Categorization Method Research Articles

Gaussian Blur Masked ResNet2.0 Architecture for Diabetic Retinopathy燚etection

Diabetic Retinopathy (DR) is a serious hazard that can result in irreversible blindness if not addressed in a timely manner. Hence, numerous techniques have been proposed for the accurate and timely detection of this disease. Out of these, Deep Learning (DL) and Computer Vision (CV) methods for multiclass categorization of color fundus images diagnosed with Diabetic Retinopathy have sparked considerable attention. In this paper, we attempt to develop an extended ResNet152V2 architecture-based Deep Learning model, named ResNet2.0 to aid the timely detection of DR. The APTOS-2019 dataset was used to train the model. This consists of 3662 fundus images belonging to five different stages of DR: no DR (Class 0), mild DR (Class 1), moderate DR (Class 2), severe DR (Class 3), and proliferative DR (Class 4). The model was gauged based on ability to detect stage-wise DR. The images were pre-processed using negative and positive weighted Gaussian-based masks as feature engineering to further enhance the quality of the fundus images by removing the noise and normalizing the images. Up-sampling and data augmentation methods were used to address the skewness of the original dataset. The proposed model achieved an overall accuracy of 91% and an area under the receiver-operating characteristic curve (AUC) score of 95.1%, outperforming existing Deep Learning models by around 10%. Furthermore, the class-wise F1 score for No DR was 92%, Mild DR was 82%, Moderate DR was 66%, Severe was DR 89% and Proliferative DR was 80%.

OBJECT CATEGORIZATION OF ENGLISH TERMS OF THE FOOD INDUSTRY

The article is devoted to the study of the peculiarities of the object categorization of English terms of the food industry. The relevance of the article is determined by the need to study object categorization in the formation, structuring and functioning of the English terminology of the food industry. The material of the study was the English-language terms of the food industry, which were obtained by the method of continuous sampling from specialized dictionaries. The analysis was carried out using definitional, semantic, categorical and conceptual research methods. The object category is widely represented by terms that designate concepts used in the terminology of the food industry and serve for their classification. It was determined that the terms representing the object category are divided into six groups: 1) terms for the designation of raw materials; 2) terms for labeling processing products; 3) terms for marking equipment and technology; 4) terms for marking packaging and labeling; 5) terms for designation of trademarks and brands; 6) terms for marking quality control and product safety. Groups of nominations corresponding to the object category are represented by the author. The study has shown that the various subcategories of the object are indeed represented in the specialized terminology of the food industry. The primary objective of the research is to shed light on the role of the object category and its linguistic representation in the English food industry terminology. The research also identifies productive linguistic elements, including special vocabulary, specialized morphemes, and syntactic constructions, that contribute to the formation of terms related to the object category. It is justified that the object category is widely used in the terminology of the food industry, as it is one of the basic categories that play an important role in the birth and formation of the naming of concepts in this industry.

P-ROCK: A Sustainable Clustering Algorithm for Large Categorical Datasets

Data clustering is crucial when it comes to data processing and analytics. The new clustering method overcomes the challenge of evaluating and extracting data from big data. Numerical or categorical data can be grouped. Existing clustering methods favor numerical data clustering and ignore categorical data clustering. Until recently, the only way to cluster categorical data was to convert it to a numeric representation and then cluster it using current numeric clustering methods. However, these algorithms could not use the concept of categorical data for clustering. Following that, suggestions for expanding traditional categorical data processing methods were made. In addition to expansions, several new clustering methods and extensions have been proposed in recent years. ROCK is an adaptable and straightforward algorithm for calculating the similarity between data sets to cluster them. This paper aims to modify the algorithm by creating a parameterized version that takes specific algorithm parameters as input and outputs satisfactory cluster structures. The parameterized ROCK algorithm is the name given to the modified algorithm (P-ROCK). The proposed modification makes the original algorithm more flexible by using user-defined parameters. A detailed hypothesis was developed later validated with experimental results on real-world datasets using our proposed P-ROCK algorithm. A comparison with the original ROCK algorithm is also provided. Experiment results show that the proposed algorithm is on par with the original ROCK algorithm with an accuracy of 97.9%. The proposed P-ROCK algorithm has improved the runtime and is more flexible and scalable.

Artificial Intelligence Technologies within the Risk-based Audit Approach – A Categorization and Classification Method –

Artificial Intelligence Technologies within the Risk-based Audit Approach – A Categorization and Classification Method –

Regulations, Agreements and Recommendations for Building a Livable Planet in Countries around the World

Caring for the earth is the common mission and responsibility of all mankind. Since the industrial revolution, mankind has been over-exploiting natural resources, and since the 1950s, a serious global ecological crisis has developed. International organizations and countries around the world have introduced regulations and agreements to provide institutional safeguards for building a livable planet. This paper adopts a combination of documentary and categorical research methods to collect various regulations and agreements signed by international organizations and countries around the world since the 1950s, and sort them out by categories according to the manifestations of ecological crises, and outline the core contents of regulations and agreements, based on which corresponding countermeasures and suggestions are put forward.

Categorization and Evaluation Methods for Control Strategies of Bilateral Tasks in Arm Prosthetics

Categorization and Evaluation Methods for Control Strategies of Bilateral Tasks in Arm Prosthetics

Assessment of Attachment in Psychosis: The Validity of the Psychosis Attachment Measure

Background. Attachment has become a central construct in explanatory models of psychosis. The Psychosis Attachment Measure is currently the most widely used measure for attachment in a population with a psychotic disorder. However, concerns have been raised about its psychometric properties. In addition, there are two perspectives to operationalize attachment: dimensional and categorical. The categorical method offers added value for the assessment of disorganized attachment which has been mostly linked with vulnerability to psychosis. Aim. The aims of this study were to re-evaluate the structural and construct validity of the dimensional and categorical approaches of the Psychosis Attachment Measure in a Dutch sample (N=287). Results. Confirmatory factor analysis indicated poor fit indices for the two-factor model with low loadings of the reversed questions of the Psychosis Attachment Measure on the avoidance factor. Removing these items improved model fit to conventional threshold values. Latent profile analyses suggested a four-class solution: secure, preoccupied, dismissive-avoidant, and disorganized attachment. The construct validity of both approaches was largely in line with expectations. Conclusion. Both the dimensional and categorical perspective of attachment in psychosis may be used to gain a better understanding of the complexities in the attachment system.

Research on the Reform of Civic Science Course Based on the "Interclassroom Behavior" of Engineering Students

In this paper, 1500 engineering college students in Jiangsu Province, China, were studied by observation, questionnaire, and categorization methods to investigate the "Inter-classroom behavior" of engineering college students. Nine types of behaviors were found: playing mobile games, watching short videos, shopping on Jindo, reading BILIBILI website, studying math or English, chatting, opening "Learning Power" app to study, drowsing and sleeping, going to the bathroom or going for a walk. The author believes that the nine types of " Inter-classroom behaviors" of engineering students reflect their needs. Integrating these student needs into the reform of the Civics course will stimulate the learning enthusiasm of engineering college students and thus enhance their Civics awareness, Civics ability and Civics self-awareness. Therefore, this paper builds a curriculum based on "physical and mental health-video productionmethodology education-examination subjects-study and study" based on the "Inter-classroom behavior" of engineering students. Therefore, this paper builds a reform system of Civic Science curriculum for engineering students based on "physical and mental health, video production, methodological education, study subjects, study and research, and sports and labor education". The sample size of this paper is still relatively small and has certain research limitations. In the future, we will expand the research base, fully explore different spatial and temporal characteristics, more comprehensively and precisely extract the needs of engineering college students, so as to study the curriculum reform based on their needs.

An Efficient Ontology Based Machine Learning for Classifying High Definition Satellite Images (Chandrayaan-3)

The analysis of satellite images to determine the kind of land, forest cover, plant type, and other aspects of a particular image has become a standard practice. Object-based image classification for land-cover mapping with remote-sensing data has received a lot of interest in recent years. Several researches have looked into a range of sensors, feature extraction, classifiers, and other important elements throughout the last decade. These data, however, have yet to be gathered into a complete reference on the implications of different guided object-based land-cover categorization methods. To solve this issue, we provide an ontology-based conceptual UKNN classification algorithm in this study. We create an 18-field database from the rit18 database's qualitative and quantitative data in this research. Instead of unexplainable characteristics provided by a CNN, this proposed study uses an ontology-based methodology framework to enable picture classification using features extracted from hyper spectral image data. The image is initially given a Gaussian filter. The suggested UNet K nearest neighbours (UKNN) classifier is utilised to translate the ontology components into image-based parameters, which are then used to improve the classification process. When a typical support vector machine (SVM) is compared to UKNN, we find that UKNN outperforms SVM in classification accuracy

REGULAÇÃO EMOCIONAL NO LOCAL DE TRABALHO: UM ESTUDO QUALITATIVO COM PROFESSORES

ABSTRACT: This study aimed to characterize the emotional labor of the professional and technological education teacher by examining the emotions and the emotion regulation strategies teachers adopt. Eight focus groups were held, with the participation of forty-one teachers to collect the data. For the data analysis, we adopted the inductive and deductive categorization methods. The results showed that different emotions are activated in the face of specific emotional demands and that teachers use a variety of strategies, either in isolation or in chains, to regulate them. However, cognitive change strategies and situation modification of the procedural model of emotional regulation were more frequently reported. The results suggest differences in the regulatory preferences of the teachers based on the career period and the training /performance area. Future research could use varied methods (e.g., observation diary) to investigate the regulation’s dynamic, context, and outcomes and develop a contextual scale of teacher emotion regulation. The findings have implications for teacher training programs, educational management, and future research.

Active Learning Based on Transfer Learning Techniques for Text Classification

Text preprocessing is a common task in machine learning applications that involves hand-labeling sets. Although automatic and semi-automatic annotation of text data is a growing field, researchers need to develop models that use resources as efficiently as possible for a learning task. The goal of this work was to learn faster with fewer resources. In this paper, the combination of active and transfer learning was examined with the purpose of developing an effective text categorization method. These two forms of learning have proven their efficiency and capacity to train correct models with substantially less training data. We considered three types of criteria for selecting training points: random selection, uncertainty sampling criterion and active transfer selection. Experimental evaluation was performed on five data sets from different domains. The findings of the experiments suggest that by combining active and transfer learning, the algorithm performs better with fewer labels than random selection of training points.

중학교 영어 다독을 통한 학습자 수준별 읽기 전략 변화연구

Objectives This study conducts English extensive reading in middle school and analyzes the changes in reading strategies by the learner’s level.
 Methods To this end, a 12-week extensive reading class was conducted for the 3 levels of 6 first-year middle school students. Data were collected using observation journals, reading journals, and interviews and analyzed using the constant comparative method of transcription, coding and categorization, and theme development. As a result, high-level learners understood the types and characteristics of various strategies well, selected and used appropriate methods for the situation, and the areas of frequently used strategies were found to be different depending on the learner's level.
 Results Students at the middle proficiency level students used Problem solving strategies when they faced the difficulties. Lower proficiency level students tried to activate their prior knowledge and use the pictures of the text, but with limited results.
 Conclusions Based on this results, the researchers would like to give some suggestions. First, Extensive reading program should be prepared beforehand. Various Extensive reading program and English library should be offered. Reading various materials will build confidence and clear goals to the students. Second, students should able to select material they can read with ease. They should not experience the frustration of reading materials beyond their reading capabilities.

Review on Human Activity Recognition for Military Restricted Areas

Abstract: Human Activity Recognition(HAR) is an active field of research and scientific development in which various models have been proposed using different methods for identification and categorization of activities using Machine Learning. HAR has reached a remarkable milestone in the area of computer vision. Except for applications in human-computer interactions, surveillance systems and robotics, lately it has extended its applicability in the fields of healthcare, multimedia retrieval, social networking, and education as well. It aims to bring latest technologies together to develop complex assistive system with adaptive capability and learning behaviour. HAR interprets human motion using computer and machine vision technologies to identify and detect simple and complex actions in real-world. This paper presents research made for surveillance of restricted military areas. Our scope is to develop a live monitoring system for tracking the illegal activities done in the restricted area for border security, which is an issue of concern since decades. In this we have introduced a deep learning model that learns to classify human actions without having prior knowledge. The features of image or video set are extracted and detected for detected for classifying whether the activity is illegal or not. Many harmful actions can be avoided or at least have their negative effects reduced as a result of the adoption of this concept. Finally, the activity recognition rate showed a good performance as a result of these findings

Assessment of Credit Pattern of Small and Marginal Farmers in Cauvery Delta Zone of Tamil Nadu, India

Finance is the lifeblood of any business same way credit is the lifeblood of agriculture. Without credit, farmers cannot do farming activities. Hence the Primary Agricultural Credit Co-operative Societies provide credit to farm and non-farm activities in rural areas to improve agriculture. The adequate and timely availability of credit at reasonable rates is crucial for agricultural development. The study is based on households’ survey conducted in six blocks from three districts viz., Ammapettai and Orathanadu blocks of Thanjavur district, Needamangalam and Mannargudi blocks of Thiruvarur district, Kilvelur and Thirumarugal blocks of Nagapattinam district. Two villages from each block were selected purposively based on more area under rice cultivation. Sample size of 366 farmers which consisted of 183 marginal and 183 small farmers was selected randomly based on proportionate random sampling method. The data were statistically tabulated and analyzed by calculating simple percentages and cumulative square root frequency method for categorization. Nearly one-fourth of the farmers (24.86%) had low level of credit orientation followed by 23.50 per cent had very low level, 21.58 per cent had high level, 15.03 per cent of farmers had medium and very high level of credit orientation. The small farmers having high credit orientation than marginal farmers, the most of the small farmer’s occupational status was farming and business. They utilize credit for their farm, household and non-farm activities. More than three-fifth of the marginal farmers (63.39%) sometimes relying on individual moneylenders for their credit source followed by 45.36 per cent of small farmers sometimes rely on individual money lenders for their credit source and more than half of the farmers (54.37%). Most of the marginal and small farmers were having low to medium level of income category, they depend on banks, co-operative societies and money lenders for their credit source. Mostly they allocate equal percentage of loan for the farm and household expenses. The policy makers can make note of the utilization pattern of agricultural credit and can give directions on the lending terms and conditions.

On the Thermal Environmental Quality of Typical Urban Settlement Configurations

Urban overheating and energy imbalances are severe environmental concerns. The role of urban sprawl patterns in the formation of Heat Island has recently absorbed the researchers’ interest. The research focuses on metropolitan areas with a range of urban typologies. However, there still is a knowledge gap in how UHI responds to different urban typologies. The interaction between urban configurations and heat island characteristics is explored in Sydney. A combination of terrestrial surveys and modelling techniques was implemented, and results were extracted based on simulation results. The Urban Taskforce Australia suggested the applied categorization methods that follow Stewart and Oke’s Local Climate Zones (LCZs) scheme. We assessed eleven urban designs on ambient air temperature, wind characteristics, heat intensity, and outdoor thermal comfort over three summer days. We correlated results to density and the built-up ratio in all configurations and found that the maximum configurational impact on the heat island reached 2.33 °C. Configurations with a built-up ratio between 0.37 to 0.5 present a sharp downward trend in the average wind speed value and indicate a minimum with a built-up ratio of 0.63. Wind maps present an increase in layouts with built-up ratios of 0.23 to 0.37, whereas they decreased with built-up ratios of higher than 0.43. The average temperature decrease in high-rise compact configurations was 1.12 °C per hour. This record is substantially higher than its open counterparts. The study showed the importance of urban configuration on thermal environmental quality. In addition, implementing appropriate urban design parameters is vital to mitigate heat islands and improve environmental thermal comfort in urban areas.

Similarity Correlation of Frequency Distributions of Categorical Data in Analysis of Cognitive Decline Severity in Asthmatics

The paper presents the method of measuring the similarity and difference in the frequency distributions of one categorical variable for different levels of another variable. This method calculates the similarity and correlation between the rows of the contingency table. In this work, we use it for the analysis of associations of cognitive indicators. The proposed categorical data association analysis method can be used as an addition to the classical chi-square test.

Credit in the method categories "The final information flow"

The purpose of this study is to develop a model of qualitative characteristics of the loan. Hypothesis. It is assumed that the emergence and development of qualitative characteristics of credit occurs in response to a change in the environment. Methods: critical analysis of scientific literature, generalization, systematization of information, categorical method "Finite information flow". the results of the study. A set of qualitative characteristics of the loan has been developed, reflecting the logic of its natural evolution, allowing its identification; an information model of credit evolution is constructed, which allows identifying and describing its types and forms, starting from any logical level identified in it. Conclusion. the proposed model of the qualitative characteristics of the loan reflects the process of gradual complication of the loan, an objective increase in the level of its organization in the process of evolution.

Keterlibatan Orangtua Siswa Berkebutuhan Khusus Di Masa Pandemi Covid-19: Studi di Sekolah Inklusi

The role of parental involvement in the development and outcome of students with special needs is instrumental, especially during the remote learning period. However, parents are not always involved in children's learning activities at home on a regular basis, especially if they feel the students have been helped at school. This study aims to look at the involvement of parents of students with special needs at inclusive elementary school level during the remote learning period due to the COVID-19 pandemic. This quantitative study utilized a questionnaire based on the Hoover-Dempsey and Sandler parental involvement model on parents of students with special needs in Greater Jakarta. The data were interpreted using the hypothetical categorization method. The results showed that parental involvement was high, especially at home. In addition, parental role construction and perception of involvement invitation from school were high. These results show that despite the alarming pandemic condition, parental involvement remains high. This is presumably because parents still have to support their children even if they have to sacrifice their time. Suggestions are discussed to maintain the level of parental involvement and to address less ideal motivating factors.

Efficacy of Psychotherapeutic Interventions in the Treatment of Breast Cancer Patients

The aim of the article is to provide a theoretical review of methods of psy-chological assistance for breast cancer patients to describe the most effective ways to apply them in the work of a psychotherapist, taking into account the characteristics of patients and disease specifics.methods of the research. The following theoretical research methods were used to solve the tasks: categorical and structural-functional methods, as well as analysis, synthesis, generalization, systematization, and comparison.results and discussion. Based on the conducted theoretical analysis, three main psychotherapeutic approaches were identified, which are most often used in the work with breast cancer patients: cognitive behavioral psychotherapy, exis tential psychotherapy, and psychodynamic psychotherapy. The aim of the article is to provide a theoretical review of methods of psy-chological assistance for breast cancer patients to describe the most effective ways to apply them in the work of a psychotherapist, taking into account the characteristics of patients and disease specifics.methods of the research. The following theoretical research methods were used to solve the tasks: categorical and structural-functional methods, as well as analysis, synthesis, generalization, systematization, and comparison.results and discussion. Based on the conducted theoretical analysis, three main psychotherapeutic approaches were identified, which are most often used in the work with breast cancer patients: cognitive behavioral psychotherapy, exis tential psychotherapy, and psychodynamic psychotherapy.

The Ways of Formation of Future Translators’ Readiness to Perform Professional Activities in the Conditions of War

the purpose of our research is to characterize the ways of assessing the readiness of future translators to perform professional activities in the condi-tions of war; to identify the level of formation of students’ motivational, seman-tic, operational and value readiness to perform translation activities.methods of the research. The following theoretical methods of the research were used to solve the tasks formulated in the article: a categorical method, structural and functional methods, the methods of the analysis, systematization, modeling, generalization. The empirical method is ascertaining research. he results of the research. So, the professional development of the indivi-dual can take place in several stages. The first stage is considered to be pre-pro-fessional training, the main purpose of which is the professional self-determina-tion of the individual, the formation of the attitude towards a certain profession, and the realization of the person’s conscious choice of his/her professional acti-vity. This is the process of forming the individual’s attitude towards himself/her-self as a subject of future professional activity, which in a long period of time will help a person adapt to life as a whole. Pre-professional training is interpreted as the preparation of the polytechnic and professional character of students, as a basic component of their further professional training.conclusions. Thus, professional formation is a process, which has the aim of the development and the formation of the personality of a future specialist as a subject of professional education and activity. We proved, that the subjec-tive qualities of a specialist are mainly determined by his/her subjective posi-tion, which should be defined as a kind of integration of the dominant sovereign qualities of a professional, which are decisive in any significant professional is-sues or problems for a specialist. The subjective position of a specialist is a ba-sic, a dominant component in the professional model of personality’s formation, a fundamental characteristic of his/her behavior in the profession. Subjectivity presupposes, first of all, the formation of worldview guidelines, moral and va-luable qualities of the individual, which determine not only the active position of the professional, but also the worldview orientations of the specialist.