Miracle-dz/UniFAR-FTUs huggingface dataset:
Social feature-based multi-path routing in delay tolerant networks

Most routing protocols for delay tolerant networks resort to the sufficient state information, including trajectory and contact information, to ensure routing efficiency. However, state information tends to be dynamic and hard to obtain without a global and/or long-term collection process. In this paper, we use the internal social features of each node in the network to perform the routing process. This approach is motivated from several social contact networks, such as the Infocom 2006 trace, where people contact each other more frequently if they have more social features in common. Our approach includes two unique processes: social feature extraction and multi-path routing. In social feature extraction, we use entropy to extract the m most informative social features to create a feature space (F-space): (F1, F2, ., Fm), where Fi corresponds to a feature. The routing method then becomes a hypercube-based feature matching process where the routing process is a step-by-step feature difference resolving process. We offer two special multi-path routing schemes: node-disjoint-based routing and delegation-based routing. Extensive simulations on both real and synthetic traces are conducted in comparison with several existing approaches, including spray-and-wait routing and spray-and-focus routing.
Mesenteric Resistance Arteries in Type 2 Diabetic db/db Mice Undergo Outward Remodeling

Objective Resistance vessel remodeling is controlled by myriad of hemodynamic and neurohormonal factors. This study characterized structural and molecular remodeling in mesenteric resistance arteries (MRAs) in diabetic (db/db) and control (Db/db) mice. Methods Structural properties were assessed in isolated MRAs from 12 and 16 wk-old db/db and Db/db mice by pressure myography. Matrix regulatory proteins were measured by Western blot analysis. Mean arterial pressure and superior mesenteric blood flow were measured in 12 wk-old mice by telemetry and a Doppler flow nanoprobe, respectively. Results Blood pressure was similar between groups. Lumen diameter and medial cross-sectional area were significantly increased in 16 wk-old db/db MRA compared to control, indicating outward hypertrophic remodeling. Moreover, wall stress and cross-sectional compliance were significantly larger in diabetic arteries. These remodeling indices were associated with increased expression of matrix regulatory proteins matrix metalloproteinase (MMP)-9, MMP-12, tissue inhibitors of matrix metalloproteinase (TIMP)-1, TIMP-2, and plasminogen activator inhibitor-1 (PAI-1) in db/db arteries. Finally, superior mesenteric artery blood flow was increased by 46% in 12 wk-old db/db mice, a finding that preceded mesenteric resistance artery remodeling. Conclusions These data suggest that flow-induced hemodynamic changes may supersede the local neurohormonal and metabolic milieu to culminate in hypertrophic outward remodeling of type 2 DM mesenteric resistance arteries.
Nonlinear Predistortion with Reduced Peak-to-Average Power Ratio

This paper presents the extension of vector precoding, a generalization of the nonlinear TomlinsonHarashima precoding, with a PAPR (peak-to-average power ratio) reduction technique for the downlink of OFDM systems. The proposed algorithm exploits alternative transmit sequences arising from vector precoding to reduce the peak power in the time-domain baseband transmit signal. The operation is completely transparent to the receivers and therefore requires neither transmission of side information nor additional processing at the receiver side.
ADAPTIVE FUZZY SYNERGETIC PSS DESIGN TO DAMP POWER SYSTEM OSCILLATIONS

This paper presents a novel indirect adaptive Power System Stabilizer (PSS) via a developed synergetic control methodology and fuzzy systems. Fuzzy system is utilized in an adaptive scheme to estimate the system using a nonlinear model. The synergetic control guarantees robustness of the controller and makes the controller easy to implement because of using a chatter free continuous control law. Additionally, the parameters of the controller are optimized by Imperialist Competitive Algorithm (ICA). The effectiveness of the proposed scheme is confirmed on a single machine power system while the stability is guaranteed through Lyapunov synthesis.
Scene Text Segmentation with Multi-level Maximally Stable Extremal Regions

The segmentation of scene text from the image background has shown great importance in scene text recognition. In this paper, we propose a multi-level MSER technology that identifies the best-quality text candidates from a set of stable regions that are extracted from different color channel images. In order to identify the best-quality text candidates, a segmentation score is defined which exploits four measures to evaluate the text probability of each stable region including: 1) Stroke width that measures the small stroke width variation of the text, 2) Boundary curvature that measures the smoothness of the stable region boundary, 3) Character confidence that measures the likelihood of a stable region being text based on a pre-trained support vector classifier, 4) Color constancy that measures the global color consistency of each selected text candidate. Finally, the MSERs with the best segmentation score from each channel are combined to form the final segmentation. The proposed method is evaluated on the ICDAR2003 and SVT datasets and experiments show that it outperforms both popular document image binarization methods and state of the art scene text segmentation methods.
Achievable schemes and limits for local recovery on a graph

Recently, a graph-theoretic model for a single-failure-recoverable distributed storage system was proposed. Unlike the usual local recovery model of codes for distributed storage, this model accounts for the fact that each server or storage node in a network is connectible to only some, and not all other, nodes. Here we provide bounds and constructive schemes for data storage in such networks. We also impose an additional requirement on the codes for such model - a minimum distance guarantee. The model is further generalized for multiple node failures and cooperative repairs.
On the properly political (disposition for the) Anthropocene

The environmental crises referenced by the term Anthropocene incite responses that reflect different understandings about the right way to live on Earth. This, one would expect, should generate a proliferation of disagreements and an expansion of politics. Yet, so-called post-political authors warn that, instead, the way in which the Anthropocene has been brought to the public eye implies an emptying out of politics and a disavowal of the inherently conflictive pursuit of different visions about the right way to live on Earth. To counter this, they propose that the problematic of the Anthropocene needs to be displaced onto the terrain of the “properly political. ” In this paper I probe what the “properly political” might mean in the context of the Anthropocene.
Reduction of dimensionality for perceptual clustering

Multidimensionality is one of the problems to be solved for a robust methodology in order to be capable of resolving simple and realistic problems. This work establishes a complete methodology based on self-organized maps (SOM) and the expectation-maximization (EM) algorithm that finds an abstract probability function, which is a mix of local experts. An application of this methodology is presented as a case study, where the problem is robot navigation in noisy environments. Readings from seven robot sonars were taken as input for the system, mapped into a two dimension space and grouped into abstract observations, in order to make recognition of navigation space environment dependant and accurate. The goal is to build the capability of predicting observations and of recognizing abstractions that were defined over the data itself.
Motion planning of a balancing robot with threefold sub-tasks: An endogenous configuration space approach

The paper presents a task-priority motion planning algorithm for a balancing robot, derived from the endogenous configuration space approach. The motion planning problem is composed of three sub-tasks. Firstly, the robot has to reach a desirable point in task space (proper motion planning). Secondly, the upward position of the robot torso should be maintained during the motion. Thirdly, the motion should save the control energy. Performance of our algorithm is presented in simulations.
Classifying Seismic Signals by Integrating Ensembles of Neural Networks

| This paper proposes a classiication scheme based on integration of multiple Ensembles of ANNs. It is demonstrated on a classiication problem, in which seismic signals of Natural Earthquakes must be distinguished from seismic signals of Artiicial Explosions. A Redundant Classiication Environment consists of several Ensembles of Neural Networks is created and trained on Bootstrap Sample Sets, using various data representations and architectures. The ANNs within the Ensembles are aggregated (as in Bagging) while the Ensembles are integrated non-linearly, in a signal adaptive manner, using a posterior con-dence measure based on the agreement (variance) within the Ensembles. The proposed Integrated Classiication Machine achieved 92.1% correct classiications on the seismic test data. Cross Validation evaluations and comparisons indicate that such integration of a collection of ANN's Ensembles is a robust way for handling high dimensional problems with a complex non-stationary signal space as in the current Seismic Classiication problem.
Case Study : Light Harvesting Complex II

Cover Figure: Purple bacteria live at the bottom of ponds or lakes, and some purple bacteria can harvest light and produce energy through photosynthesis. Their photosynthetic apparatus are found inside the bacterial membrane, consisting of several proteins. One of these proteins is the ring-like Light Harvesting Complex 2, the protein investigated in this case study. All files can be found in the lh2-casestudy-files folder.
Image Reconstruction : Off-Resonance Effects and Correction

1. INTRODUCTION When put into the magnetic field, a tiny but detectable fraction of the protons present in water in the body will align with this strong, steady magnetic field. During imaging, the tissue of interest is occasionally subjected to a brief electromagnetic radio-frequency (RF) pulse, essentially tilting the aligned protons off the axis of the main magnetic field. The protons then precess around the main field axis at a known frequency proportional to the main magnetic field. That field can be manipulated to identify the location of certain types of activity. The rate of precession can be used, for example, to encode the spatial position of the protons for imaging, by creating a gradient in the magnetic field along one direction [1]. The protons then precess at different frequencies depending on their location, as the magnetic field that they experience is due to both the main magnetic field and the applied imaging gradient. Signal intensity and spatial localization in MRI rely on a uniform magnetic field existing throughout the sample of interest. Much effort is devoted to properly designing and shimming the main magnetic field to achieve uniform intensity.
Nearest Neighbor Monitoring of Spatial Queries in Wireless Environments

In a Wireless data broadcast is a promising technique for information dissemination that leverages the computational capabilities of the mobile devices in order to enhance the scalability of the system. Under this environment, the data are continuously broadcast by the server, interleaved with some indexing information for query processing. Clients may then tune in the broadcast channel and process their queries locally without contacting the server. We propose a novel technique, called NNH (“Nearest Neighbor Histograms”), which uses specific histogram structures to improve the performance of NN search algorithms. A primary feature of our proposal is that such histogram structures can co-exist in conjunction with a plethora of NN search algorithms without the need to substantially modify them. The main idea behind our proposal is to choose a small number of pivot objects in the space, and pre-calculate the distances to their nearest neighbors.
Measuring and processing the waveform of laser pulses

The analysis of laser data to extract surface features is of great interest. Beside the range values, various information about features of the illuminated surface can be gained. In this paper, the surface features range, roughness, and reflectance are determined using different algorithms for extracting pulse properties. The accuracy of the received results is investigated by the comparison of two measurements of the same scene at different points in time to evaluate the robustness of feature extraction. The reliability and quality of the data and the used algorithms are compared and discussed.
Statistical Problem Classes and Their Links to Information Theory

We begin by recalling the tripartite division of statistical problems into three classes, M-closed, M-complete, and M-open and then reviewing the key ideas of introductory Shannon theory. Focusing on the related but distinct goals of model selection and prediction, we argue that different techniques for these two goals are appropriate for the three different problem classes. For M-closed problems we give relative entropy justification that the Bayes information criterion (BIC) is appropriate for model selection and that the Bayes model average is information optimal for prediction. For M-complete problems, we discuss the principle of maximum entropy and a way to use the rate distortion function to bypass the inaccessibility of the true distribution. For prediction in the M-complete class, there is little work done on information based model averaging so we discuss the Akaike information criterion (AIC) and its properties and variants. For the M-open class, we argue that essentially only predictive criteria are suitable. Thus, as an analog to model selection, we present the key ideas of prediction along a string under a codelength criterion and propose a general form of this criterion. Since little work appears to have been done on information methods for general prediction in the M-open class of problems, we mention the field of information theoretic learning in certain general function spaces.
Curriculum Development in Non-Formal Education.

The two parts of this book consider two main facets of nonformal curriculum development: theory and practice. Part I on nonformal curriculum theory has four chapters. Chapter 1 addresses the origins, meaning, purpose, and scope of nonformal education. Chapter 2 examines three major themes in discussions on nonformal education: nonformal education as an instrument of positive change, as a social control mechanism, and the context. Chapter 3 explores the rationale. Chapter 4 examines the rational planning model and three models that have relevance for curriculum development in nonformal education: psychosocial, liberal education, and Bhola's core-interface. The five chapters in Part II on nonformal curriculum practice consider the case of the People's Educational Association of Sierra Leone in integrating population education into adult literacy. Chapter 5 describes nonformal education in the Sierra Leone context where it is an educational response to the problems of out-of-school youth and illiterate adults and an alternative development strategy. Chapter 6 sets forth the rationale for population education and literacy. Chapter 7 describes the process of curriculum integration. Chapter 8 is a case analysis of the population education project. Chapter 9 highlights these conclusions: contingent nature of curriculum development in nonformal education; importance of learner participation; and need for staff development. Appendixes contain a 359-item bibliography and index. (YLB) *********************************************************************** Reproductions supplied by EDRS are the best that can be made * * from the original document. ***********************************************************************
The Factors Influencing Relapse in Patients Presenting to the Emergency Department with COPD Exacerbation

SUMMARY Objectives Chronic Obstructive Pulmonary Disease (COPD) is associated with high mortality and morbidity and is projected to be the third most common cause of death worldwide by 2020. For a variety of reasons, there is a drive to manage a greater number of individuals as outpatients. Preventing readmissions can reduce associated morbidity and subsequent healthcare costs. Methods The aim of the present study was to determine the factors affecting the relapse of COPD exacerbated patients in the emergency department (ED). This study combines data from two prospective cohort studies. Patients included in the study were above 18 years of age, had a previous diagnosis of COPD, and presented to the ED for the treatment of acute exacerbation. All the information relevant to the study was collected during the patient's visit to the ED. Relapse was defined as an unscheduled visit to an ED or primary physician within 2 weeks of initial ED visit for worsening COPD symptoms. Telephone follow-up was done on all patients at the end of 2 weeks. Results The cohort consists of 196 patients. Relapse rate in this study was 27%. Mean respiratory rate, exacerbations in previous year, home nebulizator therapy, home oxygen therapy, admission to intensive care or hospital ward due to COPD exacerbation, previous intubation and abnormal chest x-ray were associated with increased re-visit in univariate analysis. However, after multivariate analysis, exacerbations in previous year (OR: 1.08, 95%CI: 1.01–1.15) and abnormal chest X-ray (OR: 2.5, 95%CI: 1.10–6.11) were still significant. Conclusions In conclusion, the number of ED visits previous year and abnormal chest x-ray can predict the revisit of a COPD exacerbated patient within 14 days of an ED visit.
Owner-Occupied Housing and the Composition of the Household Portfolio Over the Life-Cycle

This paper studies the impact of the portfolio constraint imposed by the consumption demand for housing (the 'housing constraint') on the household's optimal holdings of financial assets. Since the ratio of housing to net worth declines as the household accumulates wealth, the housing constraint induces a life-cycle pattern in the portfolio shares of stocks and bonds. For reasonable degrees of risk aversion, the changes in portfolio composition over the life-cycle can be dramatic. For example, for a coefficient of relative risk aversion of 3, the ratio of stocks to net worth in the optimal portfolio is . 09 for the youngest households (ages 18-30) and . 60 for the oldest (age 70 and over). Using data from the PSID on home values to construct household level panel data on the real after-tax return to owner-occupied housing, as well as data on the returns to financial assets, the paper estimates the vector of expected returns and the covariance matrix for the set of assets consisting of housing, mortgages, stocks, Treasury bonds, and T-bills. Numerical methods are used to calculate the mean-variance efficient frontier, conditional on different values of the housing constraint, and the optimal portfolios associated with different levels of relative risk aversion.
A printed log periodic dipole antenna with 3/2 curve fractal elements

A printed log periodic dipole antenna (LPDA) with 3/2 curve fractal elements for size reduction and wider operating frequency bands is presented. The antenna dimension is about 123 × 181.71 mm2 reducing approximately 23.81% compared with the conventional LPDA. The radiation patterns are directional at all of operating frequencies and the average peak gain of the antenna is about 4.2 dBi. Additionally, the antenna has a wider impedance bandwidth about 135.45% supporting the operating frequency ranges are 800 MHz - 2600 MHz. They cover the standard of WCDMA 850, GSM 900, LTE 1800/2600, PCS 1900, UMTS 2100, and WLAN IEEE802.11b/g consequently.
International Postdocs: Educational Migration and Academic Production in a Global Market

This dissertation is a qualitative investigation into international postdoctoral employment in life science and engineering fields at universities in the United States and United Kingdom. Data were gathered through 49 in-depth, semi-structured interviews with international postdocs, faculty members who have supervised international postdocs from abroad at two universities in the US and two universities in the UK. The number of postdoctoral appointments has increased dramatically over the past decade, as has the share of these appointees who come from aboard. Yet few studies have investigated what is underlying this growing trend. By examining interactions between structure and agency at local, global and national levels, this study explored the roles that international postdocs play in academic production and the process by which they become mobile. Theory on globalization, higher education policy and models of academic production guide this study. Findings show that international postdocs are becoming scientific employees, rather than trainees, who are incorporated into capitalist modes of academic production as low-cost, high-yield scientific workers. Universities and individual faculty members seek international postdocs because of their contributions to research production; however, few postdocs have the opportunity to move into tenure-tracked faculty jobs. For international postdocs, becoming mobile is an individual process that is often constructed by individuals who negotiate home country academic policies in a global academic market. Mobility is a multi-stage process that begins with the potential to become mobile and is realized by actual mobility, which occurs through a transnational space produced by international journals that define global science.
Structured H∞ framework for impedance minimization on robot arm with compliant actuation

In most cases where robots have a physical interaction with humans, it is needed to minimize the feeling of the robot opposition to the human movement during the free movement phase. This is usually done by minimizing the robot interaction port apparent impedance. This task is particularly challenging in presence of a flexibility between the actuator and the considered interaction port. In this paper, we propose a new approach that minimizes the robot arm apparent impedance to the absolutely minimal achievable impedance ensuring passivity on the interaction port. Impedance minimization is formulated as a particular standard two-block H∞ problem. Passivity constraint is considered using the positive real lemma applied to the admittance of the interaction port. The resulting problem is a structured H∞ problem for which solvers based on non-smooth optimization have been recently developed. The proposed methodology was evaluated experimentally on a testbed and allowed to obtain very satisfying results.