Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatiotemporal gesture segmentation

Spotting patterns of interest in an input signal is a very useful task in many different fields including medicine, bioinformatics, economics, speech recognition and computer vision. Example instances of this problem include spotting an object of interest in an image (e.g., a tumor), a pattern of interest in a time-varying signal (e.g., audio analysis), or an object of interest moving in a specific way (e.g., a human's body gesture). Traditional spotting methods, which are based on Dynamic Time Warping or hidden Markov models, use some variant of dynamic programming to register the pattern and the input while accounting for temporal variation between them. At the same time, those methods often suffer from several shortcomings: they may give meaningless solutions when input observations are unreliable or ambiguous, they require a high complexity search across the whole input signal, and they may give incorrect solutions if some patterns appear as smaller parts within other patterns. In this thesis, we develop a framework that addresses these three problems, and evaluate the framework's performance in spotting and recognizing hand gestures in video. The first contribution is a spatiotemporal matching algorithm that extends the dynamic programming formulation to accommodate multiple candidate hand detections in every video frame. The algorithm finds the best alignment between the gesture model and the input, and simultaneously locates the best candidate hand detection in every frame. This allows for a gesture to be recognized even when the hand location is highly ambiguous. The second contribution is a pruning method that uses model-specific classifiers to reject dynamic programming hypotheses with a poor match between the input and model. Pruning improves the efficiency of the spatiotemporal matching algorithm, and in some cases may improve the recognition accuracy. The pruning classifiers are learned from training data, and cross-validation is used to reduce the chance of overpruning. The third contribution is a subgesture reasoning process that models the fact that some gesture models can falsely match parts of other, longer gestures. By integrating subgesture reasoning the spotting algorithm can avoid the premature detection of a subgesture when the longer gesture is actually being performed. Subgesture relations between pairs of gestures are automatically learned from training data. The performance of the approach is evaluated on two challenging video datasets: hand-signed digits gestured by users wearing short sleeved shirts, in front of a cluttered background, and American Sign Language (ASL) utterances gestured by ASL native signers. The experiments demonstrate that the proposed method is more accurate and efficient than competing approaches. The proposed approach can be generally applied to alignment or search problems with multiple input observations, that use dynamic programming to find a solution.
Multiple model adaptive wave filtering for dynamic positioning of marine vessels

This paper addresses a filtering problem that arises in the design of dynamic positioning systems for ships and offshore rigs subjected to the influence of sea waves. Its key contribution is twofold: i) it introduces an improved model for filter design, and ii) and it exploits the structure of a multiple model adaptive wave filter that relies on measurements of the vessel's position and heading only. Namely, an improvement in the control plant model is proposed that better captures the physics of the problem at hand and a bank of Kalman filters is designed for a finite number of parameter values, each corresponding to a different peak frequency of the assumed wave spectrum model. Tools from multiple model adaptive estimation (MMAE) theory are exploited to blend the information provided by the different observers, yielding position and velocity estimates of the marine vessel. These estimates are then to be used in an appropriately designed feedback control law. Simulations illustrate the efficacy of the MMAE techniques proposed and the improvement in performance that is obtained when compared with other approaches.
Design of an Augmented and Optimised Hiding Technique and Framework for Privacy Preserving Data Mining

explosion of a waft similar to a typhoon of techniques for data garnering, data dissemination, internet technologies and the manifestation of susceptible applications; privacy and security issues in knowledge discovery have reached the pinnacle opening a new sphere of influence of issue connecting to privacy of populace which requires solemn judgment. Hence forth we are pressurized to develop mechanism for altering the unique facts by some means, with the intention that the private data and private knowledge linger private even subsequent to the mining process. There are many mechanisms which have been adopted for privacy preserving data mining. Pinning our attention to the earlier works done for association rule hiding by Aris Gkoulalas et al., is based on the concept of distance flanked by the original database and its sanitized version, where all sensitive rules have been hidden. By quantifying distance, knowledge is gained with minimum modification that needs to be made in the original dataset in order to hide sensitive, while austerely affecting nonsensitive, itemsets. In this paper, we have endeavored to enhance the existing concealment technique and to develop a conceptual framework with the objective of implementing Privacy Preservation using the masking/concealing/hiding technique. They have used the Apriori algorithm to compute the large itemsets, which is less efficient and doesn't minimize side effect generated by it. We portray an efficient and optimal algorithm. Given a sensitive frequent itemset, for all the transactions containing this itemset, algorithm first identifies the transaction with the shortest length. In such a transaction, the candidate item with the maximal support value is deleted to decrease the support of the sensitive itemset. This sort of an approach hides the frequent sensitive itemsets efficiently and also it hides the non-sensitive itemsets. In this paper, we have tried to overcome the side-effect; along with harnessing the advantages of Frequent Pattern Growth Method which mines the complete set of frequent itemsets without candidate generation. We establish that any kind of Data Mining can be done securely with this algorithm and architecture without sacrificing accuracy. The investigational appraisal shows that this modus operandi yields good results on real world datasets, demonstrating its effectiveness towards solving the problem with good data utility, privacy and performance. Concisely stated it endeavours to disclose self-assurance amid privacy and revelation of information by attempting to minimize the impact on the concealed transactions.
Design of an FBG Sensor Network Based on Pareto Multi-Objective Optimization

A novel scheme based on Pareto-based multiobjective optimization technology is proposed to design a wavelength-division-multiplexing (WDM) fiber Bragg grating (FBG) sensor network. Considering multiple objectives, which are minimizing the bandwidth of the optical source and minimizing the overlapping spectra, an elitist non-dominated sorting genetic algorithm is applied for obtaining the Pareto front. Simulation results show that our approach is effective in improving the multiplexing capability of the WDM network.
The Role of Long Chain Polyunsaturated Fatty Acids in Infant Nutrition

Long chain polyunsaturated fatty acids (PUFAs) are important to all living organisms because they are essential components of cell membranes. The necessity for the presence of these essential components of fats has been known at least since 1929. Studies have been conducted which have demonstrated that the essential components of the human diet are linoleic acid 2 and linolenic acid. 3 Recent evidence has shown the importance of the PUFAs arachidonic acid (AA) and docosahexanoic acid (DHA) in infant cognitive and visual development. The PUFAs AA and DHA are synthetic products derived from linoleic and linolenic acid metabolism.
Sexual Dysfunction in Hypertensive Men A Critical Review of the Literature

Sexual dysfunction is common in hypertensive men and often is first reported by patients while receiving hypotensive therapy, leading to a widespread belief by patients and physicians that the sexual dysfunction is caused by a specific antihypertensive medication. However, it is unclear from the literature whether this problem is related to hypertension or to its therapy. Further, whether the erectile failures reported during therapy are a result of 1) reduced penile blood flow secondary to reduction of blood pressure after antihypertensive treatment or to obstructive vascular disease (or both) or 2) specific drug effects has not been well studied. Because of these unresolved issues, this common problem is not well managed and contributes to noncompliance with therapy by hypertensive male patients, which impedes the attainment of satisfactory Mood pressure control. The present article reviews the literature related to hypertension and sexual function in men and outlines a management strategy for clinicians that attempts to document normalcy of sexual function before initiating treatment in newly diagnosed hypertensive patients. Further, it does not ascribe causality to specific antihypertensive agents for the sexual dysfunction reported by treated hypertensive patients but attempts instead to delineate the pathogenesis of the dysfunction. Once the pathogenesis is established, treatment plans can be implemented to restore normotension and maintain adequate sexual function among treated hypertensive men. The article also discusses how applied research in this area may be performed.
Chemical Exposure and Occupational Symptoms Among Portuguese Hairdressers

Hairdressing is predominantly a female activity, in which several chemicals are handled, some of which are known to be allergenic and potentially carcinogenic. Several epidemiological studies showed an association between occupational exposure to chemicals in hairdressing salons and skin and respiratory-tract conditions. The aim of this study were to characterize the occupational exposure to total volatile organic compounds (VOC) and ammonia (NH3) in 50 Portuguese hairdressers' salons and to analyze the prevalence of respiratory and skin symptoms in 134 hairdressing professionals. Data indicated that internal sources of total VOC are mainly due to indoor sources, with average concentrations (1.4 mg/m3) above the Portuguese reference levels (0.6 mg/m3). Of the hairdressers' salons studied, 4% had a mean NH3 concentration higher than Portuguese (20 ppm) and American Conference of Industrial Hygienists (ACGIH) (25 ppm) reference levels. Hand dermatitis was the occupational symptom most reported by hairdressers (50%), followed by eye irritation (43%). The results of this study suggest that hairdressers' occupational activities are linked with higher risk of developing hand and wrist/arm dermatitis and symptoms in the upper respiratory tract. The proper use of disposable gloves, hands, wrists, and arms skin monitoring, and the frequent use of moisturizers in the workplace are effective measures to prevent the occurrence of dermatitis in these professionals. Displacement ventilation and/or local exhaust with adequate air exchange rate are recommended particularly in technical areas where hairdressing chemicals are mixed.
Age-related Differences in Brain Activity during True and False Memory Retrieval

Compared to young adults, older adults show not only a reduction in true memories but also an increase in false memories. We investigated the neural bases of these age effects using functional magnetic resonance imaging and a false memory task that resembles the DeeseRoedigerMcDermott (DRM) paradigm. Young and older participants were scanned during a word recognition task that included studied words and new words that were strongly associated with studied words (critical lures). During correct recognition of studied words (true memory), older adults showed weaker activity than young adults in the hippocampus but stronger activity than young adults in the retrosplenial cortex. The hippocampal reduction is consistent with age-related deficits in recollection, whereas the retrosplenial increase suggests compensatory recruitment of alternative recollection-related regions. During incorrect recognition of critical lures (false memory), older adults displayed stronger activity than young adults in the left lateral temporal cortex, a region involved in semantic processing and semantic gist. Taken together, the results suggest that older adults' deficits in true memories reflect a decline in recollection processes mediated by the hippocampus, whereas their increased tendency to have false memories reflects their reliance on semantic gist mediated by the lateral temporal cortex.
Online flooding prognosis in packed columns by monitoring parameter change in EGARCH model

In the chemical industry, packed columns are commonly used operating units for separation. However, the flooding phenomenon often reduces the efficiency of packed columns and interferes with the performance of the system. Due to this reason, research on the real-time prognosis of flooding becomes a necessity in practice. Pressure drop is a key factor that indicates flooding phenomenon in packed columns. In this paper, the trajectory of pressure drop in each time window is modeled with an exponential generalized autoregressive conditional heteroskedastic (EGARCH) process. The onset of flooding is then implied by the parameter change of the model. To capture the change in an efficient manner, a nonparametric charting technique is adopted for statistical process control (SPC). The feasibility and efficiency of the proposed method are illustrated by the experimental results.
SOBRE LA DISTRIBUCIÓN DEL PINGÜINO REY APtenodytes PAt AgonIcus (AVES: SPHENISCIDAE) EN CHILE ON THE DISTRIBUTION OF THE KING PENGUIN APtenodytes PAt AgonIcus (AVES: SPHENISCIDAE) IN CHILE

1 Feather Link, Inc. 1013 Westchester way, Cincinnati, OH 45244, USA.2 Casilla 19, Punta Arenas. alekusch@yahoo.com. 3 Los Angeles County Natural History Museum, Section of Ornithology, 900 Exposition Boulevard, Los Angeles CA 90007, USA. Direccion actual: Casilla 15, Melipilla, Chile. mma95@hotmail.com. Recibido: Feb. 02, 2011 Aceptado: May. 25, 2011
A decoupled exponential random graph model for prediction of structure and attributes in temporal social networks

The analysis of social networks often assumes time invariant scenario, while in practice actor attributes and links in such networks often evolve over time and are inextricably dependent on each other. In this article, we propose a new method to predict actor attributes and links in temporal networks. Our approach takes into account the attributes corresponding to the participating actors together with topological and structural changes of the network over time. This is achieved by building two conditional predictors to jointly infer links and actor attributes. The proposed prediction method was significantly more accurate than alternatives when evaluated on synthetic data sets and two well‐studied real‐life temporal social networks. In addition, the new algorithm is computationally more efficient than a related alternative scaling up linearly with the number of temporal observations and quadratically with the number of actors considered. © 2011 Wiley Periodicals, Inc. Statistical Analysis and Data Mining 4: 470–486, 2011
Auctioning transformable goods

In this paper we explore whether an auctioneer/buyer may benefit from introducing his transformability relationships (some goods can be transformed into others at a transformation cost) into multi-unit combinatorial reverse auctions. Thus, we quantitatively assess the potential savings the auctioneer/buyer may obtain with respect to combinatorial reverse auctions that do not consider tranformability relationships.
Atypical brain activation patterns during a face‐to‐face joint attention game in adults with autism spectrum disorder

Joint attention behaviors include initiating one's own and responding to another's bid for joint attention to an object, person, or topic. Joint attention abilities in autism are pervasively atypical, correlate with development of language and social abilities, and discriminate children with autism from other developmental disorders. Despite the importance of these behaviors, the neural correlates of joint attention in individuals with autism remain unclear. This paucity of data is likely due to the inherent challenge of acquiring data during a real‐time social interaction. We used a novel experimental set‐up in which participants engaged with an experimenter in an interactive face‐to‐face joint attention game during fMRI data acquisition. Both initiating and responding to joint attention behaviors were examined as well as a solo attention (SA) control condition. Participants included adults with autism spectrum disorder (ASD) (n = 13), a mean age‐ and sex‐matched neurotypical group (n = 14), and a separate group of neurotypical adults (n = 22). Significant differences were found between groups within social‐cognitive brain regions, including dorsal medial prefrontal cortex (dMPFC) and right posterior superior temporal sulcus (pSTS), during the RJA as compared to SA conditions. Region‐of‐interest analyses revealed a lack of signal differentiation between joint attention and control conditions within left pSTS and dMPFC in individuals with ASD. Within the pSTS, this lack of differentiation was characterized by reduced activation during joint attention and relative hyper‐activation during SA. These findings suggest a possible failure of developmental neural specialization within the STS and dMPFC to joint attention in ASD. Hum Brain Mapp 34:2511–2523, 2013. © 2012 Wiley Periodicals, Inc.
Corticotropin-releasing hormone (CRH) regulates macromolecular permeability via mast cells in normal human colonic biopsies in vitro

Objective: Persistent stress and life events affect the course of ulcerative colitis and irritable bowel syndrome by largely unknown mechanisms. Corticotropin-releasing hormone (CRH) has been implicated as an important mediator of stress-induced abnormalities in intestinal mucosal function in animal models, but to date no studies in human colon have been reported. The aim was to examine the effects of CRH on mucosal barrier function in the human colon and to elucidate the mechanisms involved in CRH-induced hyper-permeability. Design: Biopsies from 39 volunteers were assessed for macromolecular permeability (horseradish peroxidise (HRP), 51Cr-EDTA), and electrophysiology after CRH challenge in Ussing chambers. The biopsies were examined by electron and confocal microscopy for HRP and CRH receptor localisation, respectively. Moreover, CRH receptor mRNA and protein expression were examined in the human mast cell line, HMC-1. Results: Mucosal permeability to HRP was increased by CRH (2.8±0.5 pmol/cm2/h) compared to vehicle exposure (1.5±0.4 pmol/cm2/h), p = 0.032, whereas permeability to 51Cr-EDTA and transmucosal electrical resistance were unchanged. The increased permeability to HRP was abolished by α-helical CRH (9-41) (1.3±0.6 pmol/cm2/h) and the mast cell stabiliser, lodoxamide (1.6±0.6 pmol/cm2/h). Electron microscopy showed transcellular passage of HRP through colonocytes. CRH receptor subtypes R1 and R2 were detected in the HMC-1 cell line and in lamina propria mast cells in human colon. Conclusions: Our results suggest that CRH mediates transcellular uptake of HRP in human colonic mucosa via CRH receptor subtypes R1 and R2 on subepithelial mast cells. CRH-induced macromolecular uptake in human colon mucosa may have implications for stress-related intestinal disorders.
Mobile 3D-Interaktion zur virtuellen Exploration realer Umgebungen

Kombinationen von topografischen Karten und fotografischen Bildern sind eine Möglichkeit, real existierende Umgebungen für eine virtuelle Exploration abzubilden. Werden hierzu georeferenzierte Fotografien senkrecht auf der Karte platziert, ergibt sich das Problem der Navigation im 3D-Raum. Diese Arbeit stellt hierzu unter Berücksichtigung der Beschränkungen und Möglichkeiten moderner Smartphones zwei Interaktionskonzepte für mobile Geräte vor.
On the Use of Multimodal Cues for the Prediction of Degrees of Involvement in Spontaneous Conversation

Quantifying the degree of involvement of a group of participants in a conversation is a task which humans accomplish every day, but it is something that, as of yet, machines are unable to do. In this study we first investigate the correlation between visual cues (gaze and blinking rate) and involvement. We then test the suitability of prosodic cues (acoustic model) as well as gaze and blinking (visual model) for the prediction of the degree of involvement by using a support vector machine (SVM). We also test whether the fusion of the acoustic and the visual model improves the prediction. We show that we are able to predict three classes of involvement with an reduction of error rate of 0.30 (accuracy =0.68).
Sexual Selection in Prehistoric Animals: Detection and Implications

Many fossil animals bear traits such as crests or horns that probably functioned as sexually selected signals or weapons. Interpretations of these structures as functioning in mate choice or intrasexual contests are often controversial, with interpretations based on biome-chanics or physiology being favoured by many. Although testing hypotheses based on sexual selection can be difficult, especially given that there is no single, reliable means of recognising sexual selection, we argue that it is not impossible; indeed, there are now several cases where sexual selection is strongly supported. In other cases, a careful study of features such as sexual dimorphism, ontogeny, and allometry, coupled with testing of alternative hypotheses, will be necessary to distinguish between possible explanations for exaggerated features. Introducing the problem: why is it difficult to recognise sexually selected traits in extinct animals? Sexual selection, the process whereby traits are selected because they enhance mating or fertilisation success [1], is not a new phenomenon: ever since gametes diverged into eggs and sperm, their asymmetry in size has provided an opportunity for the operation of sexual selection. Sexual selection is not only responsible for much of the diversity in animal morphology and behaviour that we see today [2,3], but it is also a plausible explanation for many of the best known extravagant features found in extinct animals. Possible sexually selected traits are present across diverse fossil animal taxa (Figures 1 and 2): in some cases, such as the extinct giant deer Megaloceros [4], these have modern homologues, but many do not. This latter class includes traits such as the 'spine-brush complex' of the Palaeozoic stethacanthid sharks (Figure 1d) [5], the horns and frills of ceratopsian dinosaurs (Figure 1a) [6], the crests of many pterosaurs (Box 3, Figure Ib) and theropod dinosaurs [7,8], the long necks of sauropod dinosaurs [9], the long horns, sabre-teeth and other facial structures of palaeomerycid artiodactyls (Figure 1c) [10] and other fossil hoofed mammals , the lappets extending from the shell aperture in certain ammonite species (Figure 2b) [11], and the anterior spines and other structures found on a variety of trilobite species (Figure 2a) [12]. In addition to these skeletal traits, recently discovered Mesozoic birds and bird-like dinosaurs have revealed a rich variety of feathered structures, some of which have been interpreted as having a possible function in sexual display (Box 1) [13]. Distinguishing sexually selected traits in extinct species from those that have arisen …