Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimal trajectory planning for a quadrotor via a Gauss Pseudo-spectrum Method

The quadrotor, as a kind of Unmanned Aerial Vehicles (UAVs), has become a hot research topic, due to its small size, easy configuration, good stealthy characteristics, etc. It is a typical nonlinear system with coupling multi-variables. Therefore, it is difficult to optimize trajectory in real-time and its trajectory optimization research is limited so far. In this paper, we firstly establish a quadrotor dynamic model by Newton-Euler equations and simplify it properly. Then a Gauss Pseudo-spectrum Method (GPM) with the hp-adaptive mesh refinement algorithm is proposed to solve the problem which is a nonlinear optimal control problem with path and boundary constraints. The results verify that the method can effectively generate satisfied optimal trajectories for the aircraft and it provides mathematical foundation for the further engineering applications.
Lecture 15 : Detecting Objects by Parts

Object detection, however, faces many challenges. The challenges include the varying illumination conditions, changes in the viewpoints, object deformations, and intra-class variability; this makes objects of the same category appear different and makes it difficult to correctly detect and classify objects. In addition, the algorithms introduced herein only give the 2D location of the object in the image and not the 3D location. For example, the algorithms cannot determine if an object is in front
Comparison of accelerometer cut points for predicting activity intensity in youth.

UNLABELLED The absence of comparative validity studies has prevented researchers from reaching consensus regarding the application of intensity-related accelerometer cut points for children and adolescents. PURPOSE This study aimed to evaluate the classification accuracy of five sets of independently developed ActiGraph cut points using energy expenditure, measured by indirect calorimetry, as a criterion reference standard. METHODS A total of 206 participants between the ages of 5 and 15 yr completed 12 standardized activity trials. Trials consisted of sedentary activities (lying down, writing, computer game), lifestyle activities (sweeping, laundry, throw and catch, aerobics, basketball), and ambulatory activities (comfortable walk, brisk walk, brisk treadmill walk, running). During each trial, participants wore an ActiGraph GT1M, and V˙O2 was measured breath-by-breath using the Oxycon Mobile portable metabolic system. Physical activity intensity was estimated using five independently developed cut points: Freedson/Trost (FT), Puyau (PU), Treuth (TR), Mattocks (MT), and Evenson (EV). Classification accuracy was evaluated via weighted κ statistics and area under the receiver operating characteristic curve (ROC-AUC). RESULTS Across all four intensity levels, the EV (κ=0.68) and FT (κ=0.66) cut points exhibited significantly better agreement than TR (κ=0.62), MT (κ=0.54), and PU (κ=0.36). The EV and FT cut points exhibited significantly better classification accuracy for moderate- to vigorous-intensity physical activity (ROC-AUC=0.90) than TR, PU, or MT cut points (ROC-AUC=0.77-0.85). Only the EV cut points provided acceptable classification accuracy for all four levels of physical activity intensity and performed well among children of all ages. The widely applied sedentary cut point of 100 counts per minute exhibited excellent classification accuracy (ROC-AUC=0.90). CONCLUSIONS On the basis of these findings, we recommend that researchers use the EV ActiGraph cut points to estimate time spent in sedentary, light-, moderate-, and vigorous-intensity activity in children and adolescents.
The effects of image enhancement in OCR systems: a prototype

The accuracy of the optical character recognition (OCR) systems is highly dependent upon the quality of the image. We investigate and propose solutions to several issues that can arise in the processing of binary images of scanned, typeset text. The issues of concern are image residues from adjacent lines, character touching, boldface character recognition, and text repairing.
A Simple Technique for Reducing Pump Depletion in Long-Range Distributed Brillouin Fiber Sensors

We present a technical solution, capable of alleviating the problem of pump depletion in a long-range Brillouin distributed fiber sensor. This solution takes advantage of the presence of two sidebands in the probe wave to generate a dual gain-loss Brillouin interaction, giving rise to reduced pump depletion. Experimental results, carried out by using a Brillouin optical frequency-domain analysis configuration, demonstrated the improvement offered by the gain-loss technique.
A mathematical model of ebola virus disease: using sensitivity analysis to determine effective intervention targets

Mathematical models provide a useful framework to investigate real-world problems. They can be used in the context of disease dynamics to study how a disease will spread and how we can stop or prevent an outbreak. In December of 2013, an outbreak of Ebola began in the West African country of Guinea and later spread to Sierra Leone and Liberia. Health Organisations like the US Centers for Disease Control and the World Health Organization were tasked with providing aid to end the outbreak. We create an SEIR compartmental model of Ebola with a fifth compartment for the infectious deceased to model the dynamics of an Ebola outbreak in a village of a thousand people. We analyse the disease-free equilibrium of the model and formulate an equation for the eradication threshold R0. Sensitivity analyses points us in the direction of the transmission probability and the contact rate with infectious individuals as targets for intervention. We model the effect that vaccination and quarantine, together and separately, have on the outcome of the Ebola epidemic. We find that quarantine is a very effective intervention, but when combined with vaccination it can theoretically lead to eradication of the disease.
Climbing cleaning robot for vertical surfaces

Purpose – The purpose of this paper is to develop a climbing cleaning robot with reasonably high productivities for vertical surfaces.Design/methodology/approach – The paper analyzes the reasons for the low productivities or unreliable work of cleaning robots for vertical surfaces. Based on this analysis, a design of a new robot is created. Pilot studies were performed of laboratory and industrial prototypes of a new robot.Findings – The paper shows that the new design provides a reliable and high‐performance work of the cleaning robot for vertical surfaces. Thus, the new design provides increasing in productivities more than ten times compared with the known robot.Research limitations/implications – In this paper, it is assumed that the speed of the robot during the process of surface cleaning is constant. For future research the algorithm is proposed that automatically maintains such speed of the robot, which depends on the degree of dirtiness and is optimal for the surface to be cleaned.Practical impli.
MISO: An intermediate language to express parallel and dependable programs

One way to write fast programs is to explore the potential parallelism and take advantage of the high number of cores available in microprocessors. This can be achieved by manually specifying which code executes on which thread, by using compiler parallelization hints (such as OpenMP or Cilk), or by using a parallel programming language (such as X10, Chapel or Aeminium. Regardless of the approach, all of these programs are compiled to an intermediate lower-level language that is sequential, thus preventing the backend compiler from optimizing the program and observing its parallel nature. This paper presents MISO, an intermediate language that expresses the parallel nature of programs and that can be targeted by front-end compilers. The language defines 'cells', which are composed by a state and a transition function from one state to the next. This language can express both sequential and parallel programs, and provides information for a backend- compiler to generate efficient parallel programs. Moreover, MISO can be used to automatically add redundancy to a program, by replicating the state or by taking advantage of different processor cores, in order to provide fault tolerance for programs running on unreliable hardware.
Solution NMR characterization of apical membrane antigen 1 and small molecule interactions as a basis for designing new antimalarials

Plasmodium falciparum apical membrane antigen 1 (PfAMA1) plays an important role in the invasion by merozoites of human red blood cells during a malaria infection. A key region of PfAMA1 is a conserved hydrophobic cleft formed by 12 hydrophobic residues. As anti‐apical membrane antigen 1 antibodies and other inhibitory molecules that target this hydrophobic cleft are able to block the invasion process, PfAMA1 is an attractive target for the development of strain‐transcending antimalarial agents. As solution nuclear magnetic resonance spectroscopy is a valuable technique for the rapid characterization of protein–ligand interactions, we have determined the sequence‐specific backbone assignments for PfAMA1 from two P. falciparum strains, FVO and 3D7. Both selective labelling and unlabelling strategies were used to complement triple‐resonance experiments in order to facilitate the assignment process. We have then used these assignments for mapping the binding sites for small molecules, including benzimidazoles, pyrazoles and 2‐aminothiazoles, which were selected on the basis of their affinities measured from surface plasmon resonance binding experiments. Among the compounds tested, benzimidazoles showed binding to a similar region on both FVO and 3D7 PfAMA1, suggesting that these compounds are promising scaffolds for the development of novel PfAMA1 inhibitors. Copyright © 2016 John Wiley & Sons, Ltd.
Macroeconomic Impact of Bank Regulation and Supervision: A Cross-Country Investigation

Bank regulation and supervision (RS) is a formal institutional mechanism that aims to reduce the adverse selection and moral hazard risks in the banking sector. This paper offers an empirical exploration of the relationship between banking-sector performance and RS using data on the legal quality of bank regulation and supervision. The main channels via which RS affects bank performance are considered to be depositor trust, investment mobilization, and borrower discipline. An event study of up to fifty-three countries provides robust evidence that RS has significant positive effects on bank deposits and investment rate and significant negative effects on nonperforming loans.
Interactive Effects of Memory Structuring and Gender in Preventing Posttraumatic Stress Symptoms

This study retested effects of a Memory Structuring Intervention (MSI) and the moderating role of gender in relation to posttraumatic stress disorder (PTSD) symptoms. Thirty-four traffic accident victims with high pulse rates were randomly assigned to MSI or supportive listening (control) phone conversations soon after accidents. Based on converging clinical and neuroscience research, the MSI taught chronological organization, labeling emotions/sensations, and describing causality. PTSD symptoms were assessed 3 months later. No overall group differences were found. However, a group by gender interaction revealed that, for women, the MSI was associated with less PTSD symptoms than the control treatment, while the opposite pattern was seen in men. Limitations and possible explanations for these findings are discussed.
Searching Linked Objects with Falcons: Approach, Implementation and Evaluation

Along with the rapid growth of the data Web, searching linked objects for information needs and for reusing become emergent for ordinary Web users and developers, respectively. To meet the challenge, we present Falcons Object Search, a keyword-based search engine for linked objects. To serve various keyword queries, for each object the system constructs a comprehensive virtual document including not only associated literals but also the textual descriptions of associated links and linked objects. The resulting objects are ranked by considering both their relevance to the query and their popularity. For each resulting object, a query-relevant structured snippet is provided to show the associated literals and linked objects matched with the query. Besides, Web-scale class-inclusion reasoning is performed to discover implicit typing information, and users could navigate class hierarchies for incremental class-based results filtering. The results of a task-based experiment show the promising features of the system.
Natural and synthetic saponin adjuvant QS-21 for vaccines against cancer

One of the most widely used and potent immunological adjuvants is a mixture of soluble triterpene glycosides purified from the soap bark tree (Quillaja saponaria). Despite challenges in production, quality control, stability and toxicity, the QS-21 fraction from this extract has exhibited exceptional adjuvant properties for a range of antigens. It possesses an ability to augment clinically significant antibody and T-cell responses to vaccine antigens against a variety of infectious diseases, degenerative disorders and cancers. The recent synthesis of active molecules of QS-21 has provided a robust method to produce this leading vaccine adjuvant in high purity as well as to produce novel synthetic QS-21 congeners designed to induce increased immune responsiveness and decreased toxicity.
A taxometric study of borderline personality disorder.

Taxometric methodology was used to determine whether borderline personality disorder (BPD) represents a taxon that is categorically distinct from normal personality or whether it falls on a dimensional continuum with normality. Two taxometric procedures were used with a sample of 1,389 outpatients assessed for BPD symptoms by semistructured interview. The procedures indicated that BPD does not represent a latent category. Implications are drawn for the conceptualization and etiology of BPD, and for the categorical versus dimensional status of personality disorders in general.
Non-linear optics and harmonic generation in ZnS using femtosecond mid-IR pulses near zero dispersion wavelength

Using intense <tex>$3.6\ \mu \mathrm{m}$</tex>, 200 fs, 500 Hz laser pulses, non-linear spectral broadening, filamentation and 2<sup>nd</sup>-9<sup>th</sup> harmonic generation in ZnS (Cleartran™) with 3–40 mm propagation distance were observed. Non-linear index of Cleartran was also measured. © 2019 The Author(s)
Abnormal visual event detection based on multi‐instance learning and autoregressive integrated moving average model in edge‐based Smart City surveillance

The abnormal visual event detection is an important subject in Smart City surveillance where a lot of data can be processed locally in edge computing environment. Real‐time and detection effectiveness are critical in such an edge environment. In this paper, we propose an abnormal event detection approach based on multi‐instance learning and autoregressive integrated moving average model for video surveillance of crowded scenes in urban public places, focusing on real‐time and detection effectiveness. We propose an unsupervised method for abnormal event detection by combining multi‐instance visual feature selection and the autoregressive integrated moving average model. In the proposed method, each video clip is modeled as a visual feature bag containing several subvideo clips, each of which is regarded as an instance. The time‐transform characteristics of the optical flow characteristics within each subvideo clip are considered as a visual feature instance, and time‐series modeling is carried out for multiple visual feature instances related to all subvideo clips in a surveillance video clip. The abnormal events in each surveillance video clip are detected using the multi‐instance fusion method. This approach is verified on publically available urban surveillance video datasets and compared with state‐of‐the‐art alternatives. Experimental results demonstrate that the proposed method has better abnormal event detection performance for crowded scene of urban public places with an edge environment.
Handling misreporting in selfreported turnout using multiple overimputation

Electoral studies consistently show a substantive difference between selfreported turnout, on one side, and validated turnout and official results, on the other side. As any inaccurate data, misreported voter turnout in surveys may lead to erroneous substantive conclusions. Extant efforts to reduce this source of bias focus mainly on the reduction of misreporting in surveys by manipulating question wording. We propose a new approach to attenuate the impacts of misreported voter turnout in surveys based on multiple overimputation (MO), a method for handling of data with measurement error proposed by Blackwell, Honaker and King. We propose multiple overimputation of the selfreported turnout (MOST) using information obtained from extant surveys of the same population. We test our method in a Monte Carlo (MC) study as well as by comparing it to the validated turnout present in the American National Election Studies (ANES). We take the turnout as a response variable, compare the results produced by the selfreported, validated, and multiply overimputed turnout, and test if our approach reduces the bias produced by misreporting in the selfreported vote. MC evidence suggests that MOST improves the estimates even under conditions of relatively high volatility of population models of turnout and overreporting. In the field test MOST reduces the coefficient bias and Type I error rate. We discuss how our approach can be improved with hierarchical Bayesian modeling and mixtures. Prepared for the 70th Annual MPSA Conference.
Spectral and Colorimetric Constancy and Accuracy of Multispectral Stereo Systems

Stereo multispectral systems enable at the same time the acquisition of accurate spectral and depth information. The left and right cameras of the system can either present the same spectral sensitivities (e.g., a monochrome sensor with 7 different bandpass color filters sequentially placed in front of it for both cameras) or complementary sensitivities. The latter alternative can be accomplished by the utilization of two different filters or sets of filters for each camera of the stereo system. Even if each camera alone does not provide complete spectral information about the acquired scene, the estimation of the spectra becomes possible when both cameras are considered together. But since the reflectance spectrum of objects is a function of the wavelength, of the illumination angle and of the observation angle, the information from the left and the right cameras is generally different. This problem is already known from the RGB stereo imaging, and becomes even more relevant when it comes to multispectral stereo imaging, whose purpose is in addition an accurate color recording. In this paper, we analyze this problem experimentally by acquiring different series of stereo data and comparing them for determined regions of interest. We acquire two scenes under different lighting conditions with a standard color chart and objects whose reflectance spectra have a limited observation angle dependence. We utilize real multispectral data as well as spectra measured with a spectrophotometer to verify camera acquisition and compare them for different observation angles. We then estimate the acquired spectra using several of the possible spectral compositions, given by all the color channels available for the left and for the right camera. These estimated spectra are compared to the ground truth data and we show that the stereo system with 7 channels cameras using only 3 color channels from one camera and the 4 complementary color channels from the other camera has a good colorimetric accuracy.
Application of passive nonlinear network concept in digital signal processing

In our work we have developed a new methodology for the design of nonlinear dynamical systems and signal processing algorithms. In this paper, we discuss the basic concept of this approach, as well as some variations of the applied model. We show the results of application of this approach in signal estimation. We also compare the obtained results with that of Kalman filtering. The results indicate that we are able, applying our new approach, to obtain with relative ease the estimators that are comparable, and sometimes even superior and more robust as compared to Kalman filtering. <<ETX>>
The impact of outcome valence on the susceptibility to suggestion for post-event causal misinformation

ABSTRACT Recent research has demonstrated that people are especially susceptible to false memory development for suggested misinformation that fills a causal role (i.e., explains some known outcome) (Chrobak & Zaragoza, 2013). However, little is known about how factors associated with the witnessed outcome impact the likelihood of false memory development. In the present study, outcome valence (negative, positive, or neutral) was manipulated. Participants heard several short stories that contained an outcome (e.g., a counselor getting promoted) that lacked a causal explanation. Participants were subsequently exposed to suggested causal misinformation that explained that outcome (e.g., the counselor performed an impressive act the previous day) and then were tested on their memory for the original event. Results indicated that participants incorrectly reported the suggested causal information more when it explained either a positive or negative outcome as opposed to a neutral outcome. Theoretical and practical implications of these findings are discussed.
Gilbert damping of CoFe-alloys

We report structural, magnetic and dynamic properties of polycrystalline CoxFe1−x-alloy films on Sapphire, Silicon, and MgO substrates across the full composition range, by using a vector network analyser ferromagnetic resonance measurement technique (VNA-FMR), superconducting quantum interference device magnetometry (SQUID) and x-ray diffraction (XRD). In the approximate vicinity of 28% Co, we observe a minimum of the damping parameter, associated with a reduction in the density of states to a minimum value at the Fermi energy level. For films on all substrates, we find magnetic damping of the order of 4–5 · 10−3, showing that the substrate does not play a major role. Using a post-annealing process, we report a decrease of the magnetic damping down to 3–4 · 10−3. We find that the saturation magnetization depends approximately reciprocally on the damping parameter with varying alloy composition.
A pipelined hardware implementation of in-loop deblocking filter in H.264/AVC

In this paper we present a pipelined hardware implementation of in-loop deblocking filter in H.264/AVC. A pipelined datapath has been adopted to boost the speed of the deblocking filter process. The processing order of the filter is rearranged to facilitate the deblocking of the pixels in a pipelined fashion. A suitable buffer mechanism has also been proposed that reduces the size of the on-chip SRAM and redundant external memory accesses. The hardware implementation, under TSMC 0.13 /spl mu/m standard cell library, consumes only 7.5 K gates at a clock frequency of 200 MHz. Our architecture supports real-time deblocking of high resolution (2048/spl times/1024) video applications at 30 fps over three channels.