Miracle-dz/UniFAR-FTUs huggingface dataset:
Preliminary results on quadrotor manipulation control

We propose controller for quadrotor with arm system. Quadrotor is underactuated which makes control problem difficult. Attached manipulator makes system dynamics complicate. To control end-effector position, we used passive decomposition and it provides decomposed dynamics. Using decomposed dynamics, we proposed backstepping-like controller to control end-effector position. Proposed controller achieve desired end-effector trajectory via underatuated system while moving manipulator. Simulation results are presented.
Analysis And Presentation Of Soccer Highlights From Digital Video

In many sports games like soccer, a major portion of the essence is captured in relatively short durations of intense actions. These highlights are summaries of the games. The capture and eeective presentation of these action highlights serve as an important browsing mechanism in a video library of soccer games, and require special techniques for the analyses of digital video. In this paper we present techniques to automatically detect and extract the soccer highlights by analyzing the image contents, and to present these shots of action by the panoramic reconstruction of selected events. The analyses include the recognition of prominent features of the game, tracking of ball, camera movement compensation for eeective recognition, and construction of the panoramic views.
Determinant of Sturm-Liouville operators and semi-classical trace formulae (IHP, June 2005)

These lectures will be devoted to Semi-Classical Trace Formulae (SCTF). The aim of SCTF is to derive properties of the eigenvalues of a Schrödinger operator Ĥh in the semi-classical regime where h, the Planck constant, is very small. From the mathematical point of view, h will tend to 0. The formal idea is to compute the trace of a suitable function of Ĥh in two ways • Trace(f(Ĥh)) = ∑ j f(Ej(h)) where Ej(h) are the eigenvalues of Ĥh • Trace(f(Ĥh)) = ∫ X [f(Ĥh)](x, x)|dx| where [A](x, y) denotes the Schwartz kernel of the operator A.
Modelling analysing and feedback control of nine-level NPC PWM rectifier - clamping bridge - nine-level NPC inverter cascade

Voltage source multilevel inverters have become very attractive for power industries in power electronics applications during last years. The main purposes that have led to the development of the studies about multilevel inverters are the generation of output voltage signals with low harmonic distortion; the reduction of switching frequency. A serious constraint in a multilevel inverter is the capacitor voltage- balancing problem. In order to stabilize these DC voltages, we propose in this paper to study the cascade constituted by three phases nine-level PWM rectifier-filter-nine-level NPC voltage source inverter-PMSM. In the first part, the authors present a topology of nine-level NPC VSI, then we propose a model of this converter and an optimal PWM strategy to control it using eight bipolar carriers. Then in the second part, we study a new high voltage cascade nine-level PWM current rectifier-filter-nine-level NPC VSI-PMSM. In the last part of this paper, the authors study the stability problem of the input DC voltages of the inverter. The results obtained with this solution confirm the good performances of the proposed solution, and are full of promise to use the inverter in high voltage and great power applications as electrical traction.
Sent Home Versus Being Arrested: The Relative Influence of School and Police Intervention on Drug Use

Abstract Prior research has demonstrated that school disciplinary practices lead to juvenile justice intervention or the “school-to-prison pipeline” and that juvenile justice intervention leads to adversities, including drug-using behavior, in adolescence and adult life. Yet, it is not clear which form of official intervention, school suspension, and expulsion or police arrest, is more predictive of drug use among young people. Using data from the Rochester Youth Developmental Study, we examined both the immediate, concurrent influence of school and police intervention on drug use during adolescence and the long-term, cumulative impact of school and police intervention during adolescence on subsequent drug use in young established adulthood. The results indicate that school exclusionary practices appeared to be more predictive of drug use than police arrest during both adolescence and young adulthood. Additionally, such negative effects mainly exhibited among minority subjects, and the effects by gender appeared contingent on developmental stages.
An achievable degree of freedom for multi-hop wireless networks under layered TDD constraint

We investigate the degrees of freedom (DoF) issue for multi-hop wireless networks with multiple-node layers under layered time-division-duplex (TDD) constraint. Our recent work about cascaded linear networks shows that the number of feasible network states is related to the famous Fibonacci sequence and the maximum achievable decode-and-forward (DF) rate is r*= min {C<sub>1</sub>C<sub>2</sub>/C<sub>1</sub>+C<sub>2</sub>, C<sub>2</sub>C<sub>3</sub>/C<sub>2</sub>+C<sub>3</sub>,⋯, C<sub>K-1</sub>C<sub>K</sub>/C<sub>K-1</sub>+C<sub>K</sub>} for K-hop networks, where C<sub>k</sub>; ∀k = 1, 2, . , K, is the capacity of each hop. Based on these results, we studies the DoF aspect of multi-hop networks with multiple-node layers, mainly about achievable lower bound on the sum DoF, by viewing the network as cascaded X channels (XC). Then we analyze the ultimate case where the number of antennas at each relay layer goes to infinity, from which we find that compared with two-hop networks, larger sum DoF can be obtained if the number of hops is no less than three.
Amyloid load and TSPO in APPswePS 1-dE 9 mice : a longitudinal study

We studied concomitantly the level of neuroinflammation and A β load in the APPswePS1dE9 transgenic mouse model of Alzheimer’s disease using PET imaging. The TSPO tracer [F]DPA-714 was used to measure neuroinflammation and [ F]AV-45 for Aβ load in mice at 6, 9, 12, 15 and 19 months of age. At 19 months, we also analysed the neuroinflammatory and neuroanatomical status of mice brains. Imaging experiments showed that the main affected brain areas were the cortex and to a lesser extend the hippocampus, with a concomitant progression of neuroinflammation with increased amyloid burden. At 19 months, it was interesting to note that no increase in TSPO binding was observed in the cerebellum while immunostaining revealed W0-2-positive plaques. This indicated that in this region the amyloid deposits seemed not be a stimulator of inflammation. This was in agreement with the level of microglia and astrocytes staining that were observed. Our findings provide a better understanding of the relationships between neuroinflammation and plaque accumulation in the course of the disease in this mouse model. The monitoring of both processes should be of value to validate potential therapeutic approaches. Key-words: Alzheimer’s disease; Amyloid load; Neuroinflammation; PET M AN US CR IP T AC CE PT ED ACCEPTED MANUSCRIPT
To Call or to Recall? That's the Research Question

We present findings of a study with 62 subjects who had 796 of their outgoing mobile phone calls recorded and transcribed for their later annotation—by highlighting important information shared during calls. We found that patterns in these calls (numbers, names, interrogative adverbs), as well as some contextual parameters, are better indicators of annotation needs than the callers' profile or call quality. Callers highlight information in both parties' turns (caller and callee) more often than highlighting solely information provided by the callee, which is mostly due to annotating questions with contextual information for the highlights in the callee's turns. We discuss how this behavior changes according to call purpose. Finally, we found that annotation needs change over time: whereas some annotations might not be considered relevant after weeks, others originally considered irrelevant might become important archival notes. We present implications of these findings for the design of mobile phone annotation tools.
Peoples and international law

Peoples and International Law is a detailed survey of the law of self-determination with a focus on the concept of nations and peoples. It engages with different aspects of this law with particular emphasis on the drafting and implementation of international instruments. The second edition includes new coverage of the Declaration on the Rights of Indigenous Peoples and the African and Arab charters. It considers recent practice by the Human Rights Committee, Committee on Economic, Social and Cultural Rights and African Commission on Human and Peoples’ Rights dealing with the emerging political, economic and environmental aspects of the right. The book looks at the interaction of international law, nationalism and liberalism in theories of nationhood and self-determination, as well as, the historical development of the right and the decisions of international bodies. Lastly, it examines practice in this area, including new developments in remedial independence and international territorial administration.
In-Depth Analysis of the Antibody Response of Individuals Exposed to Primary Dengue Virus Infection

Humans who experience a primary dengue virus (DENV) infection develop antibodies that preferentially neutralize the homologous serotype responsible for infection. Affected individuals also generate cross-reactive antibodies against heterologous DENV serotypes, which are non-neutralizing. Dengue cross-reactive, non-neutralizing antibodies can enhance infection of Fc receptor bearing cells and, potentially, exacerbate disease. The actual binding sites of human antibody on the DENV particle are not well defined. We characterized the specificity and neutralization potency of polyclonal serum antibodies and memory B-cell derived monoclonal antibodies (hMAbs) from 2 individuals exposed to primary DENV infections. Most DENV-specific hMAbs were serotype cross-reactive and weakly neutralizing. Moreover, many hMAbs bound to the viral pre-membrane protein and other sites on the virus that were not preserved when the viral envelope protein was produced as a soluble, recombinant antigen (rE protein). Nonetheless, by modifying the screening procedure to detect rare antibodies that bound to rE, we were able to isolate and map human antibodies that strongly neutralized the homologous serotype of DENV. Our MAbs results indicate that, in these two individuals exposed to primary DENV infections, a small fraction of the total antibody response was responsible for virus neutralization.
Exploring the efficacy of molecular fragments of different complexity in computational SAR modeling

An important first step in computational SAR modeling is to transform the compounds into a representation that can be processed by predictive modeling techniques. This is typically a feature vector where each feature indicates the presence or absence of a molecular fragment. While the traditional approach to SAR modeling employed size restricted fingerprints derived from path fragments, much research in recent years focussed on mining more complex graph based fragments. Today, there seems to be a growing consensus in the data mining community that these more expressive fragments should be more useful. We question this consensus and show experimentally that fragments of low complexity, i.e. sequences, perform better than equally large sets of more complex ones, an effect we explain by pairwise correlation among fragments and the ability of a fragment set to encode compounds from different classes distinctly. The size restriction on these sets is based on ordering the fragments by class-correlation scores. In addition, we also evaluate the effects of using a significance value instead of a length restriction for path fragments and find a significant reduction in the number of features with little loss in performance.
A new traffic light detection and recognition algorithm for electronic travel aid

A new traffic light detection and recognition algorithm for electronic travel aid was realized. Traffic lights were detected by rectangular and circular shapes extraction. Color distributions of the circular regions in HSI and RGB color space, combined with the position of the circular shape in the rectangle were used to recognize the traffic light. Gray level normalization, top hat transformation and image interception were used to reduce the disturbances of the environment. The average recognition rate is 97% and the speed is 0.086s per frame. Video analysis was used to improve the performance of the system.
Potentials and limitations of WIFI-positioning using Time-of-Flight

Many existing approaches for WIFI-based indoor positioning systems use the received signal strength indicator (RSSI) of all the access points in reach to estimate the current location of a mobile device. Those systems' accuracy, however, is strongly influenced by external interferences and suffers both from short-term and long-term changes in the respective environments. Time-of-Flight-based (TOF) approaches bypass these problems by relying on the relation between distance and the time it takes a radio signal to travel that distance. Furthermore and in contrast to RSSI-based fingerprinting methods, they require neither a time-consuming calibration phase nor an extensive database. In this paper, we assess the advantages and limitations of TOF-based positioning techniques and compare different approaches in literature in terms of communication flow, hardware components, method of time measurement and positioning accuracy. Additionally, we present a novel approach using NULL-ACK-sequences, off-the-shelf hardware components and the CPU's time stamp counter offering a nanosecond resolution. An association with access points is hence not required and there is no need for modifications of client or infrastructure WIFI-components. We evaluate our system in various settings. Our results indicate that the accuracy of such TOF-based approaches depends on both the used hardware and the characteristics of the given environment. We find that time fluctuations caused by varying delays of the interrupt service routine as well as multipath effects render precise distance estimations based on a single measurement infeasible. In order to obtain stable ranging results we try to minimize these effects by utilizing a high amount of NULL-ACK-sequences. We investigate several filters and statistical estimations and compare them within our system settings. Using a band-pass filter and taking the average of a series of measurements, we are able to achieve a ranging accuracy with a mean absolute error of less than 1.33 meters in an ideal environment.
Implementation of Deep Convolutional Neural Net on a Digital Signal Processor

In this paper I will discuss the feasibility of an implementation of an algorithm containing a Deep Convolutional Neural Network for feature extraction, and softmax regression for feature classification, for the purpose of real-time lane detection on an embedded platform containing a multi-core Digital Signal Processor (DSP). I will explore the merits of using fixed point and floating point arithmetic in the implementation, and provide calculations estimating whether the DSP is capable of real-time operation. While initial calculations suggest that the DSP is capable of real-time operation using floating point and fixed point arithmetic (∼50Hz and ∼60 Hz respectively), problems were encountered using 16-bit fixed point in Q-format, resulting in a failure of the algorithm to properly classify lanes. Future work for this project include exploring the challenges associated with the fixed point implementation, as well completing the migration of the algorithm to multi-core DSP using BLAS libraries.
A novel sparse auto-encoder for deep unsupervised learning

This paper proposes a novel sparse variant of auto-encoders as a building block to pre-train deep neural networks. Compared with sparse auto-encoders through KL-divergence, our method requires fewer hyper-parameters and the sparsity level of the hidden units can be learnt automatically. We have compared our method with several other unsupervised leaning algorithms on the benchmark databases. The satisfactory classification accuracy (97.92% on MNIST and 87.29% on NORB) can be achieved by a 2-hidden-layer neural network pre-trained using our algorithm, and the whole training procedure (including pre-training and fine-tuning) takes far less time than the state-of-art results.
Confusion Matrix Based Posterior Probabilities Correction Confusion Matrix Based Posterior Probabilities Correction

An MLP classifier outputs a posterior probability for each class. With noisy data classification becomes less certain and the entropy of the posteriors distribution tends to increase, therefore providing a measure of classification confidence. However, at high noise levels entropy can give a misleading indication of classification certainty because very noisy data vectors may be classified systematically into whichever classes happen to be most noise-like. When this happens the resulting confusion matrix shows a dense column for each noise-like class. In this article we show how this pattern of misclassification in the confusion matrix can be used to derive a linear correction to the MLP posteriors estimate. We test the ability of this correction to reduce the problem of misleading confidence estimates and to increase the performance of individual MLP classifiers. Word and frame level classification results are compared with baseline results for the Numbers95 database of free format telephone numbers, in different levels of added noise.
Solving the Multidimensional Knapsack Problem using a CUDA accelerated PSO

The Multidimensional Knapsack Problem (MKP) represents an important model having numerous applications in combinatorial optimisation, decision-making and scheduling processes, cryptography, etc. Although the MKP is easy to define and implement, the time complexity of finding a good solution grows exponentially with the problem size. Therefore, novel software techniques and hardware platforms are being developed and employed to reduce the computation time. This paper addresses the possibility of solving the MKP using a GPU accelerated Particle Swarm Optimisation (PSO). The goal is to evaluate the attainable performance benefit when using a highly optimised GPU code instead of an efficient multi-core CPU implementation, while preserving the quality of the search process. The paper shows that a single Nvidia GTX 580 graphics card can outperform a quad-core CPU by a factor of 3.5 to 9.6, depending on the problem size. As both implementations are memory bound, these speed-ups directly correspond to the memory bandwidth ratio between the investigated GPU and CPU.
The privatised self? A theological critique of the commodification of human identity in modern technological age in an African context professing Ubuntu

Modern technology has significantly improved human life. However, its serious negative element in Africa is fostering human self-sufficiency and independence that ultimately subvert human solidarity and interdependence that are highly valued by ubuntu philosophy. The main question of this article is: From the perspective of the African communal tenet of ubuntu that places human identity within communal solidarity and interdependence, how can we theologically respond to the commodification of human identity in the modern technological age? Consequently, a description is made of how modern technological age promotes human self-sufficiency that leads to the commodification of human identity. Further, the link between the commodification of human identity and privatisation of self is described. The challenge of ubuntu philosophy expressed by the Nguni proverb umuntu ngumuntu ngabantu is unpacked, and its challenge to the human self-sufficiency promoted by the technological age is explored. The image of God is proposed as an important theological tool of responding to the commodification of human identity. Finally, some steps that the churches can use to mitigate the commodification of human identity are presented. Technology is here to stay; rather than resist it, Christians must embrace it from a perspective informed by the image of God.
Insect Population Inspired Wireless Sensor Networks: A Unified Architecture with Survival Analysis, Evolutionary Game Theory, and Hybrid Fault Models

We envision a wireless sensor network (WSN) as an entity analogous to a biological population with individual nodes mapping to individual organisms and the network architecture mapping to the biological population. In particular, a mobile wireless sensor network consisting of hundreds or more of microchip- driven nodes is analogous to a flying insect population in several important aspects. The notions of lifetime, space distribution and environment apply to both domains. The interactions between individuals, either insects or WSN sensors, can be captured with evolutionary game theory models, in which individuals are the players and reliability are the fitness (payoff) of the players. The evolutionary stable strategy (ESS) forms the basis of network survivability. Furthermore, we introduce hybrid fault models into the proposed architecture with the notion of "Byzantine generals playing evolutionary games"[13J. This unified architecture makes it possible to dynamically (realtime) predict reliability, survivability, and fault tolerance capability of a WSN. On the node level, we introduce survival analysis to model lifetime, reliability and survivability of WSN nodes. By adopting survival analysis, rather than standard engineering reliability theory, we try to address four critical issues: (i) replacing unrealistic constant failure rates with general stochastic models, (ii) replacing unrealistic independent failures with shared frailty models that effectively address common risks or events-related dependence, and with multi-state modeling for common events dependence, (Hi) harnessing the censoring-modeling mechanisms to assess the influences of unpredictable malicious events on reliability and survivability, and (iv) addressing spatial aspects of failures with spatial survival analysis, spatial frailty.
Multiple Measures of Fixation on Social Content in Infancy: Evidence for a Single Social Cognitive Construct?

The preference of infants to fixate on social information in a stimulus is well known. We examine how this preference manifests across a series of free‐viewing tasks using different stimulus types. Participants were thirty typically developing infants. We measured eye movements when viewing isolated faces, faces alongside objects in a grid, and faces naturally presented in photographed scenes. In each task, infants fixated social content for longer than nonsocial content. Social preference scores representing distribution of fixation to social versus general image content were highly correlated and thus combined into a single composite measure, which was independent of demographic and behavioral measures. We infer that multiple eye‐tracking tasks can be used to generate a composite measure of social preference in infancy. This approach may prove useful in the early characterization of developmental disabilities.