Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluating design options of Bag-of-Visual-Words based methods for action classification

In recent years, the problems of vision-based human motion analysis and action classification/recognition have attracted a lot of attention due to the significance of their solution in domains such as assisted living, surveillance, humancomputer/robot interaction, etc. Despite several breakthroughs, human action recognition remains a challenging problem that is unsolved in its generality. In this work, we are interested in action classification based on motion capture/skeletal data and we rely on the Bags of Visual Words (BoVWs) features encoding. We follow an action classification framework consisting of three main steps: (a) feature extraction, (b) representation/encoding based on a BoVWs codebook and (c) classification of the resulting action representations. In this study, our goal is to provide an experimental evaluation of various options regarding the selection of the components of this framework that, when instantiated, give rise to a specific action classification method. In that direction, the contributions of this work are manyfold. First, we investigate the performance of three existing types of 3D skeletal features. We also propose a new feature for representing human 3D pose data that is inspired by the work on Motion Boundary Histograms (MBH). The use of the proposed feature is shown to produce results that are competitive to the state of the art. We explore three different classification methods (K-Nearest Neighbors, Support Vector Machines, Radial Basis Function Neural Networks). We also investigate the size of the codebook used to represent actions, which is a major design issue in BoVW-based methods. To achieve this, we perform an empirical, almost exhaustive study to determine the best codebook size for each feature type and classifier. Most of the previous works define a specific codebook size without providing details on how this has been decided. In contrast, we explore methods that determine automatically the codebook size. This investigation shows that Affinity Propagation, an unsupervised clustering technique that determines automatically the number of clusters in a dataset, can be used effectively as a replacement of the k-Means algorithm which is used in most of the BoVW-based recognition methods. Additionally, we explore feature encoding alternatives to BoWs such as the Bag of Temporal Words (BoTW) and the Vector of Locally Aggregated Descriptors (VLAD). The obtained results show that the simple BoVW encoding outperforms these more complicated choices. All methods and action classification design choices have been evaluated quantitatively based on a series of experiments that have been carried out on the standard, extensive and ground truth-annotated Berkeley MHAD dataset. Αξιολόγηση σχεδιαστικών επιλογών μεθόδων βασιζόμενων σε συλλογή οπτικών λέξεων για την κατηγοριοποίηση ανθρώπινων δραστηριοτήτων
Package ‘rQCC’

Constructs various robust quality control charts based on the median or Hodges-Lehmann estimator (location) and the median absolute deviation (MAD) or Shamos estimator (scale). The estimators used for the robust control charts are all unbiased with a sample of ﬁnite size. For more details, see Park, Kim and Wang (2022) <doi:10.1080/03610918.2019. 1699114>. In addition, us-ing this R package, the conventional quality control charts such as X-bar, S, R, p, np, u, c, g and h charts are also easily constructed. This work was partially supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (NRF-2017R1A2B4004169).
Police-In-The-Loop Person Re-identiﬁcation

Person re-identiﬁcation (Re-ID) has gained signiﬁcant interest in the computer 1 vision community. One important application of Re-ID is the analysis of CCTV 2 footages for police investigations. This setting poses a challenge of identifying all 3 the appearances of a given identity on time while also providing an opportunity 4 to utilize feedback from a human investigator. In this paper, we propose a general 5 framework for building human-in-the-loop (HITL) Re-ID systems for criminal 6 investigations. Using this framework, we investigate various HITL re-ranking 7 methods based on relevance feedback and hierarchical clustering. Quantitative 8 evaluations on large scale datasets show signiﬁcant improvements in Re-ID perfor-9 mance. Code is available at https:// . 10
Going for Speed: Full-Stack Performance Engineering in Modern Web-Based Applications

Organizers: ● Wolfram Wingerath† (wolfram.wingerath@baqend.com) ● Benjamin Wollmer†§ (benjamin.wollmer@baqend.com) ● Felix Gessert† (felix.gessert@baqend.com) ● Stephan Succo† (stephan.succo@baqend.com) ● Norbert Ritter§ (norbert.ritter@informatik.uni-hamburg.de) † Baqend, Hamburg, Germany (https://baqend.com) § University of Hamburg (Databases and Information Systems, DBIS), Hamburg, Germany (https://vsis-www.informatik.uni-hamburg.de)
Birds of a Feather or by Note? Ideological Nationalization of Local Electoral Manifestos in Belgium

Until now, scholars trying to unravel the phenomenon of nationalization have seldom considered the local policy layer or the ideological dimension as their main subject. This paper, however, studies the ideological nationalization of Flemish local party branches. It applies the method of content analysis of electoral manifestos to the local elections and examines the programmatic overlaps between the party headquarter and its local branches. An innovative nationalization measure is introduced and subsequently included in an explanatory regression model. The results show that ideological similarities are ubiquitous and especially prevailing among leftist parties, in majority-participating party branches and in large municipalities.
Bases psycholinguistiques et neuro-anatomiques de la compréhension de l’ironie chez l’adulte Psycholinguistic and neuroanatomical foundations of irony comprehension in adults

Irony comprehension is a complex and heterogeneous linguistic construct which requires further investigations. es et neuro-anatomiques de la Recent studies brought to the identification of three main markers or concepts involved hension de l’ironie chez l’adulte. europsychol 2011 ; xx (x) : 1-7 1684/nrp.2011. 0177 in irony comprehension: prosody, context, and lexicon. In this paper, these markers are linked to the main psycholinguistic theories and neuroanatomical hypotheses of irony comprehension in order to improve our understanding of irony comprehension and its cognitive and neuronal underlying processes. Pooling together psycholinguistic, cognitive, and neuroanatomical bases of irony comprehension is seen as a novel way to better understand this complex linguistic construct.
Existence of virtual museums for educational purposes is applied to the professional environment

Virtual museums, Bibliographic Review, Professional, educational innovation, digital learning. Virtual museums are the answer a digital society, a new cultural, social, and economic system and a tool for educational innovation and digital learning. This article aims to collate all relevant evidence in virtual cultural museums with a teaching approach and detect what is published using the following question "What is published about virtual museums for educational purposes? ". Its objective is to verify what can be found in the academic field about virtual museums for didactic purposes applied to the professional environment. The research analyzes two hundred and twenty-three articles, of which seventeen were selected for their didactic and professional environment characteristics. The bibliographic review presents indicators that determine a virtual museum is an effective tool both in the field of reinforcing learning, as well as in the theoretical and practical development of activities that encourage creation by students. Review Article
CLEP_A_366874 721..730

1Department of Emergency Medicine, Ditmanson Medical Foundation Chia-Yi Christian Hospital, Chiayi City, Taiwan; 2Department of Emergency Medicine, Chiayi Branch, Taichung Veteran’s General Hospital, Chiayi City, Taiwan; 3Department of Information Management, Institute of Healthcare Information Management, National Chung Cheng University, Chiayi County, Taiwan; 4Clinical Data Center, Department of Medical Research, Ditmanson Medical Foundation Chia-Yi Christian Hospital, Chiayi City, Taiwan; 5Division of Neurology, Department of Internal Medicine, Ditmanson Medical Foundation Chia-Yi Christian Hospital, Chiayi City, Taiwan; 6Department of Nursing, Min-Hwei Junior College of Health Care Management, Tainan, Taiwan
A Survey on Genomic Dataset for Predicting the DNA Abnormalities Using Ml

— Genomic data is used in bioinformatics for collecting, storing and processing the genomes of living things. In order to process the genetic information, machine learning algorithms plays a vital role in building a computational model by using the statistical theory. This paper helps the researchers, who are doing research with the DNA dataset by applying the machine learning logics. Feature scaling machine learning techniques helps in predicting the sequence of genome for extrachromosomal amplification and predicting the tumor intensity in the human gene. Identification of unconventional chromosome in the DNA sequence minimizes the structural risk. In this paper, researchers can get clear insight on classification, sequence prediction, fuzzy relationship and SNP on genome dataset. The performance of various existing models is measured using the performance metrics and the accuracy .
Self-Enforcing Climate Coalitions for Farsighted Countries: Integrated Analysis of Heterogeneous Countries

This paper studies the formation of international climate coalitions by heterogeneous countries. Countries rationally predict the consequences of their membership decisions in climate negotiations. We offer an approach to characterise the equilibrium number of coalitions and their number of signatories independent of their heterogeneity, and we suggest a tractable algorithm to fully characterise the equilibrium. In a dynamic game analysis of a general equilibrium model of the economy integrated with climate dynamics, a grand climate coalition or multiple climate coalitions may form in equilibrium, but if the policymakers are patient, the number of signatories in all climate treaties is a Tribonacci number. Our results are robust to the possibility of renegotiation and investment in green technologies besides fossil fuels.
Mind the Gap: Norm-Aware Adaptive Robust Loss for Multivariate Least-Squares Problems

Measurement outliers are unavoidable when solving real-world robot state estimation problems. A large family of robust loss functions (RLFs) exists to mitigate the effects of outliers, including newly developed adaptive methods that do not require parameter tuning. All of these methods assume that residuals follow a zero-mean Gaussian-like distribution. However, in multivariate problems the residual is often defined as a norm, and norms follow a Chi-like distribution with a non-zero mode value. This produces a “mode gap” that impacts the convergence rate and accuracy of existing RLFs. The proposed approach, “Adaptive MB,” accounts for this gap by first estimating the mode of the residuals using an adaptive Chi-like distribution. Applying an existing adaptive weighting scheme only to residuals greater than the mode leads to more robust performance and faster convergence times in two fundamental state estimation problems, point cloud alignment and pose averaging.
Iron loss analysis in linear DC motor: laminated vs. solid core

Iron loss analysis in a linear DC motor is discussed. Two cases are considered: the motor core made of solid steel and a laminated core. Those two cases call for different methods of iron loss calculation, which are discussed in detail. Influence the magnetic bias, produced by the motor's permanent magnet excitation, on the iron loss is discussed. Iron loss calculated for both versions of the core is compared and design recommendations are made.
Effectivity Score of Simulation Tools towards Modelling Design in Internet-of-Things

—Simulation tools play an integral and significant role in studying the applicability and effectiveness of different algorithms for solving real-world problems cost-effectively. In the case of Internet-of-Things, the issues associated with real-world implementation are exponentially multi-fold. Although various simulators have facilitated the evolution of schemes to address the problems in IoT applications in the last few years, their applicability in the real world is highly questionable. Hence, this paper discusses the potential features of existing simulations (both commercial and research-based) and investigates features of different assessment environment tools to understand their current state. The paper further contributes toward a distinct research pattern. The core contribution of this manuscript is to review standard practices of using simulation tool along with different test environments. The paper also contributes towards exploring various prospects of unaddressed problems associated with a usage of existing simulation environment/tool for investigating the challenging and practical environment of an IoT ecosystem. The learning outcome of this study will assist the reader to make a decision towards adopting precise simulation tool for their work as well as it also highlights the need to perform more number of customization towards including the features that is found in research gap.
Influence of Aerosol Embedded in Shallow Cumulus Cloud Fields on the Surface Solar Irradiance

Ubiquitous shallow cumulus clouds are associated with complex variability in surface solar irradiance (SSI). Aerosol embedded in the cloud field typically has a much smaller overall radiative effect, but can significantly perturb the shape of the SSI probability density function (PDF). These perturbations have important implications for several applications that utilize SSI, but are poorly quantified and are the subject of this study. Multiple cases of shallow cumulus cloud fields with embedded aerosol are simulated at the Southern Great Plains Atmospheric Observatory using large eddy simulation (LES). The LES‐derived cloud and aerosol fields are then ingested into Monte Carlo three‐dimensional (3D) radiative transfer to simulate SSI. We find a variety of perturbations to the SSI PDF that depend on aerosol presence and optical properties. The processes leading to these perturbations include extinction of the direct beam that often increases from the clear‐sky region toward cloud edge due to aerosol hygroscopic growth, and scattering of radiation by aerosol into cloud shadows. The ability to predict the SSI PDF in the presence of aerosol is assessed by adding three representative aerosol optical properties into an existing machine learning framework. We show that machine learning accurately predicts the SSI PDF across a wide range of conditions with negligible computational expense. Importance metrics reveal the relatively high influence of aerosol optical properties in making the predictions. These new findings highlight the important role that aerosol plays in SSI variability for highly 3D cloud‐aerosol environments and provides a computationally efficient route forward for its simulation.
Combatendo vulnerabilidades em programas P4 com verificação baseada em asserções

Tendências recentes em SDN estendem a programabilidade da rede ao plano de dados através do uso de linguagens de programação como P4. Nesse contexto, a chance de se introduzir erros e, por consequência, vulnerabilidades de software na rede aumenta significativamente já que pacotes passam a ser processados de maneira genérica. Mecanismos de verificação de planos de dados existentes são incapazes de modelar programas P4 ou apresentam grandes restrições no conjunto de propriedades modeladas. Para contornar essas limitações e tornar planos de dados programáveis mais seguros, apresentamos um método de verificação de programas P4 baseado no uso de asserções e execução simbólica. Primeiro, programas P4 são anotados com asserções que expressam propriedades genéricas de corretude e segurança. Em seguida, os programas anotados são transformados em código C e todos seus possíveis caminhos são executados simbolicamente a fim de verificar a validade das asserções inseridas. Resultados mostram que é possível provar um conjunto expressivo de propriedades na ordem de segundos utilizando a técnica proposta.
Methoden zur vergleichenden Bewertung pharmazeutischer Produkte

IGWiG) was established in 2004 to, among other tasks, evaluate the benefit of pharmaceuticals. In this context it is of importance that patented pharmaceuticals are only excluded from the reference pricing system if they offer a therapeutic improvement. The institute is commissionedby the FederalJoint Committee (Gemeinsamer Bundesausschuss, G-BA) or by the Ministry of Health and Social
Prediksi kandungan lignin pada dedak padi bercampur sekam menggunakan tekstur statistik dan KNN

Pemalsuan dedak padi terjadi cukup tinggi karena harga dedak padi yang mahal. Kualitas dedak padi yang bercampur sekam dapat menurun karena kandungan serat kasar dan lignin bersifat anti-nutrisi. Kandungan lignin dapat diestimasi dengan tekstur citra dedak padi yang bercampur sekam. Penelitian ini bertujuan untuk melakukan analisis tekstur pada citra dedak padi yang bercampur sekam menggunakan metode ekstraksi ciri run length dengan klasifikasi k-nearest neighbour (KNN). Citra dedak padi yang bercampur sekam diakuisisi dengan mikroskop digital Dino Capture dengan perbesaran sebesar 200 kali. Citra yang dihasilkan berukuran 640×480 piksel dengan format bitmap. Praproses dilakukan dengan mengubah citra RGB ke dalam grayscale, kemudian dilakukan image enhancement menggunakan histogram equalization. Data uji dan data latih ditentukan menggunakan 5-fold cross validation dengan 3 ulangan. Hasil KNN dengan 7 fitur run length menghasilkan akurasi terbaik sebesar 74.55% pada sudut 135° dan k = 5.
Effect of thickness on photovoltaic properties of amorphous carbon/fullerene junction

All-carbon photovoltaic devices have attracted attention in terms of resources and environment. However, the device application is very limited because of poor performance. In this work, we studied the solar cell characteristics of amorphous carbon (a–C)/fullerene (C60) junction when the thickness of the a–C layer was varied. When the thickness of the a–C layer was varied, the short-circuit current density and open-circuit voltage increased with increasing film thickness and then decreased after a certain value. Also, the spectral response measurement results suggest that most of the power generation is due to the light absorbed by the C60 layer, and that the light absorbed by the a–C layer may contribute little to power generation. This study suggests that the improvement in the electronic properties of a–C is necessary to make a photovoltaic device with high performance.
Long-Term Trends In Loblolly Pine Productivity And Stand Characteristics In Response To Stand Density And Fertilization In The Western Gulf Region

Two levels each of fertilization and stand density were established to create four environments in a 7-year-old loblolly pine plantation on a N and P deficient western Gulf Coastal Plain site in Louisiana. Levels of fertilization were no fertilization and application of 120 lb N and 134 lb P/ac. Levels of stand density were the original stocking (1,210 trees/ac), and row thinning for a residual stocking of 303 trees/ac. Six years later (age 13), basal areas and relative stand densities on the non-thinned (NT) and thinned (T) plots were 176 and 79 ft2/ac and 90 and 37 percent, respectively. At age 14, 178 lb N, 45 lb P and 45 lb K/ac were broadcast on the previously fertilized (F) plots and a second thinning was conducted on the previously thinned plots to a residual relative density of 31 percent of maximum, which corresponded to 67 ft2/ac. Long-term measurements of climate, growth, leaf area dynamics and foliar nutrition were initiated at age 11. The objectives of this paper are to describe stand productivity between age 11 and 17 and offer ecophysiological explanations for these growth trends.
ANALISIS KEADILAN MODEL PENJADWALAN YANG DIINTEGRASIKAN DENGAN HARQ PADA SISTEM LTE

"> Penjadwalan pada Long Term Evolution (LTE) memiliki peran dalam melayani kebutuhan bandwidth yang besar. Oleh karena itu, jaringan seluler LTE membutuhkan algoritma penjadwalan yang mampu mengakomodasi informasi keluaran dari proses HARQ untuk meningkatkan fairness . Algoritma penjadwalan dikombinasikan dengan proses HARQ untuk meningkatkan keadilan throughput yang diterima oleh pengguna. Redundancy Version (RV) yang diperoleh dari proses HARQ dikombinasikan dengan nilai prioritas layanan dan Channel Quality Information (CQI) menjadi suatu nilai metrik yang digunakan untuk menentukan prioritas paket pada proses penjadwalan. Algoritma penjadwalan diujikan pada makalah ini adalah Round Robin (RR), Maximum C/I (CI), dan Proportional Fairness (PF). Proses HARQ di penerima melakukan Error Detection (ED) dan Forward Error Correction (FEC) pada paket yang diterima. User Equipment (UE) akan mengirimkan feedback ke eNode-B yang berisi informasi apakah paket berhasil diterima dengan benar atau tidak. Integrasi masing-masing algoritma penjadwalan (RR, CI, dan PF) dengan nilai CQI, rangking paket data, dan RV dapat meningkatkan nilai fairness antarpengguna. Jain’s Fairnees Index , sebagai parameter keadilan, menunjukkan adanya peningkatan keadilan throughput .
Transformer based Model for Coherence Evaluation of Scientific Abstracts: Second Fine-tuned BERT

—Coherence evaluation is a problem related to the area of natural language processing whose complexity lies mainly in the analysis of the semantics and context of the words in the text. Fortunately, the Bidirectional Encoder Representation from Transformers (BERT) architecture can capture the aforemen- tioned variables and represent them as embeddings to perform Fine-tunings. The present study proposes a Second Fine-Tuned model based on BERT to detect inconsistent sentences (coherence evaluation) in scientiﬁc abstracts written in English/Spanish. For this purpose, 2 formal methods for the generation of inconsistent abstracts have been proposed: Random Manipulation (RM) and K-means Random Manipulation (KRM). Six experiments were performed; showing that performing Second Fine-Tuned improves the detection of inconsistent sentences with an accuracy of 71%. This happens even if the new retraining data are of different language or different domain. It was also shown that using several methods for generating inconsistent abstracts and mixing them when performing Second Fine-Tuned does not provide better results than using a single technique.