Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of steer-by-wire system with bilateral control method using disturbance observer

Steer-by-wire system, in which the conventional mechanical linkages between the steering wheel and the front wheel are removed, is suited to active steering control, improving vehicle stability, dynamics and maneuverability, as well as to autonomous steering control to assist the driver. Conventional controller for SBW system is designed by general feedback control method. However, driver can not exactly feel reaction torque generated from tire. In this paper, the goals are considered as following two points. One is a reproduction of environmental impedance in steering wheel. The other is improved maneuverability for SBW system. Moreover, control stability must be satisfied. Using disturbance observer, bilateral controller is designed. Through analysis, it is confirmed that the three desired conditions in SBW system are well satisfied with this controller. The effectiveness of this research is demonstrated by experiment.
Hybrid Coherent and Frequency-Shifted-Reference Ultrawideband Radio

Ultrawideband communications often occur in heterogeneous networks where different receivers have different complexity and energy consumption requirements. In this case it is desirable to have a modulation scheme that works well with coherent receivers as well as simpler receivers, namely transmitted-reference (TR) receivers. In particular, we consider a TR scheme that employs slightly frequency-shifted reference (FSR) signals [15] and thus avoids one of the main drawbacks of conventional TR schemes, namely the need to implement a delay line. We propose and analyze a modulation scheme that works well with both FSR receivers (where it has the same performance as conventional TR modulation), and coherent receivers. Coherent receivers receiving conventional TR modulation suffer a 3 dB penalty, because they cannot make use of the energy invested into the reference pulse. Our proposed scheme avoids this drawback by including a data preprocessor that can be viewed as a nonsystematic rate-1/2 convolutional code with a high constraint length. These codes give 1.5 dB gain over our previously proposed constraint-length-two systematic codes at a BER of 1 times 10-4 in 802.15. 3a CM4 multipath fading channels.
Detection of the Entropy of the Intergalactic Medium: Accretion Shocks in Clusters, Adiabatic Cores in Groups

The thermodynamics of the diffuse, X-ray-emitting gas in clusters of galaxies is linked to the entropy level of the intracluster medium. In particular, models that successfully reproduce the properties of local X-ray clusters and groups require the presence of a minimum value for the entropy in the center of X-ray halos. Such a minimum entropy is most likely generated by nongravitational processes in order to produce the observed break in self-similarity of the scaling relations of X-ray halos. Likely candidates are supernova heating, stellar winds, radiative processes, and nuclear activity. At present, there is no consensus on the level, the source, or the time evolution of this excess entropy. In this framework a key question is whether the central entropy is the residual of the entropy originally present in the precollapse or intergalactic medium or whether it is generated within the halos after collapse. Answering this question will allow a more precise determination of the energetic budget required to build an entropy floor and lead toward an understanding of the nature of the sources of heating. In this paper we describe a strategy to investigate the physics of the heating processes acting in groups and clusters. We show that the best way to extract information from the local data is by observation of the entropy profile at large radii in nearby X-ray halos (z ≃ 0.1), at both the upper and lower extremes of the cluster mass scale. The spatially and spectrally resolved observation of such X-ray halos provides information on the mechanism of the heating. We demonstrate how measurements of the size of constant entropy (adiabatic) cores in clusters and groups can directly constrain heating models and the minimum entropy value. We also consider two specific experiments: the detection of the shock fronts expected at the virial boundary of rich clusters and the detection of the isentropic, low surface brightness emission extending to radii larger than the virial ones in low-mass clusters and groups. Both experiments are designed to measure the entropy in the low-density gas far from the core, taking advantage of the large collecting power of the present X-ray telescopes (in this case, XMM). Such observations will be a crucial probe of both the physics of clusters and the relationship of nongravitational processes to the thermodynamics of the intergalactic medium.
A Fluid Dynamic Based Coordination of a Wireless Sensor Network of Unmanned Aerial Vehicles: 3-D Simulation and Wireless Communication Characterization

A fluid dynamic algorithm based on smoothed particle hydrodynamics (SPH) is proposed for coordination of a team of unmanned aerial vehicles (UAVs) in a wireless sensor network. SPH is a Lagrangian particle method typically used to model compressible and quasi-incompressible fluid flows. In this study, SPH is used to develop a decentralized controller for a swarm of fixed-wing UAVs, which move in 3-D space under constraints of airspeed and turning radius. Vector field path-following is used to guide the swarm towards the goal. We investigate circular, racetrack and counter-rotating loiter patterns for the UAVs in the goal region. This fluid dynamics coordination treatment allows UAVs to avoid collisions with obstacles and other flying UAVs. 3-D simulations are used to test the SPH-based control algorithm. Simulations were used to explore special cases, such as the modeling of obstacles with virtual SPH particles, and the use of a variable kernel to control the inter-vehicle separation. Finally, an aerial mobile sensor network is set up using SPH as the control mechanism, and an experimental characterization of air-to-air and air-to-ground communications is conducted. The experiments use two ground stations and three Delta-wing UAVs with a wingspan of 32 inches as nodes. Each node has a IEEE 802.15. 4 ZigBee radio operating in the 2.4 GHz band. The low computational costs involved in the distributed SPH-based control algorithm make it an attractive option for implementation on simple inexpensive microprocessors. The results of simulations and experiments demonstrate the viability of setting up a mobile sensor network of inexpensive UAVs based on SPH.
Strategies for Inference Robustness in ComplexModelling : An Application to LongitudinalPerformance Measures

Advances in computation mean it is now possible to t a wide range of complex models, but selecting a model on which to base reported inferences is a diicult problem. Following an early suggestion of Box and Tiao, it seems reasonable to seekìnference robustness' in reported models, so that alternative assumptions that are reasonably well supported would not lead to substantially diierent conclusions. We propose a four-stage modelling strategy in which we: iteratively assess and elaborate an initial model, measure the support for each of the resulting family of models, assess the innuence of adopting alternative models on the conclusions of primary interest , and identify whether an approximate model can be reported. These stages are semi-formal, in that they are embedded in a decision-theoretic framework but require substantive input for any speciic application. The ideas are illustrated on a dataset comprising the success rates of 46 in-vitro fertilisation clinics over three years. The analysis supports a model that assumes 43 of the 46 clinics have odds on success that are evolving at a constant proportional rate (i.e. linear on a logit scale), while three clinics are outliers in the sense of showing non-linear trends. For the 43ìinear' clinics, the intercepts and gradients can be assumed to follow a bivariate normal distribution except for one outlying intercept: the odds on success are signiicantly increasing for four clinics and signiicantly decreasing for three. This model displays considerable inference robustness and, although its conclusions could be approximated by other less-supported models, these would not be any more parsimonious. Technical issues include tting mixture models of alternative hierarchical longitudinal models, the calibration of the Kullback-Leibler divergence between marginal posterior distributions, and the use of alternative measures of support for the range of models tted.
Beyond Social Media Determinism? How Artists Reshape the Organization of Social Movements

Artists and creative workers are engaged once more in the social and political space. In the current wave, which started in the early 2010s, they have taken part in broad social movements (e.g., Occupy, Tahrir Square), created movements of their own (e.g., Network of Occupied Theaters in Italy and Greece), experimented with alternative economic models and currencies (e.g., Macao and D-CENT), carried out social research and radical education, partnered with institutional and social actors, supported neighborhoods, filled the void left by states’ retreat from the social, and hosted and co-produced art at a time when the budget for culture and independent art is being decreased in numerous countries across the world. This article aims to investigate the organizational and relational aspects of artistic social movements. Drawing on a 2-year-long ethnographic study conducted for my PhD dissertation and deploying a number of research techniques, including participant observation, digital methods, and semi-structured interviews, I propose a new understanding of the meaning of organization in contemporary artistic social movements. My article, focusing especially on data gathered on Macao, “The New Centre for Arts, Culture and Research of Milan,” constitutes an attempt to reflect on emerging organizational models in social movements.
A data mining based method: Detecting software defects in source code

With the expansion of software size and complexity, how to detect defects becomes a challenging problem. This paper proposes a defect detection method which applies data mining techniques in source code to detect two types of defects in one process. The two types of defects are rule-violating defects and copy-paste related defects which may include semantic defects. During the process, this method can also extract implicit programming rules without prior knowledge of the software and detect copy-paste segments with different granularities. The method is evaluated with the Linux kernel that contains more than 4 million lines of C code. The result shows that the resulting system can quickly detect many programming rules and violations to the rules. After using the novel pruning techniques, it will greatly reduce the effort of manually checking violations so as a large number of false positives are effectively eliminated. As an illustrative example of its effectiveness, a case study shows that among the top 50 violations reported by the proposed model, 11 defects can be confirmed after examining the source code.
41.2: The Effect Of Edge Filtering On Vision Multiplexing

We developed a video filter that produces cartoon‐like images consisting of bipolar white and black transitions at luminance edges of the input video, for use in augmented‐vision devices. When tested in an inattentional blindness experiment it had no effect on the detectability of unexpected events, but did affect speed of responses to the attended task Response time improved when the unattended scene was filtered and degraded when the attended scene was filtered.
Moving Target Search

We consider the case of heuristic search where the location of the goal may change during the course of the search. For example, the goal may be a target that is actively avoiding the problem solver. We present a moving target search algorithm (MTS) to solve this problem. We prove that if the average speed of the target is slower than that of the problem solver, then the problem solver is guaranteed to eventually reach the target. An implementation with randomly positioned obstacles confirms that the MTS algorithm is highly effective in various situations.
Synchronous variation of dissolved organic carbon and color in lakes

Temporal variation in dissolved organic carbon (DOC) and water color (light absorption at 440 nm) was measured in 20 lakes in northern Michigan that varied in DOC, pH, morphometry, and relative productivity as indicated by chlorophyll and total phosphorus (TP). Monthly observations during May—August over 6 yr revealed that DOC and color varied by 6‐ and 28‐fold among lakes and varied substantially through time within lakes. The pattern of temporal variation differed among years but was synchronous among lakes. Of the 190 possible correlations among lake time series, most were positive for DOC (158) and color (160), and 50% of the positive correlations were significant (P < 0.05). Other variables, such as total phosphorus, chlorophyll, and pH, were less synchronous and had fewer significant positive correlations (13—25%). Temporal dynamics in DOC and color were related to ice‐out date as well as spring and summer precipitation. Years of late ice‐out and high spring rain were associated with high DOC and color in spring. A summer drought in one year lead to declines in color (up to 40%) and DOC (up to 38%) in nearly all of the lakes. The common temporal dynamics of DOC and color were most likely the result of climatic conditions that affected loading of allochthonous carbon as well as losses due to photodegradation. The variations in DOC were sufficient to cause large changes in light penetration, standing stocks of carbon, and ecosystem metabolism.
Validating the Z specification of Telephone Book System with symbolic execution

Symbolic execution has been used as a technique to validate Telephone Book Specification System. A set of test case has been prepared to integrate with Telephone Book Specification System for validation process. Supports from ztc and Z/EVES have assisted this study to get a very precise, and concise results thus reduce human error. Findings through this study are very crucial in order to raise more confidence using symbolic execution as a technique to validate formal specification.
Learning to Predict Distributions of Words Across Domains

Although the distributional hypothesis has been applied successfully in many natural language processing tasks, systems using distributional information have been limited to a single domain because the distribution of a word can vary between domains as the word’s predominant meaning changes. However, if it were possible to predict how the distribution of a word changes from one domain to another, the predictions could be used to adapt a system trained in one domain to work in another. We propose an unsupervised method to predict the distribution of a word in one domain, given its distribution in another domain. We evaluate our method on two tasks: cross-domain partof-speech tagging and cross-domain sentiment classification. In both tasks, our method significantly outperforms competitive baselines and returns results that are statistically comparable to current stateof-the-art methods, while requiring no task-specific customisations.
massively parallel signature sequencing (MPSS) Genome-wide mapping of DNase hypersensitive sites using

2006 16: 123-131; originally published online Dec 12, 2005; Genome Res. Mark J. Daly, Tyra G. Wolfsberg and Francis S. Collins Margulies, YiDong Chen, John A. Bernat, David Ginsburg, Daixing Zhou, Shujun Luo, Thomas J. Vasicek, Gregory E. Crawford, Ingeborg E. Holt, James Whittle, Bryn D. Webb, Denise Tai, Sean Davis, Elliott H. massively parallel signature sequencing (MPSS) Genome-wide mapping of DNase hypersensitive sites using
Finding dense and isolated submarkets in a sponsored search spending graph

Methods for improving sponsored search revenue are often tested or deployed within a small submarket of the larger marketplace. For many applications, the ideal submarket contains a small number of nodes, a large amount of spending within the submarket, and a small amount of spending leaving the submarket. We introduce an efficient algorithm for finding submarkets that are optimal for a user-specified tradeoff between these three quantities. We apply our algorithm to find submarkets that are both dense and isolated in a large spending graph from Yahoo! sponsored search.
Market Integration in Mozambique:: A Non-Parametric Extension to the Threshold Model

One of the main drawbacks of current methods to measure market integration is the assumption of constant transaction costs. In this paper, we propose a non-parametric extension to the commonly used threshold models, allowing us to estimate transaction costs in a more flexible way. We illustrate the method using weekly price data on maize collected in selected markets in Mozambique.
A Review of Ten Year Research on Query Log Privacy

The research on search log anonymization is ten years old. Over this time, a number of methods to reduce the risks of user identification and disclosure of sensitive information from search log analysis have been proposed. However, the impact of these findings on the behaviour of data owners and publishers has been very limited so far. In this paper, we present a brief overview and a classification of the main approaches in the literature, arguing that there has been a shift towards a more pragmatic balance between the value of the data published and the risk of an adversary breaching the user’s privacy. Then we go on to discuss what are the critical issues that must be tackled before search log anonymization moves out of research laboratories and into operational settings. We also clarify some misconceptions and mistakes in the use of the AOL search query log dataset, which is the main (and virtually only) experimental data source in the field.
Using Symmetry to Detect Abnormalies in Brain MRI

Division of Radiation Oncology Department of Oncology University of Alberta, Edmonton, AB, Canada Abstract Automated tumor segmentation from magnetic resonance imagery (MRI) plays a significant role in cancer research and clinical practice. However, tumor segmentation is an extremely challenging task: clinicians believe that a gamut of prior domain knowledge and clinical data should be used, along with the MR image. As a step toward tumor segmentation, we illustrate here a real-time algorithm to locate the brain abnormality in an MR image by putting a bounding box around it. Our approach is based on left-toright symmetry of the brain. In additional to being real-time, some advantages of the proposed algorithm are: (a) it requires no registration of MR images, (b) it needs no training image and (c) it is independent of intensity variations across MR images. Our detection algorithm can play a useful role in indexing and storage of MRI data and as an initial step toward accurate tumor boundary delineation.
A Survey on Quantum Cryptographic Protocols and Their Security

Communications in secrecy are often required in many commercial and military applications. Unfortunately, many cryptographic schemes in use today such as public-key cryptography based on the RSA algorithm would be broken with either unanticipated advances in hardware and algorithm or the advent of quantum computers. Quantum cryptography, on the other hand, has been proven secure even against the most general attack allowed by the laws of physics and is a promising technology poised for widespread adoption in realistic cryptographic applications. Quantum cryptography allows two parties to expand on a secret key that they have previously shared. Various quantum cryptographic protocols have been proposed to perform this task. In this paper, we survey some popular quantum cryptographic protocols (including the famous Bennett-Brassard 1984 protocol) and discuss their security. Specifically, we consider their security in two cases: the ideal case where a perfect single-photon source is used and the practical case where a realistic laser source is used. We compare the protocols and find that the efficient six-state protocol outperforms the others both in the tolerable quantum bit error rate and in the key generation rate when a realistic laser source is used.
A Visualization-Driven Approach to Overlay-Underlay Engineering ? ? ?

Abstract. Overlay applications are popular as they provide high-level functionality by masking the intrinsic complexity of the underlay network. However, overlays rely on the underlay to provide them with basic connectivity. Therefore, the intrinsic features of the underlay network determine the efficiency of the overlay. Accordingly, studying the interdependency of the overlay and underlay networks leads to a better understanding of overlay application behaviour. We present a visualization-driven analysis technique for evaluating the overlay architecture with respect to the underlay, inspired by the goal of overlay engineering. Using Gnutella as a case study, our analysis confirms that Gnutella topology differs from a randomly generated network and that there is an implicit correlation between the overlay and underlay topologies.
Diagram interaction during intelligent tutoring in geometry: Support for knowledge retention and deep understanding

Prior research has shown that skilled problem solvers often demonstrate meaningful links between relevant visual and verbal knowledge components, but little is known about how to support novice learners in connecting visual and verbal information during learning or whether such support will improve learning outcomes. This work explored two methods to support meaningful connections between visual and verbal information in an intelligent tutor for geometry: 1) student interaction with diagrams during problem solving, and 2) student explanations that connected diagram features to geometry rules at each problem-solving step. Research was conducted in 10 grade classrooms using an experimental version of the Geometry Cognitive Tutor. Results demonstrated that interaction with diagrams promoted longterm retention of problem-solving skills and supported performance on transfer tasks; diagram-rule explanations did not significantly influence learning. Findings suggest that student focus on relevant visual information should be carefully integrated into problem-solving practice to support deep learning.