurons in auditory cortex and in the activity of neuronal populations, that is, in local field potentials and magnetic fields. Our results provide direct support for the idea that temporary storage of information recruits the same brain areas that also process the information. Because similar activity was observed in the two species, the cellular bases of some auditory working memory processes in humans can be studied in monkeys. DOI: http://dx.doi. org/10.7554/eLife.15441. 001
Inet: Internet Topology Generator

Network research often involves the evaluation of new application designs, system architectures, and protocol implementations. Due to the immense scale of the Internet, deploying an Internet-wide system for the purpose of experimental study is nearly impossible. Instead, researchers evaluate their designs using generated random network topologies. In this report, we present a topology generator that is based on Autonomous System (AS) connectivity in the Internet. We compare the networks generated by our generator with other types of random networks and show that it generates topologies that best approximate the actual Internet AS topology. 1 Using Inet NAME inet an AS-level Internet topology generator. SYNOPSIS inet -n N [-d k] [-p n] [-s sd] [-f of] DESCRIPTION The “Inet” generator generates an AS-level representation of the Internet with qualitatively similar connectivity. It is important to note that Inet only provides the connectivity information; the generated topologies do not have any information pertaining to latency, bandwidth etc. It generates random networks with characteristics similar to those of the Internet from November 1997 to June 2000, and beyond. The generator should be used to generate network of no less than 3037 nodes, which is the number of ASs on the Internet in November 1997. The software package with source code for Unix, can be found at: http://topology.eecs. umich.edu/inet/ This project is funded in part by NSF grant number ANI-0082287. Sugih Jamin is further supported by the NSF CAREER Award ANI-9734145 and the Presidential Early Career Award for Scientists and Engineers (PECASE) 1998. Additional funding is provided by AT&T Labs-Research, and by equipment grants from Sun Microsystems Inc. and Compaq Corp.
Learning Based Java for Rapid Development of NLP Systems

Today's natural language processing systems are growing more complex with the need to incorporate a wider range of language resources and more sophisticated statistical methods. In many cases, it is necessary to learn a component with input that includes the predictions of other learned components or to assign simultaneously the values that would be assigned by multiple components with an expressive, data dependent structure among them. As a result, the design of systems with multiple learning components is inevitably quite technically complex, and implementations of conceptually simple NLP systems can be time consuming and prone to error. Our new modeling language, Learning Based Java (LBJ), facilitates the rapid development of systems that learn and perform inference. LBJ has already been used to build state of the art NLP systems. In this paper, we first demonstrate that there exists a theoretical model that describes most NLP approaches adeptly. Second, we show how our improvements to the LBJ language enable the programmer to describe the theoretical model succinctly. Finally, we introduce the concept of data driven compilation, a translation process in which the efficiency of the generated code benefits from the data given as input to the learning algorithms.
The Impact of Marijuana Legalization on Law Enforcement in States Surrounding Colorado

Since the legalization of recreational marijuana occurred in Colorado, politicians, academics, and the public have been paying close attention to what impact, if any, the legalization of recreational marijuana has on crime, substance use and abuse, and state revenue gains. However, research has not identified the potential impact that marijuana legalization has had on law enforcement officers in neighboring states. This study used survey methodology to explore how the legalization of recreational marijuana in Colorado has affected law enforcement officers and their duties in states that border Colorado. Using multistage cluster sampling, municipal police departments and sheriff’s offices in Kansas, Nebraska, and Wyoming were selected for inclusion in this study based off their proximity to Colorado and because none had legalized either medical or recreational marijuana at the time of this study. Results indicate that law enforcement officers view Colorado’s legalization of recreational marijuana as having a negative impact on their enforcement duties. Respondents note an increase in potency, perceived juvenile use, and strain on their resources as major issues they are now having to deal with. Analysis indicates that departments further away from Colorado perceive less of an impact than counties closer to Colorado’s border. Compared with Nebraska and Kansas, respondents from Wyoming perceived a larger impact on enforcement, but these differences were diminished when controlling for personal perceptions of marijuana.
Intrusion detection and honeypots in nested virtualization environments

Several research projects in the past have built intrusion detection systems and honeypot architectures based on virtual machine introspection (VMI). These systems directly benefit from the use of virtualization technology. The VMI approach, however, requires direct interaction with the virtual machine monitor, and typically is not available to clients of current public clouds. Recently, nested virtualization has gained popularity in research as an approach that could enable cloud customers to use virtualization-based solutions within a cloud by nesting two virtual machine monitors, with the inner one under control of the client. In this paper, we compare the performance of existing nested-virtualization solutions and analyze the impact of the performance overhead on VMI-based intrusion detection and honeypot systems.
The Relationship between Mobility, Physical Activity and Strength with Depression, Cognitive State and Health Status in the Elderly in Portugal

This study attempts to understand the relationship between physical activity, strength and mobility with depression, cognitive state and health status among the elderly in Portugal and identify which measures best relate with these. Using a descriptive, cross-sectional and correlational study, a sample of 118individuals was selected by exclusion and inclusion criteria. The measuring instruments used were the Mini-Mental State Examination (MMSE), Geriatric Depression Scale (GDS), 12-Item Short Form Health Survey (SF-12), International Physical Activity Questionnaire (IPAQ), Timed Up and Go (TUG) and Hand Grip Strength (HGS). The sample had a normal distribution. Pearson’s test and ANOVA were used for the statistical analysis and revealed meaningful positive correlations between GDS and SF-12, IPAQ, TUG and HGS and also in MMSE with SF-12 [physical and mental dimensions], right HGS, left HGS and IPAQ. A meaningful negative correlation was also found in MMSE with TUG. SF-12 presented a significant negative correlation with TUG. Left HGS revealed a significant positive correlation to SF-12 in both physical and mental dimensions. However, right HGS was only significant to the physical dimension. IPAQ had no significant correlation with SF-12. All the measures had a meaningful correlation with depression (GDS) and cognitive state (MMSE). Applying simple instruments of easy application such as TUG have shown good values of correlation with depression, cognitive state and health. © 2018 Published by Future Academy www.FutureAcademy. org.uk
Asymptotic behaviour in temporal logic

We study the "approximability" of unbounded temporal operators with time-bounded operators, as soon as some time bounds tend to ∞. More specifically, for formulas in the fragments PLTL⋄ and PLTL◻ of the Parametric Linear Temporal Logic of Alur et al., we provide algorithms for computing the limit entropy as all parameters tend to ∞. As a consequence, we can decide the problem whether the limit entropy of a formula in one of the two fragments coincides with that of its time-unbounded transformation, obtained by replacing each occurrence of a time-bounded operator into its time-unbounded version. The algorithms proceed by translation of the two fragments of PLTL into two classes of discrete-time timed automata and analysis of their strongly-connected components.
Multi-carrier transmission techniques for wireless communication systems: a survey

The next generation wireless communications systems require higher data rates transmission in order to meet the higher demand of quality services. Research in wireless digital communications techniques have been expending very rapidly in the last few decades, resulting more reliable wireless communication systems that operate at higher spectral efficiency. Since there have been an increased in demand for higher data rate transmission, the systems are incorporating the multi-carrier transmission techniques. Therefore, Orthogonal Frequency Division Multiplexing (OFDM) is one of the leading candidates for future wireless systems. The objective of the paper is to provide a survey on multi-carrier transmission techniques i.e. OFDM and the combination of OFDM with Code Division Multiple Access (CDMA). The review on this rapidly expending area of wireless communication field is carried out on research works for the past 15 years. And in this survey also we Trying to explain how to use Discrete Wavelet Transform based OFDM (DWT-OFDM) Instead of using Fast Fourier Transform based OFDM Fast Fourier Transform based OFDM (FFT-OFDM). This study outlines the state-of-the art of OFDM novel technique as well as the methods of multi-carrier - Code Division Multiple Access (MC-CDMA) and MC-Direct Sequence-CDMA (MC-DS-CDMA).
Sensitivity Comparison of Searches for Binary Black Hole Coalescences with Ground-based Gravitational-Wave Detectors

Searches for gravitational-wave transients from binary black hole coalescences typically rely on one of two approaches: matched filtering with templates and morphology-independent excess power searches. Multiple algorithmic implementations in the analysis of data from the first generation of ground-based gravitational wave interferometers have used different strategies for the suppression of non-Gaussian noise transients, and targeted different regions of the binary black hole parameter space. In this paper we compare the sensitivity of three such algorithms: matched filtering with full coalescence templates, matched filtering with ringdown templates and a morphology-independent excess power search. The comparison is performed at a fixed false alarm rate and relies on Monte-carlo simulations of binary black hole coalescences for spinning, non-precessing systems with total mass 25-350 solar mass, which covers the parameter space of stellar mass and intermediate mass black hole binaries. We find that in the mass range of 25 -100 solar mass the sensitive distance of the search, marginalized over source parameters, is best with matched filtering to full waveform templates, to within 10 percent at a false alarm rate of 3 events per year. In the mass range of 100-350 solar mass, the same comparison favors the morphology-independent excess power search to within 20 percent. The dependence on mass and spin is also explored.
Co‐segregation of a homozygous SMN1 deletion and a heterozygous PMP22 duplication in a patient

Despite co‐segregation of two different genetic neurological disorders within a family is rare, clinicians should take into consideration this possibility in patients presenting with unusual complex phenotypes or with unexpected electrophysiological findings. Here, we report a Spanish 11‐month‐old patient with spinal muscular atrophy type 2 and Charcot‐Marie‐Tooth 1A.
The Order of Things: How developers sort fields and methods

In source code files, fields and methods are arranged in linear order. Modern programming languages such as Java do not constrain this order-developers are free to choose any sequence. In this paper we examine the largely unexplored strategies developers apply for ordering fields and methods: First, we use visualization to explore different ordering criteria within two open source Java projects. Second, we verify our observations in a metric-based analysis on an extended set of 16 projects. Third, we present the results of a survey that reflects the opinion and applied ordering strategies of 52 developers. 87% of the participants agreed that ordering of fields and methods is meaningful or important. Our results suggest that there exists a set of criteria repeatedly used for ordering. Among these, the categories defined in the official Java Code Conventions appear to be the primary ordering criterion. However, in the individual strategies of the participants of the survey, we identified 15 ordering criteria additional to the five criteria we considered in the empirical analysis.
Development policy lending, conditionality and ownership: A political economy model

Is the World Bank’s Development Policy Lending likely to enhance ownership and have greater effectiveness than structural adjustment? We specify a dynamic common agency model in which a government committed to reform faces domestic opposition from interest groups. The dynamic specification, which is original in the context of policy reforms supported by the International Financial Institutions (IFIs), is essential to allow the strength of special interest groups to arise endogenously during the reform process. We show that conditionality could alter the country’s political equilibrium and that the design of conditionality could have an impact on the effectiveness of conditionality by reducing domestic opposition to the reform programme. However, depending on country-specific circumstances, conditional assistance could lead to lower social welfare. Thus, for conditionality not to be inconsistent with ownership, its design must be appropriate to the country circumstances and directly affect the domestic political constraint. Unless the IFIs are prepared to design the content of conditionality according to recipient countries’ special characteristics, conditionality is likely to remain inconsistent with ownership. Outline
Database Security in Private Database Clouds

Cloud computing and cloud systems are very popular in today's Information Technology (IT) and systems and have grown very quickly. Cloud computing helps organizations solve increasing IT costs such as their licenses, power consumption, physical protection, by providing better standardization, higher benefit, greater performance, and quicker responses of information services. Carrying vital importance for our private and secret information, cloud systems must provide extra security solutions for database systems with organizations. While using firewalls, and intrusion detection systems on the network for external attacks, some improved access controls must be definitely decided for internal attacks as well. Using database transaction logs and audit can be very helpful on developing a database protection system. However, storing these logs may cause some serious storage and performance problems. Another problem is to manage multiple databases at the same time. In this study we introduce a new lightweight cloud-based database security solution by enhancing our previously developed database security solution, InfoFence, while managing many databases at the same time from a central point. The performance of our proposed database security system in a private cloud has been evaluated against one of the most commonly used products on the market, Oracle Audit Vault Server, and we show that our proposed solution has better performance results in our test environment.
Jump-Diffusion Risk-Sensitive Asset Management

This paper considers a portfolio optimization problem in which asset prices are represented by SDEs driven by Brownian motion and a Poisson random measure, with drifts that are functions of an auxiliary diffusion 'factor' process. The criterion, following earlier work by Bielecki, Pliska, Nagai and others, is risk-sensitive optimization (equivalent to maximizing the expected growth rate subject to a constraint on variance.) By using a change of measure technique introduced by Kuroda and Nagai we show that the problem reduces to solving a certain stochastic control problem in the factor process, which has no jumps. The main result of the paper is that the Hamilton-Jacobi-Bellman equation for this problem has a classical solution. The proof uses Bellman's "policy improvement" method together with results on linear parabolic PDEs due to Ladyzhenskaya et al.
Fast Distributed First-Order Methods

This thesis provides a systematic framework for the development and analysis of distributed optimization methods for multi-agent networks with time-varying connectivity. The goal is to optimize a global objective function which is the sum of local objective functions privately known to individual agents. In our methods, each agent iteratively updates its estimate of the global optimum by optimizing its local function and exchanging estimates with others in the network. We introduce distributed proximal-gradient methods that enable the use of a gradient-based scheme for non-differentiable functions with a favorable structure. We present a convergence rate analysis that highlights the dependence on the step size rule. We also propose a novel fast distributed method that uses Nesterov-type acceleration techniques and multiple communication steps per iteration. Our method achieves exact convergence at the rate of O(1/t) (where t is the number of communication steps taken), which is superior than the rates of existing gradient or subgradient algorithms, and is confirmed by simulation results. Thesis Supervisor: Asuman Ozdaglar Title: Class of 1943 Associate Professor
Does the Stock of Money Have Any Causal Significance

Recent developments in macroeconomics, and economic policy in general, have produced a "new consensus" economy-wide model, in which the stock of money doesnot play any causal role. The stock of money operates a mere residual in the economic process. The absence of the stock of money in many current debates over monetary policy has prompted the statement by the Governor of the Bank of England (during his time as the Deputy Governor) that it is ironic that as central banks became more and more concerned with price stability, less and less attention is paid to money. Indeed, the decline of interest in money appeared to have coincided with low inflation in a significant number of countries. This has prompted a number of contributions that, wittingly or perhaps unwittingly, have attempted to "reinstate" a more substantial role for money in this "new" macroeconomics. In this paper we wish to argue that these attempts to "reinstate" money in current macroeconomic thinking entails two important problems.The first is that they contradict an important theoretical property of the new "consensus" macroeconomic model, namely that of dichotomy between the monetary and the real sector. The second is that some of these attempts either fail in terms of their objective, or merely reintroduce the problem rather than solving it. We conclude that if money is to be given a causal role in the "new" consensus model, then a great deal of more substantial research would be necessary.