bluuebunny/crossref_metadata_2025 huggingface dataset:
Learning to Cascade: Confidence Calibration for Improving the Accuracy and Computational Cost of Cascade Inference Systems
Authors: Enomoro Shohei , Eda Takeharu
Published: September 2022

Recently, deep neural networks have become to be used in a variety of applications.
While the accuracy of deep neural networks is increasing, the confidence score, which indicates the reliability of the prediction results, is becoming more important.
Deep neural networks are seen as highly accurate but known to be overconfident, making it important to calibrate the confidence score.
Many studies have been conducted on confidence calibration.
They calibrate the confidence score of the model to match its accuracy, but it is not clear whether these confidence scores can improve the performance of systems that use confidence scores.
This paper focuses on cascade inference systems, one kind of systems using confidence scores, and discusses the desired confidence score to improve system performance in terms of inference accuracy and computational cost.
Based on the discussion, we propose a new confidence calibration method, Learning to Cascade.
Learning to Cascade is a simple but novel method that optimizes the loss term for confidence calibration simultaneously with the original loss term.
Experiments are conducted using two datasets, CIFAR-100 and ImageNet, in two system settings, and show that naive application of existing calibration methods to cascade inference systems sometimes performs worse.
However, Learning to Cascade always achieves a better trade-off between inference accuracy and computational cost.
The simplicity of Learning to Cascade allows it to be easily applied to improve the performance of existing systems.
Deep Graph Spectral Evolution Networks for Graph Topological Evolution
Authors: Etemadyrad Negar , Li Qingzhe , Zhao Liang
Published: September 2022

Characterizing the underlying mechanism of graph topological evolution from a source graph to a target graph has attracted fast increasing attention in the deep graph learning domain. However, it is very challenging to build expressive and efficient models that can handle global and local evolution patterns between source and target graphs. On the other hand, graph topological evolution has been investigated in the graph signal processing domain historically, but it involves intensive labors to manually determine suitable prescribed spectral models and prohibitive difficulty to fit their potential combinations and compositions. To address these challenges, this paper proposes the deep Graph Spectral Evolution Network (GSEN) for modeling the graph topology evolution problem by the composition of newly-developed generalized graph kernels. GSEN can effectively fit a wide range of existing graph kernels and their combinations and compositions with the theoretical guarantee and experimental verification. GSEN has outstanding efficiency in terms of time complexity (O(n)) and parameter complexity (O(1)), where n is the number of nodes of the graph. Extensive experiments on multiple synthetic and real-world datasets demonstrate outstanding performance.
Addressing Domain Gap via Content Invariant Representation for Semantic Segmentation
Authors: Gao Li , Zhang Lefei , Zhang Qian
Published: September 2022

The problem of unsupervised domain adaptation in semantic segmentation is a major challenge for numerous computer vision tasks because acquiring pixel-level labels is time-consuming with expensive human labor. A large gap exists among data distributions in different domains, which will cause severe performance loss when a model trained with synthetic data is generalized to real data. Hence, we propose a novel domain adaptation approach, called Content Invariant Representation Network, to narrow the domain gap between the source (S) and target (T) domains. The previous works developed a network to directly transfer the knowledge from the S to T. On the contrary, the proposed method aims to progressively reduce the gap between S and T on the basis of a Content Invariant Representation (CIR). CIR is an intermediate domain (I) sharing invariant content with S and having similar data distribution to T. Then, an Ancillary Classifier Module (ACM) is designed to focus on pixel-level details and generate attention-aware results. ACM adaptively assigns different weights to pixels according to their domain offsets, thereby reducing local domain gaps. The global domain gap between CIR and T is also narrowed by enforcing local alignments. Last, we perform self-supervised training in the pseudo-labeled target domain to further fit the distribution of the real data. Comprehensive experiments on two domain adaptation tasks, that is, GTAV → Cityscapes and SYNTHIA → Cityscapes, clearly demonstrate the superiority of our method compared with state-of-the-art methods.
Justicia: A Stochastic SAT Approach to Formally Verify Fairness
Authors: Ghosh Bishwamittra , Basu Debabrota , Meel Kuldeep S.
Published: September 2022

As a technology ML is oblivious to societal good or bad, and thus, the field of fair machine learning has stepped up to propose multiple mathematical definitions, algorithms, and systems to ensure different notions of fairness in ML applications. Given the multitude of propositions, it has become imperative to formally verify the fairness metrics satisfied by different algorithms on different datasets. In this paper, we propose a stochastic satisfiability (SSAT) framework, Justicia, that formally verifies different fairness measures of supervised learning algorithms with respect to the underlying data distribution. We instantiate Justicia on multiple classification and bias mitigation algorithms, and datasets to verify different fairness metrics, such as disparate impact, statistical parity, and equalized odds. Justicia is scalable, accurate, and operates on non-Boolean and compound sensitive attributes unlike existing distribution-based verifiers, such as FairSquare and VeriFair. Being distribution-based by design, Justicia is more robust than the verifiers, such as AIF360, that operate on specific test samples. We also theoretically bound the finite-sample error of the verified fairness measure.
High-Dimensional Bayesian Optimization via Tree-Structured Additive Models
Authors: Han Eric , Arora Ishank , Scarlett Jonathan
Published: September 2022

Bayesian Optimization (BO) has shown significant success in tackling expensive low-dimensional black-box optimization problems. Many optimization problems of interest are high-dimensional, and scaling BO to such settings remains an important challenge. In this paper, we consider generalized additive models in which low-dimensional functions with overlapping subsets of variables are composed to model a high-dimensional target function. Our goal is to lower the computational resources required and facilitate faster model learning by reducing the model complexity while retaining the sample-efficiency of existing methods. Specifically, we constrain the underlying dependency graphs to tree structures in order to facilitate both the structure learning and optimization of the acquisition function. For the former, we propose a hybrid graph learning algorithm based on Gibbs sampling and mutation. In addition, we propose a novel zooming-based algorithm that permits generalized additive models to be employed more efficiently in the case of continuous domains. We demonstrate and discuss the efficacy of our approach via a range of experiments on synthetic functions and real-world datasets.
Constructing a Fair Classifier with Generated Fair Data
Authors: Jang Taeuk , Zheng Feng , Wang Xiaoqian
Published: September 2022

Fairness in machine learning is getting rising attention as it is directly related to real-world applications and social problems. Recent methods have been explored to alleviate the discrimination between certain demographic groups that are characterized by sensitive attributes (such as race, age, or gender). Some studies have found that the data itself is biased, so training directly on the data causes unfair decision making. Models directly trained on raw data can replicate or even exacerbate bias in the prediction between demographic groups. This leads to vastly different prediction performance in different demographic groups. In order to address this issue, we propose a new approach to improve machine learning fairness by generating fair data. We introduce a generative model to generate cross-domain samples w.r.t. multiple sensitive attributes. This ensures that we can generate infinite number of samples that are balanced \wrt both target label and sensitive attributes to enhance fair prediction. By training the classifier solely with the synthetic data and then transfer the model to real data, we can overcome the under-representation problem which is non-trivial since collecting real data is extremely time and resource consuming. We provide empirical evidence to demonstrate the benefit of our model with respect to both fairness and accuracy.
Show, Attend and Distill: Knowledge Distillation via Attention-based Feature Matching
Authors: Ji Mingi , Heo Byeongho , Park Sungrae
Published: September 2022

Knowledge distillation extracts general knowledge from a pretrained teacher network and provides guidance to a target student network. Most studies manually tie intermediate features of the teacher and student, and transfer knowledge through predefined links. However, manual selection often constructs ineffective links that limit the improvement from the distillation. There has been an attempt to address the problem, but it is still challenging to identify effective links under practical scenarios. In this paper, we introduce an effective and efficient feature distillation method utilizing all the feature levels of the teacher without manually selecting the links. Specifically, our method utilizes an attention based meta network that learns relative similarities between features, and applies identified similarities to control distillation intensities of all possible pairs. As a result, our method determines competent links more efficiently than the previous approach and provides better performance on model compression and transfer learning tasks. Further qualitative analyses and ablative studies describe how our method contributes to better distillation.
Improving Fairness and Privacy in Selection Problems
Authors: Khalili Mohammad Mahdi , Zhang Xueru , Abroshan Mahed , Sojoudi Somayeh
Published: September 2022

Supervised learning models have been increasingly used for making decisions about individuals in applications such as hiring, lending, and college admission. These models may inherit pre-existing biases from training datasets and discriminate against protected attributes (e.g., race or gender). In addition to unfairness, privacy concerns also arise when the use of models reveals sensitive personal information. Among various privacy notions, differential privacy has become popular in recent years. In this work, we study the possibility of using a differentially private exponential mechanism as a post-processing step to improve both fairness and privacy of supervised learning models. Unlike many existing works, we consider a scenario where a supervised model is used to select a limited number of applicants as the number of available positions is limited. This assumption is well-suited for various scenarios, such as job application and college admission. We use ``equal opportunity'' as the fairness notion and show that the exponential mechanisms can make the decision-making process perfectly fair. Moreover, the experiments on real-world datasets show that the exponential mechanism can improve both privacy and fairness, with a slight decrease in accuracy compared to the model without post-processing.
Neural Sequence-to-grid Module for Learning Symbolic Rules
Authors: Kim Segwang , Nam Hyoungwook , Kim Joonyoung , Jung Kyomin
Published: September 2022

Logical reasoning tasks over symbols, such as learning arithmetic operations and computer program evaluations, have become challenges to deep learning.
In particular, even state-of-the-art neural networks fail to achieve \textit{out-of-distribution} (OOD) generalization of symbolic reasoning tasks, whereas humans can easily extend learned symbolic rules.
To resolve this difficulty, we propose a neural sequence-to-grid (seq2grid) module, an input preprocessor that automatically segments and aligns an input sequence into a grid.
As our module outputs a grid via a novel differentiable mapping, any neural network structure taking a grid input, such as ResNet or TextCNN, can be jointly trained with our module in an end-to-end fashion.
Extensive experiments show that neural networks having our module as an input preprocessor achieve OOD generalization on various arithmetic and algorithmic problems including number sequence prediction problems, algebraic word problems, and computer program evaluation problems while other state-of-the-art sequence transduction models cannot.
Moreover, we verify that our module enhances TextCNN to solve the bAbI QA tasks without external memory.
HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference
Authors: Kruse Jakob , Detommaso Gianluca , Köthe Ullrich , Scheichl Robert
Published: September 2022

Many recent invertible neural architectures are based on coupling block designs where variables are divided in two subsets which serve as inputs of an easily invertible (usually affine) triangular transformation. While such a transformation is invertible, its Jacobian is very sparse and thus may lack expressiveness. This work presents a simple remedy by noting that subdivision and (affine) coupling
can be repeated recursively within the resulting subsets, leading to an efficiently invertible block with dense, triangular Jacobian. By formulating our recursive coupling scheme via a hierarchical architecture, HINT allows sampling from a joint distribution p(y,x) and the corresponding posterior p(x|y) using a single invertible network. We evaluate our method on some standard data sets and benchmark its full power for density estimation and Bayesian inference on a novel data set of 2D shapes in Fourier parameterization, which enables consistent visualization of samples for different dimensionalities.
Nearly Linear-Time, Parallelizable Algorithms for Non-Monotone Submodular Maximization
Authors: Kuhnle Alan
Published: September 2022

We study combinatorial, parallelizable algorithms for maximization of a submodular function, not necessarily monotone, with respect to a cardinality constraint k. We improve the best approximation factor achieved by an algorithm that has optimal adaptivity and query complexity, up to logarithmic factors in the size of the ground set, from 0.039 to nearly 0.193. Heuristic versions of our algorithms are empirically validated to use a low number of adaptive rounds and total queries while obtaining solutions with high objective value in comparison with state-of-the-art approximation algorithms, including continuous algorithms that use the multilinear extension.
Query Training: Learning a Worse Model to Infer Better Marginals in Undirected Graphical Models with Hidden Variables
Authors: Lázaro-Gredilla Miguel , Lehrach Wolfgang , Gothoskar Nishad , Zhou Guangyao , Dedieu Antoine , George Dileep
Published: September 2022

Probabilistic graphical models (PGMs) provide a compact representation of knowledge that can be queried in a flexible way: after learning the parameters of a graphical model once, new probabilistic queries can be answered at test time without retraining. However, when using undirected PGMS with hidden variables, two sources of error typically compound in all but the simplest models (a) learning error (both computing the partition function and integrating out the hidden variables is intractable); and (b) prediction error (exact inference is also intractable). Here we introduce query training (QT), a mechanism to learn a PGM that is optimized for the approximate inference algorithm that will be paired with it. The resulting PGM is a worse model of the data (as measured by the likelihood), but it is tuned to produce better marginals for a given inference algorithm. Unlike prior works, our approach preserves the querying flexibility of the original PGM: at test time, we can estimate the marginal of any variable given any partial evidence. We demonstrate experimentally that QT can be used to learn a challenging 8-connected grid Markov random field with hidden variables and that it consistently outperforms the state-of-the-art AdVIL when tested on three undirected models across multiple datasets.
MODELING THE FORMATION PROCESSES OF THE OIL AND GAS POTENTIAL OF THE VYCHEGDA TROUGH
Authors:   Perm National Research Polytechnic University, Botalov A. N. , Alekseeva O. L. ,   Perm State University
Published: September 2022

The article is devoted to reconstruction of the conditions of oil and gas potential formation in the Vychegda Trough using 2D basin modeling. Currently, the region is very poorly studied that is indicated by the low density of the entire fund of drilled wells and explored regional seismic profiles. However, the Vychegda Trough is considered as a prospective area for new oil and gas fields in the North-East of European Russia. The amount of information accumulated during the entire period of study of the Vychegda Trough makes it possible to conduct a comprehensive study of the processes of oil and gas potential formation and assess the perspectives of oil and gas bearing capacity using a modern basin modeling method.
CHARACTERISTICS OF THE OIL DEPOSITS FORMATION ON THE TERRITORY OF THE VARANDEY-ADZVINSKAYA OIL AND GAS REGION
Authors:   Perm State University, Zhemchugova T. A.
Published: September 2022

The structure, oil and gas potential of the Varandey-Adzvinskaya oil and gas region is considered in the article. Physicochemical properties and composition of oil and source rocks of the structural zone are analysed. Based on the determined features of the oil deposits formation of study area, 3 oil systems have been identified: Middle Ordovician-Lower Devonian, Middle Devonian-Lower Fransian-Timanian and Middle Frasnian-Lower Triassic, which are combined in the General geological section of the Varandey-Adzvinskaya zone. In each system, a connection between oils of various types with oil source rocks was established. The connection of different type oil with source rocks was established that made it possible to predict the migration paths of hydrocarbons for new oil and gas deposits exploration.
FEATURES OF THE STRUCTURE AND OIL AND GAS CONTENT OF THE GUINEA GULF SEDIMENTARY BASIN
Authors:   Perm State National Research University, Ekenma J. J. , Kabanov A. Z. ,   Perm State National Research University, Karaseva T. V. ,   Perm State National Research University
Published: September 2022

The article deals with the issues of the structure and development of the oil and gas content in the Guinea Gulf sedimentary basin located in the western regions of Africa and the Atlantic Ocean. The features of the basin formations are given that provided a complex structure and often ambiguous correlation of deposits. The factors that led to the development of the main hydrocarbon deposits in the province of the Niger Delta and other regions are identified. It is concluded that it is necessary to continue exploration work in the basin due to the increased prospects for oil and gas potential.
Structural transformations during annealing of cold-worked high-entropy alloy Al0.3CoCrFeNi
Authors: Ivanov I. V. , Emurlaev K. I. , Kuper K. E. , Safarova D. E. , Bataev I. A.
Published: September 2022

The paper considers the features of structural transformations during annealing of the high-entropy alloy Al0.3CoCrFeNi. The ingots obtained by argon arc melting were subjected to cold rolling with a compression ratio of 50 %. The produced worpieces were annealed in the furnace for 4 hours at temperatures of 200, 400, 600, 800 and 1000 °C. The samples obtained by the described technique were examined using the methods of synchrotron X-ray diffraction in the lumen mode and diffraction of backscattered electrons. The research data indicate that up to a temperature of 600 °C, the structure of the alloys is represented by a single phase with a face-centered cubic lattice. When annealing alloys at temperatures of 800 and 1000 °C, the phase composition is characterized by the presence of two phases: a disordered phase with a face-centered cubic lattice and an ordered phase with a primitive cubic lattice. At temperatures above 800 °C, the burning of alloys is accompanied by development of recrystallization processes. It was found that after annealing at 800 °C, the relative proportion of micro-volumes characterized by inter-angular misorientation of more than 10° was 20 %, and after annealing at 1000 °C – 65 %. Microhardness of the studied samples increases with an increase in temperature up to 600 °C and decreases with a further increase in temperature. Analysis of the width of diffraction maxima using the methods of profile analysis of diffractograms indicates an increase in distortions of the crystal lattice of the ordered phase. This behavior may be associated with the release of nanoscale inclusions in the matrix of the main phase.
Melting time of complex nickel-containing alloys in liquid steel
Authors: Renev D. S. , Zayakin O. V. , Zhuchkov V. I.
Published: September 2022

For development of new ferroalloys and their application, it is necessary to know their physical and chemical characteristics. The most important characteristics of the alloy, on which assimilation and distribution of the main elements of ferroalloys in the iron-carbon melt depend, are their time of melting and dissolution. Using a mathematical model for calculating the melting time, developed by the employees of the Ural Federal University and the Institute of Metallurgy of the Ural Branch of the Russian Academy of Sciences, the authors studied the duration of melting of complex nickel-containing ferroalloys in liquid steel. The program allows one to calculate the temperature of a piece of ferroalloy, thickness of the frozen steel crust, size of the alloy piece and duration of the melting periods depending on physicochemical and thermophysical characteristics of the ferroalloys. The melting mechanism of ferroalloys determines the time of their melting in liquid steel. This work contains mathematical modeling of melting of complex nickel ferroalloys containing %: ~10 Ni; 0.5 – 55.0 Cr; ~0.2 C; ~0.2 Si, in iron-carbon melt. It was found that all the alloys under consideration belong to the group of low-melting ferroalloys and process of their melting proceeds in three periods. With an increase in the initial diameter of ferroalloy piece from 3 to 100 mm, the melting time increases by 250 – 300 times. It is shown that an increase in Cr content up to 37 % in complex alloy leads to a decrease in the melting time, and with a further increase in the Cr content to 55 %, an increase in the melting time occurs. A decrease in temperature of liquid steel bath from 1700 to 1520 °С is accompanied by an increase in the duration of melting of complex ferroalloys by 7 – 8 times. In general, the considered complex nickel ferroalloys are characterized by a much faster melting process in liquid steel compared to standard ferrochrome and ferronickel.
Decarburization of periclase-carbon and aluminum-periclase-carbon ladle refractories
Authors: Yakushevich N. F. , Zapol’skaya E. M. , Temlyantsev M. V. , Protopopov E. V. , Temlyantseva E. N. , Prikhod’ko M. S.
Published: September 2022

In this paper, the processes of decarburization of periclase-carbon and aluminum-periclase-carbon ladle refractories were investigated. Decarburization processes take place already at the stage of drying and heating the lining after repair, during its heat treatment on gas or electric stands. These processes cause irreparable damage to refractories even before the ladle is put into direct operation (before contact with molten steel). One of the ways to increase resistance of carbon-containing refractories against oxidation is the use of antioxidants (Al, SiC, Si, etc.), which are introduced into the composition of the raw mixture at the manufacturing stage. Their action is based on priority oxidation compared to carbon. Antioxidants act in a certain temperature range, which opens up wide opportunities for development of energy- and resource-saving temperature modes for lining heat-treatment. The authors made mogravimetric analysis of periclase-carbon and aluminum-periclase-carbon non-ignited resin-bonded refractories of AMC 78-8/7HG, RI-MC175LC (RI); MayCarb 284-AX (MAYERTON) grades used in the execution of working layers of steel ladle linings. Thermogravimetric analysis of refractory samples was carried out on a LABSYS evo TG DTA DSC 1600 derivatograph when heated to a temperature of 1100 °C at a speed of 15 °C/min. X-ray phase analysis was performed on an XRD-6000 X-ray diffractometer. The results of thermogravimetric analysis are presented in the form of derivatograms. It was established that the maximum rate of carbon oxidation in all cases is reached at a temperature of 700 – 750 °C. Therefore, in order to implement a low-carbonizing first heating of the ladle after repair, temperature modes are recommended for refractories of the studied brands, including low-temperature (up to 500 °C) lining exposure.
Türkiye ve Fransa Ders Kitaplarında Kesirler Konusuyla İlgili Geometrik Temsillerin İncelenmesi
Authors: BAŞTÜRK Savaş , TAŞTEPE Mehtap , UZUN Pınar
Published: September 2022

Bilimsel bilgi tüm Dünya da aynı olmakla birlikte, öğretilen bilgi ülkeler arasında birçok açıdan farklılıklar göstermektedir. Bu farklılıkları yansıtan temel unsur öğretim programları olmakla birlikte, hem öğrenciler hem öğretmenler tarafından öğretim programlarının en iyi yansıtıcısı olan ders kitapları çok daha yoğun kullanılmaktadır. Bu araştırmada Türkiye ve Fransa’da kullanılan matematik ders kitaplarında kesirler konusu geometrik temsiller açısından incelenmiştir. Bu amaç doğrultusunda durum çalışması yöntemi kullanılmış ve doküman analizi gerçekleştirilmiştir. Elde edilen veriler içerik analizi yöntemi ile analiz edilmiştir. Sonuçlar Fransız ders kitaplarının Türk ders kitaplarına göre daha yoğun geometrik temsil içerdiğini, kullanılan geometrik şekillerin çeşitliliği anlamında iki ülke arasında farklılık olduğunu göstermiştir. Bu temsiller aracılığı ile öğrencilerden beklenen görevlerde de farklılıklar söz konusudur.
Analysis of the relationship between mathematics teacher candidates’ reflective thinking levels and their philosophical views on the nature of mathematics
Authors: YAZLIK Derya Özlem , GEDİK ALTUN Solmaz Damla , KAYA Deniz
Published: September 2022

The main aim of the present study with relational screening model was to analyze the relationship between reflective thinking skills and philosophical views regarding the nature of mathematics (NoM) in secondary school mathematics teacher candidates. In addition, it was aimed to determine whether the reflective thinking levels of the candidates displayed a significant difference according to absolutist, mixed, and semi-experimentalist groups. The study group consisted of 196 secondary school mathematics teacher candidates studying in the mathematics teaching program in the spring semester of the 2021-2022 academic year. As data collection tools, The Scale for Determining Philosophical Views Regarding the NoM and The Scale for Determining the Level of Reflective Thinking were used. In the analysis of the data, in addition to descriptive statistics, Pearson Product-Moment Correlation Coefficient and multiple linear regression analysis were employed. In the study, it was determined that both reflective thinking levels and the philosophical views regarding the NoM were found to be high in mathematics teacher candidates. Besides, it was determined that there was a positive and moderate relationship between the reflective thinking level subdimensions and and the philosphocial views on the NoM in the teacher candidates, and that the variables of the reflective thinking level subdimensions explained 44% of the variance in the philosophical views on the NoM. Moreover, it was concluded that there was a statistically significant difference between the semi-experimentalist group and the mixed and absolutist groups in favor of the semi-experimentalist group in terms of critical reflection, reflection and understanding skills, and between the absolutist group and the mixed and semi-experimentalist groups in favor of the absolutist group in terms of habitual actions subdimension.
城市微生物菌相調查計畫——採集土壤教學 v2
Authors: Wu Hsin-Mao
Published: September 2022

Soil sample, citizen scientist, 土壤樣本採集，公民科學家
Análisis de la fatiga pandémica como sentimiento existencial presente en referencia a las descripciones fenomenológicas de Heidegger y Levinas
Authors: Velázquez González Juan
Published: September 2022

El acontecimiento de la pandemia desatada en 2020 agudizó un fenómeno afectivo conocido como fatiga pandémica, cercano en términos médicos al “síndrome de fatiga crónica”. La explicación psicológica del fenómeno ofrece una primera aproximación, que se ve enriquecida por su descripción y análisis fenomenológico como sentimiento existencial del presente. Esta designación insiste en la referencia corporal de los temples de ánimo expuestos por Heidegger, y permite describir mejor el fenómeno de la fatiga en referencia a su estudio por Levinas. La fatiga profunda presente se muestra así como un sentimiento de cansancio que sujeta la existencia a un no poder ser y hacer lo que antes se podía, es decir, al pasado prepandémico. Junto a la descripción, el análisis fenomenológico del vínculo entre el aburrimiento profundo —estudiado por Heidegger— y la fatiga existencial pandémica pone de manifiesto los distintos niveles de comprensión ontológica de esta última y su carácter perjudicial.
EXPLORING THE CAUSES OF SELECTED CONDUCT DISORDERS AMONG SCHOOL-GOING ADOLESCENTS IN UGANDA AND SOUTH AFRICA
Authors: Loyce Kiiza Kobusingye , Newllin Marongwe
Published: September 2022

The study’s main issue was the causes of selected conduct disorders among adolescents in school. Adolescent conduct disorders emanate from a variety of factors that include social, economic, school, genetic status and parental factors. The purpose of the study was to explore the causes of selected conduct disorders among adolescents in school. The study was qualitative, explorative and phenomenological in nature. The study participants were parents and teachers. Data were collected using online (WhatsApp) focus group discussions due to restrictions brought about by COVID-19 that made physical interaction risky. Data were analysed in an integrative manner using findings from the two countries from parents and teachers, and thematically using themes generated from the outcomes of the online discussions. Findings indicate that conduct disorders among secondary school adolescents are a result of developmental, parental, school, social and academic factors. The study concludes that conduct disorders are recognised among the secondary school adolescents in Uganda and South Africa and pose a challenge to education and affect the proper functioning of schools. From the findings and conclusions, the researchers recommend hands-on parenting, adolescent psycho-social services, guidance and counseling services in schools, career guidance based on students’ needs, academic strengths and aspirations, positive peer groups and moderation of punishment at home and at school. This has implications on the need for dynamics in parenting, teacher-student relationships and psychosocial services that are detrimental in building healthy developmental milestones that have a direct impact on behavior and conduct among adolescents.
PENGETAHUAN, SIKAP DAN AMALAN BELIA DI LEMBAH KLANG TERHADAP UNSUR-UNSUR TRADISI DALAM PERLEMBAGAAN PERSEKUTUAN
Authors: Abd Wahab Mastura , Muda Khadijah , Wan Razali an Mohd Fazrul Azdi , Mohd Tohar Siti Nor Azhani
Published: September 2022

Unsur-unsur tradisi dalam Perlembagaan Persekutuan merangkumi peruntukan-peruntukan berkaitan institusi beraja, agama Islam, bahasa Melayu, dan hak istimewa orang Melayu. Namun, kini masih timbul isu pertikaian, penghinaan dan provokasi ke atas unsur-unsur tradisi ini oleh sebilangan rakyat Malaysia. Maka kajian ini bertujuan untuk menentukan tahap pengetahuan, sikap dan amalan belia terhadap unsur-unsur tradisi dalam Perlembagaan Persekutuan. Kajian ini dijalankan secara keratan rentas dengan pengedaran borang soal selidik ke atas 416 respoden dalam kalangan belia pelbagai etnik secara pensampelan mudah (convenience). Data dianalisis secara deskriptif dan inferensi menggunakan perisian SPSS. Hasil kajian mendapati bahawa tahap pengetahuan, sikap dan amalan belia terhadap unsurunsur tradisi secara keseluruhannya adalah tinggi. Justeru, setiap etnik di Malaysia perlu mengetahui, memahami, menerima dan menghayati sejarah penggubalan Perlembagaan Persekutuan dan unsur-unsur tradisi yang menjadi peruntukan-peruntukan asas dalam perlembagaan tersebut bagi mengukuhkan sifat keluhuran terhadap perlembagaan dan meningkatkan persefahaman antara kaum yang melibatkan isu berkaitan unsur-unsur tradisi ini.
RESEARCH RELATED TO FIREFLIES (COLEOPTERA: LAMPYRIDAE) AROUND THE WORLD OVER THE YEAR 2000 – 2021: AN OVERVIEW AND GUIDELINES
Authors: Ab Rashid Muhammad Fakruhayat , Abd Rahman Azimah , Abdul Rashid Siti Masayu Rosliah
Published: September 2022

Fireflies are groups of the Coleoptera order and the Lampyridae family. Fireflies are typically classified as nocturnal insects, however some are diurnal, and others have mixed nocturnal and diurnal characteristics. They are also known as luminescent insects due to their ability to emit light. Bibliometric analysis is a popular and rigorous method for discovering and analyzing enormous volumes of scientific data. Therefore, the objective of this study is to present overview and guidelines in studies related to firefly research worldwide from 2000 to 2021 using bibliometric analysis to provide researchers and scholars around the world an overview of results and trends in firefly research. A textual query on three databases; Scopus (289 papers), Web of Science (303 papers), and PubMed (541 papers) using the term “Fireflies Coleoptera Lampyridae” was performed on 30 August 2021 retrieving 1133 scholarly papers from 2000 to 2021 related to firefly studies for in-depth analysis. Bibliometric analysis were performed using Rstudio software version 4.1.1 and biblioshiniy for bibliometrix to visualize and analyze trends of firefly research. This bibliometric analysis was analyzed the annual scientific publication growth, the most productive authors, most frequent word has been using, most famous journal name, and which countries has highest collaboration with other country in firefly research. According to the findings of the analysis, there is significant inconsistency in global trends in annual scientific production, with the number of publications increasing and decreasing. In firefly research, according to the findings has show the most relevant authors is Fu X (Scopus), Fu XH (WoS), and Hosseinkhani S (PubMed). Moreover, the most relevant journals articles in fireflies studies is Zootaxa (Scopus & WoS), and Photochemical & Photobiological Sciences : Official Journal Of The European Photochemistry Association And The European Society For Photobiology (PubMed). Futhermore, the most frequently utilized keywords in fireflies study is lampyridae, firefly, bioluminescence, animals and fireflies. China and USA is the most highest collaboration among others countries in fireflies research. This research can help researchers or academics who are new to firefly research by providing information on which publications and authors to refer when performing firefly research.
SLANGA DALAM MEDIA SOSIAL: SATU PENDEKATAN MINIMALIS
Authors: Mohamed Sultan Fazal Mohamed , Azwan Pisol Muhammad Syafreza
Published: September 2022

Slanga ialah penggunaan bahasa yang tidak rasmi dan tidak dianggap sebagai bahasa standard dalam bahasa. Slanga juga mempunyai perbendaharaan kosa kata yang tersendiri dan dikategorikan sebagai kosa kata tidak formal. Namun kajian ini ialah mengenai penggunaan slanga yang digunakan dalam media sosial yang bertujuan untuk interaksi sosial. Objektif kajian ini adalah untuk menganalisis ayat selapis slanga dalam whatsapp dan instagram menggunakan kerangka minimalis dan menjelaskan pembentukan jenis ayat yang dianggap sebagai tidak formal. Kajian yang akan dilakukan oleh pengkaji hanya menggunakan kaedah kualitatif. Kaedah ini bersifat deskriptif yang lebih kepada penghuraian ‘makna’ ayat yang dikaji dengan mengumpul dan menjalankan analisis kandungan ke atas 25 ayat slanga daripada media sosial iaitu Instagram dan Whatsapp sebagai instrumen pemerhatian. Hasil kajian yang telah diperoleh daripada penggunaan bahasa slanga dalam media sosial seperti Whatsapp dan Instagram didapati mempunyai hubungan dengan kata ganti nama diri, kata kerja dan pengaruh bahasa asing. Slanga ini terdiri daripada empat bentuk perkataan slanga iaitu kata slang a yang merujuk kepada kata ganti nama (KGN) diri, kata slanga merujuk ekspresi, kata slanga merujuk kata kerja (KK) dan juga kata slanga yang dipengaruhi oleh bahasa asing. Kajian ini berjaya menunjukkan bahawa penggunaan slanga yang sedang berleluasa akibat media sosial mempunyai impak yang negatif terhadap bahasa Melayu jika tidak dibendung dengan sempurna.
SOCIAL INTERACTION AMID COVID-19 AND RESPONSES TO THE PANDEMIC IN SARAWAK
Authors: Liau Juna , Wan Ahmad Sharifah Sophia
Published: September 2022

This article documents social interaction among rural and urban indigenous communities in Sarawak during the COVID-19 pandemic and their responses to the outbreak at individual, household and community levels. The study on social interaction is crucial to shed light on larger social institutions and to examine how social actions are organized across space and time. The study framed within the symbolic interactionist perspective - emphasize the role of symbols and language as the core elements of social interaction. Research methods used in the study are participant observation and interviews to understand relevant context and process. In participant observation, researchers took part in socio-cultural activities of the community in the villages and their dwellings places in urban areas and participated in social media platforms. Data from observation and interactions (face-to-face or mediated by technology) analysed based on themes and contents. The findings show that social interaction among community members significantly altered during the pandemic in terms of the mode of interactions, frequencies, locations, reasons, duration, types and topics of interactions. These include the shift of face-to-face interactions to digital interactions, reduced numbers of interactions, significant more home-based interactions, and then unequal access to digital interactions. Other findings highlight that cultural themes related to communalism, supernaturalism and family and/or children influenced the community members’ engagement in social interactions. The community responses towards the outbreak varied according to the socio-economic background of individuals and households. Through these data the study shed light on how community members interacted during the pandemic; the exchanged of ideas and information, conflict during interactions, responses to the pandemic and the issues surround inequality of access to information and communication technologies.
Integrated Learning System of Sign Language
Authors:   Novosibirsk state technical University, Novosibirsk, 630073, Russian Federation, Lukoyanychev A. V.
Published: September 2022

The developed integrated system of sign language teaching, aimed at a wide range of users, is considered. The Dimskis notation for sign language writing implementation and the Unity 3D cross-platform development to control an animated 3D character are used in this system. The approach for the describing of 3D character movements based on the meta-language is proposed. The Dimskis notation has been expanded, within the framework of the meta-language. Additional and service characters, control words, special coordinates were introduced. Special control symbols and rules for processes synchronization have been developed. It is allows one to implement the movement of several elements at different times, to create complex movements, returning them to the initial state, to cancel the transferences of individual moving elements by using the "fictitious" movement, to change only individual coordinates of the avatars hand. The technique of creating the sign language reference book is considered. The advantages of this approach are analyzed. In addition to this full-fledged functional toolkit for creating the reference book the integrated system has the ability to test the users knowledge. The mode gesture demonstration — answer selection is proposer for mobile devices. For stationary devices with a fixed web camera the user has to show the gesture proposed by the system. The following stages of this mode implementation are considered: image capture, gesture localization, gesture identification, decision making. The gesture localization is based on the double background subtraction and histogram method. The gesture identification is based on the projection method and is carried out in two stages. At the first stage the entire hand is analyzed. If it is difficult to make a decision at this stage, then the second stage is carried cut, where only fingers are analyzed. The trend of arm movement between key frames is additionally determined for dynamic gestures. The features of each of the stages are shown. The algorithm for making a decision is given. The results of an experimental investigation are presented.
The universal content of courtly virtues as a prerequisite for Renaissance humanism
Authors:   Taras Shevchenko National University of Kyiv, Kyiv, Ukraine, Yefimenko V. V.
Published: September 2022

The article examines the formation of the foundations of the humanist ideology of the Renaissance in the culture of the European Middle Ages. The main stages of the formation and development of the culture of the Middle Ages and their achievements are traced. We pay attention on the "The Autumn of the Middle Ages" (J. Huizinga) and on such an important component of the culture of that time as the court culture, the culture of castles. It was during this period of a long era that the most important changes took place in the social and spiritual worlds of Europeans, which ultimately enabled the formation of the ideology of humanism with the system-forming worldview principle of anthropocentrism. On the examples of the work of troubadours and trouvers, Ch. de Troyes, B. de Born, the so-called of "marginal" sources that are, as it were, on the periphery of the text of medieval culture, but significantly supplement it ("The Miracles of Notre Dame" by Gautier de Coinci), an analysis is given of the filling of traditional courtly virtues with a new universal meaning, the affirmation of the worldview principle of anthropocentrism in the practice of human relations. The impact on this process of the Albigensian Crusade, a kind of catalyst for the growth of the demand for humanity in a society full of suffering and death, is noted. To virtues with a traditional meaning, such as kindness, generosity, courage, virtues with a humanistic meaning are added – mercy, love and friendship with vassals, care for subjects, equality with them in everything. New dramatic and even tragic dimensions of courtly virtues discovered by the troubadours during and after the Albigensians crusade became synonymous with humanism, a prerequisite for the formulation of the humanistic ideology of the Renaissance. The obvious connection with innovations in the system of the European society moral values, in the interpretation of the concept of common law, recognition of the right to autonomy in the development of a secular state is indicated.
İKİ FARKLI POMZA AGREGASI İÇEREN CAM TOZU KATKILI BETONLARIN FİZİKSEL VE MEKANİK ÖZELLİKLERİNİN İNCELENMESİ
Authors: CEYHAN Ali , SEVİNÇ Ahmet Hayrullah , URAS Yusuf
Published: September 2022

Bu çalışmada, farklı oranlarda bazaltik ve asidik pomza kullanılarak üretilen betonların fiziksel ve mekanik özelliklerini incelenmiştir. Pomza agregaları normal agregadan %50 ve %100 oranında ikame edilmiştir. Ayrıca daha çevreci bir beton üretmek amacıyla atık olan cam tozu çimentodan %10 oranında ikame edilerek 5 farklı karışım üretilmiştir. Üretilen numunelere birim hacim ağırlığı, su emme, porozite, ultrasonik ses geçiş hızı ve basınç dayanımı deneyleri uygulanmıştır. Çalışmanın sonucunda %100 oranında ikame edilen asidik pomza agregası en düşük yoğunluk, ultrasonik ses geçiş hızı ve basınç dayanımı değerleri verirken su emme ve porozite değerleri ise en yüksek çıkmıştır. %100 asidik pomza agregası içeren beton karışımı hariç diğer hafif beton karışımların tamamı TS 2511 standardında belirtilen taşıyıcı hafif betonu basınç dayanımı değerinden (17,2 MPa) daha yüksek basınç dayanım değerleri elde edilmiştir.
Clinical relevance of IL-6 gene rs1800795 polymorphism in patients with ischemic heart disease and chronic heart failure
Authors: Khazova Elena V. , Valiakhmetov Renat V. , Murzakova Aigul R. , Bulashova Olga V.
Published: September 2022

BACKGROUND: Inflammatory cascade contributes to the development of chronic heart failure. In this way, Interleukin-6 measurement in serum is relevant for understanding a course and prognosis in patients with chronic heart failure. Interleukin-6 expression correlates with IL-6 gene rs1800795 polymorphism.
AIM: This study analyzes the research articles about Interleukin-6 effects and IL-6 gene rs1800795 polymorphism in the patients with cardiovascular diseases with ischemic etiology.
MATERIALS AND METHODS: Systematic review and synthesis of findings of independent studies addressing the association between Interleukin-6 measurement and IL-6 gene rs1800795 polymorphism in the patients with coronary artery disease and chronic heart failure, including prognosis assessment.
RESULTS: The articles that were focused on the clinical features and outcomes in the patients with coronary artery disease and chronic heart failure depending on Interleukin-6 level have been analyzed. IL-6 gene rs1800795 polymorphism and its clinical significance have been introduced from the perspective of Interleukin-6 expression, C-reactive protein and lipids level in the blood. The meta-analysis data indicate the correlation between the rs1800795 and risk of coronary artery disease in comparison with homozygotes, as well as additive, recessive and dominant models. This review demonstrates relationship of polymorphism determination to left ventricular functioning, risks of chronic heart failure progression and future cardiovascular diseases.
CONCLUSIONS: The present study demonstrates that IL-6 gene rs1800795 polymorphism can provide comprehensive insights for prognosis assessment in patients with chronic heart failure.