Miracle-dz/UniFAR-FTUs huggingface dataset:
Recognizing planned, multi-person action

Multi-person action recognition requires models of structured interaction between people and objects in the world. This paper demonstrates how highly structured, multi-person action can be recognized from noisy perceptual data using visually grounded goal-based primitives and low-order temporal relationships that are integrated in a probabilistic framework. The representation, which is motivated by work in model-based object recognition and probabilistic plan recognition, makes four principal assumptions: (1) the goals of individual agents are natural atomic representational units for specifying the temporal relationships between agents engaged in group activities, (2) a high-level description of temporal structure of the action using a small set of low-order temporal and logical constraints is adequate for representing the relationships between the agent goals for highly structured, multi-agent action recognition, (3) Bayesian networks provide a suitable mechanism for integrating multiple sources of uncertain visual perceptual feature evidence, and (4) an automatically generated Bayesian network can be used to combine uncertain temporal information and compute the likelihood that a set of object trajectory data is a particular multi-agent action. The recognition method is tested using a database of American football play descriptions and manually-acquired but noisy player trajectories. The strengths and limitations of the system are discussed and compared with other multi-agent recognition algorithms.
Palm vein biometric identification system using local derivative pattern

This paper explains about the implementation of Local Derivative Pattern (LDP) as feature extraction algorithm and Histogram Intersection matching algorithm in a palm vein-based biometric identification system. LDP has been able to take on the image of the palm vein characteristics based on gray level differences of a pixel compared to adjacent pixels in the form of histogram. It is added by directional feature characteristic and it has order and radius parameters. Histogram Intersection method is used to calculate the similarity value of histogram characteristic between model and test data. The greater the matching value obtained, the more similar those histogram characteristics. This study showed the efficiency of LPD feature extraction algorithms which was able to get the best accuracy of 98.3%, with the configuration parameters: order value 2, radius 12, and image partition 4×4. Further testing was also done and obtains an optimal threshold value, which is about 37.2, generating FAR and FRR of 0.01 and 0.01 respectively.
Using affective state to adapt characters, NPCs, and the environment in a first-person shooter game

Innovations in computer game interfaces continue to enhance the experience of players. Affective games - those that adapt or incorporate a player's emotional state - have shown promise in creating exciting and engaging user experiences. However, a dearth of systematic exploration into what types of game elements should adapt to affective state leaves game designers with little guidance on how to incorporate affect into their games. We created an affective game engine, using it to deploy a design probe into how adapting the player's abilities, the enemy's abilities, or variables in the environment affects player performance and experience. Our results suggest that affectively adapting games can increase player arousal. Furthermore, we suggest that reducing challenge by adapting non-player characters is a worse design choice than giving players the tools that they need (through enhancing player abilities or a supportive environment) to master greater challenges.
Performance of the Charge-Injection Capability of Suzaku XIS

A charge-injection technique is applied to the X-ray CCD camera, XIS (X-ray Imaging Spectrometer) aboard Suzaku. The charge transfer inefficiency (CTI) in each CCD column (vertical transfer channel) is measured by the injection of charge packets into a transfer channel and subsequent readout. This paper reports on the performances of the charge-injection capability based on the ground experiments using a radiation-damaged device, and in-orbit measurements of the XIS. The ground experiments show that charges are stably injected with a dispersion of 91 eV in FWHM in a specific column for the charges equivalent to an X-ray energy of 5.1 keV. This dispersion width is significantly smaller than that of the X-ray events of 113 eV (FWHM) at approximately the same energy. The amount of charge loss during transfer in a specific column, which is measured with the charge-injection capability, is consistent with that measured with the calibration source. These results indicate that the charge-injection technique can accurately measure column-dependent charge losses, rather than the calibration sources. The column-to-column CTI correction to the calibration source spectra significantly reduces the line widths compared to those with a columnaveraged CTI correction (from 193 eV to 173 eV in FWHM on an average at the time of one year after the launch). In addition, this method significantly reduces the low-energy tail in the line profile of the calibration source spectrum.
A Diamond for the Poor ? Assessing Porter ’ s Diamond Model for the Analysis of Agro-Food Clusters in the Developing Countries

Clusters are a critical way for agri-food SMEs to be(come) competitive in this era of globalization. Several theoretical models (e.g., flexible specialization, collective efficiency) have been developed to study clusters. One prominent model, Porter’s diamond model, has been ignored in cluster research in developing countries. This paper argues that this is not justified and that Porter’s more holistic diamond model is superior in explaining cluster dynamics.
Single Machine Scheduling with Job Delivery to minimize makespan

In the single machine scheduling problem with job delivery to minimize makespan, jobs are processed on a single machine and delivered by a capacitated vehicle to their respective customers. We first consider the special case with a single customer, that is, all jobs have the same transportation time. Chang and Lee (2004) proved that this case is strongly NP-hard. They also provided a heuristic with the worst-case performance ratio $\frac{5}{3}$, and pointed out that no heuristic can have a worst-case performance ratio less than $\frac{3}{2}$ unless P = NP. In this paper, we provide a new heuristic which has the best possible worst-case performance ratio $\frac{3}{2}$. We also consider an extended version in which the jobs have non-identical transportation times and the transportation time of a delivery batch is defined as the maximum transportation time of the jobs contained in it. We provide a heuristic with the worst-case performance ratio 2 for the extended version, and show that this bound is tight.
Socio-situational setting classification based on language use

We present a method for automatic classification of the socio-situational setting of a conversation based on the language used. The socio-situational setting depicts the social background of a conversation which involves the communicative goals, number of speakers, number of listeners and the relationship among the speakers and the listeners. Knowledge of the socio-situational setting can be used to search for content recorded in a particular setting or to select context-dependent models for example for speech recognition. We investigated the performance of different feature sets of conversation level features and word level features and their combinations on this task. Our final system, that classifies the conversations in the Spoken Dutch Corpus in one of 14 socio-situational settings, achieves an accuracy of 89.55%.
Estimation of Saccadic Ratio from eye image sequences to detect human alertness

Saccadic Ratio (SR), a ratio between Peak Saccadic Velocity and the Saccadic Duration, exhibits correlation with human alertness. A simple non-linear model of horizontal saccade with input as the position of pupil center relative to the corners is proposed. The relative position of pupil center is initially determined using recently developed method based on horizontal, and vertical form factors and edge detection method based on local form factor. An Extended Kalman filter based algorithm has been developed to estimate the saccadic velocity and the saccadic ratio from this initial information for eye image video database captured with a speed higher than 60 fps. A Kalman filter based technique is also applied on the same database and the results are compared with that of the proposed method. Correlation of SR with a questionnaire based alertness assessment index is investigated. The experimental results indicate that the estimated SR by the proposed method is highly correlated with state of human alertness.
Object-Oriented Ontogenetic Programming: Breeding Computer Programs that Work Like Multicellular Creatures

As the research field called Genetic Programming has shown during the last decade, it is possible not only to write computer programs by hand but also to let the computer itself develop programs that solve given problems. This is achieved by simulating natural evolution on the computer for “breeding” programs that are well adapted to a specific problem environment. The use of mechanisms found in nature can lead to solutions to complex problems that by far outperform any man-made approaches. The reasons are that complex problems often are difficult to solve analytically and many other possible approaches are not accessible to the human way of thinking. The use of the mechanisms of evolution based on genetic variation and “survival of the fittest” is only one example. Another example are Artificial Neural Networks that imitate clusters of nervous cells and their interactions for solving difficult problems (inspired among others by the human brain). The here presented work explores a different and new approach to adopting problem solving methods found in nature. It uses the natural cell control mechanism called Gene Regulation that according to modern molecular genetics is the basis of the cooperation between and differentiation into all the different cells in living creatures. The most astonishing example of self-organization between simple units that cooperate to solve complex problems is not the interaction between nervous cells on the basis of mutual electrical activation through explicit and directed connections. It is the interaction between all kinds of cells in a living creature which is based on the diffusion of messages in the form of produced substances. This interaction is much more powerful and flexible than the neural interaction because of many reasons. The main reason is, that a cell in this context is not only a simple unit which can have different levels of activation, but it is a complex system with many behavioural possibilities. The communication between the cells not only bases on different activation intensities but on many different message types which (also depending on their intensity) can have very sophisticated effects on the behaviour of a cell. This new programming and control paradigm has been combined with genetic programming for breeding “multicellular” programs (which probably is the only feasible way of producing them). The system that implements this combination can not only be used to create programs with a new modular structure which has several advantages. It also is a great tool for developing systems of cooperating autonomous units like Amorphous Computers and Multiagent Systems.
Statistical Modeling of SAR Images: A Survey

Statistical modeling is essential to SAR (Synthetic Aperture Radar) image interpretation. It aims to describe SAR images through statistical methods and reveal the characteristics of these images. Moreover, statistical modeling can provide a technical support for a comprehensive understanding of terrain scattering mechanism, which helps to develop algorithms for effective image interpretation and creditable image simulation. Numerous statistical models have been developed to describe SAR image data, and the purpose of this paper is to categorize and evaluate these models. We first summarize the development history and the current researching state of statistical modeling, then different SAR image models developed from the product model are mainly discussed in detail. Relevant issues are also discussed. Several promising directions for future research are concluded at last.
The Culturable Soil Antibiotic Resistome: A Community of Multi-Drug Resistant Bacteria

Understanding the soil bacterial resistome is essential to understanding the evolution and development of antibiotic resistance, and its spread between species and biomes. We have identified and characterized multi-drug resistance (MDR) mechanisms in the culturable soil antibiotic resistome and linked the resistance profiles to bacterial species. We isolated 412 antibiotic resistant bacteria from agricultural, urban and pristine soils. All isolates were multi-drug resistant, of which greater than 80% were resistant to 16–23 antibiotics, comprising almost all classes of antibiotic. The mobile resistance genes investigated, (ESBL, bla NDM-1, and plasmid mediated quinolone resistance (PMQR) resistance genes) were not responsible for the respective resistance phenotypes nor were they present in the extracted soil DNA. Efflux was demonstrated to play an important role in MDR and many resistance phenotypes. Clinically relevant Burkholderia species are intrinsically resistant to ciprofloxacin but the soil Burkholderia species were not intrinsically resistant to ciprofloxacin. Using a phenotypic enzyme assay we identified the antibiotic specific inactivation of trimethoprim in 21 bacteria from different soils. The results of this study identified the importance of the efflux mechanism in the soil resistome and variations between the intrinsic resistance profiles of clinical and soil bacteria of the same family.
Scalable Iterative Graph Duplicate Detection

Duplicate detection determines different representations of real-world objects in a database. Recent research has considered the use of relationships among object representations to improve duplicate detection. In the general case where relationships form a graph, research has mainly focused on duplicate detection quality/effectiveness. Scalability has been neglected so far, even though it is crucial for large real-world duplicate detection tasks. We scale-up duplicate detection in graph data (DDG) to large amounts of data and pairwise comparisons, using the support of a relational database management system. To this end, we first present a framework that generalizes the DDG process. We then present algorithms to scale DDG in space (amount of data processed with bounded main memory) and in time. Finally, we extend our framework to allow batched and parallel DDG, thus further improving efficiency. Experiments on data of up to two orders of magnitude larger than data considered so far in DDG show that our methods achieve the goal of scaling DDG to large volumes of data.
Biometric data encryption using 3-D chaotic system

Biometrics is gaining a lot of popularity as a tool to authenticate an individual using the unique biometric attributes. The exchange of biometric data over unsecured network channels makes it vulnerable to breach of security by illegal access. To overcome this challenge this paper proposes an efficient and secured chaos based encryption scheme having exceptionally desirable complex behavior which is difficult to predict and analyze. In this paper for shuffling the pixels of biometric data Arnold cat map is used and diffusion is also introduced after scrambling to make the encryption process non invertible. This method uses 3-D Chen chaotic system to change the statistical properties of biometric data so as to resist statistical attacks. Experimental results also show the resistant of proposed algorithm against perceptual and brute force attacks makes it suitable for transmission of biometric data over open and shared networks.
Context-aware TLB preloading for interference reduction in embedded multi-tasked systems

Rapid system responsiveness and execution time predictability are of significant importance for a large class of real-time embedded systems. Multi-tasking leads to interference in the shared processor resources such as caches and TLBs, which in turn results in not only deteriorated performance but also, and for some applications even more importantly, highly suboptimal worst-case execution time (WCET) estimates due to the interference unpredictability. We present a methodology for task-aware D-TLB interference reduction and preloading through an application-specific task's state introspection at context-switch time for embedded multitasking. The proposed technique addresses the problem through a synergistic cooperation between the compiler, for an application-specific analysis of the task's context, and the OS, for a run-time introspection of the context and an efficient identification of TLB entries of current (live) and of "near-future" usage.
CellTracker Green labelling vs. rose bengal staining: CTG wins by points in distinguishing living from dead anoxia-impacted copepods and nematodes

Hypoxia and anoxia have become a key threat to shallow coastal seas. Much is known about their impact on macrofauna, less on meiofauna. In an attempt to shed more light on the latter group, in particular from a process-oriented view, we experimentally induced short-term anoxia (1 week) in the northern Adriatic Sea (Mediterranean) and examined the two most abundant meiofauna taxa - harpacticoid cope- pods and nematodes. Both taxa also represent different ends of the tolerance spectrum, with copepods being the most sen- sitive and nematodes among the most tolerant. We compared two methods: CellTracker Green (CTG) - new labelling ap- proach for meiofauna - with the traditional rose bengal (RB) staining method. CTG binds to active enzymes and therefore colours live organisms only. The two methods show consid- erable differences in the number of living and dead individ- uals of both meiofauna taxa. Generally, RB will stain dead but not yet decomposed copepods and nematodes equally as it does live ones. Specifically, RB significantly overesti- mated the number of living copepods in all sediment layers in anoxic samples, but not in any normoxic samples. In con- trast, for nematodes, the methods did not show such a clear difference between anoxia and normoxia. RB overestimated the number of living nematodes in the top sediment layer of normoxic samples, which implies an overestimation of the overall live nematofauna. For monitoring and biodiversity studies, the RB method might be sufficient, but for more pre- cise quantification of community degradation, especially af- ter an oxygen depletion event, CTG labelling is a better tool. Moreover, it clearly highlights the surviving species within the copepod or nematode community. As already accepted for foraminiferal research, we demonstrate that the CTG la- belling is also valid for other meiofauna groups.
Determination of the critical exponents for the isotropic-nematic phase transition in a system of long rods on two-dimensional lattices: Universality of the transition

Monte Carlo simulations and finite-size scaling analysis have been carried out to study the critical behavior and universality for the isotropic-nematic phase transition in a system of long straight rigid rods of length k (k-mers) on two-dimensional lattices. The nematic phase, characterized by a big domain of parallel k-mers, is separated from the isotropic state by a continuous transition occurring at a finite density. The determination of the critical exponents, along with the behavior of Binder cumulants, indicate that the transition belongs to the 2D Ising universality class for square lattices and to the three-state Potts universality class for triangular lattices.
Mental Attribution in Interaction: How the Second Person Perspective dissolves the Problem of Other Minds

In this paper, we will address the question of the impact of the second person perspective of psychological attribution on the traditional problem of knowing other minds. With that purpose in mind, we will introduce the notion of a second-personal perspective of mental attribution within the context of the classical problem of other minds, and discuss the epistemic and ontological implications that follow once the second person perspective is honored. In particular, we will examine how its recognition transforms the traditional problem of other minds, both in its epistemological, ontological and semantical dimensions, and offers a way to go beyond the objective/subjective dichotomy of Modern Philosophy. A proper notion of intersubjectivity, we will argue, is not a simple addition to this dichotomy, but it offers the way to get over the traditional philosophical problems that follow from this modern philosophical paradigm.
Polyreference Frequency-Domain Least-Squares Estimation with Confidence Intervals

The PolyMAX estimator is used intensively in modal analysis applications nowadays. The main advantages are its speed and the very clear stabilization diagrams it yields. Recently, an algorithm allowing a fast calculation of confidence intervals has been derived for frequency-domain least-squares estimators based on a common-denominator model. In this contribution, the approach is extended to the PolyMAX estimator, i.e. a polyreference frequency-domain least-squares estimator, based on a right matrix-fraction description. If the coherences of the measured frequency response functions (FRFs) are available, the covariance matrix of the estimated model parameters can be obtained without major additional calculations. The confidence intervals can then be calculated in a second step. The correctness of the approach is verified by means of Monte Carlo simulations. NOMENCLATURE Hm(Ω f ) FRF right matrix-fraction model H(Ω f ) measured FRF N(Ω f ) numerator matrix polynomial D(Ω f ) denominator matrix polynomial No(Ω f ) Numerator matrix polynomial for output o Ω f polynomial basis function θ coefficients matrix θD denominator coefficients matrix θNo numerator coefficients matrix ε(Ω f , θ,H) error equation W(ω f ) weighting matrix in error equation J jacobian matrix Γo jacobian submatrix corresponding to numerator coefficients Υ jacobian submatrix corresponding to denominator coefficients (.)T matrix transpose M reduced normal equations Ro reduced normal equations submatrix So reduced normal equations submatrix To reduced normal equations submatrix I identity matrix , by definition ∆H perturbation on the FRF ∆θD perturbation on the denominator coefficients ∆M perturbation on the reduced normal equations ∆Υ perturbation on the Υ jacobian submatrix Ξ covariance matrix submatrix Cov(.) covariance matrix δi j kronecker delta (1 if i = j, 0 elsewhere) Re(.) taking real part Im(.) taking imaginary part Dcom companion matrix Vr eigenvector of companion matrix λr eigenvalue of companion matrix Lr modal participation vector P weighting matrix for covariance matrix . m mth iteration γ2 multiple coherence function Syy autopower spectrum of outputs S f f autopower spectrum of outputs