Miracle-dz/UniFAR-FTUs huggingface dataset:
Non-sharing communities? An empirical study of community detection for access control decisions

Social media users often find it difficult to make appropriate access control decisions which govern how they share their information with a potentially large audience on these platforms. Community detection algorithms have been previously put forth as a solution which can help users by automatically partitioning their friend network. These partitions can then be used by the user as a basis for making access control decisions. Previous works which leverage communities for enhancing access control mechanisms assume that members of the same community will have the same access to a user's content, but whether or to what extent this assumption is correct is a lingering question. In this paper, we empirically evaluate a goodness of fit between the communities created by implementing 8 community detection algorithms on the friend networks of users and the access control decisions made by them during a user study. We also analyze whether personal characteristics of the users or the nature of the content play a role in the performance of the algorithms. The results indicate that community detection algorithms may be useful for creating default access control policies for users who exhibit a relatively more static access control behaviour. For users showing great variation in their access control decisions across the board (both in terms of number and actual members), we found that community detection algorithms performed poorly.
A Co-designed HW/SW Approach to General Purpose Program Acceleration Using a Programmable Functional Unit

In this paper, we propose a novel programmable functional unit (PFU) to accelerate general purpose application execution on a modern out-of-order x86 processor in a complexity-effective way. Code is transformed and instructions are generated that run on the PFU using a co-designed virtual machine (Cd-VM). Groups offrequently executed micro-operations (micro-ops) are identified and fused into a macro-op (MOP) by the Cd-VM. The MOPs are executed on PFU. Results presented in this paper show that this HW/SW co-designed approach produces average speedups in performance of 17% in SPECFP and 10% in SPECINT, and up-to 33\%, over modern out-of-order processor. Moreover, we also show that the proposed scheme not only out-performs dynamic vectorization using SIMD accelerators but also outperforms an 8-wide issue out-of-order processor.
The Computational Intelligence of MoGo Revealed in Taiwan's Computer Go Tournaments

In order to promote computer Go and stimulate further development and research in the field, the event activities, Computational Intelligence Forum and World 9times9 Computer Go Championship, were held in Taiwan. This study focuses on the invited games played in the tournament Taiwanese Go players versus the computer program MoGo held at the National University of Tainan (NUTN), Tainan, Taiwan. Several Taiwanese Go players, including one 9-Dan (9D) professional Go player and eight amateur Go players, were invited by NUTN to play against MoGo from August 26 to October 4, 2008. The MoGo program combines all-moves-as-first (AMAF)/rapid action value estimation (RAVE) values, online "upper confidence tree (UCT)-like" values, offline values extracted from databases, and expert rules. Additionally, four properties of MoGo are analyzed including: (1) the weakness in corners, (2) the scaling over time, (3) the behavior in handicap games, and (4) the main strength of MoGo in contact fights. The results reveal that MoGo can reach the level of 3 Dan (3D) with: (1) good skills for fights, (2) weaknesses in corners, in particular, for "semeai" situations, and (3) weaknesses in favorable situations such as handicap games. It is hoped that the advances in AI and computational power will enable considerable progress in the field of computer Go, with the aim of achieving the same levels as computer chess or Chinese chess in the future.
The Importance of Place and Time in Translating Knowledge About Canada's Compassionate Care Benefit to Informal Caregivers

Canada's Compassionate Care Benefit (CCB), an employment insurance program designed to allow Canadian workers time off to care for a dying relative or friend, has had low uptake since its inception. Due to their role in working with family caregivers, social workers are one group of primary health care professionals who have been identified as benefiting from a knowledge translation campaign. Knowledge tools about the CCB have been developed through social worker input in a prior study. This article presents the findings of a qualitative exploratory intervention. Social workers (n = 8) utilized the tools for 6 months and discussed their experiences with them. Data analysis revealed references to time and space constraints in using to the tools, and demonstrated the impact of time geography on knowledge translation about the CCB. The results suggest that knowledge translation about the CCB could be targeted toward caregivers earlier on in the disease progression before the terminal diagnosis, and knowledge tools must be disseminated to more locations. These results may be valuable to policymakers and palliative care providers, as well as theorists interested in ongoing applications of time geography in knowledge translation and the consumption/production of care.
QoE-driven performance analysis of cloud gaming services

With the popularity of cloud computing services and the endorsement from the video game industry, cloud gaming services have emerged promisingly. In a cloud gaming service, the contents of games can be delivered to the clients through either video streaming or file streaming. Due to the strict constraint on the end-to-end latency for real-time interaction in a game, there are still challenges in designing a successful cloud gaming system, which needs to deliver satisfying quality of experience to the customers. In this paper, the methodology for subjective and objective evaluation as well as the analysis of cloud gaming services was developed. The methodology is based on a nonintrusive approach, and therefore, it can be used on different kinds of cloud gaming systems. There are challenges in such objective measurements of important QoS factors, due to the fact that most of the commercial cloud gaming systems are proprietary and closed. In addition, satisfactory QoE is one of the crucial ingredients in the success of cloud gaming services. By combining subjective and objective evaluation results, cloud gaming system developers can infer possible results of QoE levels based on the measured QoS factors. It can also be used in an expert system for choosing the list of games that customers can appreciate at a given environment, as well as for deciding the upper bound of the number of users in a system.
ULTRA-COMPACT DWARF CANDIDATES NEAR THE LENSING GALAXY IN ABELL S0740

We analyze three-band imaging data of the giant elliptical galaxy ESO 325-G004 from the Hubble Space Telescope Advanced Camera for Surveys (ACS). This is the nearest known strongly lensing galaxy, and it resides in the center of the poor cluster Abell S0740 at redshift z = 0.034. Based on magnitude, color, and size selection criteria, we identify a sample of 15 ultra-compact dwarf (UCD) galaxy candidates within the ACS field. This is comparable to the number of UCDs found within similar regions in more nearby clusters (Virgo, Fornax, Hydra). We estimate circular half-light radii Re,c from two-dimensional Sérsic and King model fits and apply an upper cutoff of 100 pc for our UCD selection. The selected galaxies have typical Sérsic indices n ≈ 1.5, while larger sources with Re,c > 100 pc are more nearly exponential, perhaps indicating that the latter are dominated by background disk galaxies. Many of the UCD candidates are surrounded by a faint “fuzz” of halo light, which may be the remnants of stripped material, and there is some evidence for intrinsic flattening of the UCDs themselves. An apparent separation in size between the most compact UCDs with Re,c < 17 pc and larger ones with Re,c > 40 pc may hint at different formation mechanisms. We do not find any M32 analogues in this field. The colors of the UCD candidates span the range from blue to red globular clusters (GCs), although the brightest ones are predominantly red. The UCD candidates follow the flattened, elliptical distribution of the GCs, which in turn follow the galaxy halo light, suggesting a common evolution for these three components. Planned follow-up spectroscopy can determine which candidates are truly members of Abell S0740 and how similar they are in distribution to the GCs.
Outcomes, recall and expectations : four essays on fertility and income support

Declines in fertility and increases in welfare dependency are among the most important concerns in contemporary Australia. This research discusses _aspects of these issues using several recent datasets of the Commonwealth Department of Families, Community Services and Indigenous Affairs (FaCIA). We present new analysis in these areas. Chapter 2 explores the effect of education on people's fertility expectations using the first wave of the Household, Income and Labour Dynamics in Australia (HILDA) Survey. The analysis is conducted in two stages. First, total intended lifetime fertility (the sum of realized fertility to date and expectations of the future number of children) is modelled as a function of education and a host of other variables reflecting the opportunity costs and consumption elements of child rearing. A second set of estimations concerns the determinants of the expected future number of children, controlling for the number of children a person already has. Generally, no evidence is found that higher education necessarily lowers people's fertility expectations. Chapter 3 analyses the reliability of survey data with respect to welfare dependency. It matches a survey data with the longitudinal administrative. records of FaCSIA by a unique identifier, in order to investigate at individual level the degree of respondent error of past and current welfare reliance. Respondent errors are found to be significant, and are associated with particular characteristics of the interviewees, including sex, education and income support (IS) history. After this, the chapter uses the variables from the survey and/or the administrative data to the question of how past IS experience predicts current IS status. Comparison of the estimation results shows that using variables from different sources leads to different conclusions. Further, the research examines whether paid-employment serves as a steppingstone for the recipients of Unemployment Benefit (UB); that is, whether it helps the recipients to leave benefit quicker. The issue is analysed in Chapters 4 and 5 with a unique administrative data set, the Longitudinal Data Set (LDS) One Percent Sample. Several key and robust findings are as follows: (1) having earnings increases the probability of earning more, providing evidence for the stepping-stone hypothesis,
Learning Query Intent for Sponsored Search

As sponsored search contributes the major income of many search engines, how to deliver ads effectively is studied intensively from both industrial and academia. Among various previous studies, many of them are keyword relevance based and few considered the underlying user intents behind queries for ads delivery. In this paper, we propose to classify search queries into different search intent categories such as “car buyer”, “car reviewer” and “car maintainer” about cars for ads delivery. However many classical machine learning models for query classification may fail in categorizing queries into the predefined intent categories since it is hard to collect data for training and in addition, the traditional bag of words features cannot accurately reflect user intents. In this work, we propose a random walk based solution on top of Web click-through graph, which optimize the features for measuring user intent during random walk as well. Through this way, we can automatically generate large scale training data, weight features according to query intent, and classify queries into intent categories simultaneously. The experimental results on real world user search click-through data show that our approach can improve ad click-through rate (CTR) as high as 62.5% in contrast to the relevance based ads delivery solutions without taking user intent into consideration.
Performance analysis of non‐preemptive hol GE/G/1 queue with two priority classes of sip‐t signaling system in carrier grade VoIP network

Abstract For analytic simplicity, the priority queueing of a VoIP network is modeled under the assumption that the traffic arrival process is Poisson distributed and the service time is exponentially distributed, while knowing that the holding times of calls are not an exponential distribution. Under this condition, the non‐Markovian process (e.g. Supplementary Variable Technique) is often considered. However, the analysis for priority processes has always been difficult to tackle directly, particularly when the number of priorities is greater than two. Earlier studies were therefore restricted to two priority classes (e.g. M1 B1, M2 B2/G1, G2/1). Although the analytical results are available, very complicated closed‐form expressions of mean queue length are still required for each class. The objective of this paper is to obtain a simple and analytic closed‐form for the mean length of an HOL (Head of Line) GE/G/1 queue with more than two priority classes. Compared with M 1 B1, M2 B2/G1, G2/1, the HOL GE/G/1 priority queue computations of an SIP‐T signaling system require only a few parameters (e.g. mean and variance) since measurements of actual interarrival or service times are often constrained. The performance analyses from mathematical calculations and computer simulations further confirm the accuracy and robustness of an HOL GE/G/1 queue. Hence, the optimum values of interarrival time SQVs (Squared Coefficient of Variations) and service time SQVs can be determined for GM (Guaranteed SIP‐T messages) and NGM (Non‐guaranteed SIP‐T messages).
The Prediction of Adolescents’ Aggression Levels in Terms of Value Orientations, Gender and Parents’ Education Level

The purpose of this study is to examine whether value orientations of adolescents, gender and state of parents’ education predict aggression. The study was designed as predictive correlational research model. The participants consisted of 890 adolescents. Data were collected by Aggression Scale, Portrait Values Scale and a personal information questionnaire. Data were analyzed through mean, Pearson correlation and hierarchical regression analysis. Results indicated that there was significant negative correlation between aggression levels and value orientations of adolescent. It was found that value orientations, gender and parents’ education level together explained 18.7% of the variance of aggression in adolescence. Findings showed that success, universalism, benevolence and education level of father significantly contributed to prediction of aggression in adolescents while the contributions of the security, conformity, self-direction, gender and education level of mother were not significant.
The Security Analysis and Attacks Detection of OSPF Routing Protocol

The widespread use of the Internet proposes great challenges for information security. Routing protocols are used to distribute network topology information among routers. Routers find the best route according to the topology information, and realize the network data forwarding. Without correct router information, the network packet transmission is inefficient or incorrect, which may even cause network paralyzed. Therefore, secure routing protocol is an import factor to ensure network security. This paper emphasizes the security of OSPF routing protocol. We firstly outline the background of OSPF technology, and present the OSPF security analysis, including authentication mechanism, reliable flooding mechanism and hierarchical routing mechanism. Then the vulnerabilities of OSPF and protecting methods are introduced. In addition, we propose the attacks detection system of OSPF routing protocol from the perspective of the OSPF security, in order to detect attacks without affecting the network operation. Lastly, future research on OSPF routing protocol are concluded.
International Trade and Income Differences JOB MARKET PAPER

Standards of living between the richest and poorest countries differ by more than a factor of 30. Is there a role for international trade in accounting for this fact? To answer this question, I construct a multi-country general equilibrium model. Within this framework, I derive an accounting procedure analytically decomposing income per worker into three components: differences in capital-output ratios, productivity, and a contribution from trade. Since the contribution from trade is measurable, I am able to quantify the variation in income per worker attributable to trade. In a sample of 77 countries, I show that the contribution from trade is negligible, less than 1 percent. That is, trade’s contribution is so small that relative incomes are almost the same in a model with no trade. To further understand this result and how cross-country income differences respond to changes in barriers to trade, I calibrate the model by picking country specific productivity parameters and trade costs so the pattern of bilateral trade implied by the model matches the data. I find the calibrated trade costs are systematically asymmetric with poor countries facing higher costs to export their goods relative to rich countries. Furthermore, my calibrated model generates both prices and cross-country income differences consistent with the data. Through counterfactual exercises, I find that by removing the asymmetry in trade costs (i.e. provide poor countries with equivalent market access to rich countries markets) cross-country income differences decline by up to 34 percent. Eliminating all barriers to trade reduces cross-country income differences by up to 56 percent. By facilitating a more efficient allocation of production across countries, reductions in barriers to trade are quantitatively important for economic development.
Migrating Existing Applications to a Distributed Environment using Aspect Oriented Programming

Aspect Oriented Programming (AOP) is a new programming paradigm that offers a novel modularization unit for the crosscutting concerns. Functionalities originally spread across several modules and tangled with each other can be factored out into a single, separate unit, called an aspect. The source code fragments introduced to port an existing application to a distributed environment (such as Java RMI) are typically scattered and tangled, thus representing an ideal candidate for the usage of aspects. In this paper, we propose a distribution framework based on AOP and we describe the steps necessary to migrate an existing program to it. In our solution, the original application remains oblivious of the distribution concern and all required aspects are generated automatically. The approach was validated on a case study.
A Hybrid Reinforcement Learning Approach for Coordinated Configuration of Virtual Machines and Appliances

Cloud computing has a key requirement for resource configuration in a real-time manner. In such virtualized environments, both virtual machines (VMs) and hosted applications need to be configured on-the-fly to adapt to system dynamics. The interplay between the layers of VMs and applications further complicates the problem of cloud configuration. Independent tuning of each aspect may not lead to optimal system wide performance. In this paper, we propose a framework, namely CoTuner, for coordinated configuration of VMs and resident applications. At the heart of the framework is a model-free hybrid reinforcement learning (RL) approach, which combines the advantages of Simplex method and RL method and is further enhanced by the use of system knowledge guided exploration policies. Experimental results on Xen-based virtualized environments with TPC-W and TPC-C benchmarks demonstrate that CoTuner is able to drive a virtual server cluster into an optimal or near-optimal configuration state on the fly, in response to the change of workload. It improves the systems throughput by more than 30% over independent tuning strategies. In comparison with the coordinated tuning strategies based on basic RL or Simplex algorithm, the hybrid RL algorithm gains 25% to 40% throughput improvement. Moreover, the algorithm is able to reduce SLA violation of the applications by more than 80%.
Discovering frequent episodes and learning hidden Markov models: a formal connection

This paper establishes a formal connection between two common, but previously unconnected methods for analyzing data streams: discovering frequent episodes in a computer science framework and learning generative models in a statistics framework. We introduce a special class of discrete hidden Markov models (HMMs), called episode generating HMMs (EGHs), and associate each episode with a unique EGH. We prove that, given any two episodes, the EGH that is more likely to generate a given data sequence is the one associated with the more frequent episode. To be able to establish such a relationship, we define a new measure of frequency of an episode, based on what we call nonoverlapping occurrences of the episode in the data. An efficient algorithm is proposed for counting the frequencies for a set of episodes. Through extensive simulations, we show that our algorithm is both effective and more efficient than current methods for frequent episode discovery. We also show how the association between frequent episodes and EGHs can be exploited to assess the significance of frequent episodes discovered and illustrate empirically how this idea may be used to improve the efficiency of the frequent episode discovery.
BOUNDARY LAYER CODES FOR STUDENTS IN JAVA

Simple JAVA computer codes for boundary layer problems intended for student use solving the homework problems in a text such as Boundary Layer Analysis by Schetz, 1993 and similar problems on a PC or Work Station have been developed. The notion is to make platformindependent codes conveniently available via the internet. At this point, there are four separate codes for: 1) Thwaites-Walz incompressible, laminar integral method, 2) incompressible, laminar boundary layers by an implicit numerical method, 3) Moses, incompressible turbulent integral method, and 4) incompressible turbulent boundary layers by an implicit numerical method. A brief description of each code precedes the operating instructions. Also, a default input for a typical example and results for that case are presented and discussed.
Non‐parametric estimation of finite mixtures from repeated measurements

This paper provides methods to estimate finite mixtures from data with repeated measurements non‐parametrically. We present a constructive identification argument and use it to develop simple two‐step estimators of the component distributions and all their functionals. We discuss a computationally efficient method for estimation and derive asymptotic theory. Simulation experiments suggest that our theory provides confidence intervals with good coverage in small samples.