Miracle-dz/UniFAR-FTUs huggingface dataset:
Fuzzy shape recognition for robot repositioning

We address the problem of shape recognition in the context of autonomous navigation of mobile robots. We present an association procedure which is able to establish the correspondence between elements of a learned fuzzy internal representation of the environment and currently perceived objects. Using this procedure, a mobile robot is able to periodically decrease the uncertainty affecting its position.
Delay-Optimal Dynamic Mode Selection and Resource Allocation in Device-to-Device Communications—Part II: Practical Algorithm

In Part I of this paper (“Delay-Optimal Dynamic Mode Selection and Resource Allocation in Device-to-Device Communications-Part I: Optimal Policy”), we investigated dynamic mode selection and subchannel allocation for an orthogonal frequency-division multiple access (OFDMA) cellular network with device-to-device (D2D) communications to minimize the average end-to-end delay performance under the dropping probability constraint. We formulated the optimal resource control problem into an infinite-horizon average-reward constrained Markov decision process (CMDP), and the optimal control policy derived in Part I using the brute-force offline value iteration algorithm based on the reduced-state equivalent Bellman equation still faces the well-known curse-of-dimensionality problem, which limits its practical application in realistic scenarios with multiple D2D users and cellular users. In Part II of this paper, we use linear value approximation techniques to further reduce the state space. Moreover, an online stochastic learning algorithm with two timescales is applied to update the value functions and Lagrangian multipliers (LMs) based on the real-time observations of channel state information (CSI) and queue state information (QSI). The combined online stochastic learning solution converges almost surely to a global optimal solution under some realistic conditions. Simulation results show that the proposed approach achieves nearly the same performance as the offline value iteration algorithm and outperforms the conventional CSI-only scheme and throughput-optimal scheme in a stability sense.
Of the largest eigenvalue for modularity-based partitioning

Despite the popularity and broad range of spectral clustering algorithms, there is little work addressing the statistical significance of clustering results. Spectral clustering uses the eigenvalues of matrices, such as the Laplacian graph or the adjacency matrix minus a null model, to partition a network. Even though the distribution of the largest eigenvalue for these matrices is not known, random matrix theory provides analytical formulas for a family of matrices called Gaussian random ensembles. We demonstrate that the Tracy-Widom mapping of the largest eigenvalue of Gaussian random ensembles can be modified to predict the distribution of the largest eigenvalue of matrices used for modularity-based spectral clustering. Using this finding we derive formulas that control the type I error rate on modularity-based partitions.
A 3.1–10.6 GHz ultra wide-band impulse radio transmitter with notch implementation for in-band interferers in 90nm CMOS

One of the serious challenges in Ultra Wide-band (UWB) systems is the in-band interferer system in the middle of the UWB band which affects the system performance severely. In this paper an analog in-band interference avoidance IR-UWB transmitter is presented. The fully integrated transmitter generates a novel UWB pulse with a tunable notch at the frequency of 802.11a interferer. The pulse covers the whole UWB spectrum (3.1-10.6 GHz) which makes it suitable for high resolution high data-rate applications. The transmitter has a bi-phase modulation and has been fabricated in IBM 90nm CMOS.
Studying interactions between prefetching and cache line turnoff

While lots of prior studies focused on performance and energy optimizations for caches, their interactions have received much less attention. This is unfortunate since in general the performance-oriented techniques influence energy behavior of the cache, and the energy-oriented techniques usually increase program execution cycles. The overall energy and performance behavior of caches in embedded systems when multiple techniques co-exist remains an open research problem. This paper studies this interaction and illustrates how performance and energy optimizations affect each other. We also point out several potential optimizations that could be based on this study.
Changes in lysosome shape and distribution correlated with changes in cytoplasmic pH

Lysosomes labeled by uptake of extracellular horseradish peroxidase display remarkable changes in shape and cellular distribution when cytoplasmic pH is experimentally altered. Normally, lysosomes in macrophages and fibroblasts cluster around the cell center. However, when the cytoplasmic pH is lowered to approximately pH 6.5 by applying acetate or by various other means, lysosomes promptly move outward and accumulate in tight clusters at the very edge of the cell, particularly in regions that are actively ruffling before acidification but become quiescent. This movement follows the distribution of microtubules in these cells, and does not occur if microtubules are depolymerized with nocodazole before acidification. Subsequent removal of acetate or the other stimuli to acidification results in prompt resumption of ruffling activity and return of lysosomes into a tight cluster at the cell center. This is correlated with a rebound alkalinization of the cytoplasm. Correspondingly, direct application of weak bases also causes hyperruffling and unusually complete withdrawal of lysosomes to the cell center. Thus, lysosomes appear to be acted upon by microtubule- based motors of both the anterograde (kinesin) type as well as the retrograde (dynein) type, or else they possess bidirectional motors that are reversed by changes in cytoplasmic pH. During the outward movements induced by acidification, lysosomes also appear to be smaller and more predominantly vesicular than normal, while during inward movements they appear to be more confluent and elongated than normal, often becoming even more tubular than in phorbol-treated macrophages (Phaire-Washington, L., S. C. Silverstein, and E. Wang. 1980. J. Cell Biol. 86:641-655). These size and shape changes suggest that cytoplasmic pH also affects the fusion/fission properties of lysosomes. Combined with pH effects on their movement, the net result during recovery from acidification is a stretching of lysosomes into tubular forms along microtubules.
Does globalization matter on fiscal decentralization of OECD

In this paper we re-examine the effects of globalization on fiscal decentralization of OECD by using the overall KOF index of globalization and its main subcomponents - economic, political and social integration. Using different indicators of fiscal decentralization, we find a positive impact of the overall index of globalization on both revenue and expenditure decentralization side, although not robust across different panel data specifications. Focusing on the links between decentralization and different aspects of globalization, we find that both economic and social integration foster fiscal decentralization, whereas political integration checks growth of it.
Reinforcing the Seams: Using Focus Groups To Connect with Specific Employee Groups. AIR 1999 Annual Forum Paper.

This paper reports on the use of focus groups at Oakton Community College (Illinois) to connect with classified staff and to get their feedback on key issues. A total of four single-session focus groups, three with classified staff (employees with varying levels of academic preparation and current responsibilities) and one with supervisors/managers, were conducted. Three main topics were discussed: staff development, morale, and compensation/classification. Concerning staff development, a key staff concern was the need for staff-oriented professional development workshops; supervisors, however, expressed a desire for more opportunities to interact and share common concerns with each other. Concerning morale, staff felt morale was strongly connected to having opportunities to be listened to and valued as employees; supervisors focused on improving orientation programs for staff. Concerning compensation and classification issues, staff wanted more information about the system in use at the college and worried about opportunities for upward mobility. The focus group effort has influenced professional development efforts, and has led to plans to develop a supervisor/manager discussion group and to implement annual workshops on compensation and classification. Letters used to solicit focus group participants and the focus group question protocol are appended. (Contains 11 references.) (DB) ******************************************************************************** Reproductions supplied by EDRS are the best that can be made from the original document. ********************************************************************************
A Shape Representation Based on Polar Vector Fourier Descriptors

Fourier descriptors (FDs) are the widely used shape descriptors. But FDs can only be used to objects with single boundary, and it is inapplicable to objects with several components. In this paper, a region-based method, which is called Polar Vector Fourier Descriptors (PVFDs), is developed to extract invariant features. Firstly, the Cartesian coordinate system is converted into polar coordinate system. Secondly, the original two-dimensional image is reshaped into a vector (which is called Polar Vector (PV)) by linking radial vector end-to-end along the polar angle. Then, PVFDs are derived by applying Fourier transformation to PV. Consequently, the derived PVFDs are invariant to scaling and rotation. Furthermore, it is applicable to objects with several components (such as some Chinese characters etc.). Experimental results show that the proposed method is superior to Hu's moments and complex moments (CMs).
Biologically inspired visual odometry based on the computational model of grid cells for mobile robots

Visual odometry is a core component of many visual navigation systems like visual simultaneous localization and mapping (SLAM). Grid cells have been found as part of the path integration system in the rat's entorhinal cortex, and they provide inputs for place cells in the rat's hippocampus. Together with other cells, they constitute a positioning system in the brain. Some computational models of grid cells based on continuous attractor networks have also been proposed in the computational biology community, and using these models, self-motion information can be integrated to realize dead-reckoning. However, so far few researchers have tried to use these computational models of grid cells directly in robot visual navigation in the robotics community. In this paper, we propose to apply continuous attractor network model of grid cells to integrate the robot's motion information estimated from the vision system, so a biologically inspired visual odometry can be realized. The experimental results show that good dead-reckoning can be achieved for different mobile robots with very different motion velocities using our algorithm. We also implement a full visual SLAM system by simply combining the proposed visual odometry with a quite direct loop closure detection derived from the well-known RatSLAM, and comparable results can be achieved in comparison with RatSLAM.
Application of BMD Approach to Identify Thresholds of Cadmium-Induced Renal Effect among 35 to 55 Year-Old Women in Two Cadmium Polluted Counties in China

Background Cadmium (Cd) is a heavy metal that can cause renal tubular dysfunction in humans. Women are among the high-risk group for Cd health effects. Determining the thresholds of Cd-induced renal effects is important. Thus, in this article, we aimed to identify the benchmark dose (BMD) and its low limit (BMDL) levels as the Cd thresholds for Chinese women. Methods Epidemiologic investigation was performed in county A and county B to obtain data on Cd exposure and its renal effect on respondents. Levels of Cd (UCd), β2-microglobulin (UB2M), and N-acetyl-β-D-glucosaminidase (UNAG) were measured in morning urine samples. The BMD approach was mainly performed. Results Results of the BMD approach were similar whether the method was conducted for the two sets of data (collected in CA and CB, respectively) separately or cooperatively. The BMD/BMDL values of UCd for all subjects were 1.07/0.44 and 2.12/0.53 µg/g cr based on UB2M and UNAG, respectively, given a predetermined BMR of 0.05. Conclusions The presented thresholds of Cd-induced renal effects (i.e., the BMDLs of UCd) are close to the counterpart values reported in Japan, Sweden and Belguim.
Online heterogeneous multiagent learning under limited communication with applications to forest fire management

Many robotic missions require online estimation of the unknown state transition models associated with uncertainty that stems from mission dynamics. The learning problem is usually distributed among agents in multiagent scenarios, either due to the absence of a centralized processing unit or because of the large size of the joint learning problem. This paper addresses the problem of multiagent learning in the likely scenario that agents estimate different models from their measured data, but they can share information by communicating model parameters. Previous approaches either consider homogeneous scenarios or perform model transfer in an open-loop manner, which hinders the convergence rate. We develop a closed-loop multiagent learning algorithm, Collaborative Filtering-Decentralized Incremental Feature Dependency Discovery (CF-Dec-iFDD), which enables agents to learn and share models in heterogeneous scenarios. Each agent learns a linear function approximation of the actual model, and the number of features is increased incrementally to adjust model complexity based on the observed data. The agents obtain feedback from other agents on the model error reduction associated with the communicated features. Although this increases the communication cost of exchanging features, it improves the quality/utility of what is being exchanged, leading to improved convergence rate. The approach is demonstrated in indoor hardware flight tests on a forest fire management scenario for which agents must learn the transition model of the fire spread depending on external factors such as wind and vegetation. It is shown that CF-Dec-iFDD has superior convergence rate compared to the alternative approaches.
Coverage-based Evaluation of Parser Generalizability

We have carried out a series of coverage evaluations of diverse types of parsers using texts from several genres such as newspaper, religious, legal and biomedical texts. We compared the overall coverage of the evaluated parsers and analyzed the differences by text genre. The results indicate that the coverage typically drops several percentage points when parsers are faced with texts on genres other than newspapers.
An Efficient Resource Management System for On-Line Virtual Cluster Provision

As a prevalent paradigm for flexible, scalable and on-demand provisions of computing services, Cloud Computing can be an alternative platform for scientific computing. In this paper, we propose an efficient resource management system for on-line virtual clusters provision, aiming to provide immediately-available virtual clusters for academic users. Particularly, we investigated two crucial problems: efficient VM image management and intelligent resource mapping, either of them has remarkable impact on the performance of the system. VM image management includes image preparation and local image management on physical resources. A resource mapping refers to a mapping from user’s resource constraints to specific physical resources. We explore how to simplify VM image management and reduce image preparation overhead by the multicast file transferring and image caching/reusing. Additionally, the Load-Aware Mapping, a novel resource mapping strategy, is proposed in order to further reduce deploying overhead and make efficient use of resources. The strategy takes account of both image cache and VM load distribution information. System evaluation is conducted through various real stress workloads, and results show that our approaches are effective comparing to other common solutions.
Interim Report of the Meteoroid and Debris Special Investigation Group

The LDEF Meteoroid and Debris Special Investigation Group (hereafter MD (2) Small impact (microimpact) features; (3) Impact cratering and penetration data to derive projectile sizes and masses; (4) Particulate flux estimates in low-Earth orbit; (5) The LDEF Meteoroid and Debris database.
Trust networks for recommender systems

This book describes research performed in the context of trust/distrust propagation and aggregation, and their use in recommender systems. This is a hot research topic with important implications for various application areas. The main innovative contributions of the work are: -new bilattice-based model for trust and distrust, allowing for ignorance and inconsistency -proposals for various propagation and aggregation operators, including the analysis of mathematical properties -Evaluation of these operators on real data, including a discussion on the data sets and their characteristics. -A novel approach for identifying controversial items in a recommender system -An analysis on the utility of including distrust in recommender systems -Various approaches for trust based recommendations (a.o. base on collaborative filtering), an in depth experimental analysis, and proposal for a hybrid approach -Analysis of various user types in recommender systems to optimize bootstrapping of cold start users.
DL-PA and DCL-PC: model checking and satisfiability problem are indeed in PSPACE

We prove that the model checking and the satisfiability problem of both Dynamic Logic of Propositional Assignments DL-PA and Coalition Logic of Propositional Control and Delegation DCL-PC are in PSPACE. We explain why the proof of EXPTIME-hardness of the model checking problem of DL-PA presented in (Balbiani, Herzig, Troquard, 2013) is false. We also explain why the proof of membership in PSPACE of the model checking problem of DCL-PC given in (van der Hoek, Walther, Wooldridge, 2010) is wrong.
High-Performance Unsupervised Relation Extraction from Large Corpora

We present URIES - an unsupervised relation identification and extraction system. The system automatically identifies interesting binary relations between entities in the input corpus, and then proceeds to extract a large number of instances of these relations. The system discovers relations by clustering frequently co- occuring pairs of entities, based on the contexts in which they appear. Its complex pattern-based representation of the contexts allows the clustering step to achieve very high precision, sufficient for the clusters to perform as sets of seeds for bootstrapping a high-recall relation extraction process. In a series of experiments we demonstrate the successful performance of URIES and compare it to the two existing systems - a weakly supervised high-recall Web relation extraction system called SRES, and an unsupervised relation identification system that uses a simpler bag-ofwords representation of contexts. The experiments show that URIES performs comparably to SRES, but without any supervision, and that such performance is due to the power of its complex contexts representation and to its novel candidate selection method.
On Approximating Maximum Independent Set of Rectangles

We study the Maximum Independent Set of Rectangles (MISR) problem: given a set of n axis-parallel rectangles, find a largest-cardinality subset of the rectangles, such that no two of them overlap. MISR is a basic geometric optimization problem with many applications, that has been studied extensively. Until recently, the best approximation algorithm for it achieved an O(log log n)-approximation factor. In a recent breakthrough, Adamaszek and Wiese provided a quasi-polynomial time approximation scheme: a (1-ε)-approximation algorithm with running time nO(poly(log n)/ε). Despite this result, obtaining a PTAS or even a polynomial-time constant-factor approximation remains a challenging open problem. In this paper we make progress towards this goal by providing an algorithm for MISR that achieves a (1 - ε)-approximation in time nO(poly(log logn/ε)). We introduce several new technical ideas, that we hope will lead to further progress on this and related problems.
Objective and subjective socioeconomic status and susceptibility to the common cold.

OBJECTIVE We ask whether subjective socioeconomic status (SES) predicts who develops a common cold when exposed to a cold virus. DESIGN 193 healthy men and women ages 21-55 years were assessed for subjective (perceived rank) and objective SES, cognitive, affective and social dispositions, and health practices. Subsequently, they were exposed by nasal drops to a rhinovirus or influenza virus and monitored in quarantine for objective signs of illness and self-reported symptoms. MAIN OUTCOME MEASURES Infection, signs and symptoms of the common cold, and clinical illness (infection and significant objective signs of illness). RESULTS Increased subjective SES was associated with decreased risk for developing a cold for both viruses. This association was independent of objective SES and of cognitive, affective and social disposition that might provide alternative spurious (third factor) explanations for the association. Poorer sleep among those with lesser subjective SES may partly mediate the association between subjective SES and colds. CONCLUSIONS Increased Subjective SES is associated with less susceptibility to upper respiratory infection, and this association is independent of objective SES, suggesting the importance of perceived relative rank to health.
A Virtual Retina for Studying Population Coding

At every level of the visual system – from retina to cortex – information is encoded in the activity of large populations of cells. The populations are not uniform, but contain many different types of cells, each with its own sensitivities to visual stimuli. Understanding the roles of the cell types and how they work together to form collective representations has been a long-standing goal. This goal, though, has been difficult to advance, and, to a large extent, the reason is data limitation. Large numbers of stimulus/response relationships need to be explored, and obtaining enough data to examine even a fraction of them requires a great deal of experiments and animals. Here we describe a tool for addressing this, specifically, at the level of the retina. The tool is a data-driven model of retinal input/output relationships that is effective on a broad range of stimuli – essentially, a virtual retina. The results show that it is highly reliable: (1) the model cells carry the same amount of information as their real cell counterparts, (2) the quality of the information is the same – that is, the posterior stimulus distributions produced by the model cells closely match those of their real cell counterparts, and (3) the model cells are able to make very reliable predictions about the functions of the different retinal output cell types, as measured using Bayesian decoding (electrophysiology) and optomotor performance (behavior). In sum, we present a new tool for studying population coding and test it experimentally. It provides a way to rapidly probe the actions of different cell classes and develop testable predictions. The overall aim is to build constrained theories about population coding and keep the number of experiments and animals to a minimum.