Miracle-dz/UniFAR-FTUs huggingface dataset:
Using Temporal Checkers for Functional Coverage

Checkers based on temporal logic expressions provide efficient way to express and detect events that comprise of complex temporal scenarios. These checkers are used to detect violations of the specification and monitor coverage events. In this paper, we extend temporal logic checkers with auxiliary variables. These variables are attached to sub expressions and are assigned values when the sub expressions are evaluated. The use of auxiliary variables enables implementation of large cross-product coverage models with small number of checkers. This helps to reduce the simulation overhead caused by checkers, thus increasing the efficiency of simulation resources.
Compass visualizations for human-robotic interaction

Compasses have been used for centuries to express directions and are commonplace in many user interfaces; however, there has not been work in human-robotic interaction (HRI) to ascertain how different compass visualizations affect the interaction. This paper presents a HRI evaluation comparing two representative compass visualizations: top-down and in-world world-aligned. The compass visualizations were evaluated to ascertain which one provides better metric judgment accuracy, lowers workload, provides better situational awareness, is perceived as easier to use, and is preferred. Twenty-four participants completed a within-subject repeated measures experiment. The results agreed with the existing principles relating to 2D and 3D views, or projections of a three-dimensional scene, in that a top-down (2D view) compass visualization is easier to use for metric judgment tasks and a world-aligned (3D view) compass visualization yields faster performance for general navigation tasks. The implication for HRI is that the choice in compass visualization has a definite and nontrivial impact on operator performance (world-aligned was faster), situational awareness (top-down was better), and perceived ease of use (top-down was easier).
An O(m+n) measure of penetration depth between convex polyhedral bodies for rigid multibody dynamics (cid:73)

In this work, we deﬁne a new metric of the distance and depth of penetration between two convex polyhedral bodies. The metric is computed by means of a linear program with three variables and m + n constraints, where m and n are the number of facets of the two polyhedral bodies. As a result, this metric can be computed with O ( n + m ) algorithmic complexity, superior to the best algorithms known for calculating Euclidean penetration depth. Moreover, our metric is equivalent to the signed Euclidean distance and thus results in the same dynamics when used in the simulation of rigid-body dynamics in the limit of the time step going to 0. We demonstrate the use of this new metric in time-stepping methods for rigid body dynamics with contact and friction.
A novel approach for hyperspectral unmixing based on Nonnegative Matrix Factorization

Traditional Nonnegative Matrix Factorization (NMF) algorithm is sensitive to the initial value when being applied to hyperspectral unmixing, because of the local minima in the objective function. In order to solve the problem, two constraints of abundance separation and smoothness are introduced into the NMF algorithm. The proposed algorithm retains the advantages of NMF, and effectively overcomes the shortcoming of local minima at the same time. Experimental results on simulated and real hyperspectral data demonstrate that the proposed approach can overcome the shortcoming of local minima, and obtain better results with respect to other state-of-art approaches. Meanwhile, the algorithm performs well for noisy data, and can also be used for the unmixing of hyperspectral data in which pure pixels do not exist.
Code Coverage of Adaptive Random Testing

Random testing is a basic software testing technique that can be used to assess the software reliability as well as to detect software failures. Adaptive random testing has been proposed to enhance the failure-detection capability of random testing. Previous studies have shown that adaptive random testing can use fewer test cases than random testing to detect the first software failure. In this paper, we evaluate and compare the performance of adaptive random testing and random testing from another perspective, that of code coverage. As shown in various investigations, a higher code coverage not only brings a higher failure-detection capability, but also improves the effectiveness of software reliability estimation. We conduct a series of experiments based on two categories of code coverage criteria: structure-based coverage, and fault-based coverage. Adaptive random testing can achieve higher code coverage than random testing with the same number of test cases. Our experimental results imply that, in addition to having a better failure-detection capability than random testing, adaptive random testing also delivers a higher effectiveness in assessing software reliability, and a higher confidence in the reliability of the software under test even when no failure is detected.
Multiple access in MAC layer based on surrounding conditions of wireless stations

Many parameters of wireless communications are uniquely configured, regardless of their communication environments. However, we believe that stations are able to achieve efficiency in communications using surrounding information. One of the systems that is expected to improve the performance of wireless communications is Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) in the MAC Layer. In this paper, we propose a new model to improve network performance using information about the number of stations in the backoff algorithm of CSMA/CA. Although there are already some proposals for the use of the backoff algorithm, most of them are proposed under an ideal scenario, in which the communication conditions of all the stations are the same. However, we propose a model that can adapt to scenarios in which the communication conditions of each station are different. The performance of CSMA/CA enhanced with our algorithm is extensively investigated in simulations performed under multiple scenarios. The obtained results indicate that our model can simultaneously achieve good communication performance and fairness.
A Random Matrix Approach to the Lack of Projections in C*_red(F_2)

In 1982 Pimsner and Voiculescu computed the K_0- and K_1-groups of the reduced group C*-algebra C*_red(F_k) of the free group F_k on k generators and settled thereby a long standing conjecture: C*_red(F_k) has no projections except for the trivial projections 0 and 1. Later simpler proofs of this conjecture were found by methods from K-theory or from non-commutative differential geometry. In this paper we provide a new proof of the fact that C*_red(F_k) is projectionless. The new proof is based on random matrices and is obtained by a refinement of the methods recently used by the first and the third named author to show that the semigroup Ext(C*_red(F_k)) is not a group for k >= 2. By the same type of methods we also obtain that two phenomena proved by Bai and Silverstein for certain classes of random matrices: ``no eigenvalues outside (a small neighbourhood of) the support of the limiting distribution'' and ``exact separation of eigenvalues by gaps in the limiting distribution'' also hold for arbitrary non-commutative selfadjoint polynomials of independent GUE, GOE or GSE random matrices with matrix coefficients.
Regression Model in Transitional Geological Environment For Calculation Farming and Production of Oil Palm Dominant Factor in Indragiri Hilir Riau Province

Palm oil commodity is plantation sub-sector commodity which can increase the income of farmers and communities, providers of raw material processing industries that create added value. Cultivated by smallholders self consists of land area, peatlands tidal, coastal peatlands and coastal lands. Differences typology of this land will contribute to the different productions. Generally, this study aimed to analyze the factors of production and farming oil palm, according to the typology of land Specifically aimed to analyze the production and cultivation of oil palm as well as the dominant factor affecting the production Kalapa smallholders' according to the typology of the land and to formulate policy implications of oil palm development patterns of the people in Indragiri Hilir in Riau province. To answer this research analyzed with descriptive statistics and build a multiple regression model with dummy variables Ordinary Least Square method (OLS). Memperlihatan research results that palm oil production and farming on land typology highest compared with tidal peat, peat coast, and coastal lands. Oil palm farming income on a non-pattern land typology best compared with other lands (peat tides, coastal peatlands, and coastal land). The dominant factor affecting the production of palm oil in Indragiri Hilir is the amount of fertilizer, labor, plant age, herbicides, and soil typology dummy land. Policy Implications development of oil palm plantation in Indragiri Hilir in order to increase production, productivity and farm income oil palm can be through the construction of roads production, provision of means of production and palm oil processing industry to shorten the distance and shorten the time of transport that TBS of oil palm plantations to the factory. Furthermore, the use of fertilizers, labor and land typology is very responsive to TBS production. Therefore, in the farming of oil palm cultivation should follow the recommended technical.
Formulation Optimization of a Palm-Based Nanoemulsion System Containing Levodopa

Response surface methodology (RSM) was utilized to investigate the influence of the main emulsion composition; mixture of palm and medium-chain triglyceride (MCT) oil (6%–12% w/w), lecithin (1%–3% w/w), and Cremophor EL (0.5%–1.5% w/w) as well as the preparation method; addition rate (2–20 mL/min), on the physicochemical properties of palm-based nanoemulsions. The response variables were the three main emulsion properties; particle size, zeta potential and polydispersity index. Optimization of the four independent variables was carried out to obtain an optimum level palm-based nanoemulsion with desirable characteristics. The response surface analysis showed that the variation in the three responses could be depicted as a quadratic function of the main composition of the emulsion and the preparation method. The experimental data could be fitted sufficiently well into a second-order polynomial model. The optimized formulation was stable for six months at 4 °C.
INFLUÊNCIA DA OSCILAÇÃO DECADAL DO PACÍFICO E DO PADRÃO PACIFIC SOUTH AMERICA NO CLIMA DA AMÉRICA DO SUL PARA O PERÍODO 1970-2003

RESUMO Este estudo tem como objetivo identificar os padrões climáticos de circulação e precipitação sobre a América do Sul durante as fases negativa e positiva da Oscilação Decadal do Pacífico ODP, entre 1970 e 2003, associado-os aos modos de oscilação de baixa frequência no Pacífico Sul, para dados mensais da renalise I do NCEP-NCAR, reanálise do JRA-55 e dados de precipitação do GPCC. Os resultados mostram que os dados do NCEPNCAR e JRA-55 são bastante similares indicando anomalia positiva e negativa de altura geopotencial em altos níveis troposféricos sobre o sudeste da América do Sul, nas fases negativa e positiva da ODP, favorecendo, respectivamente, condições mais secas e mais úmidas que o normal para esta região. Associados a estes padrões de geopotencial, anomalias anticilônicas e ciclônicas de circulação em altos e baixos níveis são observadas nas fases negativa e positiva da ODP. A variabilidade da precipitação nas fases negativa e positiva da ODP é mais significativa no setor leste da América do Sul, sendo observada respectivamente menos e mais precipitação na faixa noroeste-sudeste do setor central do continente sulamericano.
COMPARATIVE STUDY OF FEATURE EXTRACTION TECHNIQUES FOR PUNJABI SPEECH RECOGNITION

This paper evaluates comparative recognition performance of Linear Predictive Coefficients (LPC), Linear Predictive Cepstral Coefficient (LPCC), Perceptual Linear Prediction Coefficients (PLP), Mel Frequency Cepstral Coefficient (MFCC) and Wavelet coefficients. These features have been tested for speaker independent isolated Punjabi digits recognition. The comparative study of recognition performance of LPC, LPCC, PLP, MFCC and Wavelet coefficients has been studied. The recognition performance of PLP is better than LPC and LPCC coefficients. The recognition performance of LPCC coefficients is 4.2% better than LPC. The recognition performance of PLP is 10.95% better than LPCC coefficient. And MFCC coefficient gives 2.76% better performance than PLP. Wavelet Coefficients gives 14.79% better recognition performance than MFCC. A classifier is implemented by using Hidden Markov Model (HMM) on MATLAB for training and testing of Punjabi digits.
hdFilter: Toward faster Bloom filter-based packet forwarding

We propose Bloom filter-based data structure, hdFilter to improve the forwarding performance in Bloom filter-based packet forwarding architecture. hdFilter includes one Bloom filter for corresponding prefixes and one negative Bloom filter for some prefixes that cause the false positive. Through mathematical work and corresponding simulations, we show that hdFilter lowers the false positive rate (that affects the number of accesses to the slow memory) while showing the same fast memory access time or reduces the fast memory access time while showing similar false positive rate compared to normal Bloom filter.
Integration host factor is required for anaerobic pyruvate induction of pfl operon expression in Escherichia coli

The expression of the pyruvate formate-lyase gene (pfl) is induced by anaerobic growth, and this is increased further by growth in pyruvate. Previous work has shown that anaerobic induction is strongly dependent on the activator FNR and partially dependent on a second transcription factor, ArcA, while pyruvate induction only required FNR. Anaerobic and pyruvate regulation both require the presence of a 5' nontranslated regulatory sequence which spans approximately 500 bp of DNA. A mobility shift assay was developed to identify proteins that bind to this regulatory region. Several binding activities were separated by heparin agarose chromatography, and one of these activities was characterized and shown to be integration host factor (IHF). Mobility shift and DNase I footprinting experiments defined a single IHF binding site in the pfl promoter-regulatory region. With pfl-lacZ fusions, it could be shown that introduction of a himD mutation abolished pyruvate-dependent induction of anaerobic expression in vivo. The same result was observed when the pfl IHF binding site was mutated. In addition, the partial anaerobic induction of expression found in an fnr strain was completely blocked in an fnr himD double mutant and in an fnr IHF binding site double mutant. Taken together, these data suggest that IHF is necessary for both pyruvate induction and the anaerobic induction mediated by ArcA.
The Large-Scale Crowd Behavior Perception Based on Spatio-Temporal Viscous Fluid Field

Over the past decades, a wide attention has been paid to crowd control and management in the intelligent video surveillance area. Among the tasks for automatic surveillance video analysis, crowd motion modeling lays a crucial foundation for numerous subsequent analysis but encounters many unsolved challenges due to occlusions among pedestrians, complicated motion patterns in crowded scenarios, etc. Addressing the unsolved challenges, the authors propose a novel spatio-temporal viscous fluid field to model crowd motion patterns by exploring both appearance of crowd behaviors and interaction among pedestrians. Large-scale crowd events are hereby recognized based on characteristics of the fluid field. First, a spatio-temporal variation matrix is proposed to measure the local fluctuation of video signals in both spatial and temporal domains. After that, eigenvalue analysis is applied on the matrix to extract the principal fluctuations resulting in an abstract fluid field. Interaction force is then explored based on shear force in viscous fluid, incorporating with the fluctuations to characterize motion properties of a crowd. The authors then construct a codebook by clustering neighboring pixels with similar spatio-temporal features, and consequently, crowd behaviors are recognized using the latent Dirichlet allocation model. The convincing results obtained from the experiments on published datasets demonstrate that the proposed method obtains high-quality results for large-scale crowd behavior perception in terms of both robustness and effectiveness.
Modulation Schemes for Single-Phase B6 Converters With Two Asymmetrical Terminal Voltages

The B6 converter uses six switches divided equally among three phase legs. It has been commonly used as a three-phase rectifier or inverter, mostly under balanced conditions. Three-phase conversion, however, is not the only area where the B6 converter has been used. The same topology has been tried for single-phase power decoupling and single-phase ac–dc–ac conversion, where comparably lesser switches are needed. Although the basic modulation principle is still reliant on three modulating references for the three phase legs, requirements imposed on the modulating references are different and usually asymmetrical. How these asymmetrical references should be formulated to meet various performance specifications of a single-phase B6 converter is the theme of this paper. Simulation and experimental results have been obtained to verify the modulation schemes proposed.
Extended Target Tracking using a Gaussian-Mixture PHD Filter

This paper presents a Gaussian-mixture (GM) implementation of the probability hypothesis density (PHD) filter for tracking extended targets. The exact filter requires processing of all possible measurement set partitions, which is generally infeasible to implement. A method is proposed for limiting the number of considered partitions and possible alternatives are discussed. The implementation is used on simulated data and in experiments with real laser data, and the advantage of the filter is illustrated. Suitable remedies are given to handle spatially close targets and target occlusion.
Improved Engineering Design Strategy Applied to Prosthesis Modelling

The prosthesis design is a delicate and accurate engineering task that can be automated in the early steps before manufacturing. The challenge of the creation of the biomedical model is the complexity of the geometrical modelling as we have to deal with natural shapes. The representation of the human bones in terms of machining parameters the bottleneck in the design of complex products, and concurrent procedures can aid in this task. This work addresses the design requirements in order to build an anatomical skull prosthesis piece in the Computed Aided Design (CAD) systems. A novel methodology based on ellipse adjustment has been investigated in order to define the manufacture parameters. In geometric terms an ellipse seems with the bone? s border shape in a Computed Tomography (CT) slice. The arc that fills the correspondent failure in the bone border is extracted from the respective adjusted ellipse to each CT slice and the set of those extracted arcs can be superimposed to define the stack of images to build a 3D CAD model. Evolutionary Algorithms were also applied to improve the quality of data generated. A prototype was implemented by an open source Java based tool (ImageJ) in order to create synthetic defects to simulate problems in the 3D virtual skull model. In context of product development this approach brings an essential integration between design and manufacturing process to reduce the elapse time among the medical procedure, modelling and machining.
Marsupial teams of robots: deployment of miniature robots for swarm exploration under communication constraints

SUMMARY Mobile Ad hoc Networks have attracted much attention in the last years, since they allow the coordination and cooperation between agents belonging to a multi-robot system. However, initially deploying autonomously a wireless sensor robot network in a real environment has not taken the proper attention. Moreover, maintaining the connectivity between agents in real and complex environments is an arduous task since the strength of the connection between two nodes (i.e., robots) can change rapidly in time or even disappear. This paper compares two autonomous and realistic marsupial strategies for initial deployment in unknown scenarios, in the context of swarm exploration: Random and Extended Spiral of Theodorus. These are based on a hierarchical approach, in which exploring agents, named scouts, are autonomously deployed through explicit cooperation with supporting agents, denoted as rangers. Experimental results with a team of heterogeneous robots are conducted using both real and virtual robots. Results show the effectiveness of the methods, using a performance metric based on dispersion. Conclusions drawn in this work pave the way for a whole series of possible new approaches.
Biogeography and community structure of abyssal scavenging Amphipoda (Crustacea) in the Pacific Ocean

Abstract. In 2015, we collected more than 60 000 scavenging amphipod specimens during two expeditions to the Clarion–Clipperton fracture zone (CCZ) in the Northeast (NE) Pacific and to the DISturbance and re-COLonisation (DisCOL) experimental area (DEA), a simulated mining impact disturbance proxy in the Peru Basin in the Southeast (SE) Pacific. Here, we compare biodiversity patterns of the larger specimens (>15 mm) within and between these two oceanic basins. Eight scavenging amphipod species are shared between these two areas, thus indicating connectivity. Overall diversity was lower in the DEA (Simpson index, D = 0.62), when compared to the CCZ (D=0.73), and particularly low at the disturbance site in the DEA and the site geographically closest to it. Local differences within each basin were observed too. The community compositions of the two basins differ, as evidenced by a non-metric dimensional scaling (NMDS) analysis of beta biodiversity. Finally, a single species, Abyssorchomene gerulicorbis (Schulenberger and Barnard, 1976), dominates the DEA with 60 % of all individuals.
Post Extraction Using Title Finding

Linhai Song , Xueqi Cheng, Yan Guo, Bo Wu , Yu Wang 2 1 Institute of Computing Technology, Chinese Academy of Sciences, Beijing 2 Graduate School of the Chinese Academy of Sciences, Beijing Abstract: With the development of Web2.0, web mining applications pay more attention to blog pages. In order to prevent noises in blog pages from affecting the precision of web mining algorithms, it is very necessary to acquire posts from blog pages correctly. In this paper, we propose a blog post extraction algorithm which uses title finding. There are two stages in this algorithm. In the first stage, text nodes which indicate the title of the post are found and used as the beginning of the post. We take a machine learning approach to realize this stage, and employ SVM as classification model. In the second stage, we find the end of the post. Two methods are introduced in this stage, one uses VIPS segmentation results, and the other is based on hand-coded rules. Experiments are conducted to see how we find titles and how we extract posts. Experimental results show that our algorithm has ideal effects.