bluuebunny/crossref_metadata_2025 huggingface dataset:
Irritable bowel syndrome phenotypes: leading factors of genetics and epigenetics, mechanisms of formation
Authors: Gaus Olga V. , Livzan Maria A.
Published: March 2023

Aim. To develop individualized approaches to the treatment of irritable bowel syndrome (IBS) based on the interaction of genetic and epigenetic factors, to characterize the phenotypes of the disease.
Materials and methods. According to the formulated concept of the authors, from the cohort of patients with IBS, subgroups were distinguished post-infectious IBS (n=45), IBS in overweight and obese people (n=49), comorbid IBS (n=75) and essential IBS (n=51). In each subgroup the prevalence of candidate gene polymorphisms associated with IBS (COMT, SLC6A4, FTO), nutritional habits, levels of anxiety and depression, secretion of cortisol, serotonin, dopamine and zonulin levels in feces were studied.
Results. Patients with post-infectious IBS are characterized by the carriage of the S allele of the SLC6A4 gene, the val/val genotype of the COMT gene, the prevalence of diarrhea, a high level of anxiety and frequent refusal of milk and dairy products. The phenotype IBS in overweight and obese individuals is characterized by L/L genotypes of the SLC6A4 gene, met/met of the COMT gene and A/A of the FTO gene, constipation, low plasma dopamine levels, signs of depression, frequent episodes of overeating, addiction to fatty and sweet foods, excessive consumption of sugar, lack of vegetables in the diet. The comorbid IBS phenotype is characterized by more frequent detection of the val/val genotype of the COMT gene and the carriage of the S allele of the SLC6A4 gene, clinically pronounced anxiety and depression, early onset of the disease, severe course, significant food restrictions and significant increase in epithelial permeability. With the essential phenotype, there are no bright stigmas of the disease; it is not possible to identify distinctive genetic and epigenetic factors, as well as the leading pathogenetic mechanism.
Conclusion. The analysis of genetic and epigenetic factors, the leading mechanisms of the formation and course of IBS allows us to identify additional (except for postinfectious) phenotypes of the disease: IBS in overweight and obese people, comorbid and essential.
Sentiment analysis and offensive language detection in social media
Authors: Shiny M.
Published: March 2023

Sentiment Analysis is a field of study that focuses on figuring out how to extract, identify, or otherwise describe emotions in units of written text. One of the most common tasks in sentiment analysis is finding the polarity of a person's feelings. There are many blog posts, tweets, and comments in Indian languages online these days. Sentiment analysis in Indian languages is a relatively new field, and research in this area is just beginning. There is a lot of offensive content on social media, which is a worry for businesses and government agencies. This paper presents the methodology of sentiment analysis and offensive language detection in social media.
Techniques for Detecting Video Shot Boundaries: A Review
Authors: Sharma S. , Malakar P.
Published: March 2023

Due to the Corona Virus Diseases (COVID-19) pandemic, education is completely dependent on digital platforms, so recent advances in technology have made a tremendous amount of video content available. Due to the huge amount of video content, content-based information retrieval has become more and more important. Video content retrieval, just like information retrieval, requires some pre-processing such as indexing, key frame selection, and, most importantly, accurate detection of video shots. This gives the way for video information to be stored in a manner that will allow easy access. Video processing plays a vital role in many large applications. The applications required to perform the various manipulations on video streams (as on frames or say shots). The high definition of video can take a lot of memory to store, so compression techniques are huge in demand. Also, object tracking or object identification is an area where much considerable research has taken place and it is in progress.
Fire and smoke detection with deep learning: A review
Authors: Vinay Kumar Jain , Chitrangad Jain
Published: March 2023

This paper outlines a state-of-the-art method for smoke and fire detection utilizing Convolutional Neural Networks (CNNs). The current smoke detectors installed in buildings pose a challenge for effective fire detection. The inefficiency of traditional methods in terms of speed and cost led to the exploration of using Artificial Intelligence (AI) to identify and alert from Closed Circuit Television (CCTV) footage. In this paper, an analytical overview of AI is conducted by using a selfcreated dataset of video frames containing flames and smoke. The data undergoes pre-processing before being used to train a CNN-based machine learning model. The goal of this review study is to understand the available literature in the field and propose a highly accurate, cost-effective, and simple system for fire detection in various scenarios.
Chaotic Particle Swarm Optimization with Attractive Search Space Border Points for Optimal Reactive Power Dispatch
Authors: P. Lokender Reddy , Yesuratnam G.
Published: March 2023

This paper presents a reliable approach for optimal reactive power dispatch based on chaotic particle swarm optimization with attractive search space border points, where the particles are randomly attracted to the boundary points of the search space in each direction avoiding stagnation of the population. The introduction of chaotic dynamics improves the stability and rate of convergence. The algorithm is further improved by using Latin Hypercube Sampling (LHS) to create diversity in the population. The proposed algorithm is used for optimal reactive power dispatch with three objective functions, namely: minimization of real power loss, voltage stability index, and sum squared voltage deviations. The algorithm is tested on a standard 30-bus system of the Institute of Electrical and Electronics Engineers (IEEE) and on a practical 75-bus Indian Power System. The results obtained with the proposed algorithm are compared with the conventional interior point method and the basic particle swarm optimization algorithm, and the effectiveness of the proposed algorithm is demonstrated.
Controlling Speed in Induction Motors with Fuzzy Logic and a PI Controller
Authors: Deepika Dewangan , Alka Mishra , Surekha Bhusnur
Published: March 2023

The purpose of this paper is to illustrate the dynamical response of speed using the design of a Fuzzy Logic Controller (FLC) to regulate the motor speed, while the load changes. Induction motor power control has become popular in recent years in high-performance drive systems. It is due to its amazing qualities, such as high-performance, a high energy factor, and significant toughness. The overall performance of the controller is estimated using MATLAB or Simulink software and a common Proportional Integral (PI) management technique. This work discusses the design and construction of a voltage supply inverter-based Space Vector Pulse Width Modulation (SVPWM) system for regulating the speed of an induction motor. This observation also incorporates a fuzzy controller into the SVPWM to maintain the motor speed constant even when the load varies. FLC is used to alter the pulse width of the Pulse Width Modulation (PWM) converter, which controls the motor pace. This paper describes the application of a rule-based Mamdani type FLC to a closed loop induction motor model.
Design of drowsy and alcohol consumption detection system in vehicles using at mega microcontroller
Authors: Shiny J.
Published: March 2023

Driver drowsiness and alcohol consumption are the most common causes of traffic accidents and the resulting financial losses. Researchers have been working on developing driver inattention monitoring systems as drowsy and drunken driving have significantly increased the number of road accidents, which results in serious and deadly collisions. The enormous benefits of sleep detection in road transportation cannot be overstated. The proposed work consists of the design of a drowsy and alcohol consumption detection system in the vehicle using an AT Mega microcontroller monitoring and control system to avoid accidents due to driver inattention. This system consists of an eye blink sensor and an alcohol sensor in the vehicle to alert the driver. This proposed system generates a model which can prevent such accidents.
The effect of teaching based on mathematical modeling on students' academic achievement in mathematics and science education: a meta-analysis
Authors: Hatice Gözde Uysal , Sedat Kanadli
Published: March 2023

The aim of this study is to determine the effect of teaching based on mathematical modeling on the students' academic achievement in mathematics and science education through meta-analysis. In this study, experimental studies carried out in the national and international literature were included in the meta-analysis. As a result of the literature review, 23 studies were obtained. The effect sizes were combined according to the random-effects model. As a result of the metaanalysis, the common effect size for academic achievement was calculated as 0.976 with a 95% CI of [0.742, 1.205]. It has been determined that mathematical modeling applications have a "large" effect on the students' academic achievement. As a result of the moderator analysis, it was determined that the effect sizes differed significantly according to the education level and course type but did not show a significant difference according to the research method, research design, and statistical test type. In addition, it was determined that the size of the class and the duration of the experimental procedure were not significant predictors of the effect sizes. According to these results, it can be said that teaching based on mathematical modeling can be an effective method of improving the academic achievement of students in science and mathematics education.
Ontological development of a competency based and learning objective oriented measurement tool
Authors: Kemal Şimşek , Aysun Aytaç , Jale İpek
Published: March 2023

This study aimed to define the concepts and learning objectives related to the polygons sub-learning area of the 7 - grade mathematics course as ontology-based and to develop a measurement tool based on this ontology within the framework of competency ontology. In this study, we determined and included the learning objectives in the ontology alongside the concepts and prerequisites. The most crucial difference that distinguishes this study from others is that it is objectively oriented. Throughout the study, we followed ontology development processes that met the system's requirements based on the ontology development. In this context, we saw that the ontology developed answered the intended competency questions. We think this study will make very important contributions in terms of bringing a different perspective to measurement and assessment in mathematics education.
Investigation of the opinions of hearing impaired students on digital teaching materials prepared on the decimal breaking operations
Authors: Sercan Ertaş , Jale İpek
Published: March 2023

The purpose of this research was to determine the opinions of hearing-impaired students about the digital teaching material prepared for subtraction, which requires decimal breaking. To achieve this goal, a digital teaching material that includes decimal breaking operations was developed. The case study method, a qualitative research method, was used to determine the opinions about the developed material. Four secondary school students, two primary school students, one secondary school mathematics teacher, and one primary school mathematics teacher participated in the study during the 2020-2021 academic years. Documents, interview forms, system records, observations, and video recordings were used as data collection tools to contribute to the research. The data obtained from the data collection tools were analyzed using the techniques commonly used in qualitative research, including content analysis and descriptive statistics. The results of the research showed that the developed digital teaching material has a positive impact on students' learning, the absence of distracting elements on the material reduces students' distraction, and students showed interest and success in using the material. The teachers' opinions supported the students' opinions and once again demonstrated the effectiveness of the digital teaching material in the education of hearing-impaired students.
Revisiting the modality and redundancy effect in an augmented reality-based language learning environment
Authors: Bora Demir , Ceyhun Karabıyık , Muzaffer Özdemir , Meltem Baturay
Published: March 2023

This study examines the effect of modality and redundancy in an Augmented Reality (AR) based language learning environment for teaching vocabulary in a foreign language. The study aims to determine the effectiveness of the redundancy and modality principles, examine the relationship between cognitive load, satisfaction, anxiety, willingness, and achievement, identify predictors of achievement, and understand how students perceive AR-based vocabulary learning in three different presentation modes (animation + narration + text, animation + narration, and animation + text). The study used a pre- and post-test control group quasi-experimental design, with 97 Turkish-speaking undergraduate students from the Faculty of Education at a state university participating. The study participants were divided into three groups and practiced using the same AR-based flashcards in three different modalities (animation + narration + text, animation + narration, and animation + text). After completing a short distractive task during the practice session, the participants were given an achievement test. The analysis of the data revealed that while the group that used animation + narration outscored the other two groups, the difference was only significant between the animation + text group and the animation + narration group, which supported the modality principle. However, there was no significant difference between the animation + narration + text group and the animation + narration group, which did not support the redundancy principle. The study also included qualitative data from a focus group interview to support the quantitative findings. The conclusion of the study is that the principles of CTML (Cognitive Theory of Multimedia Learning) should be reconsidered in relation to the use of AR technology in instructional settings.
Conversion process of natural gas into liquid fuels
Authors: Suriya Krishna K. A. , Farzan Khan , Yogesh Chandra Upreti , Bala Bharat Sai S.
Published: March 2023

Gas-to-Liquid (GTL) technology has developed over the past few decades into a financially sound industry offering market diversification to remote natural gas resource stakeholders. Presently, several patented technologies are available for the petroleum industries to transport natural gas cheaply in liquefied form. In the recent past, low natural gas prices in North America can be attributed to the isolation of shale gas resources using GTL technology. Some small technology providers are currently using GTL to eliminate associated gas flaring in remote oil fields. Several smaller technology providers are now looking to GTL to stop associated gas flaring in remote producing fields. In addition, GTL has the potential to extract liquid fuel in gas-rich inland areas. The GTL technology is preferred as the existing technologies that process natural gas through olefins are more complex and have so far proven difficult and costly in terms of commercial viability. The various GTL technologies having prospective market scope are reviewed this article.
Fruit recognition using image processing
Authors: Pratibha Sahu , Abhishek Dewangan , Snehlata Mandal
Published: March 2023

Manually classifying and evaluating anything is difficult. It is difficult to manually count ripe fruits and evaluate their quality. Increasing labor costs, a shortage of skilled workers, and declining storage costs are just some of the major challenges associated with fruit production, marketing, and storage, among others. An effective method for localizing all clearly visible objects or portion of an object from an image has been proposed in this study, requiring less memory and processing resources. The main obstacles for object detection, such as object overlap, background noise, low resolution, etc, that prevents us from obtaining better results has been overcome by processing every input image. It also built an enhanced classification or recognition algorithm based on convolutional neural networks, which has shown to perform better than baseline studies.
A review on image captioning system from artificial intelligence, machine learning and deep learning techniques
Authors: Revathi B. S. , A. Meena Kowshalya
Published: March 2023

Image Captioning is the process of generating textual descriptions of an image, which need to be syntactically and semantically correct. This paper extensively surveys very early literature that includes the advent of Artificial Intelligence, the Machine Learning pathway, the early Deep Learning and the current Deep Learning methodology for Image Captioning. This survey paper aims to develop a system to predict captions for the given images with a higher accuracy by combining the results of different Deep Learning Techniques. This model based on a neural network consists of a vision CNN followed by the language generator RNN. It generates complete sentence in natural language from an input image. The state of art is achieved by comparing three different encoder –decoder models. By comparing three models, the blue score of CNN-LSTM Model with Flikr 8k dataset is 0.44, CNN-LSTM Word Embedding with Flikr 8k dataset is 0.68 and CNN –GRU model Visual Attention with MSCOCO Dataset is 0.86.
Implementation of image fusion model using DCGAN
Authors: Sreedhar P. S. S. S. , Balaji Tedla , Sai Somayajulu Meduri
Published: March 2023

Remote Sensing Images (RSI) are captured by the satellites. The quality of the RSIs primarily depends on environmental conditions and image-capturing device capability. Rapid development in technology leads to the generation of High- Resolution (HR) images from satellites. However, these images are to be processed in a scientific way for the best results. A new Image Fusion (IF) technique with the help of wavelets, Deep Convolutional Generative Adversarial Networks (DCGAN), was designed to get super-resolution images for satellite images. Residual Convolution Neural Network (ResNet) increases the fused image accuracy by minimizing the vanishing gradient problem. Peak Signal to Noise Ratio (PSNR), Structural Similarity Index Method (SSIM), Feature Similarity Index Method (FSIM), and Universal Image Quality (UIQ) are taken as the metrics for comparing the results with other models. The experimental results are better than previous methods and minimize the spatial and spectral losses during the fusion.
Machine learning and deep learning techniques for detecting fraud involving credit cards
Authors: Aastha Joshi , Nirmal Gaud
Published: March 2023

A credit card is still a highly common form of installment that allows for cashless purchases and is acceptable both offline and online to conduct payments and other trades. The prevalence of cloned credit cards is rising along with innovation. Budgetary fraud always seems to get worse when international communication gets better. These infringements have generated billions of dollars. These actions are executed with such skill that they vaguely align actual commercial transactions. Simple plan requirements and other less composite techniques won't function as a consequence. In order to lessen confusion and re-establish order, all banks currently need a well-organized approach for identifying credit card fraud. It has taken into consideration a number of common machine learning and deep learning methods for the classification of default accounts, which basically entails analyzing credit card fraud. It consist of synthetic neural networks, decision trees, random forests, and logistic regression (ANN). For every approach, the model has been trained and its accuracy has been assessed. The classification computations are merged to create a sample, and then it is compared to different deep learning and machine learning algorithms.
Mathematical Modelling of EOR Methods
Authors: Tirumala Rao Kotini , Aman Singh
Published: March 2023

The choice of appropriate and affordable procedures to boost oil recovery is usually recognized as one of the main challenges in reservoir development due to the huge demand for crude oil. Reservoir flow simulators are valuable tools for understanding and forecasting fluid flow in complex systems. The goal of this study is to run a mathematical model to evaluate the performance of various oil recovery methods, as well as to validate the model's accuracy with simulated field data. Thereby, the results of this developed model indicate that the model is approximately matched with the simulated field data. Enhanced oil recovery typically refers to chemical, miscible, thermal, and microbial processes. A system of nonlinear partial differential equations composed of Darcy's and mass conservation equations governs the model. The system is then numerically solved using the IMPEC (Implicit Pressure and Explicit Concentration) scheme by a finite difference method. We chose this approach because the experimental approaches are not only time consuming, but also costly. As a result, mathematical models could aid in the understanding of a reservoir and how such processes can be optimized to maximize oil recovery while lowering production costs. This paper provides a brief overview of mathematical modelling of various enhanced oil recovery methods, focusing on developing a generalized framework and describing some of the key challenges and opportunities.
Self-efficacy of senior prelicensure nursing students during student-led high-fidelity patient simulation
Authors: Jennie Bergen , Carmen V. Harrison
Published: March 2023

Simulation has been shown to offer nursing students supplemental learning experiences outside of regular clinical settings. However, these learning experiences are primarily conducted with faculty serving as the patient voice, leading the scenario and prompting nursing actions. As students function within the scenario, psychomotor, cognitive, and affective learning occur within the context of the nurse's role. Little is known about whether student participation as the patient increases the self-efficacy of students' abilities to enhance their understanding of the patient's experience during a deteriorating patient simulation scenario. The purpose of the study is to examine students' self-reported evaluations of simulation sessions. Secondary data from a simulation evaluation tool will be examined with a mixed-method, descriptive, and comparative design to determine if students reported increased self-efficacy following student-led, compared to faculty-led, high-fidelity patient simulation sessions. Findings from this study will help determine the need for more innovative pedagogy to support learning outcomes.
Solar Energy Applications for Agriculture: A Review
Authors: Manoj Khoja
Published: March 2023

Various solar energy harvesting technologies have been developed and tested for agricultural applications. Renewable energies such as biomass, solar, and wind energy offer long-term energy sources for farmers and can replace other fuels. Many renewable energy technologies are used in agriculture, depending on the type of energy required, the availability of renewable energy sources, and the design of agricultural structures and processes. Solar energy is used in agriculture for a variety of purposes to increase self-sufficiency, save money and bills, and reduce pollution when replaced with other fuels. Solar collectors can be used to dry plants and heat homes, barns, and greenhouses. These include solar thermal and electrical devices such as photovoltaics, solar water pumps, solar dryers, solar greenhouse heating, livestock ventilation, and solar aeration pumps, which can be powered by photovoltaics (solar panels). This article describes different types of applications used for agricultural purposes.
Combined Neural Network and Fuzzy Control for Maximum Power Point Tracking In Solar PV System
Authors: Keshaw Ram , B. Chiranjeev Rao , Raina Jain
Published: March 2023

The most effective renewable energy in the future among energy. Using photovoltaic (PV) panels is the most effective approach to utilize solar energy for electrical power. The photovoltaic panel that uses solar energy has non-linear voltage-current and voltage-control properties. The control yield from the solar-powered PV board is highest at a certain voltage point. The maximum power point voltage is the voltage at which the PV board produces the most power. The construction of the solar-powered PV board and a description of its features have been presented. In order to acquire the highest control point voltage, the difference between the real Maximum Power Point Tracking (MPPT) voltage and the MPPT voltage deduced from the Artificial Neural Network (ANN) arrangement is displayed, and it is successfully accepted. The result appears to be an exact match for the accuracy of ANN. The PV board's highest control point can be successfully and accurately tracked using the ANN display that was obtained. From the various results obtained, it becomes obvious that the suggested computation proves to be considerably simpler in following the PV board's most extreme control point. The reaction time is drastically reduced when the proposed control approach is used since the PV voltage closely tracks the highest control point voltage. Additionally, the proposed strategy's precision is incredibly logical. In every irradiance and temperature scenario, the control framework performs well.
Assessing measurement invariance with dichotomous items: The case of early grade mathematic assessment from the zambian sample
Authors: Brian Mumba , Devrim Alici , N. Bilge Uzun
Published: March 2023

Assessment of measurement invariance is an essential component of construct validity in psychological measurement. However, the procedure for assessing measurement invariance with dichotomous items partially differs from that of invariance testing with continuous items. However, many studies have focused on invariance testing with continuous items or ordered polytomous items. Hence, this study assessed the measurement invariance with dichotomous items using Confirmatory Factor Analysis. The study was conducted with data from primary school students who participated in the Early Grade Mathematics Assessment Survey (EGMA) from different provinces of Zambia in 2018. The study determined measurement invariance for three subtests of EGMA according to gender. The total sample consisted of 4698 individuals (49% male, n = 2305 and 51% female, n = 2393). The method used was a Confirmatory Factor Analysis with three highly correlated factors, number identification, number discrimination, and recognition of number patterns. The findings revealed measurement invariance of the EGMA model as defined by three subtests (number identification, number discrimination, and recognition of number patterns) across gender subgroups. However, individual analysis of each subtest revealed that the test scores have the same unit of measurement for both male and female on two factors, excluding those of number identification that lack measurement invariance. Finally, these results contribute to evidence of validity for EGMA scores in terms of their internal structure from the perspective of equality of measurement.
Usage of whatsapp in education by pre-service teachers: A logical study
Authors: D. R. Robert Joan
Published: March 2023

WhatsApp is a social network used by most individuals in the world. Very few are not interested or not using Whatsapp. It has a vital place in the society to transmit information from any place-to-place. The information may be a text, a picture, a video, or a voice. Therefore, WhatsApp can be used for multi-message transfers. This study examines the use of WhatsApp in education by pre-service teachers. The researcher selects a sample of 60 pre-service teachers from a College of Education in Kanyakumari District. The investigators have used the "WhatsApp Education Inventory" to collect the data. From this study, the investigator concluded that the pre-service teachers utilize WhatsApp for their education according to their own interests. Moreover, no background variables are affected by the use of WhatsApp in their education. Most pre-service teachers are using WhatsApp for their education and progress. In this study, there exist no difference between the groups of type of families and religion, similarly among the groups of occupation of the father, occupation of the mother and income of the parents. Finally, it suggests that the pre-service teachers use WhatsApp in a creative and positive way to equip themselves and the future generation. Spending a lot of time on WhatsApp leads to addiction. Therefore, unnecessary usage of WhatsApp should be avoided to the future students to use their gadgets for a good purpose in a moral way.
ICT integration approach: a comparative study of physical education and sports teachers and language, science and humanities teachers
Authors: Yakup Koç , Ahmet Mutlu
Published: March 2023

In this study, it was aimed to determine the information and communication technologies integration approaches of physical education and sports teachers and language, science and humanities teachers. A survey model was used in the research. The research group consisted of teachers working in public high schools affiliated with the Ministry of National Education in Istanbul for 2020–2021 academic year and who were selected by a simple random sampling method. In this context, the research was conducted with 619 teachers. "Personal Information Form" and "Information and Communication Technologies Integration Approaches Scale" were used as data collection tools. In the analysis of the obtained data, descriptive statistics, a t-test, a one-way ANOVA, and the Pearson product-moment correlation coefficient were used. As a result, it was understood that information and communication technologies integration levels of physical education and sports teachers were significantly lower than language, science and humanities teachers. It was determined that the information and communication technology integration levels of the physical education and sports teachers differed significantly according to their in-service training status. In addition, the information and communication technology integration levels of language, science, and humanities teachers differed significantly according to in-service training, finding their income levels sufficient, choosing the profession willingly, and marital status.
Impact of place based education as teaching pedagogies for active engagement of sixth grade students in learning science
Authors: Jurmi Thinley , Purna Bahadur Chhetri
Published: March 2023

To enable learning to the fullest for whole development of children, theories stated that the children should be actively engaged during the learning process. However, Bhutanese classrooms predominately use traditional methods of teaching within the four walls. Like any other country, Bhutan's educational system gears up to use different teaching strategies to maximize students' engagement for a better academic score. The purpose of this study was to improve the learners' engagement in learning by using place-based education approaches as teaching methods. The study further delved into which of the engagement types are well catered by PBE approaches for better learning of science. This study was carried out with 27 class IV students from Bjimthangkha Primary School, Wangdue District, Western Bhutan. The data for both the baseline and post-intervention periods were gathered using closed format survey questionnaires and observations. The application of intervention strategies lasted for three consecutive weeks. Descriptive statistics were used to analyze the data. The findings indicated that students' engagement in learning science has improved after employing place-based education as a teaching approach. Subsequently, the academic learning score in science has improved.
Correlation between swayam learning and its achievement among prospective teachers - a study in kanniyakumari district
Authors: D. R. Robert Joan , Sheeja Y.
Published: March 2023

In the current scenario, Swayam learning is becoming a part of the curriculum of higher education. At this point, the prospective teachers are not staying away from the word "swayam." In the curriculum of the College of Education, there is a compulsory certificate course from Swayam Learning App. All the candidates who are getting a degree in education must complete any one of the online courses from Swayam. Therefore, the prospective teachers are very excited for the completion of the online Swayam course. After the results were revealed, certificates were given to the candidates who had completed the course. The ultimate aim of the investigator is to find the correlation between Swayam learning and its achievement among prospective teachers. For that, the investigators designed a tool called "Checklist for Swayam Learning" and administered it in the College of Education in Kanniyakumari District. The investigator used the survey method for the present investigation. The population of the present study was the Prospective Teachers who are studying in College of Education at Kanniyakumari District. In the present investigation, there is no significant difference between the residential locality and branch of the subjects, there is a significant difference between the results of the Swayam examination and finally, there is no significant difference between the father's and mother's occupations. The prospective teachers are requested to study the concepts clearly and watch the video classes frequently with concentration. The use of the online platform Swayam is not only for getting certificates but also to collect information about their learning.
A survey report of different technique or component for dimensionality reduction in data science
Authors: Sangeeta Devi , Munish Saran , Rajan Kumar , Upendra Nath Tripathi
Published: March 2023

To train a machine learning model using a data record which has multiple properties, is typically a difficult task. The development of over fitting of the susceptible model and the growth of model characteristics are always inversely correlated. Since not all of the traits are always significant, this observation was made, and for instance, several attributes might merely make the data noisier. Techniques for dimensionality reduction are employed to address this issue. In this paper we have also discussed the different approaches and techniques of dimensionality reduction techniques.
Blockchain Technology: Opportunities and Challenges in Various Domains
Authors: Aman Kumar Dhiman , Ajay Kumar
Published: March 2023

Blockchain has been used in non-financial applications since it was first introduced with Bitcoin. Bitcoin uses peer-topeer technology to operate without a central authority or banks; the management of transactions and the issuance of bitcoins is carried out collectively by the network. Bitcoin is open source; its design is public, no one owns or controls bitcoin, and anyone can participate. In blockchain technology, no intermediaries are used to establish a decentralized system. Based on literature reviews, this paper discusses blockchain technology concepts, mechanisms, applications, opportunities, and other relevant solutions for real-world problems. Blockchain concepts are discussed in this paper using healthcare, education, and logistics examples. Finally, it will discuss the various blockchains, their permissions, architectures, and emerging features.
Analysis of high-rise building by using fluid viscous dampers
Authors: Khadiranaikar R. B. , Farhanaz Kerur
Published: March 2023

Fluid viscous dampers are dynamic actuators that when stroke, it absorb the energy that by tectonic disturbances, wind absorption, or heat on a structure. Every multi-story building structure that is subjected to ground motion in daily life needs to be studied to determine how it responds because this is a common issue for construction. The structure's foundation is vibrating due to the earthquake. Buildings oscillate as a result of these vibrations, which could seriously harm the structure and observe the earthquake behaviour of structures with and without Fluid Viscous Dampers (FVD) and conventional Reinforce Concrete (RC) moment-resistant frames. The analysis takes place on displacement changes that caused by the addition of FVD in the structure and reduction in base shear in reinforced concrete structures after installing FVD and by using response spectrum and time history analysis. It compares the findings of storey displacement, storey stiffness, base shear, and storey drift assessments. This research provides information on several studies done on multi-story buildings while taking into account the various factors. The examination on vibration characteristics of a G+20 structure with and without a viscous damper is presented in the proposed work. Practically all multi-storeyed buildings must be analysed as three-dimensional systems, according to the current edition of the IS: 1893–2016. The building floor plans may be seen as asymmetrical and the hill slope topography of India is typically geologically stable.
Review on usage of steel slag for roads
Authors: Suman D. M.
Published: March 2023

India is the 3rd largest producer of steel with a capacity of 101 Metric Ton (MT), and this capacity is expected to grow up to 125-150 MT by 2025. The iron and steel industries generate millions of tons of various types of slag. These slags are generated during iron making and steel making processes, and are residue from these processes made of minerals like silica, alumina, and titanium from iron sand, as well as combinations of calcium and magnesium oxides. 2-4 tons of waste are generated for each ton of steel produced in different forms such as solids, liquids, and gas. The disposal of such slags is a major challenge for the steelmaking industry. With a growing availability of huge quantities of such slag materials, there is currently great focus on research to develop slag processing technologies that enable re-use of such slags in various infrastructure construction projects. The properties of the slags are very similar to the properties of natural aggregates in terms of both physical and chemical composition, and they have immense potential for extensive use in road construction and infrastructure projects as an alternative to natural aggregates. Rapid infrastructure development has led to a scarcity of natural aggregates as the demand is too high for them. These slags from the iron and steel industry are processed to make them suitable for use as natural aggregates replacements, contributing to sustainability in the construction industry. These slags can be used as an alternative to natural aggregates in sub-base, base and asphalt layers, and in concrete aggregates instead of being dumped as industrial waste near the plants. Standards, codal requirements, and suitable specifications need to be established for the large-scale use of slag continuously in construction, as well as for the implementation of large-scale recycling and re-use of slag from these industries, which can solve environmental issues in handling such industrial wastes.
Analysis of the Effect of Shenghua Zhuyu Herbal Acupoint Plaster in the Treatment of Postpartum Malodor
Authors: Zheng Xia , Shao Juan , Zhi Liqin
Published: March 2023

Objective: To assess the clinical effect of Shenghua Zhuyu ointment, which was applied onto the Zhongji, Qihai, and Guanyuan acupoints, on postpartum lochia. Methods: We randomly divided 166 patients who were admitted in 2018–2021 into an observation group and a control group. The control group was treated with conventional clinical methods, whereas the observation group was treated by applying Shenghua Zhuyu ointment on the Zhongji, Qihai, and Guanyuan acupoints. The amount and duration of lochia, abdominal pain, hospitalization time were observed; B-scan ultrasonography was performed to check whether the placenta was discharged. Results: The treatment received by the observation group of patients was shown to be more effective than that of the control group. Besides, the experimental group had less lochia than that of the control group. The observation group also had shorter duration of lochia and hospital stay than those of the control group (P < 0.05). The placenta excretion was better, and the degree of abdominal pain was lower in the observation group than those of the control group (P < 0.05). Conclusion: The acupoint application of Shenghua Zhuyu herbal acupoint plaster has a significant impact on retained placenta, in which it can aid the discharge of residual placenta and improve the patients’ physical functions and symptoms.
Application Effect of Medium-Length Peripheral Catheter in Critically Ill Patients Undergoing Hepatobiliary Surgery
Authors: Song Xiaoxue , Liu Xiaoyan , Liu Xiaomei , Chen Xi
Published: March 2023

Objective: To investigate the effect of using peripheral medium-length catheters in critically ill patients undergoing hepatobiliary surgery. Methods: A retrospective analysis of the nursing experience and effect of using medium-length catheters for infusion in 102 critically ill patients undergoing hepatobiliary surgery from March 2021 to April 2022 was conducted. Results: All 102 patients had successful catheter placement with no catheter-associated infections, blockage, decannulation, or breakage. However, four cases had blood oozing from the puncture site, but it resolved after changing the dressing. Conclusion: Medium-length catheters are superior to traditional infusion tools in terms of benefit; thus, they deserve to be widely promoted in clinical practice.
Value of N-Terminal Pro B-Type Natriuretic Peptide, High-Sensitivity C-Reactive Protein, and Homocysteine Levels in Predicting Cardiovascular Events in Chronic Heart Failure Patients After Discharge
Authors: Yu Qian , Zhao Linya , Chen Yinyin , Zhao Qing
Published: March 2023

Objective: To investigate the value of N-terminal pro B-type natriuretic peptide (NT-proBNP), high-sensitivity C-reactive protein (hs-CRP), and homocysteine (Hcy) levels in predicting cardiovascular events (CV) in patients with chronic heart failure (CHF). Methods: A total of 63 patients with CHF admitted to our hospital between June 2019 and July 2021 were selected. Their NT-proBNP, hs-CRP, and Hcy levels were detected at discharge, and a 12-month follow-up was done after their discharge to collect clinical data. The collected data were inclusive of data from 21 CHF patients with cardiovascular disease and 42 CHF patients without cardiovascular disease. The effect of NT-proBNP, hs-CRP, and Hcy levels on the occurrence of CV was analyzed. Results: The levels of NT-proBNP, hs-CRP, and Hcy in the group with cardiovascular disease were significantly higher than those in the group without cardiovascular disease (P < 0.05); the levels of serum NT-proBNP, hs-CRP, and Hcy at discharge had certain value in predicting short-term CV in CHF patients (P < 0.05). Conclusion: NT-proBNP, hs-CRP, and Hcy levels can be used to predict CV in CHF patients, thus having clinical application value.
Relationship Between Postprandial Blood Glucose, Fasting Insulin, and Glycated Hemoglobin Levels and Early Diabetic Nephropathy in Patients with Type 2 Diabetes Mellitus
Authors: Fan Xing , Li Zhe
Published: March 2023

Objective: To investigate the relationship between postprandial blood glucose (PBG), fasting insulin (FINS), and glycated hemoglobin (HbA1c) levels and early diabetic nephropathy in patients with type 2 diabetes. Methods: 96 cases of type 2 diabetes mellitus treated in our hospital from May 2021 to May 2022 were selected as the research subjects. The patients were divided into two groups according to the urinary albumin excretion rate (UAER), with 53 cases in the type 2 diabetes group (UAER < 30 ?g/min) and 43 cases in the early diabetic nephropathy group (30 ?g/min ? UAER < 300 ?g/min). PBG, FINS, and HbA1c levels were detected in 87 healthy patients. Results: The levels of PBG, FINS, and HbA1c in the early diabetic nephropathy group were higher than those in the control group (P < 0.01) and the type 2 diabetes group (P < 0.01). Conclusion: PBG, FINS, and HbA1c are factors affecting the occurrence of diabetic nephropathy in patients with type 2 diabetes; thus, controlling the levels of PBG, FINS, and HbA1c can effectively prevent the occurrence of diabetic nephropathy in type 2 diabetes mellitus.
Penerapan Problem Based Learning Berbantuan E-Book Berbasis Komik untuk Meningkatkan Aktivitas dan Hasil Belajar IPA
Authors: Puteri Krisdiana Enrika
Published: March 2023

Berdasarkan hasil observasi pembelajaran yang dilakukan di Sekolah Dasar Negeri Bareng 05 Kota Malang diperoleh fakta bahwa hasil belajar dan keaktifan siswa selama pembelajaran muatan IPA masih belum maksimal. Alternatif pemecahan masalah tersebut ialah dengan penerapan model Problem Based Learning (PBL) dengan menggunakan komik berbentuk e-book. Penelitian ini menggunakan model penelitian tindakan kelas dari Kemmis & Mc Taggart. Setiap siklus penelitian terdiri dari tahap planning, acting & observing, reflecting, dan revisi plan. Setiap siklus dilaksanakan dua kali kegiatan pembelajaran. Hasil penelitian menunjukkan bahwa penerapan model Problem Based Learning berbantuan e-book berbasis komik dapat meningkatkan aktivitas dan hasil belajar muatan IPA siswa kelas IV Sekolah Dasar Negeri Bareng 05. Berdasarkan hasil penelitian ini, dirasakan pada peneliti selanjutnya untuk mengembangkan dan meneliti e-book sebagai media pembelajaran yang dibuat sesuai dengan materi yang akan diajarkan.
Optimalisasi Strategi Pembelajaran Bahasa Inggris Melalui Penguatan Karakter Mulia
Authors: Rozelyna Yusaeny
Published: March 2023

Pembelajaran Bahasa Inggris abad ke 21 merujuk pada kompetensi komunikatif, interkultural, sikap berupa kepercayaan diri untuk mandiri dan bertanggung jawab, serta keterampilan bernalar kritis dan kreatif. Penelitian ini bertujuan untuk mendeskripsikan efektivitas penguatan karakter mulia terhadap optimalisasi pembelajaran Bahasa Inggris. Penelitian Tindakan Kelas (PTK) dengan menggunakan metode kualitatif dan kuantitatif sederhana digunakan untuk menjawab rumusan masalah penelitian ini. Observasi peserta didik dan guru dalam proses pembelajaran, angket, wawancara dan dokumentasi nilai digunakan untuk mengumpulkan data penelitian. Peneliti menggunakan assessment diagnostic kognitif sebagai studi pendahuluan penelitian. Data observasi peserta didik dan guru digunakan untuk menjawab optimalisasi proses pembelajaran Bahasa Inggris. Untuk menjawab penguatan pendidikan karakter dalam proses pembelajaran, peneliti menggunakan data angket. Data wawancara setelah proses pembelajaran, dokumentasi nilai proses dan hasil digunakan sebagai triangulasi data untuk mencapai validitas penelitian. Peningkatan nilai proses pembelajaran merupakan implikasi dari perubahan perilaku positif peserta didik. Peneliti merekomendasikan penelitian di masa datang untuk meneliti efektivitas pendekatan berbasis teks pada mata pelajaran serumpun.