Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimization of All Pairs Similarity Search

All pairs similarity search (APSS) is the problem of finding all the similar pairs of items, whose similarity is above a given threshold. APSS algorithm is applied to many data mining fields, such as document matching, collaborative filtering. Due to a large scale of data in real life, some recent work used partitioning, inverted indexing, parallel accumulation, and hashing approximation to optimize the APSS algorithm. To optimize the APSS problem, this paper analyzes and compares two parallel approaches. To demonstrate the performance gain of our optimization approaches, we implement our algorithms on Spark and conduct the evaluation on a dataset of one million movies, which gains better performance speedup than other works.
Similar or Dissimilar Users? Or Both?

E-commerce sites utilize collaborative filtering(CF) techniques to offer recommendations to their customers. To recruit new customers and keep the current ones, it is imperative for online vendors to provide accurate predictions efficiently without deeply violating users' privacy. To improve the overall performance of CF systems, it is important to use the appropriate data.We investigate how to improve naive Bayesian classifier(NBC)-based CF systems' online performance. For this purpose, we group users in various clusters so that predictions can be generated on similar or dissimilar; or both groups of users' data. Grouping users into clusters makes it possible to utilize smaller amount of data. We perform real data-based experiments to assess how overall performance changes with different data. Our results show that online time to generate referrals improves significantly when clustering is utilized to get proper data.
Measuring Exchange Rate Misalignment

We propose a new methodology to measure exchange rate misalignment for Turkey, which has already undergone a severe economic crisis. We estimate the real exchange rate within a time varying parameter model, where a return-to-normality assumption about the parameters are assumed. Contrary to common belief, it is found that, except the initial four months of the stabilization program, the Turkish Lira remained structurally undervalued for most of 2000. Also, we observe a pattern where the Lira has been structurally overvalued after the crisis in 1994 until 1998, and has displayed structural undervaluation after that.
Relevance of Specific versus General Combining Ability in Winter Wheat

Knowledge of quantitative genetic parameters is crucial in allocating resources for different steps of multistage selection programs. The main objective of the present study was to investigate the magnitude of variance of general combining ability (GCA) and specifi c combining ability (SCA) effects and their interaction with environments in wheat (Triticum aestivum L.). We used four data sets (Exp. 1, 2, 3, and 4) generated in commercial hybrid winter wheat breeding programs with a total of 940 hybrids evaluated in multienvironment trials in 2010 and 2011 in France. In at least three out of four experiments, general combining ability variance for females (σ 2 GCA-F ), specifi c combining ability variance (σ 2 SCA ), general combining ability of females × environment interaction variance (σ 2 GCA-F×E ), and general combining ability of males × times environment interaction variance (σ 2 GCA-M×E ) were signifi cantly larger than zero but general combining ability variance for males (σ 2 GCA-M ) was signifi cant only in Exp. 4. For Exp. 3, we found no signifi cant difference between the best performing hybrid and the best performing commercial variety. In contrast, 1.8% of hybrids in Exp. 2 and more than 21% of the hybrids in Exp. 1 and 4 signifi cantly (P < 0.05) outperformed the best commercial variety included in the respective experiment. This superiority was even apparent when projecting our fi ndings on line varieties of the same cycle of selection. In Exp. 2, 3, and 4, general combining ability variance (σ 2 GCA ) was more pronounced compared to σ 2 SCA . Moreover, correlation between GCA predicted and observed hybrid performance was medium to high (r Exp.1 = 0.50, P < 0.01; r Exp.2 = 0.90, P < 0.01; r Exp.3 = 0.59, P < 0.01; and r Exp.4 = 0.92, P < 0.01). Consequently, selection based on GCA effects is promising in hybrid wheat breeding program.
A Spectroscopic Survey for Binary Stars in the Globular Cluster NGC5053

We carried out a radial velocity survey for spectroscopic binaries in the low density globular cluster NGC5053. Our sample contains a total of 77 cluster member giant and subgiant stars with visual magnitudes of 14.5-18.6. Of these 77 stars, 66 stars have on average of 3-4 measurements with a total of 236 velocities. A typical velocity error per measurement is about 3 km/s. The stars in our sample are spatially distributed from the cluster center out to 10 arcminutes in radius (4.5 core radii). Among these 66 stars with multiple velocity measurements, we discovered 6 spectroscopic binary candidates. Of these six candidates, one was discovered as a binary previously by Pryor et al. (1991) and candidate ST is a binary with a very short-period of three to five days. We obtained three possible orbital solutions for binary candidate ST by fitting its radial velocity data. These orbital solutions are consistent with star ST being a cluster member, although its spectrum has much stronger MgI triplet absorption line than that of a typical low-metallicity giant star. We estimated the fraction of binary systems which may have been missed from our detection due to unfavorable binary orbital configurations. Our survey has a binary discovery efficiency of 29% for systems with 3d < P < 10yr, 0.125 < q < 1.75 and eccentric orbits (0 < e < 1). This yields a binary frequency of 29%. With Kolmogorov-Smirnov (K-S) tests, the hypothesis of a frequency in NGC5053 higher than 50% is rejected with a confidence level higher than 85%. We conclude that the binary frequency in NGC5053 is 21-29% with 3d < P < 10yr, 0.125 < q < 1.75. This value is somewhat higher than estimates for other clusters by various surveys. This is perhaps related to the fact that NGC5053 is relatively dynamically young compared to other clusters. (shortened version)
Status Incentives and Performance

Studies in economics and management suggest that people invest effort to achieve pure status, and this investment increases in status incentives. We design field experiments to investigate these two behavioral hypotheses. We define status as the subjects' relative rank in their group based on their performance in a task. We explore two real tasks. In both of the tasks, subjects' earnings are nominal and independent of their performance; so status-seeking preference should be the sole reason for achieving higher ranks. Our results indicate that inducing higher status incentives may not necessarily improve individual performance and may depend upon the task. Copyright © 2012 John Wiley & Sons, Ltd.
Introduction to Autonomous Robotics using Lego Mindstorms NXT

To thoroughly teach fundamentals of robotics to computer science undergraduates, a well-balanced curriculum should be designed and complemented with hands-on applications on a platform that allows rapid construction of complex robots, and implementation of sophisticated algorithms. This paper describes such a course where the Lego Mindstorms NXT kits are used as the robot platform. The aims, scope, and contents of the course are presented and the design of the laboratory sessions as well as the term projects, which address more than one core problem of robotics and artificial intelligence simultaneously, are explained in detail.
A unified signed-digit adder for high-radix modular exponentiation on GF(p) and GF(2p)

Addition on GF(p) and GF(2p) differs only in terms of the propagation of the carry. The unification of carry propagation and carry-less operations can provide higher performance using less hardware resources. Modular multiplication is a basic kernel computation for RSA and ECC, which is realized using repeated additions. Modular exponentiation, which uses modular multiplication, requires high radix values so as to provide the necessary security level for modern secure applications. The proposed arithmetic unit can support high radix modular exponentiation on both fields using a signed-digit number adder, which provides a balance between carry propagation and carry-less operations. The proposed design is optimized for Xilinx Virtex 5 devices.
Public debt around the world: a new data set of central government debt

Commonly used data sets on the level of public debt provide incomplete country and period coverage. This article presents a new data set that includes complete series of central government debt for 89 countries over the period 1991 to 2005 and for 7 other countries for the period 1993 to 2005.
What has been the tax competition experience of the past 20 years

This paper describes tax reforms in OECD countries over the last 20 years and how they are related to tax competition. Both individual countries' reforms and multilateral initiatives and developments are covered. This is followed by an overview of the empirical evidence on tax competition. Our conclusion is that the evidence for some interdependence in tax setting behaviour is strong, although the exact process driving this remains unclear. While the most basic tax competition models fail to explain the development in OECD countries, there is more than one possible explanation for the reforms undertaken if more advanced models are considered. The multilateral initiatives that were implemented however do not seem to be related to resource-based tax competition, instead they are about taxing rights.
Integrated neural-network-based method for predicting synthetic permeability in lead-zinc sintering process

In order to deal with the time variance and strong nonlinearity of lead-zinc sintering process, an integrated method of predicting synthetic permeability based on neural networks (NNs) and a particle swarm algorithm has been developed. In this paper, the concept of the exponent of synthetic permeability, which reflects the state of the permeability of the process, is first explained. Next, NNs are used to establish time-sequence-based and technological-parameter-based models for predicting the permeability. Then, an integrated structure based on a fuzzy classifier is described and used to construct an intelligent integrated model for predicting the permeability that combines the two models just mentioned. Finally, the results of actual runs show the method to be both effective and practical.
A Cost-Capacity Analysis for Assessing the Efficiency of Heterogeneous Computing Assets in an Enterprise Cloud

Cloud providers and organizations with a large IT infrastructure manage evolving sets of hardware resources that are subject to continual change. As existing computing assets age, newer, more capable and more efficient ones are generally acquired. Significant variability of hardware components leads to inefficient use of computing assets within the organization. We claim that only a detailed understanding of the whole infrastructure will lead to significant optimizations and savings. In this paper we report results on a dataset of 1,171 assets from two different data centers, on which we present a thorough analysis of how the costs of running a computing asset are related to its resource capacity (i.e., CPU and RAM). This analysis is formalized in a cost model that could be used by organizations to make an optimal decision with regards to which computing assets should migrate their workload (i.e. should be disconnected or discarded) and which ones should receive such workload.
Performance Evaluation of AODV and DSDV for Implementing Robot Swarm

In Mobile Ad-Hoc Networks, routing the data towards a destination node is the most fundamental task. Different routing protocols have been proposed considering specific appli cation and scenario characteristics. The constant change in the positions of the nodes make this task challenging. In the proposed work, a set of agents, here referred to robots, are made to converge towards each other and an external stimulus, fire, using software based sensors that detect heat without knowing prior positions of other robots and starting off at random positions. Agents use input from their peers to make and modify individual decisions which allows for better synergy, more informed and efficient path finding, collision avoidance, etc. For accomplishing this objective, Particle Swarm Optimization(PSO), a population based approach in solving optimization problems, requires an efficient routing protocol which is fast and reliable making the best use of the feeble hardware that comprise the robots. The robots require frequent communication with each other and they have performed well when paired with the routing protocol AODV as compared to DSDV and the simulations performed have given promising
A Theory of Bisimulation for the (cid:25)-calculus (cid:3)

We study a new formulation of bisimulation for the (cid:25)-calculus [MPW92], which we have called open bisimulation ((cid:24)). In contrast with the previously known bisimilarity equivalences, (cid:24) is preserved by all (cid:25)-calculus operators, including input pre(cid:12)x. The di(cid:11)erences among all these equivalences already appear in the sublanguage without name restrictions: Here the de(cid:12)nition of (cid:24) can be factorised into a \standard" part which, modulo the di(cid:11)erent syntax of actions, is the CCS bisimulation, and a part speci(cid:12)c to the (cid:25)-calculus, which requires name instantiation. Attractive features of (cid:24) are: a simple axiomatisation (of the (cid:12)nite terms), with a completeness proof which leads to the construction of minimal canonical representatives for the equivalence classes of (cid:24); an \e(cid:14)cient" characterisation, based on a modi(cid:12)ed transition system. This characterisation seems promising for the development of automated-veri(cid:12)cation tools and also shows the call-by-need (cid:13)avour of (cid:24). Although in the paper we stick to (cid:25)-calculus, the issues developed may be relevant to value-passing calculi in general. Work supported by the ESPRIT BRA project 6454 \CONFER".
Management control transformations

Purpose – The purpose of the paper is to clarify ongoing transformations in an organisation's management control systems (MCSs) by investigating the nature and emergence of internal change mechanisms.Design/methodology/approach – This study uses an inductive methodological approach. Data were obtained from focused interviews with managers at different levels in one public and one private Swedish organisation. Various internal and external documents were also analysed.Findings – The findings indicate that one starting point for achieving continuous MCS transformation in organisations is to select specific transformation mechanisms. These mechanisms appear capable of linking various aspects of organisational time and place, and turning general expectations of continuous change into coordinated action through accountability and organisational learning.Research limitations/implications – The study focuses on enablers rather than barriers in MCS transformation processes. Selection of the specific organisations.
Neuronal L-Type Calcium Channels Open Quickly and Are Inhibited Slowly

Neuronal L-type calcium channels are essential for regulating activity-dependent gene expression, but they are thought to open too slowly to contribute to action potential-dependent calcium entry. A complication of studying native L-type channels is that they represent a minor fraction of the whole-cell calcium current in most neurons. Dihydropyridine antagonists are therefore widely used to establish the contribution of L-type channels to various neuronal processes and to study their underlying biophysical properties. The effectiveness of these antagonists on L-type channels, however, varies with stimulus and channel subtype. Here, we study recombinant neuronal L-type calcium channels, CaV1.2 and CaV1.3. We show that these channels open with fast kinetics and carry substantial calcium entry in response to individual action potential waveforms, contrary to most studies of native L-type currents. Neuronal CaV1.3 L-type channels were as efficient as CaV2.2 N-type channels at supporting calcium entry during action potential-like stimuli. We conclude that the apparent slow activation of native L-type currents and their lack of contribution to single action potentials reflect the state-dependent nature of the dihydropyridine antagonists used to study them, not the underlying properties of L-type channels.
You Shouldn't Collect My Secrets: Thwarting Sensitive Keystroke Leakage in Mobile IME Apps

IME (input method editor) apps are the primary means of interaction on mobile touch screen devices and thus are usually granted with access to a wealth of private user input. In order to understand the (in)security of mobile IME apps, this paper first performs a systematic study and uncovers that many IME apps may (intentionally or unintentionally) leak users' sensitive data to the outside world (mainly due to the incentives of improving the user's experience). To thwart the threat of sensitive information leakage while retaining the benefits of an improved user experience, this paper then proposes I-BOX, an app-transparent oblivious sandbox that minimizes sensitive input leakage by confining untrusted IME apps to predefined security policies. Several key challenges have to be addressed due to the proprietary and closed-source nature of most IME apps and the fact that an IME app can arbitrarily store and transform user input before sending it out. By designing system-level transactional execution, I-BOX works seamlessly and transparently with IME apps. Specifically, I-BOX first checkpoints an IME app's state before the first keystroke of an input, monitors and analyzes the user's input, and rolls back the state to the checkpoint if it detects the potential danger that sensitive input may be leaked. A proof of concept I-BOX prototype has been built for Android and tested with a set of popular IME apps. Experimental results show that I-BOX is able to thwart the leakage of sensitive input for untrusted IME apps, while incurring very small runtime overhead and little impact on user experience.
Humanoid Navigation Strategy Using Fuzzy Motion Planner in a Uneven Smart Home Environment

This paper presents a fuzzy motion planner for humanoid robots in complex uneven environments. First, we define locomotion primitives for humanoid robots. A high-level planner finds a global path from a global navigation map that is generated based on a combination of 2.5 dimensional maps of the 3D workspace. A mid-level planner creates waypoints that help the robot efficiently cope with various obstacles using only a small set of locomotion primitives that are useful for stable navigation of the robot. A local planner searches for an optimal sequence of locomotion primitives along the global path by using fuzzy motion planning. We verify our approach on a virtual humanoid robot in a simulated environment. Simulation results show a reduction in planning time and the feasibility of the proposed method.
Corporate non-participation in the ASB standard-setting process

The standard-setting process of the UK's Accounting Standards Board (ASB) can be examined from different theoretical frameworks. One considers it a political process where interested parties choose to lobby on the basis of lobbying costs and benefits accrued from successful lobbying. The examination of the motives of various parties to lobby or not is considered important for understanding the process. Another framework assumes a non-pluralistic process, dominated by a few powerful groups to the detriment of the interests of other groups which are effectively excluded from the process. Drawing from the first framework, this study examines the factors which influenced the choice of a sample of UK listed companies not to make a submission on the ASB's discussion paper proposals on deferred tax. A perception that their participation would not make a difference to the outcome of the process and reliance on their external auditors to represent their position were found to be the most important factors for not making a submission. In contrast, no support was found for the suggestion that agreement with the proposals is more likely to prompt a non-response than disagreement with the proposals.
Diversity Leads to Accelerating Growth in Online Social Systems

Research on the growth of online social systems not only is interesting in its own right, but also yields insights for website management and web crawling. Traditional models that describing the growth of online systems can be divided between linear and nonlinear versions. Linear models, including the BA model, assume that the average activity of users in a system is a constant independent of system size. Hence the total activity is a linear function of the system size. On the contrary, nonlinear models suggest that the average activity is affected by the system size and the total activity is a nonlinear function of the system size. In the current study, we obtain supporting evidence for the nonlinear growth assumption from data on Internet users’ file sharing and blogging behavior. We find that there is a power law relationship between the activity F and the system size P, which can be expressed as F ~ P  (> 1). We call this pattern accelerating growth and analytically attribute it to time-variant diversity in individual activities. We also show that a greater diversity leads to a faster growth. Our findings of the relationship between diversity and growth rate is supported by empirical data and numerical simulations.
Higher-Order Rewriting via Conditional First-Order Rewriting in the Open Calculus of Constructions

Although higher-order rewrite systems (HRS) seem to have a first-order flavor, the direct translation into first-order rewrite systems, using e.g. explicit substitutions, is by no means trivial. In this paper, we explore a two-stage approach, by showing how higher-order pattern rewrite systems, and in fact a somewhat more general class, can be expressed by conditional first-order rewriting in the open calculus of constructions (OCC), which itself has been presented and implemented using explicit substitutions. The key feature of OCC that we exploit is that conditions are allowed to contain quantifiers and equations which can be solved using first-order matching. The way we express HRS works in spite of the fact that structural equality of OCC does not subsume α-conversion. Another topic that we touch upon in this paper is the use of higher-order abstract syntax in a classical framework like OCC, because it is often used in connection with higher-order rewriting.
Business Cycle and Monetary Policy Analysis with Market Rigidities and Financial Frictions

We describe a dynamic macroeconomic model that incorporates firm-level borrowing constraints, competitive CES loan production, and rigidities on both setting prices and wages. The external finance premium (interest-rate spread) is countercyclical with technology and financial shocks, and procyclical with consumption spending shocks. The real effects of financial shocks are significantly amplified when either considering greater rigidities for price/wage setting or a low elasticity of substitution in loan production (banking real rigidities). In the monetary policy analysis, a stabilizing Taylor (1983)-style rule performs slightly better when incorporating a positive and small response coefficient to the external finance premium.