Miracle-dz/UniFAR-FTUs huggingface dataset:
Action selection through affective states modelling

We introduce an action selection framework for the advanced behavioural animation of virtual creatures. In modern creative media, the behavioural animation of characters which act in a believable fashion is an ongoing challenge. Traditional action selection approaches which attempt to make an agent act rationally often fall short of the believability required for the modern consumer. Often the most believable action is not the most rational one, and our judgement of an agent's behaviour may also be based on the perception of its personality. Our approach, Affective Spaces Modelling, addresses these issues by creating a multi-dimensional environment constructed of aspect dimensions, with each aspect dimension representing a linear scale of a single component of the agent's internal state. Affective states can then be modelled by placing them in a single point in this environment. As the agent's state changes within the affective state space, different affects trigger appropriate actions. We demonstrate through a case study how the technique can be used to simulate different types of agent behaviour, operating both individually and as part of a group. Our case studies focus on groups of agents, allowing for the direct comparison of different personalities and examples of behavioural phenomena.
Load Balancing a Cluster of Web Servers using Distributed Packet Rewriting

In this paper, we present and evaluate an implementation of a prototype scalable web server. The prototype consists of a load-balanced cluster of hosts that collectively accept and service TCP connections. The host IP addresses are advertised using the Round Robin DNS (RR-DNS) technique, allowing any host to receive requests from any client. Once a client attempts to establish a TCP connection with one of the hosts, a decision is made as to whether or not the connection should be redirected to a different host---namely, the host with the lowest number of established connections. We use the low-overhead Distributed Packet Rewriting (DPR) technique [Bestavros, Crovella, Liu, and Martin 1998] to redirect TCP connections. In our prototype, each host keeps information about the remaining hosts in the system. Load information is maintained using periodic multicast amongst the cluster hosts. Performance measurements suggest that our prototype outperforms both pure RR-DNS and the stateless DPR solutions.
Attitude control of a Quadrotor using Brain Emotional Learning Based Intelligent Controller

For the first time in this paper, Brain Emotional Learning Based Intelligent Controller (BELBIC) is applied to attitude control of a Quadrotor. BELBIC controller is designed based on the computational model of emotional learning process in mammalian brain limbic system. Proposed control algorithm is employed because of the learning ability and independency to system model and also satisfactory performances dealing with disturbances and changing in system parameters. Quadrotor is an Unmanned Aerial Vehicle (UAV) which has the capability of Vertical Take-Off and Landing (VTOL). Simulation results of controlling Quadrotor with BELBIC are addressed. Also pitch angle disturbance is applied due to examine system performances.
Real-Time Body Tracking with One Depth Camera and Inertial Sensors

In recent years, the availability of inexpensive depth cameras, such as the Microsoft Kinect, has boosted the research in monocular full body skeletal pose tracking. Unfortunately, existing trackers often fail to capture poses where a single camera provides insufficient data, such as non-frontal poses, and all other poses with body part occlusions. In this paper, we present a novel sensor fusion approach for real-time full body tracking that succeeds in such difficult situations. It takes inspiration from previous tracking solutions, and combines a generative tracker and a discriminative tracker retrieving closest poses in a database. In contrast to previous work, both trackers employ data from a low number of inexpensive body-worn inertial sensors. These sensors provide reliable and complementary information when the monocular depth information alone is not sufficient. We also contribute by new algorithmic solutions to best fuse depth and inertial data in both trackers. One is a new visibility model to determine global body pose, occlusions and usable depth correspondences and to decide what data modality to use for discriminative tracking. We also contribute with a new inertial-based pose retrieval, and an adapted late fusion step to calculate the final body pose.
A method of estimating the equal error rate for automatic speaker verification

In an automatic speaker verification (ASV) system, the equal error rate (EER) is a measure to evaluate the system performance. Usually it needs a large number of testing samples to calculate the EER. In order to estimate the EER without running the experiments using testing samples, a method of model-based EER estimation which computes likelihood scores directly from client speaker models and imposter models is proposed. However, the distribution of the computed likelihood scores is significantly biased against the distribution of likelihood scores obtained from testing samples. Here we propose a novel idea to manipulate the speaker models of the client speakers and the imposters so that the distribution of the computed likelihood scores is closer to the distribution of likelihood scores obtained from testing samples. Then a more reliable EER can be calculated by the speaker models. The experimental results show that the proposed method can properly estimate the EER.
HEVC vs . H . 264 / AVC Through Performance and Complexity Comparison

The main goal of the High Efficiency Video Coding (HEVC) standardization effort was to enable significantly improved compression performance relative to existing standards-in the range of 50% bit-rate reduction for equal perceptual video quality. In order to compare the performance and complexity without significant rate-distortion performance degradation, the HEVC coder vs. H.264/AVC coder are tested for the fixed Quantization Parameter (QP) value, when Main profile, appropriate motion vector (MV) search ranges and hierarchical B pictures are used. Simulation results have shown that the bit-rate is reduced up to 50%, while the encoding time saving is reached over 70% depending on the tested video sequence, when reference HEVC software HM-15.0 is compared to reference H.264/AVC software JM 18.6. However, there was negligible loss in term Signal-to-Noise Ratio (SNR). Key-Words: H.264/AVC standard, HEVC standard, Encoding time saving, Signal-to-Noise ratio, Bit-rate reduction.
Fast and reliable structure-oriented video noise estimation

Noise can significantly impact the effectiveness of video processing algorithms. This paper proposes a fast white-noise variance estimation that is reliable even in images with large textured areas. This method finds intensity-homogeneous blocks first and then estimates the noise variance in these blocks, taking image structure into account. This paper proposes a new measure to determine homogeneous blocks and a new structure analyzer for rejecting blocks with structure. This analyzer is based on high-pass operators and special masks for corners to stabilize the homogeneity estimation. For typical video quality (PSNR of 20-40 dB), the proposed method outperforms other methods significantly and the worst-case estimation error is 3 dB, which is suitable for real applications such as video broadcasts. The method performs well both in highly noisy and good-quality images. It also works well in images including few uniform blocks.
Liposomes Loaded with Hydrophobic Iron Oxide Nanoparticles: Suitable T2 Contrast Agents for MRI

There has been a recent surge of interest in the use of superparamagnetic iron oxide nanoparticles (SPIONs) as contrast agents (CAs) for magnetic resonance imaging (MRI), due to their tunable properties and their low toxicity compared with other CAs such as gadolinium. SPIONs exert a strong influence on spin-spin T2 relaxation times by decreasing the MR signal in the regions to which they are delivered, consequently yielding darker images or negative contrast. Given the potential of these nanoparticles to enhance detection of alterations in soft tissues, we studied the MRI response of hydrophobic or hydrophilic SPIONs loaded into liposomes (magnetoliposomes) of different lipid composition obtained by sonication. These hybrid nanostructures were characterized by measuring several parameters such as size and polydispersity, and number of SPIONs encapsulated or embedded into the lipid systems. We then studied the influence of acyl chain length as well as its unsaturation, charge, and presence of cholesterol in the lipid bilayer at high field strength (7 T) to mimic the conditions used in preclinical assays. Our results showed a high variability depending on the nature of the magnetic particles. Focusing on the hydrophobic SPIONs, the cholesterol-containing samples showed a slight reduction in r2, while unsaturation of the lipid acyl chain and inclusion of a negatively charged lipid into the bilayer appeared to yield a marked increase in negative contrast, thus rendering these magnetoliposomes suitable candidates as CAs, especially as a liver CA.
Consumption of unpasteurized milk and its effects on atopy and asthma in children and adult inhabitants in rural Poland

Consumption of unpasteurized cow's milk has been identified as a possible protective factor for atopy and asthma. Most studies have been conducted among children and in farming populations. We investigated the effects of consumption of unpasteurized milk in early life on atopy, asthma, and rhinitis in village and town inhabitants in a region of Poland and assessed whether any protective effects of milk consumption differed according to place of residence and farming status.
Book Chapter Supplement : Structured Learning from Cheap data

In this supplement we theoretically analyze the problem of learning with partially annotated outputs. We need a more refined notation as in the book chapter: we denote Y◦(y) and Y◦(y) for the space of all outputs that compatible and non-compatible, respectively, with y. Thus, for example, the term Y◦ n in the book chapter is denoted by Y(yn) here. We also use a more little different notation for the loss l (see below).
Attention Identification via Relative Saliency of Localized Crowd Faces

While viewing a crowd, the human vision automatically gets focused towards the most attentive face. This happens when a particular face in the crowd dominates the other faces in terms of beauty, expression, color, shape, size and structure, etc. Human attention towards such faces happens due to its higher visual saliency values. A computer vision system can be modeled based on this aspect of human psychology. Visual saliency of a face in a crowd may vary according to many parameters. In this paper, we propose a novel method to calculate the distribution of visual saliency of faces in the crowd based on their feature difference, spatial distance and size. This method has been tested on various crowd images and inspiring results have been found. Therefore, this can be used to mimic the cognitive behavior of the human vision system to create artificially intelligent computer vision systems.
Access ordering and memory-conscious cache utilization

As processor speeds increase relative to memory speeds, memory bandwidth is rapidly becoming the limiting performance, factor for many applications. Several approaches to bridging this performance gap have been suggested. This paper examines one approach, access ordering, and pushes its limits to determine bounds on memory performance. We present several access-ordering schemes, and compare their performance, developing analytic models and partially validating these with benchmark timings on the Intel i860XR. <<ETX>>
The improved breathability of polyurethane coated cotton fabric via micro-cracking

Abstract Polyurethane (PU) coating became popular in the last decades to achieve water resistance garment fabrics with enhanced visual properties. But reduced breathability of coated fabric is a setback for clothing industry. This paper represents a facile method of enhancing breathability (air and water vapor permeability) of PU coated fabrics which may be so-called micro-cracking in relevant solvent bath differed in solvent bath, concentration, and duration time. The samples were subjected to air permeability, water vapor permeability, water resistance, and tensile strength measurements and the results were also statistically analyzed. The study showed that the proposed process increased water vapor and air permeability of coated but the permeability values were still significantly lower than that of uncoated sample. This result is also verified through water resistance measurements and; tensile strength of the samples were affected at minimum after micro-cracking.
Kinematic analysis and path planning of a new kinematically redundant planar parallel manipulator

SUMMARY In this work, the 3-RPRR, a new kinematically redundant planar parallel manipulator with six-degrees-of-freedom, is presented. First, the manipulator is introduced and its inverse displacement problem discussed. Then, all types of singularities of the 3-RPRR manipulator are analysed and demonstrated. Thereafter, the dexterous workspace is geometrically obtained and compared with the non-redundant 3-PRR planar parallel manipulator. Finally, based on a geometrical measure of proximity to singular configurations and the condition number of the manipulators' Jacobian matrices, actuation schemes for the manipulators are obtained. Different actuation schemes for a given path are obtained and the quality of their actuation schemes are compared. It is shown that the proposed manipulator is capable of following a path while avoiding the singularities.
The Study on the Influential Factors of Photocatalytic Performance of Eosin-Sensitized TiO2 Nanoparticles

The photocatalytic activity of eosin-sensitized TiO2 nanoparticles on photocatalytic degradation rate (PDR) of methyl orange under sunlight irradiation was studied. The influential factors on the degradation, such as eosin concentration, TiO2 dosage, sensitization time and sensitization temperature were also investigated. The results show that: The performance of TiO2 nanoparticles for PDR of methyl orange has been improved obviously for eosin sensitizing. The PDR of methyl orange reached 45.28% under the conditions of eosin concentration of 20mg/L, TiO2 dosage of 0.5000g/L, sensitization time of 24h and sensitization temperature of 20°C.
Who is the hero? semi-supervised person re-identification in videos

Given a crowd-sourced set of videos of a crowded public event, this paper addresses the problem of detecting and re-identifying all appearances of every individual in the scene. The persons are ranked according to the frequency of their appearance and the rank of a person is considered as the measure of his/her importance. Grouping appearances of every person from such videos is a very challenging task. This is due to unavailability of prior information or training data, large changes in illumination, huge variations in camera viewpoints, severe occlusions and videos from different photographers. These problems are made tractable by exploiting a variety of visual and contextual cues i.e., appearance, sensor data and co-occurrence of people. A unified framework is proposed for efficient person matching across videos followed by their ranking. Experimental results on two challenging video data sets demonstrate the effectiveness of the proposed algorithm.
Data Fusion for Ground Moving Target Tracking

The aim of ground surveillance is the large scale, continuous and near real time determination of a dynamical ground picture. This task comprises detection and tracking of moving single targets and convoys, mobile weapon systems, and military equipment. The sensors of choice are airborne GMTI-radar (GMTI: ground moving target indicator) and SAR (synthetic aperture radar). As ground target tracking often suffers from dense target situations, high clutter, and low visibility, the integration and fusion of external background information is essential for providing precise and continuous tracks. We present multi hypotheses techniques for tracking several targets in complex ground situations with clutter. Methods to incorporate topographic information, in particular digital road maps, are described and demonstrated
Myofascial Pain Syndromes – Trigger Points Literature

During the past few months, several new studies, reviews and case studies on myofascial pain syndrome [MPS] and myofascial trigger points [TrPs] have been published. Myofascial pain syndrome and TrPs are increasingly being recognized not only in the United States, but also in Europe. Testa and colleagues [Milan, Italy] published an excellent review article detailing the clinical signs that lead to the diagnosis of MPS. Chaitow and Delany published a review article in an orthopedic journal, which may indicate an increasing acceptance of the concepts of MPS and TrPs by a medical discipline that previously has expressed little or no interest in the subject matter. Three other articles emphasized that MPS needs to be included in the differential diagnostic process of radiculopathy, dental pain, and pelvic pain, respectively. New referred pain patterns were described from TrPs in the iliopsoas muscle causing knee pain and in the splenius capitis muscle causing tinnitus. Several articles on the use of botulinum toxin and MPS appeared in the literature. Following the integrated TrP hypothesis that suggests that excessive release of acetylcholine at the motor endplate leads to the formation of TrPs, the use of botulinum toxin is likely to increase particularly for persistent MPS that has not responded well to other TrP therapy (1). After 10 years of preparing this review of the pertinent literature on MPS and TrPs, David Simons welcomes the assistance of physical therapist Jan Dommerholt in preparing this review column. Each article review indicates whether it is prepared by Simons [DGS] or Dommerholt [JD].
Information Retrieval eXperience (IRX): Towards a Human-Centered Personalized Model of Relevance

We approach Information Retrieval (IR) from a User eXperience (UX) perspective. Through introducing a model for Information Retrieval eXperience (IRX), this paper operationalizes a perspective on IR that reaches beyond topicality. Based on a document's topicality, complexity, and emotional value, a model of relevance is proposed to influence user's IRX and, consequently, the synthesis and use of the retrieved information. Additionally, methods are discussed to assess UX through interaction and feedback mechanisms. As such, the proposed multi-dimensional IRX model is highly user-dependent and determines document's relevance from a non-traditional human-centered, personalized perspective on IR.
Chapter 6 Metacognitive Control of Learning and Remembering

The study of learning and memory has a long and veritable history in psychological research. One recent and important development is the growth of research in metamemory—the study of what people understand about their memory and how they use that knowledge to direct their own learning experiences in service of their goals. Metamemory research has been guided in part by the framework proposed by Nelson and Narens (1994), which differentiates between metacognitive monitoring of one’s states of learning and metacognitive control over the processes by which one achieves desired levels of skill and memory. These processes are guided by learners’ knowledge and beliefs about how memory works, about what aspects of performance are reliable indicators of durable learning, and about what actions are effective for advancing learning (cf. Dunlosky & Hertzog, 2000; Hertzog, Dunlosky, & Robinson, 2007). This chapter will discuss the role of metacognition in the learning of simple verbal materials, with a particular emphasis on metacognitive control. Learners can regulate their study experience to enhance learning in a myriad of ways (cf. Benjamin, 2008; Dunlosky, Serra, & Baker, 2007; Serra & Metcalfe, 2009). Here we consider forms of control that have been studied in simple laboratory tasks and that generalize in a straightforward way to options available to students studying for tests: self-pacing study effectively, devising efficient study schedules, judiciously selecting items for study and re-study, strategically making use of selftesting strategies, accommodating study to anticipated test conditions, and using successful retrieval strategies. We will review research that reveals how learners use these strategies in simple laboratory tasks and that suggests how such metacognitive skills can be improved through instruction or experience. We will end by addressing the supportive role that information technology can play in the processes by which metacognition influences learning and memory.
Do Redundant Mutants Affect the Effectiveness and Efficiency of Mutation Analysis?

Mutation analysis is an unbiased and powerful method for assessing input values and test oracles. However, in comparison to other techniques, such as those that rely on code coverage, it is a computationally-expensive and time-consuming method, especially for large software systems. This high cost is due, in part, to the fact that many mutation operators generate redundant mutants that may both misrepresent the mutation score and increase the runtime of the mutation analysis process. After showing how the conditional operator replacement(COR) mutation operator can be defined in a redundant-free manner, this paper uses four real-world programs, ranging in size from 3,000 to nearly 40,000 lines of code, to show the prevalence of redundant mutants. Focusing on the conditional operator replacement (COR)and relational operator replacement (ROR) mutation operators that create 41% of all mutants in the chosen programs, the case study reveals that the removal of redundant mutants reduces the runtime of mutation analysis by up to 34%. Additional empirical results show that redundant mutants can lead to a mutation score that is misleadingly overestimated by as much as 10%. Overall, this paper convincingly demonstrates that it is possible to improve the effectiveness and efficiency of a mutation analysis system by identifying and removing redundant mutants.
Expressive Logical Framework for Reasoning about Complex Events and Situations

Business and enterprise management processes become more and more event-driven. Being event-driven means that processes rely on receiving events to monitor the execution progress, and issuing events to initiate its next stages. What is more important, being event-driven enables these processes to become more active and flexible. There is a paradigm shift today from passive processes to active ones (based on push of information rather than on pull of information and knowledge). Also the management of business processes needs to be flexible, i.e, to adapt to ad hoc changes (events) during operations. All these requirements suggest use of Complex Event Processing (i.e., event patterns, event pattern rules, and event constraints) for realising event-driven business processes. We implement these concepts in a completely logical framework using Concurrent Transaction Logic (CT R). Particularly, CT R is used for specifying, reasoning, and executing event-driven activities.