Miracle-dz/UniFAR-FTUs huggingface dataset:
A Survey of Task-Based Machine Learning Content Extraction Services for VIDINT

This paper provides a comparison of current video content extraction tools with a focus on comparing commercial task-based machine learning services. Video intelligence (VIDINT) data has become a critical intelligence source in the past decade. The need for AI-based analytics and automation tools to extract and structure content from video has quickly become a priority for organizations needing to search, analyze and exploit video at scale. With rapid growth in machine learning technology, the maturity of machine transcription, machine translation, topic tagging, and object recognition tasks are improving at an exponential rate, breaking performance records in speed and accuracy as new applications evolve. Each section of this paper reviews and compares products, software resources and video analytics capabilities based on tasks relevant to extracting information from video with machine learning techniques.
“One Shot” Sample Evaluation of 22G, 22G upgraded, 21G and 19G needle for Endobronchial Ultrasound-EBUS-TBNA

Background: There are still diagnostic issues with lung cancer and mediastinum lymphadenopathy. Endobronchial ultrasound (EBUS) is a state of the art equipment for the diagnosis of lymphadenopathy and central lesions. Objective: To investigate the sample size with one pass. Patients and Methods: 248 Stage IV patients were included in our study. All patients had a CT of the thorax with either lymphadenopathy or lyphadenopathy plus pulmonary lesions. Patients had a biopsy with endobronchial ultrasound with 22G Mediglope, 22G Mediglope Sonotip, 21G Olympus and 19G Olympus needle. We collected information regarding the cancer type, cell block, tissue, age, sex, lesion size and needle type. Results: The cancer type diagnosis was associated with the needle diameter. The number of cell-blocks were associated with the lesion size and needle diameter. Slices from the tissue and cell-blocks were again associated with the lesion size and needle diameter. Conclusion: One pass is enough for cancer diagnosis, however; careful selection has to be made among patients regarding the needle diameter. In the case of lymphoma suspicion we should use 19G needle.
Classification of Facial Expression In-the-Wild based on Ensemble of Multi-head Cross Attention Networks

How to build a system for robust classification and recognition of facial expressions has been one of the most important research issues for successful interactive computing applications. However, previous datasets and studies mainly focused on facial expression recognition in a controlled/lab setting, therefore, could hardly be generalized in a more practical and real-life environment. The Affective Behavior Analysis in-the-wild (ABAW) 2022 competition released a dataset consisting of various video clips of facial expressions in-the-wild. In this paper, we propose a method based on the ensemble of multi-head cross attention networks to address the facial expression classification task introduced in the ABAW 2022 competition. We built a uni-task approach for this task, achieving the average F1-score of 34.60 on the validation set and 33.77 on the test set, ranking second place on the final leaderboard.
Resource-aware Approach in the Design of Complex Information Systems as a Problem of Multicriteria Optimization

One of the modern information society tasks is the design of complex multiprocessor information systems, taking into account the rational use of system resources. It includes the development of a new resource-aware approach for the design of next generation information systems, such as smart home systems, autonomous transport, cyber-physical systems, etc. The paper has an educational character and is intended for novice researchers with the aim of introducing them to the subject area. It considers a demonstrative explanation of the problem of resource allocation in the design of complex information systems. It describes the basics of the problem of complex assessments of the technical solutions and the formal approach for solving this problem, including the methods from the theory of Data Mining and Operation Research. It also considers the problem of finding a trade-off between system parameters when looking for new solutions. Approaches to the comparative assessment of multiprocessor systems are demonstrated using simple examples. The ranking of the multiprocessor systems is performed in accordance with a complex criterion. Due to the specifics of technical solutions the formation of such a complex criterion is a rather difficult task, therefore many criteria (parameters) are used to make the assessment. The problem of finding the optimal variant of a multiprocessor system is presented as a problem of multicriteria optimization. The use of multicriteria optimization makes it possible to search for a trade-off between several alternatives or to find the non-dominant solutions, where none of them is better than the other in all the considered parameters and therefore have the same importance. In this case, many solutions are allowed, each of which is acceptable in the absence of preliminary information about the importance of the criteria. From the set of several non-dominated solutions obtained as a result of multicriteria optimization, it is possible to choose one that is most preferable for a specific applied problem.
Implementation of an empirical tool for fast prediction of bomb airblast loading

As terrorist attacks continue all over the world and, therefore, the alarming rate of countries governments as well as the awareness of people about danger is significantly increasing, in recent years high explosive airblast effects assessment and protection have become a fundamental concern for structural designers. In this article, the implementation of an original predictive tool based on the literature empirical data to develop analyses of blast loading consequent to a bomb explosion is described. The in-house developed model enables the fast calculation of the distribution of the main blast wave parameters around and over three-dimensional complex geometries virtually reproducing potential attractive targets for terrorists. Considering these capabilities, the use of the proposed novel methodology is desirable in the preparatory and retrofit design in view of evaluating blast-induced adverse consequences and, accordingly, to identify and effectively set up the most appropriate protective strategies and countermeasures.
Detecting Vehicles on the Edge: Knowledge Distillation to Improve Performance in Heterogeneous Road Traffic

The drastic growth in the number of vehicles in the last few decades has necessitated significantly better traffic management and planning. To manage the traffic efficiently, traffic volume is an essential parameter. Most methods solve the vehicle counting problem under the assumption of state-of-the-art computation power. With the recent growth in cost-effective Internet of Things (IoT) devices and edge computing, several machine learning models are being tailored for such devices. Solving the traffic count problem on these devices will enable us to create a real-time dashboard of network-wide live traffic analytics. This paper proposes a Detect-Track-Count (DTC) framework to count vehicles efficiently on edge devices. The proposed solution aims at improving the performance of tiny vehicle detection models using an ensemble knowledge distillation technique. Experimental results on multiple datasets show that the custom knowledge distillation setup helps generalize a tiny object detector better.
Inferring epidemiological parameters based on allele frequencies

In this paper, I develop a methodology for inferring the transmission rate and reproductive value of an epidemic based on genotype data from a sample of infected hosts. The epidemic is modeled by a birth-death process describing the transmission dynamics in combination with an inﬁnite-allele model describing the evolution of alleles. I provide a recursive formulation for the probability of the allele frequencies in a sample of hosts, and a Bayesian framework for estimating transmission rates and reproductive values based on observed allele frequencies. Using the Bayesian method, I reanalyze tuberculosis data from the US. I estimate a net transmission rate of 0 . 19 / year [0 . 13 , 0 . 24] and a reproductive value of 1 . 02 [1 . 01 , 1 . 04]. I demonstrate that the allele frequency probability under the birth-death model does not follow the well-known Ewens’ sampling formula which holds under the Kingman’s coalescent.
Comparative Analysis Among Steganographic LSB Variants

-Combining the best features of steganography and cryptography is the trending concept which is being followed for the purpose of information security. Steganography provides the provision for hiding secret data in some cover file in order to make it undiscovered by the perpetrators. On the complementary, cryptography secures that secret data by manipulating its original form and converting it into an unintelligent form. Hence, making the data more powerful and secure against the prevailing security attacks and breaches. This paper represents the implementation of this combination on the two LSB variants namely sequential LSB and randomized LSB. A comparison among the two approaches is carried out by adding a secret text into a video cover file. The concept of chaotic sequence has been used as the security approach that converts the secret data into random bits pattern. The proposed work uses the traditional LSB approach as basic ste-ganographic model. The inference on the basis of parameters concludes that the randomized LSB shows better results than the sequential LSB scheme.
A Single-Phase PFC Rectifier With Wide Output Voltage and Low Frequency Ripple Power Decoupling

1 —This paper proposes a single-phase PFC rectifier to achieve high power factor, wide output voltage range, and ripple power decoupling without using electrolytic capacitors. It consists of two parts: power factor correction (PFC) circuit and output voltage regulation circuit. The load side is involved in both parts, which is different from the regular two-stage conversion structure. The proposed rectifier can be directly applied to low voltage cases due to the wide output voltage range. And the decoupling capacitor voltage can be smaller than the peak grid voltage, which reduces the voltage stress. Besides, the low frequency ripple power buffer is implemented without a dedicated power-buffering controller. This paper firstly introduces the circuit structure, operation principles, and control method. Then, the system design consideration is given. Finally, the effectiveness of the proposed topology is verified by the simulations and experimental results.
New Information Extracting and Analysis Methodology for the Terminology Research Purposes: The Field of Biology

This study is part of a larger research developing a database of organism names for preserving linguistic diversity and for terminological studies. This article addresses the issue of retrieving the names of organisms from digitized resources of specialized literature for subsequent collection in the new database. The study used image processing algorithms, Optical Character Recognition (OCR) and language recognition algorithms, altogether creating a methodology that reflects the possibility of using data retrieval for the terms of the field of biology in Latvian and other local languages – the names of organisms along with their scientific or Latin name. Further on, these retrieved data are scrutinized and prepared for addition in the developed database.
Mapping QTL Using Naturally Occurring Genetic Variance among Commercial Inbred Lines of Maize ( Zea mays L . )

There are many commercial inbred lines available in crops. Large amount of genetic variation is preserved among these lines. The genealogical history of the inbred lines is usually well documented. However, quantitative trait loci (QTL) responsible for the genetic variances among the lines are largely unexplored due to lack of statistical methods. In this study, we show that the pedigree information of the lines along with the trait values and marker information can be used to map QTL without the need of further crossing experiments. We develop a Monte Carlo method to estimate locus specific identity-by-descent (IBD) matrices. These IBD matrices are further incorporated into a mixed model equation for variance component analysis. QTL variance is estimated and tested at every putative position of the genome. The actual QTL are detected by scanning the entire genome. Applying this new method to a well documented pedigree of maize ( Zea mays L.) that consists of 404 inbred lines, we mapped eight QTL for the maize male flowering trait GDUSHD (growing degree day heat units to pollen shedding). These detected QTL contributed over 80% of the variance observed among the inbred lines. The QTL were then used to evaluate all the inbred lines using the best linear unbiased prediction (BLUP) technique. Superior lines were selected according to the estimated QTL allelic values, a technique called marker assisted selection (MAS). The MAS procedure implemented via BLUP may be routinely used by breeders to select superior lines and line combinations for development of new cultivars.
Reduction of High Dimensional Data Using Discriminant Analysis Methods

— In recent years, analysis of high dimensional data for several applications such as content based retrieval, speech signals, fMRI scans, electrocardiogram signal analysis, multimedia retrieval, market based applications etc. has become a major problem. To overcome this challenge, dimensionality reduction techniques, which enable high dimensional data to be represented in a low dimensional space have been developed and deployed for varieties of application to fast track the study of the information structure. In this paper, a comparative study of LDA and a KDA among the dimensionality reduction techniques were considered using data samples collected from survey and it was implemented using object oriented programming language (C#). The results reveal that less data components were discovered by LDA across the different dataset tested in comparison with KDA .
Identification of variety-specific ISSR markers in small cardamom ( Elettaria cardamomum Maton.)

233 Cardamom (Elettaria cardamomum Maton.) has recently become a major focus of Biotechnology research. It exhibits considerable variation under cultivation (Korikanthimath, 2003). There are three botanical varieties in this monotypic genus namely, Malabar, Mysore and Vazhukka with prostrate, erect and semi-erect panicle characteristics respectively, as the discriminative morphological markers. The identification of varieties is important during their breeding and registration process. All the varieties and races are interfertile and the observed variations are probably due to natural crossing (Korikanthimath, 2003).
SwarmGrid: Demand-Side Management with Distributed Energy Resources Based on Multifrequency Agent Coordination

This paper focuses on a multi-agent coordination for demand-side management in electrical grids with high penetration rates of distributed generation, in particular photovoltaic generation. This coordination is done by the use of swarm intelligence and coupled oscillators, proposing a novel methodology, which is implemented by the so-call SwarmGrid algorithm. SwarmGrid seeks to smooth the aggregated consumption by considering distributed and local generation by the development of a self-organized algorithm based on multifrequency agent coordination. The objective of this algorithm is to increase stability and reduce stress of the electrical grid by the aggregated consumption smoothing based on a frequency domain approach. The algorithm allows not only improvements in the electrical grid, but also increases the penetration of distributed and renewable sources. Contrary to other approaches, this objective is achieved anonymously without the need for information exchange between the users; it only takes into account the aggregated consumption of the whole grid.
Pressure Transients in a Hydraulic Servo Having Unequal Oil Volumes

This paper reports a theoretical and experimental evaluation of the pressure transients in a hydraulic servo used to position a mass when the oil volumes on the two sides of the jack are substantially different. Application of small perturbation theory to the closed loop shows that the pressure transients are smallest when the oil volumes are equal. The worst condition is shown to be at the stroke ends, the peak pressure increasing as the volume ratio increases. Predicted values obtained by analogue computer are in good accord with measurements made on an experimental rig. An approximate guide is suggested for the relationship of peak pressures in the unequal and equal volume conditions.
Diversity of computation: using a novel ‘intrinsic ignition’ framework to study brain communication

A general theory of brain function has to be able to explain local and non-local network computations over space and time. We propose a new framework to capture the key principles of how local activity influences global computation, ie describing the propagation of information and thus the broadness of communication driven by local activity. More specifically we consider the diversity in space (nodes or brain regions) over time using the concept of intrinsic ignition, which are naturally occurring intrinsic perturbations reflecting the capability of a given brain area to propagate neuronal activity to other regions in a given brain state. Characterising the profile of intrinsic ignition for a given brain state provides insight into the precise nature of hierarchical information processing. Combining this data-driven method with a causal whole-brain computational model can provide novel insights into the imbalance of brain states found in neuropsychiatric disorder.
Smart Textile with Stress Control Function

Since their inception, textiles have been important in human history and significantly impacted the economic development and global trade. Although they are more popular as clothing serving two main attributes - aesthetics and protection. However, with the rapidly changing needs of consumers over a few decades, smart textiles are now generating creative and novel solutions for many engineering and medical problems. With the help of new discoveries and innovative researches, they can provide many smart functions such as colour change, temperature change, shape control, super-hydrophobicity etc. In this work, a new intelligent function, i.e. stress control, in the textile will be introduced. This novel function of stress control allows programming and storing the internal stress in the structure of textile, and also enabling it to retrieve the stored stress reversibly with an external stimulus such as heat. The paper addresses the fundamentals of stress control and the related mechanism using a viscoelastic model consists of spring and dashpot elements. As an example of the potential application, the stress control in textile can be used for smart medical compression treatment to allow pressure control for an efficient treatment of compression therapy used in chronic venous disorders. It is anticipated that the research into stress control in textiles will grow in multiple dimensions as a result of their promising potential in many stress controlling applications such as pressure garments, bandages, devices,
3D Web-Based Shape Modelling: Data Extraction and Delivery

— Despite the rapid development of hardware including specialized graphical processing units (GPUs) and widening the bandwidth, truly interactive applications allowing for near real-time visualization without loss of a visual quality are still to become a reality. Building up an adaptive 3D Web-based shape modelling environment enables us to design platform independent 3D objects in a collaborative manner, yet delivering compressed meshes, and images to clients with different platforms and devices in an optimized manner is still a difficult job. In this paper, we explore the crucial issues of delivering 3D objects. We focus on data transmission over different transmission bandwidths between servers delivering the service and clients with different platform devices. Our case study relies on a client-server adaptive architecture, supported by different rendering techniques, and is able to deliver compressed meshes and images. We identify the obstacles in delivering compressed data files as well as image streams, and present results based on bandwidth capacity, storage size, extraction and loading times.
Empirical modelling of oxidation behaviours of coals stored under different conditions

ABSTRACT In this study, oxidation behaviours of lignite samples stored under different conditions (deep freezer;-25°C, nitrogen tank; 18°C and oven; 30°C) for 16 weeks were investigated. Therefore; oxygen consumption rates of the coal having two size fractions (74 μm and 500 μm) and activation energies were calculated by oxygen analyser and TG/DTG analysis, respectively. In addition, the ignition temperatures and combustion risk index values of coal samples were determined by the crossing point method. As a result, the activation energies were determined to be between 28.0413 and 39.5839 kJ/mol. It was also determined that the consumption of oxygen increased after the temperature of the coal reaching 90°C. At the beginning of the storage period, lignite samples with a fine particle size in the ‘medium risk’ class in terms of the propensity to spontaneous combustion were included in the ‘high risk’ class at the end of the process. Finally, the relationship among all the obtained experimental results was outlined for the first time by creating a numerical model through the design of experiment (DOE) and it was seen that the coal samples stored in the deep freezer had advantages in terms of oxidation behaviour compared to the other two storage conditions.
Lessons learned from an application of static concurrency analysis

Static concurrency analysis may be used to detect synchronization anomalies such as deadlocks and race conditions in concurrent programs [Tay83b]. Its notable drawback is that combinatorial state space explosion places a practical limit on the size of programs that may be analyzed [Tay83a]. One approach to assessing feasibility is to attempt to analyze representative concurrent programs. This report summarizes the results of one such exercise. We feel that the lessons learned will be valuable to those exploring similar paths. The following section presents a brief outline of the foundation of our approach to static concurrency analysis; Section 3 contains more details of the toolset used. Sec-
EFFECTS OF PULMONARY REHABILITATION PROTOCOL ON THE VARIABLES OF EXERCISE TOLERANCE INA WOMAN WITH CHRONIC OBSTRUCTIVE PULMONARY DISEASE: A CASE REPORT

This study aimed to evaluate the effects of a pulmonary rehabilitation protocol on the variables of exercise tolerance in women with chronic obstructive pulmonary disease. A 60-year-old woman patient, BMI of 32.90 kg/m2, participated in 24 sessions of a pre- and post-pulmonary rehabilitation protocol. This program consisted of four phases: stretching, aerobic exercises, resistance exercise training and relaxation.The results obtained in the six-minute walking test after the rehabilitation program showed improvement in the distance covered (Pre = 234 meters; Post = 324 meters), increase of load exercise for the UL based on the diagonal Kabat method (Pre = 1; Post = 3.5 kg) and increase of respiratory muscle strength. It can be concluded that the pulmonary rehabilitation protocol has provided an increase in variables of exercise tolerance in the COPD patient.