Miracle-dz/UniFAR-FTUs huggingface dataset:
Generative Graphical Models for Maneuvering Object Tracking and Dynamics Analysis

We study the challenging problem of maneuvering object tracking with unknown dynamics, i.e., forces or torque. We investigate the underlying causes of object kinematics, and propose a generative model approach that encodes the Newtonian dynamics for a rigid body by relating forces and torques with object's kinematics in a graphical model. This model also accommodates the physical constraints between maneuvering dynamics and object kinematics in a probabilistic form, allowing more accurate and efficient object tracking. Additionally, we develop a sequential Monte Carlo inference algorithm that is embedded with Markov Chain Monte Carlo (MCMC) steps to rejuvenate the path of particles. The proposed algorithm can estimate both maneuvering dynamics and object kinematics simultaneously. The experiments performed on both simulated and real-world data of ground vehicles show the robustness and effectiveness of the proposed graphical model-based approach along with the sampling-based inference algorithm.
Recursive filtering and smoothing for reciprocal Gaussian processes-pinned boundary case

The least square estimation problem for pinned-to-zero discrete-index reciprocal Gaussian processes in additive white noise is solved, thus completing and extending some previous results available in the literature. In particular, following the innovations approach a (finite) set of recursive equations is obtained for the filter and for the three standard classes of smoothers (fixed-point, fixed-interval, fixed-lag). Recursive expressions for the mean square performance of the proposed estimators are also given. >
Localizing Software Faults Simultaneously

Current automatic diagnosis techniques are predominantly of a statistical nature and, despite typical defect densities, do not explicitly consider multiple faults, as also demonstrated by the popularity of the single-fault Siemens set. We present a logic reasoning approach, called Zoltar-M(ultiple fault), that yields multiple-fault diagnoses, ranked in order of their probability. Although application of Zoltar-M to programs with many faults requires further research into heuristics to reduce computational complexity, theory as well as experiments on synthetic program models and two multiple-fault program versions from the Siemens set show that for multiple-fault programs this approach can outperform statistical techniques, notably spectrum-based fault localization (SFL). As a side-effect of this research, we present a new SFL variant, called Zoltar-S(ingle fault), that is provably optimal for single-fault programs, outperforming all other variants known to date.
Automatic Generation of High-Quality Building Models from Lidar Data

Automating data acquisition for 3D city models is an important research topic in photogrammetry. In addition to techniques that rely on aerial images, generating 3D building models from point clouds provided. by light detection and ranging (Lidar) sensors is gaining importance. The progress in sensor technology has triggered this development. Airborne laser scanners can deliver dense point clouds with densities of up to one point per square meter. Using this information, it's possible to detect buildings and their approximate outlines and also to extract planar roof faces and create models that correctly resemble the roof structures. The author presents a method for automatically generating 3D building models from point clouds generated by the Lidar sensing technology.
Vehicle Trajectory-Based Data Forwarding Schemes for Vehicular Ad Hoc Networks

This paper introduces three vehicle trajectory-based data forwarding schemes, tailored for vehicular ad hoc networks. Nowadays GPS-based navigation systems are popularly used for providing efficient driving paths for drivers. With the driving paths called vehicle trajectories, we can make data forwarding schemes more efficient, considering the micro-scoped mobility of individual vehicles in road networks as well as the macro-scoped mobility of vehicular traffic statistics. This paper shows why the vehicle trajectory is a key ingredient in the design of the vehicle-to-infrastructure, infrastructureto-vehicle, and vehicle-to-vehicle data forwarding schemes over multihop. Through the mathematical formulation, the key design techniques are shown for three forwarding schemes based on vehicle trajectory, compared with a state-of-the-art data forwarding scheme based on only vehicular traffic statistics.
Schema-based GPS Following and Obstacle Avoidance

The ERTS robotic golf cart is controlled using a Schema Architecture to follow a path of GPS waypoints and to avoid obstacles. The theory behind a bare-bones version of the architecture is presented, followed by actual testing data in simulation and on the real golf cart. Finally, more involved versions of the architecture which were implemented, but not tested extensively (due to lack of availability of the phyical platform) are presented, and future possibilities discussed. A discussion of the merits and vices of application of the ethological, behaviour-based approach to the golf cart platform and associated tasks concludes this paper. 1 Background and Overview The Schema Architecture [1] is an ethologically-inspired paradigm for behaviour-based control of robots. It stipulates that at any given time t, an agent is under the influence of a number of forces. The agent’s overall behavior at time t will then be entirely determined by a linear combination of these forces. Forces may be generated by any of a number of sources. An dog’s instinctal drive to move towards good food smells will generate a force to that effect (in the direction of the good smell). Likewise, the same dog’s instinct to avoid loud noises will cause a force directed away from a vaccuum cleaner. In the absence of any other forces, the dog’s behaviour would then be to move towards the food, or away from the vaccuum cleaner. However, what if the food smell is coming from the same direction as the vaccuum cleaner noise? In this situation, there are two forces working at odds with one another. The dog’s behaviour at this point would then be the sum of the magnitudes of the two forces. If the dog were really hungry, the magnitude towards the food might be enough to overpower the drive to move away from the scary noise. If the sound is really loud or scary, however, its magnitude might be enough to drive the dog to move away from the good food smell (see 1). This example demonstrates the general reasoning involved in implementing a Schema-based model. Obviously, the real world is not as simple as the dog example given above. The general concept, however, remains the same. The force an agent feels in response to perceptions will be towards the source of that Figure 1: Forces acting on the theoretical dog in various situations. A: Force is towards the food smell. B: Force is away from the scary noise. C: Both the food smell and the scary smell are generating forces in opposite directions. The final force is determined by the relative magnitudes. In this case the noise is stronger, so the result is a force away, but much weaker than if there were no food smell and only the noise.
Recurrent Collateral Connections of Striatal Medium Spiny Neurons Are Disrupted in Models of Parkinson's Disease

The principal neurons of the striatum, GABAergic medium spiny neurons (MSNs), are interconnected by local recurrent axon collateral synapses. Although critical to many striatal models, it is not clear whether these connections are random or whether they preferentially link functionally related groups of MSNs. To address this issue, dual whole patch-clamp recordings were made from striatal MSNs in brain slices taken from transgenic mice in which D1 or D2 dopamine receptor expression was reported with EGFP (enhanced green fluorescent protein). These studies revealed that unidirectional connections were common between both D1 receptor-expressing MSN (D1 MSN) pairs (26%) and D2 receptor-expressing MSN (D2 MSN) pairs (36%). D2 MSNs also commonly formed synapses on D1 MSNs (27% of pairs). Conversely, only 6% of the D1 MSNs formed detectable connections with D2 MSNs. Furthermore, synaptic connections formed by D1 MSNs were weaker than those formed by D2 MSNs, a difference that was attributable to fewer GABAA receptors at D1 MSN synapses. The strength of detectable recurrent connections was dramatically reduced in Parkinson's disease models. The studies demonstrate that recurrent collateral connections between MSNs are not random but rather differentially couple D1 and D2 MSNs. Moreover, this recurrent collateral network appears to be disrupted in Parkinson's disease models, potentially contributing to pathological alterations in MSN activity patterns and psychomotor symptoms.
Statistical Methods for Analyzing Right‐Censored Length‐Biased Data under Cox Model

Summary Length‐biased time‐to‐event data are commonly encountered in applications ranging from epidemiological cohort studies or cancer prevention trials to studies of labor economy. A longstanding statistical problem is how to assess the association of risk factors with survival in the target population given the observed length‐biased data. In this article, we demonstrate how to estimate these effects under the semiparametric Cox proportional hazards model. The structure of the Cox model is changed under length‐biased sampling in general. Although the existing partial likelihood approach for left‐truncated data can be used to estimate covariate effects, it may not be efficient for analyzing length‐biased data. We propose two estimating equation approaches for estimating the covariate coefficients under the Cox model. We use the modern stochastic process and martingale theory to develop the asymptotic properties of the estimators. We evaluate the empirical performance and efficiency of the two methods through extensive simulation studies. We use data from a dementia study to illustrate the proposed methodology, and demonstrate the computational algorithms for point estimates, which can be directly linked to the existing functions in S‐PLUS or R.
Dense Real-Time Games

The rapid development of complex and safety-critical systems requires the use of reliable verification methods and tools for system design (synthesis). Many systems of interest are reactive, in the sense that their behavior depends on the interaction with the environment. A natural framework to model them is a two-player game: the system versus the environment. In this context, the central problem is to determine the existence of a winning strategy according to a given winning condition. We focus on real-time systems, and choose to model the related game as a nondeterministic timed automaton. We express winning conditions by formulas of the branching-time temporal logic TCTL. While timed games have been studied in the literature, timed games with dense-time winning conditions constitute a new research topic. The main result of this paper is an exponential-time algorithm to check for the existence of a winning strategy for TCTL games where equality is not allowed in the timing constraints. Our approach consists on translating to timed tree automata both the game graph and the winning condition, thus reducing the considered decision problem to the emptiness problem for this class of automata. The proposed algorithm matches the known lower bound on timed games. Moreover, if we relax the limitation we have placed on the timing constraints, the problem becomes undecidable.
Case Study: Giant Cell Arteritis with Vertebral Artery Stenosis

In giant cell arteritis (GCA), involvement of the vertebral arteries is rare with reported rates of 3%–4% for ischemic events secondary to vertebral artery stenosis or occlusion for those patients with GCA. This case study describes a patient who initially presented with acute onset of vertigo but was also found to have transient, side-alternating upper limb neurological findings. While initial imaging showed no vascular abnormalities, it was not until GCA was eventually confirmed with a temporal artery biopsy that the initial scans were shown to have bilateral narrowing of the vertebral arteries. While rare, vertebral artery involvement is an important complication to consider in the setting of GCA due to the high rate of associated mortality, despite immunosuppressive therapy.
The Australian terrestrial carbon budget

This paper reports a study of the full carbon (C- CO2) budget of the Australian continent, focussing on 1990- 2011 in the context of estimates over two centuries. The work is a contribution to the RECCAP (REgional Carbon Cycle Assessment and Processes) project, as one of numer- ous regional studies. In constructing the budget, we estimate the following component carbon fluxes: net primary produc- tion (NPP); net ecosystem production (NEP); fire; land use change (LUC); riverine export; dust export; harvest (wood, crop and livestock) and fossil fuel emissions (both territorial and non-territorial). Major biospheric fluxes were derived using BIOS2 (Haverd et al., 2012), a fine-spatial-resolution (0.05 ) of- fline modelling environment in which predictions of CABLE (Wang et al., 2011), a sophisticated land surface model with carbon cycle, are constrained by multiple observation types. The mean NEP reveals that climate variability and ris- ing CO2 contributed 12± 24 (1 error on mean) and 68± 15 TgC yr 1 , respectively. However these gains were partially offset by fire and LUC (along with other minor fluxes), which caused net losses of 26 ± 4 TgC yr 1 and 18± 7 TgC yr 1 , respectively. The resultant net biome pro- duction (NBP) is 36± 29 TgC yr 1 , in which the largest con- tributions to uncertainty are NEP, fire and LUC. This NBP offset fossil fuel emissions (95 ± 6 TgC yr 1 ) by 38± 30 %. The interannual variability (IAV) in the Australian carbon budget exceeds Australia's total carbon emissions by fossil fuel combustion and is dominated by IAV in NEP. Territo- rial fossil fuel emissions are significantly smaller than the rapidly growing fossil fuel exports: in 2009-2010, Australia exported 2.5 times more carbon in fossil fuels than it emitted by burning fossil fuels.
Chow polylogarithms and regulators

where r denotes the cross-ratio. In this note we show that the Bloch-Wigner function can be naturally extended to the (infinite dimensional) variety of all algebraic curves in CP 3 which are in sufficiently general position with respect to a given simplex L. (By definition a simplex in CP 3 is a collection of 4 hyperplanes in generic position). We call the corresponding function the Chow dilogarithm function. When our curve is a straight line we obtain just the Bloch-Wigner function evaluated at the cross-ratio of the 4 intersection points of this line with the faces of the simplex L. It is interesting that even in this case we get a new presentation of L2(z). Any algebraic surface in CP 4 which is in general position with respect to a given simplex produces a 5-term relation for the Chow dilogarithm function. Namely, the intersection of the surface with a codimension 1 face of the simplex provides a curve and a simplex in CP . A simplex in CP 4 has 5 codimension 1 faces. The alternating sum of the corresponding 5 values of the Chow dilogarithm is zero.
FlowMate: scalable on-line flow clustering

We design and implement an efficient on-line approach, FlowMate, for clustering flows (connections) emanating from a busy server, according to shared bottlenecks. Clusters can be periodically input to load balancing, congestion coordination, aggregation, admission control, or pricing modules. FlowMate uses in-band (passive) end-to-end delay measurements to infer shared bottlenecks. Delay information is piggybacked on feedback from the receivers, or, if impossible, TCP or application round-trip time estimates are used. We simulate FlowMate and examine the effects of network load, traffic burstiness, network buffer sizes, and packet drop policies on clustering correctness, evaluated via a novel accuracy metric. We find that coordinated congestion management techniques are more fair when integrated with FlowMate. We also implement FlowMate in the Linux kernel v2.4. 17 and evaluate its performance on the Emulab testbed, using both synthetic and tcplib-generated traffic. Our results demonstrate that clustering of medium to long-lived flows is accurate, even with bursty background traffic. Finally, we validate our results on the Internet Planetlab testbed.
Biological invasions at the gene level

Despite several recent contributions of population and evolutionary biology to the rapidly developing field of invasion biology, integration is far from perfect. I argue here that invasion and native status are sometimes best discussed at the level of the gene rather than at the level of the species. This, and the need to consider both natural (e.g. postglacial) and human‐induced invasions, suggests that a more integrative view of invasion biology is required.
‘Mistake-proofing’ a device to manage construction sites more effectively

During non-recession period, construction industry has a considerable profit margin in developing countries as a result of which government and related authorities are not fully sensitized and devoted to amelioration of the efficacy of the construction process. However, when recession strikes a country, the industry, in the wake of its relatively low rate of productivity, loses its economic justifiability. Bearing in mind the strikingly huge number of employment in the construction and its peripheral industries and the fact that these industries account for a considerable percentage of gross national income, devastating economic impact and pervasive unemployment as an immediate ramification of economic recession and its impact on construction industry is, indeed, beyond any doubts. The failure and inability of the conceptual models of Construction Management (time-cost-quality tradeoff, work break down structure, critical path methods, and earned value) to deliver on the mantra of ‘on-time, at budget, and at desired quality’ become evident to practitioner and academics; so pursuing a new management theory is inevitable. Lean construction is a management philosophy which decreases the cost of construction through elimination of waste, so it is appropriate in recession periods and since it maximize the value from customer point of view, it is also suitable during flourishing economy. Errors seem an inherent qualification in construction projects that causes rework and resource waste, if it can be redressed, and dissatisfaction for users of construction product. This paper investigates a tool named ‘poka yoke’, a Japanese word translated into English as ‘mistake proofing’. It is a robust tool which prevents inadvertent error in work and prevents workers from performing incorrectly, this concept provides great opportunities to bring quality into project delivery and also free workers from tedious recurring job and increase safety in construction sites. The research may help contractors to manage their sites more effectively. Finally, an innovative and simple example of implementation of mistake-proofing is proposed.
MODEL SELECTION AND PARAMETER ESTIMATION IN NON-LINEAR NESTED MODELS: A SEQUENTIAL GENERALIZED DKL-OPTIMUM DESIGN

This work proposes a sequential procedure which is useful to select the best model among several nested non-linear models and to estimate eciently the parameters of the chosen model. At the rst step of this procedure, a generalized DKL-optimum design is computed, which is optimal for the double goal of model selection and parameter estimation. Subsequently, at each following step, an adaptive generalized DKL-optimum design is computed on the base of the data accrued and tests previously performed. The proposed sequential scheme selects the best non-linear model with probability converging to one; moreover it estimates eciently its parameters, since the adaptive sequential DKL-optimum designs converge to the D-optimum design for the \true" model.
North Central Sociological Association 2018 Teaching Address: John F. Schnabel Lecture Teaching as Mentoring; Mentoring as Teaching

ABSTRACT Graduate student mentoring is widely considered a critical element of postbaccalaureate education, yet the mentoring of undergraduates is a frequently neglected topic in academic discourse. The benefits of mentoring are all too often reaped by only a small group of students who demonstrate academic promise. Yet the impact of mentoring on undergraduate student persistence is resoundingly positive, especially for students in the academic middle and the students most at risk of abandoning the pursuit of higher education. Much of the academic discussion of mentoring undergraduate students focuses on the possibilities presented via independent research projects, academic advising, and more formal mentoring programs. Although substantial debate exists regarding what mentoring is, and how or whether it is achievable en masse, I propose that teaching itself can exist as a form of mentoring, and vice versa, especially within the small liberal arts university environment.
Two-Dimensional Radiation-Hydrodynamic Model for Supercritical Disk Accretion Flows onto Neutron Stars

We performed two-dimensional radiation hydrodynamic simulations of supercritical accretion flows around neutron stars (NSs). In contrast with accretion flows onto black holes (BHs), we find that shell-shaped high-density regions form around the NSs, since the radiation force is enhanced in the innermost regions. The enhanced radiation force drives strong outflows above and below the disk. The mass-accretion rate onto the NS exceeds the critical rate, LE=c 2 , with LE being the Eddington luminosity. However it is about 20–30% of that onto the BH, under the condition that we employ the same mass-input rate, P Minput, which is the mass injected from the outer disk boundary per unit time. The mass-outflow rate is a few-times larger in flows around NSs than in flows around BHs. The supercritical NS accretion flows mainly release the accretion energy as kinetic energy of the outflows, though the disk luminosity is predominant over the kinetic energy output rate in the BH accretion flows. The resulting velocity and mass-outflow rate of the outflows are 0.2–0.3c and 150–700LE=c 2 , respectively, for a mass-input rate of 3 � 10 2 . P Minput=. LE=c 2 / . 3 � 10 3 . This implies that the SS 433 jets can be roughly explained by supercritical