Miracle-dz/UniFAR-FTUs huggingface dataset:
Real-time Weapon Surveillance using CV-based Motion Capture and DL-driven Analysis

The rising crime rate during highly populated eventsor also in secluded, areas of concern have made security the top priority in the industry. Abnormality detection and continuous monitoring have become crucial applications for computer vision. As the need for protecting people and their possessions grows, video surveillance systems are increasingly put into place to aid in pattern recognition, event identification, and information gathering. Our proposed system correctly identifies and categorizes various types of firearms by leveraging convolutional neural networks (CNNs) and object identification methods. The model's resilience and flexibility are ensured by the fact that it was trained using a large dataset that included still photos and videos of numerous types of weaponry. In this study, we focus on automating the detection of firearms using VGG16 and Faster RCNN. Image datasets that have been manually labeled are used in the implementation. Despite both algorithms' great accuracy, putting them to use for practical purposes needs a striking balance between swiftness and precision. Public places, transport hubs, and other sensitive areas can benefit greatly from the use of our real-time weapon detection technology. It is a useful resource for pinpointing potential dangers so that people can be protected from them in a timely manner.
Passage Retrieval vs. Document Retrieval in the Monolingual Task with the IR-n System

The paper describes our participation in monolingual tasks at CLEF 2006. We have submitted results for the following languages: English, French, Portuguese and Hungarian. We focused on studying different weighting schemes (okapi and dfr) and retrieval strategies (passage retrieval and document retrieval) to improve retrieval performance. After an analysis of our experiments and of the official results at CLEF, we find that our different configurations (French, Portuguese and Hungarian) achieve considerably improved scores.
Restaurant Recommendations with Implicit User Behavior via Image Classification and Sentiment Analysis from Social Media

Traditional recommendation systems often fall short in understanding users' true food preferences on social media platforms. This paper introduces an innovative approach to enhance the dining experience by leveraging implicit user behavior via image classification and sentiment analysis. The proposed system combines food image classification (MobileNetV2) and sentiment analysis (Transformer Flair) on social media comments, creating a robust framework for implicit recommendation. The results demonstrate the system's efficacy in accurately predicting food categories and extracting positive sentiments from user comments. By systematically linking these insights to user profiles, the paper establishes a recommendation system that considers both culinary preferences and geographical location. The seamless integration of computer vision and natural language processing allows for a more tailored and personalized restaurant suggestion, addressing the limitations of existing recommendation systems. The research highlights the potential of harnessing implicit user data from social media to revolutionize the landscape of personalized dining recommendations, setting the stage for future advancements in understanding and adapting to users' evolving preferences.
Intense, vigorous, soft and fun: identity work and the international MBA

Purpose – A critical debate has been on‐going about the desired nature of international MBAs. One aspect of this debate, which has remained significantly underdeveloped, is the impact on students' identity of the way that MBAs are shaped and projected. This paper seeks to address this issue.Design/methodology/approach – Taking the decision to do an MBA as a point of high intensity identity work, artefacts that input to that decision are subjected to narrative analysis. A total of 140 MBA brochures from the USA and Europe were analysed.Findings – The findings lay out the dominant narrative style of the MBA identity as projected through brochures and associated publicity material.Research limitations/implications – Narrative analysis emphasises some potential findings whilst de‐emphasising others. Its strengths are to be able to incorporate a large amount of empirical material and to uncover underlying patterns within that material. Its limitations are that it is not as focused on micro detail in the way th.
Fracture Estimation Based on Deformation History with Recurrent Neural Networks

Capturing the material deformation limits is an im-portant consideration in different engineering applications. While materials are deforming under different loading conditions, the fracture can take place and is often preceded by localization of plastic deformation. These localization fields depend on the amount and direction, or in more generally, the history of the applied loads during deformation. Forming Limit Curves (FLCs) are commonly used to describe the maximum applicable strain before localization, but they are generally valid only for the case of proportional loading. Actual loading scenarios are rarely proportional, meaning that loading can change significantly during deformation. Recent studies show that this effect of non-proportionality, or loading history, could be predicted with machine learning based methods. In this paper, we demonstrate that Recurrent Neural Networks (RNN) can capture the effect of the deformation history on localization and thereby give a reasonable estimate for non-proportional FLCs. The model is trained with a dataset of bilinear loading paths generated with a finite element-based Marciniak-Kuczynski (MK) model. The model is validated with multi-linear loading paths.
Self-Organizing Map with Dynamical Node Splitting: Application to Handwritten Digit Recognition

This article presents a simple yet elegant pattern recognizer based on a dynamic node-splitting scheme for the self-organizing map that can adapt its structure as well as its weights. The scheme makes use of a structure adaptation capability to place the nodes of prototype vectors into the pattern space accurately so as to make the decision boundaries as close to the class boundaries as possible. In order to show the performance of the proposed scheme, experiments with the unconstrained handwritten digit database of Concordia University in Canada were conducted. The proposed method for an incremental formation of feature maps is 96.05 percent of the recognition rate. In view of the elegant simplicity of the approach, the reported performance is remarkable and can stand up to one of the best results reported in the literature with the same database.
Energetic cost of calling: general constraints and species‐specific differences

The energetic cost of acoustic signalling varies tremendously among species. Understanding factors responsible for this heterogeneity is important for understanding the costs and benefits of signalling. Here, we present a general model, based on well‐established principles of bioenergetics, which predicts the energetic cost of call production across species. We test model predictions using an extensive database of resting and calling metabolic rates of insects, amphibians and birds. Results are largely supportive of model predictions. Calling metabolic rates scale predictably with body mass and temperature such that calling and resting metabolic rates are directly proportional to each other. The cost of acoustic signalling is ∼8 times higher than resting metabolic rate in ectotherms, and ∼2 times higher in birds. Differences in the increase in metabolic rate during calling are explained by the relative size of species’ sound‐producing muscles. Combined with published work, we quantify call efficiency and discuss model implications.
Categorical Perception as a Function of Stimulus Quality

Abstract A number of experiments were carried out in order to test the hypothesis that categorical perception of speech stimuli is a function of synthetis quality – specifically, that the greater complexity of more natural speech stimuli makes it difficult for listeners to focus on particular stimulis parameters as psychoacoustic cues. The results show that there is an increase in categorical perception as synthesis quality improves from a simple synthesis by rule, via LPC synthesis, to a much more complex type called sinewave generation.
International Journal of Research in Advent Technology Action and Horror Genre Identification of Movies Using Artificial Neural Network

ABSTARCT: Motion-pictures play a significant role in fulfilling people's entertainment needs. There is a substantial amount of multimedia data in the world, diverse in content and origin. In order to make efficient use of this data it should be labeled or indexed in some manner. Such labeling would make it easier for individuals to retrieve the type of content desired. Today, due to advancements in Internet technology, consumers have access to an abundant amount of movies from various on-line services. This has created the need for automatic content-driven movie retrieval. Although considerable advancements have been made in the areas of video retrieval and collaboration. Movie genres identification still act as a key task in such systems. The proposed method for Action and Horror genre classification uses Artificial Neural Network (ANN). The system consists of an artificial neural network trained with values of color pixels. The system is tested with a dataset of 100 sample movie videos taken from a public domain YouTube. The system achieved over all accuracy of 90% in classifying the video into action and horror genres.
Allergy and parasites reevaluated: wide-scale induction of chronic urticaria by the ubiquitous fish-nematode Anisakis simplex in an endemic region.

BACKGROUND The ubiquitous fish-nematode Anisakis simplex produces acute urticaria or angioedema in the course of gastro-allergic anisakiasis. We studied the relationship between this nematode and chronic urticaria (CU), as well as the clinical usefulness of measuring specific IgG4 in A. simplex-sensitized patients with CU. METHODS First, the prevalence of sensitization to A. simplex was estimated in 135 consecutive CU patients and the result was compared with known data about sensitization in a healthy population. Then, clinical response to a 2-month diet without fish was analyzed in 76 CU patients. The improvement rate in patients with and without sensitization to A. simplex was compared. Finally, the improvement rate, other clinical data and specific immunoglobulins in sensitized patients with and without detectable specific IgG4 were compared. RESULTS a) The A. simplex sensitization rate in CU patients was 52.6 % compared with a known prevalence of between 16 and 20 % in our region. b) Of 65 sensitized patients, 52 experienced clinical improvement after the diet compared with only three of 11 patients without sensitization to A. simplex (p = 0.001). c) Of 43 patients with detectable specific IgG4, 38 showed clinical improvement compared with only 14 of 22 patients without detectable IgG4 (p = 0.02). Eight of nine patients with previous fish-associated cutaneous symptoms had detectable specific IgG4 compared with 15 of 32 patients who reported no previous fish-associated symptoms or acute urticaria (p = 0.03). CONCLUSIONS Our results indicate that A. simplex is a possibly widespread etiologic agent able to induce CU. This parasite model constitutes the first report that associates an infectious agent with CU on a large scale. The detection of IgG4 antibodies reflects a previous acute parasitic infection and a temporary diet without fish improves symptoms in most patients with detectable specific IgG4.
The third dimension: Value‐oriented contents in psychological contracts

We propose value-oriented content of psychological contracts as being distinct from transactional and relational content, which we affirm using confirmatory factor analysis for employee, as well as organizational obligations. In a sample of 171 German parish volunteers, value-oriented volunteer and relational organizational obligations are significantly and positively related to job satisfaction as well as to time spent volunteering. The distinctive role of value-oriented content is reinforced by the finding that its associated employee obligations were the only ones that were significantly and positively related to both outcomes. Thus, value-oriented obligations may foster favourable work relationships and may even have the potential to stabilize work relationships during crises if obligations regarding an organization's core values are fulfilled. Examining the generalizability of these findings to nonvolunteer samples in future research is recommended.
A robust AQM controller design for various delay networks

The existing active queue management (AQM) algorithms are not well adapted to the uncertainty of the time-delay networks. When an algorithm designed for the small time-delay network (LAN) is used for a large-delay networks (WAN, Internet), its performance is normally poor. This paper presents a robust AQM design algorithm based on the D stability region to overcome this issue. The TCP/AQM model meeting various time-delay is first established. Secondly, a set of desired D-stable regions in the complex plane is specified and then a numerical optimization algorithm with various time-delay constraints is run to find the controller parameters such that all the roots of the closed-loop system are within the specified regions to reduce the queuing delay and improve the effective throughput. Compared with the PI controller via experimental simulations, the novel AQM algorithm is indeed more efficient and robust in various delay networks.
Efficient and accurate B-rep generation of low degree sculptured solids using exact arithmetic

We present eecient representations and algorithms for exact boundary computation on low degree sculptured CSG solids using exact arithmetic. Most of the previous work using exact arithmetic has been restricted to polyhedral models. In this paper, we generalize it to higher order objects , whose boundaries are composed of rational paramet-ric surfaces. The use of exact arithmetic and representation guarantees that a geometric algorithm is numerically accurate and is likely to be required for perturbation techniques which handle degeneracies. We present eecient algorithms for computing the intersection curves of trimmed paramet-ric surfaces, decomposing them into multiple components for eecient point location queries inside the trimmed regions , and computing the boundary of the resulting solid using topological information and component classiication tests. We also employ a n umber of previously developed algorithms like algebraic curve classiication, multivariate Sturm sequences, and multivariate resultants. We h a ve implemented key parts of these algorithms and preliminary implementations indicate the performance of our algorithm to be about one order of magnitude slower than similar algorithms using IEEE oating-point arithmetic.
jTraqX: A free, platform independent tool for isobaric tag quantitation at the protein level

Many proteomic studies focus on quantitative aspects, using different stable isotope labeling techniques that require specialized software to analyze the generated data. Here we present jTraqX, an easy‐to‐use tool for processing and visualizing protein quantification data. jTraqX is platform independent and is compatible with all available 4‐plex isobaric tags. jTraqX can be freely downloaded at http://sourceforge.net/projects/protms.
Automatic Signature Verification: The State of the Art

In recent years, along with the extraordinary diffusion of the Internet and a growing need for personal verification in many daily applications, automatic signature verification is being considered with renewed interest. This paper presents the state of the art in automatic signature verification. It addresses the most valuable results obtained so far and highlights the most profitable directions of research to date. It includes a comprehensive bibliography of more than 300 selected references as an aid for researchers working in the field.
Helper agent: designing an assistant for human-human interaction in a virtual meeting space

This paper introduces a new application area for agents in the computer interface: the support of human-human interaction. We discuss an interface agent prototype that is designed to support human-human communication in virtual environments. The prototype interacts with users strategically during conversation, spending most of its time listening. The prototype mimics a party host, trying to find a safe common topic for guests whose conversation has lagged. We performed an experimental evaluation of the prototype's ability to assist in cross-cultural conversations. We designed the prototype to introduce safe or unsafe topics to conversation pairs, through a series of questions and suggestions. The agent made positive contributions to participants' experience of the conversation, influenced their perception of each other and of each others' national group, and even seemed to effect their style of behavior. We discuss the implications of our research for the design of social agents to support human-human interaction.
Measuring in Automatically Reconstructed 3D Models

In this paper a system for the 3D documentation of a scene within an absolute coordinate system is presented. It follows the idea of structure-frommotion and was designed to fit well into the standard archaeological documentation process. It only requires equipment that is already present at an excavation site, namely a digital camera and a total station. Besides that, data that is surveyed during the archaeological documentation process is reused to transform the model into the geo-referenced coordinate system used at the site. The paper discusses possible sources of error that influence the accuracy of reconstructed models in general. The achieved measuring accuracies are evaluated on synthetic as well as real data.
Methodological Issues in Enumerating Homeless Individuals

Abstract The enumeration of homeless individuals is a topic of great importance to programs and professionals serving them, as funding for essential services to this population is often contingent upon quantitative evidence that a significant problem exists. However, this task is often difficult due to methodological quandaries such as the lack of a standard definition of homelessness, variations in study locales, and the transience of the homeless population. The paper examines some methodological issues in counting the homeless, specifically in the context of the most extensive effort to estimate a national figure to date: the 1984 study conducted by the Department of Housing and Urban Development (HUD). By evaluating the relative methodological strengths and weaknesses of this older (but still highly relevant) study, the reader can better evaluate relevant factors pertinent in arriving at an accurate estimate of this highly vulnerable population.
Music, social learning and senses in university pedagogy: An intersection between art and academe

Integration of music in an academic university teaching setting is an example of how artistic practice and competences have potentials to resonate beyond the immediate discipline. The article explores music activities as contributing to learning environments for university students, creating shared experiences in groups of diverse learners with different needs. The music activities are discussed in light of challenges in today's university concerning student diversity. Two empirical examples of experiments with music in university teaching at a Danish university are presented. Empirical data were collected by means of qualitative research methods (teaching logs and qualitative surveys) and analysed in a socio-cultural learning perspective. The first empirical example presents music as supporting students relate to each other in the classroom. The second example describes how music may support students' sensory awareness when practising qualitative research like fieldwork. Both examples imply interdisciplinary potentials of putting music into play in university pedagogy.
Joint QTL Linkage Mapping for Multiple-Cross Mating Design Sharing One Common Parent

Background Nested association mapping (NAM) is a novel genetic mating design that combines the advantages of linkage analysis and association mapping. This design provides opportunities to study the inheritance of complex traits, but also requires more advanced statistical methods. In this paper, we present the detailed algorithm of a QTL linkage mapping method suitable for genetic populations derived from NAM designs. This method is called joint inclusive composite interval mapping (JICIM). Simulations were designed on the detected QTL in a maize NAM population and an Arabidopsis NAM population so as to evaluate the efficiency of the NAM design and the JICIM method. Principal Findings Fifty-two QTL were identified in the maize population, explaining 89% of the phenotypic variance of days to silking, and nine QTL were identified in the Arabidopsis population, explaining 83% of the phenotypic variance of flowering time. Simulations indicated that the detection power of these identified QTL was consistently high, especially for large-effect QTL. For rare QTL having significant effects in only one family, the power of correct detection within the 5 cM support interval was around 80% for 1-day effect QTL in the maize population, and for 3-day effect QTL in the Arabidopsis population. For smaller-effect QTL, the power diminished, e.g., it was around 50% for maize QTL with an effect of 0.5 day. When QTL were linked at a distance of 5 cM, the likelihood of mapping them as two distinct QTL was about 70% in the maize population. When the linkage distance was 1 cM, they were more likely mapped as one single QTL at an intermediary position. Conclusions Because it takes advantage of the large genetic variation among parental lines and the large population size, NAM is a powerful multiple-cross design for complex trait dissection. JICIM is an efficient and specialty method for the joint QTL linkage mapping of genetic populations derived from the NAM design.
The FSSP database: fold classification based on structure-structure alignment of proteins

The FSSP database presents a continuously updated classification of 3-D protein folds based on an all-against-all comparison of structures currently in the Protein Data Bank (PDB) [Bernstein et al. (1977) J. Mol. Biol., 112, 535- 542]. The database currently contains an extended structural family for each of 600 representative protein chains which have <25% mutual sequence identity. The results of the exhaustive pairwise structure comparisons are reported in the form of a fold tree generated by hierarchical clustering and as a series of structurally representative sets of folds at varying levels of uniqueness. For each query structure from the representative set, there is a database entry containing structure-structure alignments with its structural neighbours in the representative set and its sequence homologs in the PDB. All alignments are based purely on the 3-D co-ordinates of the proteins and are derived by an automatic structure comparison program (Dali). The FSSP database is accessible electronically on the World Wide Web and by anonymous ftp.