Miracle-dz/UniFAR-FTUs huggingface dataset:
Complex ground plane detection based on V-disparity map in off-road environment

The work in the paper is to apply image pairs gathered by vehicle-mounted stereo cameras to detect the position of ground. The research focus is to detect complex ground planes for vehicle from image pairs based on investigating of the V-disparity map. This paper describes an enhancement of traditional V-disparity algorithm for off-road environment especially. The enhanced method can acquire the parameters of ground plane such as slope and pit. Experimental results with real data from stereo cameras mounted on a vehicle moving in off-road environment are presented. According to the simulation results, by comparison with traditional V-disparity algorithm, the average of recognition rate for ground using the enhanced V-disparity algorithm increases from 37.68% to 86.67%. The enhanced method can minimize errors of ground representation, and it is an efficient way to extract more details of ground structure than traditional V-disparity algorithm. The process is without dealing with any explicit structure such as road edges or lane marking. So it can be used for autonomous vehicle driving in off-road environment in the future.
The Design of a Spreadsheet Programming Interface for Sensor Networks

Sensor networks are currently difficult to program and maintain. To simplify programming we present an interface for programming sensor networks based on the concept of spreadsheets. Our interface is explicitly designed to handle habitat monitoring and animal tracking scenarios, which we believe constitute a large portion of sensor network applications. Our approach is simple enough so that scientists without strong programming backgrounds can still program and maintain a network of sensors. This Work-in-Progress explores the design of our interface and scenarios in which our design does well. This WIP also briefly explores some challenges we faced while designing our interface. We also discuss possible extensions to our design and applications that may benefit from those extensions.
The Lingering Anomalous Secular Increase of the Eccentricity of the Orbit of the Moon: Further Attempts of Explanations of Cosmological Origin

New analyses of extended data records collected with the Lunar Laser Ranging (LLR) technique performed with improved tidal models were not able to resolve the issue of the anomalous rate e ˙ of the eccentricity e of the orbit of the Moon, which is still in place with a magnitude of e ˙ =(5±2)×10 −12 y r −1 . Some possible cosmological explanations are offered in terms of the post-Newtonian effects of the cosmological expansion and of the slow temporal variation of the relative acceleration rate S ¨ S −1 of the cosmic scale factor S. None of them is successful since their predicted secular rates of the lunar eccentricity are too small by several orders of magnitude.
On the S-matrix of type-0 string theory

The recent discovery of non-perturbatively stable two-dimensional string backgrounds and their dual matix models allows the study of complete scattering matrices in string theory. In this note we adapt work of Moore, Plesser, and Ramgoolam on the bosonic string to compute the exact S-matrices of 0A and 0B string theory in two dimensions. Unitarity of the 0B theory requires the inclusion of massless soliton sectors carrying RR scalar charge as asymptotic states. We propose a regularization of IR divergences and find transition probabilities that distinguish the otherwise energetically degenerate soliton sectors. Unstable D-branes can decay into distinct soliton sectors.
An efficient policy for D2D communications and energy harvesting in cognitive radios: Go Bayesian!

Recently, there has been a surge of interests in paradigms such as device-to-device (D2D) communications and radio frequency energy harvesting (RFEH) to improve the spectrum as well as energy efficiencies of next-generation decentralized cognitive radio networks. However, little attention has been paid to the dual but competing task of subband selection of any desired bandwidth in D2D mode (i.e., opportunistic vacant spectrum access) and RFEH mode as well as need to minimize the subband switching cost (SSC) for an efficient implementation. Taking these factors into account, a new D2D-RFEH policy is proposed. It consists of: 1)Bayesian approach based Tunable Thompson Sampling (TTS) algorithm to learn subband statistics, 2) Subband access scheme employing TTS algorithm for minimizing collisions among the secondary users, and 3) Mode selection scheme. The simulation results, complexity and SSC analysis validate the superiority of the proposed policy over the policies employing frequentist approach based learning algorithms.
Simple BiCMOS CCCTA Design and Resistorless Analog Function Realization

The simple realization of the current-controlled conveyor transconductance amplifier (CCCTA) in BiCMOS technology is introduced. The proposed BiCMOS CCCTA realization is based on the use of differential pair and basic current mirror, which results in simple structure. Its characteristics, that is, parasitic resistance (R x) and current transfer (i o/i z), are also tunable electronically by external bias currents. The realized circuit is suitable for fabrication using standard 0.35 μm BiCMOS technology. Some simple and compact resistorless applications employing the proposed CCCTA as active elements are also suggested, which show that their circuit characteristics with electronic controllability are obtained. PSPICE simulation results demonstrating the circuit behaviors and confirming the theoretical analysis are performed.
Daily strengths use and employee well‐being: The moderating role of personality

This study combines strengths use and personality theories to develop a multilevel model of employee well-being. We hypothesized that individuals would experience higher well-being on the days they use their strengths. In addition, we predicted that Neuroticism, Extraversion, and their blend would bolster this main effect. A total of 87 Norwegian naval cadets filled out a general survey and then completed a diary questionnaire for 30 consecutive days (total N = 2610). Results of multilevel modelling showed that daily strengths use was positively related to daily positive affect and work engagement, after controlling for previous levels of the dependent variables. In addition, we found evidence for the predicted three-way interaction effects. These findings contribute to character strengths and personality theories by showing how blends of personality traits modify the effects of daily strengths use behaviours. Practitioner points: Employees who use their strengths at work build their own positive affect and work engagement. Personality influences how successful employees are in using strengths; strengths use works best for those high in Extraversion and low in Neuroticism. Organizations and managers should facilitate employee strengths use, because when employees use their strong points, they are more dedicated and energized during work.
Quantum algorithms for testing Boolean functions

We discuss quantum algorithms, based on the Bernstein-Vazirani algorithm, for finding which variables a Boolean function depends on. There are 2^n possible linear Boolean functions of n variables; given a linear Boolean function, the Bernstein-Vazirani quantum algorithm can deterministically identify which one of these Boolean functions we are given using just one single function query. The same quantum algorithm can also be used to learn which input variables other types of Boolean functions depend on, with a success probability that depends on the form of the Boolean function that is tested, but does not depend on the total number of input variables. We also outline a procedure to futher amplify the success probability, based on another quantum algorithm, the Grover search.
4-(Phenylsulfanyl)butan-2-One Suppresses Melanin Synthesis and Melanosome Maturation In Vitro and In Vivo

In this study, we screened compounds with skin whitening properties and favorable safety profiles from a series of marine related natural products, which were isolated from Formosan soft coral Cladiella australis. Our results indicated that 4-(phenylsulfanyl)butan-2-one could successfully inhibit pigment generation processes in mushroom tyrosinase platform assay, probably through the suppression of tyrosinase activity to be a non-competitive inhibitor of tyrosinase. In cell-based viability examinations, it demonstrated low cytotoxicity on melanoma cells and other normal human cells. It exhibited stronger inhibitions of melanin production and tyrosinase activity than arbutin or 1-phenyl-2-thiourea (PTU). Also, we discovered that 4-(phenylsulfanyl)butan-2-one reduces the protein expressions of melanin synthesis-related proteins, including the microphthalmia-associated transcription factor (MITF), tyrosinase-related protein-1 (Trp-1), dopachrome tautomerase (DCT, Trp-2), and glycoprotein 100 (GP100). In an in vivo zebrafish model, it presented a remarkable suppression in melanogenesis after 48 h. In summary, our in vitro and in vivo biological assays showed that 4-(phenylsulfanyl)butan-2-one possesses anti-melanogenic properties that are significant in medical cosmetology.
Multi-dimensional Carrierless Am/pm Systems for Digital Subscriber Loops 1

The Carrierless Amplitude/Phase modulation (CAP) is a viable alternative for the Digital Subscriber Loop (DSL) systems such as the HDSL, ADSL and VDSL. In this paper, the conventional two-dimensional CAP-16 line code is extended to a three-dimensional scheme. The three-dimensional system is designed so that the new overall transfer matrix maintains perfect reconstruction of the transmitted information. The system is designed by solving a minimax optimization problem by using the sequential quadratic programming algorithm; this searches the whole space of signals under the perfect reconstruction condition and the DSL constraints. The three-dimensional CAP system leads to an increase in the throughput by 50% at the expense of the output SNR degradation by 3-4 dB. Note that this increase in the throughput can also be achieved by a CAP-64 system. However, the dynamic range of the proposed three-dimensional CAP approach is 7.4 dB less than the CAP-64 and this leads to faster equalization. Furthermore, the equalizer performance in the three-dimensional case is 1-3 dB better. Another novel application of the multi-dimensional CAP approach is presented, and is referred to as the Orthogonality Division Multiple Access, ODMA. In this approach, the CAP system is extended to more-than-three dimensions by maintaining the overall symbol rate same as the two-dimensional case. The ODMA system allows multiple access operation of the DSL communication link with minimal hardware penalty. The performance of the ODMA system for the multiple access environment is found to match the conventional 2-dimensional CAP, allowing suitable multiple access topology with minimal complexity overhead.
Online Handwritten Digit Recognition Using Gaussian Based Classifier

Discrete Hidden Markov Model (HMM) and hybrid of Neural Network (NN) and HMM are popular methods in handwritten word recognition system. The hybrid system gives better recognition result due to better discrimination capability of the NN. A major problem in handwriting recognition is the huge variability and distortions of patterns. Elastic models based on local observations and dynamic programming such HMM are not efficient to absorb this variability. But their vision is local. But they cannot face to length variability and they are very sensitive to distortions. Then the SVM is used to estimate global correlations and classify the pattern. Support Vector Machine (SVM) is an alternative to NN. In Handwritten recognition, SVM gives a better recognition result. The aim of this paper is to develop an approach which improve the efficiency of handwritten recognition using artificial neural network Keyword: Handwriting recognition, Support Vector Machine, Neural Network
Enhancing Similarity Matrices for Music Audio Analysis

Similarity matrices have become an important tool in music audio analysis. However, the quadratic time and space complexity as well as the intricacy of extracting the desired structural information from these matrices are often prohibitive with regard to real-world applications. In this paper, we describe an approach for enhancing the structural properties of similarity matrices based on two concepts: first, we introduce a new class of robust and scalable audio features which absorb local temporal variations. As a second contribution, we then incorporate contextual information into the local similarity measure. The resulting enhancement leads to significant reduction in matrix size and also eases the structure extraction step. As an example, we sketch the application of our techniques to the problems of audio summarization and audio synchronization, obtaining effective and computationally feasible algorithms
Answer inference for crowdsourcing based scoring

Crowdsourcing is an effective paradigm in human centric computing for addressing problems by utilizing human computation power. While efforts have been made to study the crowdsourcing systems for labeling tasks such as classification, those for scoring tasks with continuous and correlative answers have not been well studied. In this paper, we propose two inference algorithms, MCE (Maximum Correlation Estimate) and WMCE (Weighted Maximum Correlation Estimate), to infer true answers based on answers submitted by workers. When estimating answers, WMCE algorithm assigns diverse weight to submitted answers of workers based on their quality while MCE algorithm assigns identical weight to submitted answers of all workers. For a fixed worker population, we reveal that the increase in task redundancy1 can improve accuracy of estimated answers but such improvement is limited within a certain level. We further show that WMCE algorithm can reduce the influence of this limitation better than MCE algorithm for the same crowdsourcing system. Simulation results validate our theoretical analysis and show that WMCE algorithm outperforms MCE algorithm in the accuracy of estimated answers.
Emotional Intelligence and Health Outcomes

This paper presents the relatively novel concept of Emotional Intelligence (EI) within the context of health care and health outcomes. The paper uses the available literature to present what is already known, describe emerging trends and highlight what is still unknown, regarding the role of EI in determining various health outcomes. The author offers an interpretive analysis of the existing evidence and presents a preliminary explanatory model of the association between EI and various health outcomes. The model is discussed, and directions for future studies and applications are presented.
Articulating for Tibetan Experiences in the Contemporary World: A Cultural Study of Pema Tseden’s and Sonthar Gyal’s Films

ABSTRACT In recent years, Pema Tseden and Sonthar Gyal have created a number of films on Tibet that have won many international awards. Their works diverge greatly from the stereotypical images of Tibet. This paper explores the re-representation of Tibet in their works from a postcolonial perspective by employing Stuart Hall’s (1996) theorisation of articulation as a strategy of resisting visual stereotypes. The purpose is to explore the directors’ attempt at demystifying Tibet and their concern with Tibetan identity anxiety in the context of modernisation and globalisation. Through critical examination of the neorealist depiction of Tibet, the issues of modernity, the crisis in identity, and the characters’ attempts at self-redemption, it is argued that the directors voice the need for reconstructing the Tibetan identity by negotiating tradition and modern life. It is concluded that their works signify the inception of true minority nationality films in Chinese cinema. It is an inspiration to other ethnicities in China in speaking about their experiences in the world of modernisation and globalisation.
Conditions for Direct Applicability of Electronic Capacitors to Dual-Stage Grid-Connected Power Conversion Systems

Active capacitance reduction circuits (ACRCs) are dc–dc converters, terminated by a small auxiliary capacitor, typically utilized to replace bulk electrolytic capacitors in dual-stage grid-connected power conversion systems. Electronic capacitors are ACRCs supporting “plug-and-play” operation in addition to the ability to emulate virtually any finite capacitance at dc-link connected terminals. Despite excellent steady-state functionality, all ACRCs possess the poor response to steplike no-load-to-full-load (and vice versa) transients due to the fact that the auxiliary capacitor utilized (and thus corresponding energy stored) is much smaller than the bulk dc-link capacitor being replaced. Nevertheless, in grid-feeding applications where fuel cells of photovoltaic generators act as a power source, the rate of generated power change is limited. This is also true regarding some off-grid systems such as LED lighting with dimming, where sudden load changes are unnecessary and electronic capacitors seem to be directly applicable in such systems. Therefore, this paper reveals the limits of steplike and ramplike load variations, tolerable by a system equipped with an electronic capacitor, based on its power rating and auxiliary capacitance value utilized. Examples are given for typical systems with 400-V dc link, connected to 50-Hz mains. The validity of presented findings is well-supported by simulations and experiments.
Poking Left To Be Right? A Model-Based Analysis of Temporal Order Judged by Mice

The theory of visual attention (TVTVA) provides a formal framework for the assessment of visual attention and related processes. Its center is a mathematical model of visual encoding processes and discretely defined components of attention. Building on this model, TVTVA offers quantitative and process-related explanations for a variety of phenomena in the domain of visual attention. Because the theory relies on very general assumptions which might hold true for other domains of sensory processing, we tested its possible explanatory value for tactile processing in mice. Reanalyzing published data of temporal-order judgments by mice, we show how a TVTVA-based analysis identifies the processes which drive observable behavior and that it comes to conclusions quite different from those of conventional analyses of temporal-order judgments. According to this analysis, despite the same overall capacity dedicated to the task, some mice assume attentional biases toward one side, possibly to optimize their overall performance. We suggest that TVTVA's concepts provide a powerful point of vantage to find explanations for observable behavior where conventional analysis easily leads to dead ends.
Plant MPSS databases: signature-based transcriptional resources for analyses of mRNA and small RNA

MPSS (massively parallel signature sequencing) is a sequencing-based technology that uses a unique method to quantify gene expression level, generating millions of short sequence tags per library. We have created a series of databases for four species (Arabidopsis, rice, grape and Magnaporthe grisea, the rice blast fungus). Our MPSS databases measure the expression level of most genes under defined conditions and provide information about potentially novel transcripts (antisense transcripts, alternative splice isoforms and regulatory intergenic transcripts). A modified version of MPSS has been used to perform deep profiling of small RNAs from Arabidopsis, and we have recently adapted our database to display these data. Interpretation of the small RNA MPSS data is facilitated by the inclusion of extensive repeat data in our genome viewer. All the data and the tools introduced in this article are available at .
Building a flexible and efficient routing infrastructure: Need and chal-lenges

The Achilles heel of the otherwise extremely successful Internet infrastructure has been its rigidity, which has primarily stemmed from the ossification of shortest-pathrouting in the basic architecture. The increasing effect of this rigidity of the current Internet infrastructure, coupled with the popular belief that basic IP routing cannot be changed, has led to many companies and researchers turn to infrastructure-based overlay networks to meet specific application requirements. These overlay networks, however, are mostly independent efforts, sharing nothing but the underlying IP infrastructure. We first try to argue for the need for reversing this trend, and in the process propose a panacea – a global shared overlay infrastructure. We envision that a single set of overlay infrastructure nodes, supporting a few simple primitives, would allow end-hosts to choose routes over the infrastructure, thus enabing the endhosts to achieve various services they desire. The foremost challenge we face here is to design flexible primitives that the infrastructure should export. The second requirement is to support a mechanism that allows end-hosts to find paths based on application-sensitive metrics. We achieve this by building a NEtwork Weather Service ( NEWS) that measures performance characteristics of the infrastructure. The final requirement, also of paramount importance, is to make sure that the infrastructure is DoS resistant 1. Thus, end-hosts, by querying theNEWSnodes build application-specific services using the routing primitives that the infrastructure exports. Experiments using an initial deployment of NEWSover PlanetLab have shown that our techniques perform very well.
UNIVERSITY OF DORTMUND REIHE COMPUTATIONAL INTELLIGENCE COLLABORATIVE RESEARCH CENTER 531 Design and Management of Complex Technical Processes and Systems by means of Computational Intelligence Methods Upper and Lower Bounds for Randomized Search Heuristics in Black-Box Optimization

Randomized search heuristics like local search, tabu search, simulated annealing or all kinds of evolutionary algorithms have many applications. However, for most problems the best worst-case expected run times are achieved by more problem-specific algorithms. This raises the question about the limits of general randomized search heuristics. Here a framework called black-box optimization is developed. The essential issue is that the problem but not the problem instance is known to the algorithm which can collect information about the instance only by asking for the value of points in the search space. All known randomized search heuristics fit into this scenario. Lower bounds on the black-box complexity of problems are derived without complexity theoretical assumptions and are compared to upper bounds in this scenario.
ThumbReels: query sensitive web video previews based on temporal, crowdsourced, semantic tagging

During online search, the user's expectations often differ from those of the author. This is known as the "intention gap" and is particularly problematic when searching for and discriminating between online video content. An author uses description and meta-data tags to label their content, but often cannot predict alternate interpretations or appropriations of their work. To address this intention gap, we present ThumbReels, a concept for query-sensitive video previews generated from crowdsourced, temporally defined semantic tagging. Further, we supply an open-source tool that supports on-the-fly temporal tagging of videos, whose output can be used for later search queries. A first user study validates the tool and concept. We then present a second study that shows participants found ThumbReels to better represent search terms than contemporary preview techniques.