Miracle-dz/UniFAR-FTUs huggingface dataset:
Experiments on the vibration suppression of a piezoelectric beam using a self-sensing mechanism

This paper deals with a problem of vibration suppression of a piezoelectric beam using a self-sensing algorithm. Two methods, which are PPF(positive position feedback) and SRF(strain rate feedback), are considered to suppress a residual vibration of a piezoelectric beam developed during the step positioning of a beam end point. It turns out that the vibration suppression based on using PPF algorithm is better than using SRF. Two self-sensing algorithms are treated here, which are a strain and its rate estimator of a beam movement, in order to provide feedback information for the closed loop vibration suppression control. The efficacy of the proposed idea is evaluated through experiments.
Enhancing Industrial Video Surveillance over Wireless Mesh Networks

Industry 4.0 brings forward higher requirements on the monitoring of industrial production. Video surveillance based on Wireless Mesh Networks (WMNs) has demonstrated its effectiveness in a number of applications. Different from some typical applications of WMN that solve the "last mile" Internet access problem, WMN-based video surveillance for industrial monitoring is very likely to work in extreme circumstances or requiring high performance. Thus, the guarantee of video quality is the key for the success of industrial video surveillance. Through extensive experimental research, we find that the state of the art mapping and queuing algorithms are approaching complication and the room for improvement is decreasing. The possible solution for performance breakthrough lies in exploiting the potentials of data granularity for mapping. In this work, we propose IMesh, a video transmission solution based on WMN, which takes frame type, frame location, data packets and other factors into consideration and quantifies their impacts on video quality. The proposed approach is particularly suitable for video surveillance in industrial production under aggressive conditions. To the best of our knowledge, IMesh is the first one that differentiates, prioritizes, and schedules video data in the packet level, which is the finest granularity one can achieve while keep the MAC layer protocol unchanged. Experiment results show that the proposed solution outperforms previous works both in terms of video quality and packet delay.
Content-Aware Rate Control for Video Transmission with Buffer Constraints in Multipath Networks

Being an integral part of the network traffic, nowadays it's vital to design robust mechanisms to provide QoS for multimedia applications. The main goal of this paper is to provide an efficient solution to support content-aware video transmission mechanism with buffer underflow avoidance at the receiver in multipath networks. Towards this, we introduce a content-aware time-varying utility function, where the quality impacts of video content is incorporated into its definition. Using the proposed utility function, we formulate a multipath Dynamic Network Utility Maximization (DNUM) problem for the rate allocation of video streams, where it takes into account QoS demand of video streams in terms of buffer underflow avoidance. Finally, using primal-dual method, we propose a distributed solution that optimally allocates the shared bandwidth to video streams. The numerical examples demonstrate the efficacy of the proposed content- aware rate allocation algorithm for video sources in both single and multiple path network models.
OHSU Summarization and Entity Linking Systems

We present two distinct text analysis systems. We first present two supervised sentence ranking approaches for use in extractive update summarization. For the first, we use the same general machine learning approach described in Fisher and Roark (2008) for update summarization. In the second, we use a similar machine learning approach, but include sub-sentential units produced by our discourse segmenter, see Fisher and Roark (2007b), as possible units for inclusion in a summary. Interestingly, we find that one approach performs significantly better in the production of the base summary, while the other approach performs significantly better in the update summary. We then present a large-corpus entity linking system. This system expands queries using internal links within Wikipedia and link entities with minimum-spanning-tree clustering. We present and evaluate empirical results on the TAC 2009 knowledge-base-population data, and demonstrate competitive results with a simple system.
Image registration using Hough transform and Phase correlation in Wavelet domain

This paper presents a method for registering images using phase correlation technique in fourier domain, hough transform and multi-resolution wavelet. To register images, source and input images are transformed to wavelet domain. An angular transition can be obtained by applying hough transform technique followed by phase correlation. Then we apply phase correlation technique to find x-axis and y-axis transition. We apply wavelet transform to reduce processing time and also use its coefficients as edge information instead of canny detector. With multi-resolution property of wavelet transform, registration time can be greatly reduced. After we get all transition parameters, we transform the input images according to these parameters. Then, we compose and blend all images into a new large image with details of all source images. From our experiment, we can find the accurate transition both x-y translation and angular transition with less error.
Estimateurs par Ondelettes : Adaptation a laR egularit

A wavelet thresholding algorithm is used to recover a function of unknown smoothness from noisy data. It is known that it can be tuned to be minimax in order over a wide range of Besov-type smoothness constraints and L p-losses. We provide a method to estimate an adaptive threshold parameter for each resolution level. It is shown that the proposed algorithm is adaptive in order, i.e. it attains the rate of convergence which is minimax up to a constant over Besov regularity classes and L p-error measures, 1 p 1. The algorithm is computationally straightforward: the whole eeort to compute the threshold is order N log N for the sample size N. Estimateurs par Ondelettes: Adaptation a la R egularit e Inconnue R esum e : On utilise un estimateur par ondelettes dans le cas o u la r egularit e de la fonction a estimer est inconnue. On propose un algorithme de seuillage adaptatif, dans lequel le para-m etre de seuillage est estim e a chaque niveau de r esolution. On d emontre que cet algorithme atteind une vitesse de convergence minimax a une constante pr es pour les risques L p sur les classes de Besov.
A geometric theory of swimming: Purcell's swimmer and its symmetrized cousin

We develop a qualitative geometric approach to swimming at low Reynolds numbers which avoids solving differential equations and uses instead landscape figures describing the swimming and dissipation. This approach gives complete information about swimmers that swim on a line without rotations and gives the main qualitative features of general swimmers that can also rotate. We illustrate this approach for a symmetric version of Purcell's swimmer, which we solve by elementary analytical means within slender body theory. We then apply the theory to derive the basic qualitative properties of Purcell's swimmer.
Interdependent Construal of Self and the Endorsement of Conflict Resolution Strategies in Interpersonal, Intergroup, and International Disputes

Intergroup relations are more competitive and discordant than relations between interacting individuals. Social identity theory suggests that this discontinuity should be greatest among individuals who identify strongly with their in-group. To test this prediction, students from countries with collectivistic and individualistic cultures completed a measure of self-construal. They were then asked to identify how they would respond to a conflict, either with another individual, between their group and another group or between their country and another country. Participants responded more negatively to intergroup and international conflicts than to interpersonal conflicts. Self-construal, however, moderated this effect. Controlling for country of origin, students who were high in interdependence endorsed threat more and acceptance of the others’ demands less in an international conflict versus an interpersonal conflict. Those low in interdependence differed less in their endorsement of conflict resolution strategies in an international versus an interpersonal conflict.
Computing Disparity on Demand: Disparity based Classification using Error-Tolerant Decision Tree Ensembles

Most range-based recognition systems require the calculation of a full disparity map at adequate resolutions prior to the recognition step. There also exist range-based systems that only require the computation of a sparse disparity map. We introduce a 3D shape classification method in which the disparity calculation is guided by the needs of the classification process. The method uses decision trees for shape classification and calculates the disparity only at certain locations in the image, as required by the tree structure. The calculation is very efficient as only the minimum number of disparity values are calculated. To render the classification robust, we use an ensemble of trees. The proposed ensemble method is different from the currently known ensemble methods and makes the classification system more robust to errors in the disparity calculation. The method was applied to a real world problem and good classification results were obtained.
Data Visualizations on small and very small screens

We can now access to information almost everywhere, at any time, using mobile phone or PDA with connection to the Web. A good way to resume data is visualization but the size of the screen and bad environment generate huge constraints. We first present some general recommandations for small screens. Then we study the case of time series visualization for more particularly of stock values and describe two solutions fot PDA and two solutions for mobile.
Evaluating Recognition-Based Motion Capture on HumanEva II Test Data

The advent of the HumanEva standardized motion capture data sets has enabled quantitative evaluation of motion capture algorithms on comparable terms. This paper measures the performance of an existing monocular recognition-based pose recovery algorithm on select HumanEva data, including all the HumanEva II clips. The method uses a physically-motivated Markov process to connect adajacent frames and achieve a 3D relative mean error of 8.9 cm per joint, better than recently reported results. It further investigates factors contributing to the error, and finds that research into better pose retrieval methods offers promise for improvement of this technique and those related to it. Finally, it investigates the effects of local search optimization with the same recognition-based algorithm and finds no significant deterioration in the results, indicating that processing speed can be largely independent of the size of the recognition library for this approach.
Dewey and the American movement to homeschooling

ABSTRACT The last 10 years has seen a dramatic increase in the number of parents in the United States choosing to homeschool their children instead of sending them to public school. One report had the number increasing by 61.8% from 2003 to 2012, with the total number of homeschooled children reaching nearly 2 million (Snyder, T. D., and S. A. Dillow. 2015. Digest of Education Statistics 2013 (NCES 2015-011). Washington, DC: National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education). With more students withdrawing from public education to a more insulated environment (often due to religious reasons), there are concerns about the long-term ramifications this trend may cause. This paper addresses the degree to which a religious homeschooled education might be problematic within John Dewey’s conception of education as laid out in Democracy and Education. For Dewey ‘Common subject matter accustoms all to a unity of outlook upon a broader horizon’ (Dewey, John. 1985. Democracy and Education, Collected Works. Middle Works Vol 9, 26. Carbondale: Southern Illinois University Press). I argue that persons raised in a virtual vacuum in which education is rooted within a particular faith may be less capable of serving as vibrant members of a democratic-based society.
MPL-Boosted Integrable Features Pool for pedestrian detection

This paper presents a fast and accurate pedestrian detection method. To find a balance between speed and accuracy, we propose a Multi-Pose Learning Boosted Integrable Features Pool (MPL-Boosted IFP) approach. Our method achieves high recall-rate while taking the speed-advantage of cascade-of-rejectors approach. We build different types of feature sets, in which features are extremely fast to compute by using integral image. These features are used for building a large number of candidate weak classifiers by using linear SVM. Finally, MPL-Boost method selects the best weak classifiers suited for detection and construct the rejector-based cascade detector. The experiment results show our method achieve better detection precision than HOG and HOG-LBP classifier, meanwhile, speed up these methods near 30 times.
Goat Farming Systems in the Southern Province of Sri Lanka: Feeding and Management Strategies

A survey (n=276) was carried out to gather information on goat farming systems in three districts in the Southern province of Sri Lanka. The objective was to identify the prospects and constrains to improve the economic productivity of the herds. Goats were ranked highest in population and second in terms of importance to the house hold. Buddhists were dominated in goat rearing while selling of live goats for meat production was popular in all three districts. Kid mortality (60-70% out of total deaths) became a serious threat which was mainly due lack of nourishment for kids during early growth, susceptibility to contagious diseases etc. There was an increased risk of an epidemic outbreak in all districts due to their generally low health status. Employing bio-diversity-based concepts in feeding was more prominent among rural farmers but acute feed shortage during dry spells was a major constraint in all districts. Despite the least attention paid, goat production has become a major livelihood activity in surveyed areas. In respect to goat production, breeding improvement, introduce more strategic feeding during dry season and health care should be improved and proper marketing facilities should be organized. Recommendations to overcome this situation would be to educate farmers on scientific goat management practices.
Prion Protein Repeat Expansion Results in Increased Aggregation and Reveals Phenotypic Variability

ABSTRACT Mammalian prion diseases are fatal neurodegenerative disorders dependent on the prion protein PrP. Expansion of the oligopeptide repeats (ORE) found in PrP is associated with inherited prion diseases. Patients with ORE frequently harbor PrP aggregates, but other factors may contribute to pathology, as they often present with unexplained phenotypic variability. We created chimeric yeast-mammalian prion proteins to examine the influence of the PrP ORE on prion properties in yeast. Remarkably, all chimeric proteins maintained prion characteristics. The largest repeat expansion chimera displayed a higher propensity to maintain a self-propagating aggregated state. Strikingly, the repeat expansion conferred increased conformational flexibility, as observed by enhanced phenotypic variation. Furthermore, the repeat expansion chimera displayed an increased rate of prion conversion, but only in the presence of another aggregate, the [RNQ+] prion. We suggest that the PrP ORE increases the conformational flexibility of the prion protein, thereby enhancing the formation of multiple distinct aggregate structures and allowing more frequent prion conversion. Both of these characteristics may contribute to the phenotypic variability associated with PrP repeat expansion diseases.
Writing together for academic publication as a youth-adult PAR team: moving from distance and distaste towards transformative engagement

Abstract While participatory action research’s (PAR) democratic and social justice principles promote team member involvement across the research, collaborative team writing for publication is not standard practice. Peer-reviewed publications are predominately written by academic team member(s), and may include varied but often limited, co-authorship from youth, teachers and/or community team members. Drawing from narrative approaches, this paper narrates a youth-adult PAR team’s movement from a sense of distance and distaste towards academic writing to experiencing writing for publication as a process of transformative team engagement. In doing so, this account offers a story of possibility and agency for teams considering this facet of democratic youth-adult PAR team work.
'All of a Sudden, It's Becoming Toronto': Community Identity and Belonging in the Beaches' Anti Condominium Activism

FOREWORD ACKNOWLEDGEMENTS INTRODUCTION | A VILLAGE WITHIN THE CITY 2 From Cottage Country to NIMBY Fortress 7 Condominium Boom in Toronto 8 The Application and The Appeal 10 Methods and Methodology CHAPTER ONE | THEORETICAL FOUNDATIONS 21 A Neighbourhood in Danger: Strangers or Neighbours? 23 Affect, Nostalgia, and the Fear of Change 26 The Limits of NIMBY Rhetoric 32 Small-Town Desires as Anti-Urbanism 36 Settler Colonial Imaginaries CHAPTER TWO | RESIDENTS’ PERSPECTIVES 45 ‘I'll Stack My Beachness Up Against Anyone's’ 50 ‘This is a Stable Place, My Neighbourhood is Not Going to Change’ 52 ‘All of a Sudden, It’s Becoming Toronto’ 59 Alien Structures 61 ‘As Much State of Mind as Geography’ CONCLUSION | AFFECTIVE PLANNING 64 Considering the Affective in Planning EPILOGUE APPENDICES REFERENCES
Cooperative Spectrum Sensing for Cognitive Radios Using Kriged Kalman Filtering

A cooperative cognitive radio (CR) sensing problem is considered, where a number of CRs collaboratively detect the presence of primary users (PUs) by exploiting the novel notion of channel gain (CG) maps. The CG maps capture the propagation medium per frequency from any point in space and time to each CR user. They are updated in real-time using Kriged Kalman filtering (KKF), a tool with well-appreciated merits in geostatistics. In addition, the CG maps enable tracking the transmit-power and location of an unknown number of PUs, via a sparse regression technique. The latter exploits the sparsity inherent to the PU activities in a geographical area, using an ℓ1-norm regularized, sparsity-promoting weighted least-squares formulation. The resulting sparsity-cognizant tracker is developed in both centralized and distributed formats, to reduce computational complexity and memory requirements of a batch alternative. Numerical tests demonstrate considerable performance gains achieved by the proposed algorithms .
Impact of Homophily on Diffusion Dynamics Over Social Networks

The purpose of this study is to analyze the impact of homophily on diffusion over social networks. An agent-based simulation model is developed to serve as the experimental ground for this analysis. Diffusion dynamics of a nonsticky innovation is investigated by varying homophily levels in the social network depicted in the model as the primary control variable. First of all, the results show that homophily is self-reinforcing. Second, starting from a nonhomophilous network, early increases in the level of homophily have a positive effect on the extent of diffusion, whereas further increases have a negative impact. Finally, several local minima and maxima are observed in the relation between the homophily level and the extent of diffusion. Our analysis focuses on node properties such as connectedness and average degrees in order to explain the observed regular relationship between homophily and diffusion. We argue that (i) homophily increases the connectedness of different status groups separately and (ii) increasing levels of homophily decreases the marginal importance of a single homophilous tie by increasing the sources of valuable information. Future research involves investigating the coevolution of social behavior and networks by allowing the adopted innovation to lead to value homophily, exploration of different diffusion initiation types, and different adoption heuristics.
Association of Physical Performance and Pain With Fear of Falling Among Community—Dwelling Japanese Women Aged 65 Years and Older

AbstractOur aim was to explore the association of physical performance and pain with fear of falling among community-dwelling Japanese women.The subjects were 278 women aged 65 years and over. We collected information on fear of falling, painful joints, comorbidities, falls in the previous year, and cataracts. Walking time (distance of 6 m), chair stand time (5 times), grip strength, the timed up and go test (TUG), and functional reach were measured.The prevalence of fear of falling was 36.3%, and it increased with age, but it was not significant (P = 0.081). Multivariate logistic regression analysis showed that poor physical performance (longer walking time, longer chair stand time, weaker grip strength, and longer TUG) and pain (low back, and upper and lower extremity pain) were significantly associated with fear of falling after adjusting for age, body mass index, comorbidities, falls in the previous year, and cataracts.Maintaining physical functioning and managing pain may be important for elderly women with fear of falling.
An Energy Efficient Routing for Wireless Sensor Networks: Hierarchical Approach

Wireless sensor networks (WSNs) is one of the emerging field of research in recent era of communication world. These networks collect information from the environments and deliver the same to the applications to determine characteristics of the environment or detect an event. Since the sensor nodes have limited amount of energy, it is a major issue in wireless sensor networks to develop an energy-efficient routing protocol. Many energy efficient routing protocols have been proposed to solve this problem and increase the lifetime of the network. This paper proposes an energy efficient hierarchical based routing protocol. In this, clusters are made based on their geographical location & cluster heads are chosen on the basis of highest residual energy within the cluster as well as minimum distance to the base station from the cluster heads. Simulation is done using MATLAB. The results show that the network lifetime & residual energy of the nodes increases as we increase the number of cluster in the network.
Asynchronous implementation of a distributed average consensus algorithm

This paper discusses distributed average consensus in the context of a distributed embedded system with multiple agents connected through a communication network. Adversities such as switching of network topologies, agents joining or leaving the network, and communication link creation or failure may arise in these systems. To address these difficulties, we propose an asynchronous implementation of a distributed average consensus algorithm that has the following properties: (1) unbiased average, (2) homogeneous implementation, (3) robustness to network adversities, (4) dynamic consensus, and (5) well-defined tuning parameters. We demonstrate an application of the implementation on a specific distributed embedded system, the Distributed Flight Array, where we solve two average consensus problems to estimate altitude and tilt of the vehicle from multiple distance measurements.