Structured Knowledge Research Articles

MSKD: Structured knowledge distillation for efficient medical image segmentation

In recent years, deep learning has revolutionized the field of medical image segmentation by enabling the development of powerful deep neural networks. However, these models tend to be complex and computationally demanding, posing challenges for practical implementation in clinical settings. To address this issue, we propose an efficient structured knowledge distillation framework that leverages a powerful teacher network to assist in training a lightweight student network. Specifically, we propose the Feature Filtering Distillation method, which focuses on transferring region-level semantic information while minimizing redundant information transmission from the teacher to the student network. This approach effectively mitigates the problem of inaccurate segmentation caused by similar internal organ characteristics. Additionally, we propose the Region Graph Distillation method, which exploits the higher-order representational capabilities of graphs to enable the student network to better imitate structured semantic information from the teacher. To validate the effectiveness of our proposed methods, we conducted experiments on the Synapse multi-organ segmentation and KiTS kidney tumor segmentation datasets using various network models. The results demonstrate that our method significantly improves the segmentation performance of lightweight neural networks, with improvements of up to 18.56% in Dice coefficient. Importantly, our approach achieves these improvements without introducing additional model parameters. Overall, our proposed knowledge distillation methods offer a promising solution for efficient medical image segmentation, empowering medical experts to make more accurate diagnoses and improve patient treatment.

Process Defects Knowledge Modeling in Laser Powder Bed Fusion Additive Manufacturing: An Ontological Framework

Comprehensive knowledge of the laser powder bed fusion (LPBF) process defects, their causal factors, and relationships can enable proactive prevention and/or mitigation of those defects to ensure the production of high-quality products. However, this knowledge is scattered in a plethora of research articles, and there is a need for a formal and structured knowledge base to document the LPBF process defects knowledge and model the complex network of relationships among those defects and their causal factors. In response, this paper proposes an ontological framework to systematically structure and represent the knowledge of LPBF defects in a sustainable, reusable, and extensible way. In doing so, we first conducted a detailed literature review and analysis of current LPBF defect surveys to systematically develop a consistent and comprehensive classification of defects and potential causal factors. Then, to effectively represent the gathered knowledge, the ontological framework was designed to: (1) organize and formalize knowledge on LPBF defects and the causal factors, (2) model the complex network of causal links and cascading effects among the defects and causal factors, (3) enable easy querying of the stored knowledge, and (4) include ontological entities that are suitable for extension and reuse. A prototype LPBF defects ontology was developed in Web Ontology Language (OWL)/Resource Description Framework (RDF) formalism using the Protégé tool to effectively realize those design requirements. The developed ontology covers thirty-one unique defects and knowledge of their causal factors, including defect-to-defect causal relationships and hierarchical categorization under four major categories of high-level defect classes. Similarly, forty-five unique causal factors were categorized under twelve major categories. The proposed ontological framework and knowledge model offer a pathway to (1) provide a comprehensive knowledge base on LPBF defects for in-depth tutoring and training of novice researchers and practitioners; (2) help investigators to identify root causes of detected defects for informed corrective action; (3) guide process planning tasks from a defect control perspective; and (4) support future application and reuse of the knowledge. This study also provides several examples to illustrate the modeling of cascading effects in causal relationships, discovering knowledge using an ontology reasoner, visualizing the complex network of causal links using OntoGraph, and retrieving stored knowledge by answering competency questions using SPARQL queries. In the future, the reasoning capabilities of our proposed ontology can also be leveraged to develop expert systems for optimizing the AM workflow and quantitatively predict and diagnose LPBF defects.© 2023 Society of Manufacturing Engineers (SME). Published by Elsevier Ltd. All rights reserved.This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)Peer-review under responsibility of the Scientific Committee of the NAMRI/SME.

PAPER

Introduction: Natural child birth is the birth without routine medical intervention particularly anesthesia. Natural child birth attempts to minimize the medical intervention particularly use of anesthetic medication and surgeries such as episiotomies, forceps and caesarean section. Benefits of Natural birthing are faster recovery after the birth and less vaginal tearing since the women will push instinctively during the delivery and shorter the pushing time, ability to change the birthing position, decreased risk of needing of risky intervention avoid side effect associated with the epidural and ability to bond and breastfeed the child immediately. Aim of this study: To assess the knowledge of nursing officers before the awareness programme on natural birthing, To assess the effectiveness of awareness programme on knowledge regarding natural birthing among nursing officers and to find out the association between pre-test knowledge with the selected demographic variable. Methodology: A Quantitative research approach was adopted under the study. The study was conducted in selected hospitals of Dehradun. Convenient sampling technique was used to select the sample. The sample compromised of 40 nursing officer. The tools developed and utilized for the study was semi structured knowledge questionnaire regarding natural birthing. It was prepared to determine the knowledge of nursing officers regarding natural birthing in selected hospital of Dehradun. Awareness programme was also prepared to determine its effectiveness. Result: The study revealed that the mean post test-test knowledge score (29) of nursing officers regarding natural birthing were higher than the mean pre-test knowledge (18.02). In pre-test majority of participants 7(17.5%) of nursing officers had below average knowledge, 28(70%) had average knowledge and 5(12.5%) had above average knowledge and in the post-test assessment 4(10%) of nursing officers had average knowledge, 36(90%) had above average level of knowledge regarding natural birthing and no one was in below average of knowledge. Conclusion: The study concludes that the planned nursing intervention is an effective strategy in improving knowledge of nursing officers regarding natural birthing and more educational strategies can be undertaken to enhance the knowledge of nursing officers. The purpose of the present study was to find out the level of knowledge regarding natural birthing in selected hospitals in Dehradun.

Social sustainability for whom? Developing an analytical approach through a tripartite collaboration

PurposeSocial sustainability is a concept frequently referred to in public debates concerning how to construct the governance of future societies. The interpretations of its meaning, however, are ambiguous, and practices often dubious. Confronting top-down technocratic governance structures, this paper aims to argue for for tripartite collaborations between residents, higher education institutions (HEIs) and local government, as an approach toward social sustainability that involves residents’ interests in local governance.Design/methodology/approachThis study argues that a specific time-spatial method of analysis can benefit the co-creation of knowledge as it passes through the spectrum of resident–HEI–local government. It provides a way for resident perceptions to become structured knowledge that originates from the residents, effectively engendering a bottom-up governance structure.FindingsThis study shows how to include residents in policymaking and implementation processes as co-creators of knowledge, and thereby displays the possibility of examining knowledge and competence within municipal projects for social sustainability.Originality/valueThe model developed in this study can be used as a methodological instrument to analyze and expand resident participation in local social sustainability work. It thereby provides a toolbox for inclusive policymaking and strategies.

Effectiveness of Video Assisted Teaching Programme on Knowledge Regarding Parenting Styles and Its Influence on Development of Children among Parents of Preschoolers

Aims & Objectives The goal of the research study is to assess the effectiveness of video-assisted teaching programmes on knowledge regarding parenting styles and their influence on the development of children among parents of preschoolers. Methods Pre-experimental one-group pre-test post-test design was used to assess the effectiveness of a video-assisted teaching programme(VATP) on knowledge regarding parenting styles and their influence on the development of children among parents of preschoolers at selected schools in Mysuru. A structured knowledge questionnaire was prepared and used to assess the effectiveness of the video-assisted teaching programme. The reliability (R=0.95) of the tool was tested and validity was ensured in consultation with guides and experts in the field of statistics, paediatrics and nursing. The study was carried out in Shanthala Vidya Peeta School at Mysuru by Non-probability convenient sampling technique, 60 parents of preschoolers were selected. A structured knowledge questionnaire was administered to collect the needed data. Data were analysed by using descriptive and inferential statistics. Result Concerning the knowledge assessment, the mean pre-test score was 11.5 and the post-test score was 19.2. The mean difference between the pre-test score and the post-test score was 7.7. The computed Paired't' value was 13.8 and it was significant at the 5% level. This showed that VATP on knowledge regarding parenting styles and their influence on the development of children was effective. Therefore the research hypothesis (H1) is accepted, i.e. there is a significant difference between the mean pre-test and mean post-test knowledge score. Interpretation and conclusion This study revealed that the VATP on knowledge regarding parenting styles and its influence on the development of children among parents of preschoolers was effective.

Topological properties and organizing principles of semantic networks

Interpreting natural language is an increasingly important task in computer algorithms due to the growing availability of unstructured textual data. Natural Language Processing (NLP) applications rely on semantic networks for structured knowledge representation. The fundamental properties of semantic networks must be taken into account when designing NLP algorithms, yet they remain to be structurally investigated. We study the properties of semantic networks from ConceptNet, defined by 7 semantic relations from 11 different languages. We find that semantic networks have universal basic properties: they are sparse, highly clustered, and many exhibit power-law degree distributions. Our findings show that the majority of the considered networks are scale-free. Some networks exhibit language-specific properties determined by grammatical rules, for example networks from highly inflected languages, such as e.g. Latin, German, French and Spanish, show peaks in the degree distribution that deviate from a power law. We find that depending on the semantic relation type and the language, the link formation in semantic networks is guided by different principles. In some networks the connections are similarity-based, while in others the connections are more complementarity-based. Finally, we demonstrate how knowledge of similarity and complementarity in semantic networks can improve NLP algorithms in missing link inference.

Using Networked Ontologies to Support the Development of Software Systems with Adaptive User Interface

The new ways of interacting with computers, smartphones, and other devices have brought new challenges, such as the need to ensure that different types of users can easily use the same system. Adaptive User Interface (AUI) systems have been recognized as a solution to this matter. They change the user interface to better meet the needs of different users. However, developing such systems is not trivial. It is necessary to capture the users’ characteristics and preferences and constantly adapt the system accordingly. In this paper, we discuss the use of ontologies to support the development of AUI systems. We argue that by providing structured knowledge about such systems, ontologies help understand how they work and offer a basis to structure them, identify the necessary adaptations and implement mechanisms to make them happen in run-time. We have explored the use of ontologies from an ontology network (i.e., networked ontologies) to develop a social network about academic subjects that automatically adapts its interface according to the low vision and colorblind user’s needs and usage characteristics. This exploratory study showed that using networked ontologies to develop an AUI system is useful and feasible. The ontology was useful at the conceptual level by serving as a basis to define the system’s structural model and at the operational level by providing the semantics used in a reasoning engine to adapt the UI at run-time. The first version of an ontology-based process to guide the development of AUI systems emerged from this experience and it is also presented in this paper.

Content-based and Knowledge-enriched Representations for Classification Across Modalities: A Survey

This survey documents representation approaches for classification across different modalities, from purely content-based methods to techniques utilizing external sources of structured knowledge. We present studies related to three paradigms used for representation, namely (a) low-level template-matching methods, (b) aggregation-based approaches, and (c) deep representation learning systems. We then describe existing resources of structure knowledge and elaborate on the need for enriching representations with such information. Approaches that utilize knowledge resources are presented next, organized with respect to how external information is exploited, i.e., (a) input enrichment and modification, (b) knowledge-based refinement and (c) end-to-end knowledge-aware systems. We subsequently provide a high-level discussion to summarize and compare strengths/weaknesses of the representation/enrichment paradigms proposed, and conclude the survey with an overview of relevant research findings and possible directions for future work.

Assessment of knowledge and attitude towards menstrual cup usage among adolescent girls

A woman is the essence of whole universe. If there would be no women, the human race is surely going to end. Women deserves more care and attention especially during the reproductive phase. Menstruation is a unique phenomenon of females of reproductive age group. Cultural, religious and traditional beliefs can lead to different restrictions that women face during their menstrual period. Menstrual cup is a device for menstrual flow management and is claimed to be a healthy and environmentally friendly alternative to the conventional menstrual sanitary protections.Even though menstrual cup is highly efficient it requires fair amount of self-confidence and assurance to insert into one’s own body. And the prevailing myths on breakage of hymen make the confusion of adolescents even worse. This study was aimed at assessing knowledge and attitude towards menstrual cup usage among adolescent girls. Descriptive survey design was used. A total of 100 adolescent girls were selected using convenient quota sampling methods. Data was collected using structured knowledge questionnaire to assess knowledge and an attitude rating scale to assess attitude towards menstrual cup usage. The study results revealed that 50 % students had good knowledge, 35 % students had satisfactory knowledge, 8 % students had excellent knowledge, 6 % students had poor knowledge and one percent students had very poor knowledge about menstrual cup usage. Majority (81%) had a positive attitude towards menstrual cup usage, 19% had neutral attitude and none had negative attitude. Hence majority of the subjects had a good attitude towards menstrual cup usage. There was no relation between knowledge and attitude of adolescent girls towards menstrual cup usage. Women have lots of concerns about managing menstrual flow. Fear of spotting, stains, squishy, messy, smelling and annoying nature of sanitary pads is still a major dilemma. Other alternative measure to sanitary napkins is menstrual cup. Adolescent girls achieve their knowledge on menstrual cup through the social media.In a developing world, menstrual management is not only difficult but also may have serious adverse impact on the lives of women. Even when taboos are not a major problem, convenient or inexpensive menstrual collection materials are not available. Efforts to produce inexpensive materials are solely lacking. Women use clothes, absorbent pads or tampons to manage menstrual flow. Washing the clothes or disposing the pads hygienically is a challenge for most of the females. By interacting with other teens, investigators understood that women have lots of concerns about using sanitary pads. Other alternative measure to sanitary napkins is menstrual cup but females require self-confidence and assurance to insert it to one’s own body.

Effect of Artificial Intelligence-based Health Education Accurately Linking System (AI-HEALS) for Type 2 diabetes self-management: protocol for a mixed-methods study

BackgroundPatients with type 2 diabetes (T2DM) have an increasing need for personalized and Precise management as medical technology advances. Artificial intelligence (AI) technologies on mobile devices are being developed gradually in a variety of healthcare fields. As an AI field, knowledge graph (KG) is being developed to extract and store structured knowledge from massive data sets. It has great prospects for T2DM medical information retrieval, clinical decision-making, and individual intelligent question and answering (QA), but has yet to be thoroughly researched in T2DM intervention. Therefore, we designed an artificial intelligence-based health education accurately linking system (AI-HEALS) to evaluate if the AI-HEALS-based intervention could help patients with T2DM improve their self-management abilities and blood glucose control in primary healthcare.MethodsThis is a nested mixed-method study that includes a community-based cluster-randomized control trial and personal in-depth interviews. Individuals with T2DM between the ages of 18 and 75 will be recruited from 40-45 community health centers in Beijing, China. Participants will either receive standard diabetes primary care (SDPC) (control, 3 months) or SDPC plus AI-HEALS online health education program (intervention, 3 months). The AI-HEALS runs in the WeChat service platform, which includes a KBQA, a system of physiological indicators and lifestyle recording and monitoring, medication and blood glucose monitoring reminders, and automated, personalized message sending. Data on sociodemography, medical examination, blood glucose, and self-management behavior will be collected at baseline, as well as 1,3,6,12, and 18 months later. The primary outcome is to reduce HbA1c levels. Secondary outcomes include changes in self-management behavior, social cognition, psychology, T2DM skills, and health literacy. Furthermore, the cost-effectiveness of the AI-HEALS-based intervention will be evaluated.DiscussionKBQA system is an innovative and cost-effective technology for health education and promotion for T2DM patients, but it is not yet widely used in the T2DM interventions. This trial will provide evidence on the efficacy of AI and mHealth-based personalized interventions in primary care for improving T2DM outcomes and self-management behaviors.Trial registrationBiomedical Ethics Committee of Peking University: IRB00001052-22,058, 2022/06/06; Clinical Trials: ChiCTR2300068952, 02/03/2023.

A Study to Evaluate the Effectiveness of Structured Teaching Programme on Knowledge Regarding Evidence based Nursing Practice among Staff Nurses in Selected Hospitals, Guwahati

This study aims to examine the level of knowledge of staff nurses about evidenced based nursing practice before and after the structured teaching programme and its effectiveness. Evaluative approach with one group pre test post test design was used to assess the knowledge of 50 samples in selected hospitals of Guwahati. Structured knowledge questionnaire was used which included 40 MCQs and STP of 45 minute was given before and after the intervention. It was found that in pre-test the mean score of the samples were 10.4 with a standard deviation of 2.43 at a SEM of 0.347. The score ranges from 7-15 in pre-test. In post- test mean score percentage was 72.65% with a mean score of 29.06. The standard deviation was 2.90 with SEM of 0.414 and range from 20-36 after It was found that the STP is effective in changing the level of knowledge at 0.01 level of significance. There was significant association between pre-test level of knowledge and selected socio demographic variables- Professional Qualification, Experience and In-Service education

Effect of Video-assisted Teaching on Knowledge and Practice of Preterm Care Bundle amongst Mothers of Preterm Babies

Abstract Background: Preterm is defined as all births before the completion of 37 weeks of gestation. The complications of preterm birth are the largest direct cause of neonatal deaths, responsible for 35% of the world’s 3.1 million deaths per year. Aims: The aims of the study were to assess the effect of video-assisted teaching on knowledge and practice of preterm care bundle amongst mothers of preterm babies. Methods: Pre-experimental one-group pre-test–post-test design with purposive sampling was used to collect data from 30 samples admitted in level I neonatal intensive care unit of a tertiary care hospital in Kerala. The pre-test was done using a structured knowledge questionnaire and observational practice checklist, followed by video-assisted teaching on the preterm care bundle and reinforced with a demonstration of skills. Post-test was done on the 5th day. Results: In the pre-test, 21 (70%) of the samples had inadequate knowledge and 17 (56.67%) had inadequate practice, while in post-test, 29 (96.67%) had adequate knowledge and 30 (100%) had adequate practice on preterm care bundle. The calculated paired t-test value on pre- and post-test knowledge score was 29.24 and calculated paired t-test value on pre- and post-test practice score was 56.63, which was higher than the table value (t29 = 2.04, P < 0.05). There was a significant positive correlation (r = 0.771, P < 0.001) between knowledge and practice of preterm care bundle. There was a significant association (P < 0.05) between pre-test level of knowledge on preterm care bundle with selected socio-demographic and clinical data variables such as area of residence and a highly significant association (P < 0.001) between pre-test level of knowledge on preterm care bundle with parity. There was a significant association (P < 0.05) between pre-test level of practice on preterm care bundle with selected socio-demographic and clinical data variables such as education, area of residence and a highly significant association (P < 0.001) between pre-test level of practice on preterm care bundle with parity. During the study, an investigator found that video-assisted teaching was effective in improving knowledge and practice of preterm care bundle amongst mothers of preterm babies. Conclusion: Therefore, video-assisted teaching is an effective method for improving the knowledge and practice amongst mothers of preterm babies as a supportive measure in the NICUs.

Effectiveness of an Instructional Module on Knowledge and Anxiety of Caregivers of Children Undergoing Cardiac Catheterization – An Experimental Study

Background: Diagnosis of cardiovascular disorders in children is a very stressful time for the entire family. During this period family caregivers are anxious about their child’s condition. At this time, nurses play an important role to educate the parents or caregivers about the child’s health, procedure that has to be performed, and pre- and post-operative care after procedure. This study was conducted to assess the effectiveness of an “instructional module” on knowledge and anxiety of caregivers of children undergoing cardiac catheterization. Materials and Methods: Caregivers of children with congenital heart disease were randomly enrolled in two groups with 30 caregivers in each control and experimental group. Preoperative knowledge and anxiety in both the groups were assessed by a self-structured questionnaire and the State-Trait Anxiety Inventory. An instructional module in the form of a booklet regarding cardiac catheterization was developed and administered to the experimental group while the control group received routine care instuctions. Caregivers’ postintervention knowledge was assessed by a structured knowledge questionnaire. Results: Median knowledge score was 2 (2–2) in the control group and 2 (1–2) in the experimental group among caregivers of the children during preintervention phase. The median anxiety score of the caregivers of children underwent cardiac catheterization during preintervention phase was 57.50 (47–61) in the control group and 53 (47.75–56) in the experimental group. The results revealed that there was a significant improvement in knowledge score regarding cardiac catheterization procedure and also there was reduction in the level of anxiety among caregivers in the postintervention experimental group (P < 0.001). Conclusion: The study suggests that the “instructional module” is effective in reducing the anxiety and improving the knowledge levels of caregivers regarding the preoperative and postoperative care of children who underwent cardiac catheterization.

EFFECTIVENESS OF STRUCTURED TEACHING PROGRAMME ON KNOWLEDGE REGARDING CERVICAL CANCER AMONG REPRODUCTIVE AGE GIRLS IN SELECTED NURSING COLLEGE, LUCKNOW

Background: Cervical cancer is the most common malignancy and health problem in women of all sections of society. Cancer is a group of diseases characterized by the uncontrolled growth and spread of abnormal cells. Cervical cancer is the most common cause of death among women worldwide, with about 570, 000 cases and 311,000 deaths, despite the fact that cervical cancer is preventable. It ranks as the first most frequent cancer among women between 21 – 44 yr of age. Methods: A quantitative study was carried out in 35 adolescent girls and the non-probability purposive sampling technique was used for the selection of the subjects and the college. The data was collected through of using a structured knowledge questionnaire. A structured teaching program was developed and administered to the reproductive age girls (17-35 years). Results: The data were analyzed by using descriptive and inferential statistics. The result revealed that after the intervention the mean and standard deviation of the post-test knowledge was 17.65±2.11 being compared to mean and standard deviation of pre-test knowledge 7.2±2.35. The enhancement of knowledge score is the mean difference 10.54. It indicates that there was a significant improvement in the level of knowledge of participants. The calculated t- value (6.57) on analysis of the data was found to be significant at p value 0.05. Conclusions: The study concluded that a structured teaching programme was significant effective to improving the level of knowledge of cervical cancer.

The problem of individualization of learning in the context of change of paradigm bases

Introduction. The problem of individualization of education is one of the leading problems of modern pedagogy and psychology. The article proposes a new perspective of its comprehension: in the subjective projection and in the context of changing the paradigm bases.Materials and Methods. In the process of scientific research, theoretical research methods were used: logical-subject and comparative analysis, interpretation, generalization, scientific theorization.Results. In the subjective projection, the individualization of learning manifests itself as an opportunity, assimilating the content being studied, to understand its connection with one's own «I», to know oneself, i.e. subjectivization of the content and procedural aspects of learning. The difference between subjectivization and the subjectivized form of the studied content is shown. The measure of individualization of training is defined: 1) a narrow horizon of subjectivation: subjective reality is represented in a non-subjective way as a rationally autonomous subjectivity; 2) the limiting horizon of subjectification: subjective reality is presented in a subjective way; 3) autonomous subjectification or zero horizon of subjectification: subjective phenomena exist autonomously, without expressing the meaning of the content being studied. It is shown that the measure of individualization as a systemic property is determined by the accepted method of structured knowledge, included the content of education (classical, post-non-classical structuring of knowledge). This method is predetermined by the paradigm foundations of the learning system. The measure of individualization of learning in the article is considered in the context of the classical, non-classical, post-non-classical paradigm.Discussion and Conclusions. The conclusions proposed in the article are aimed at solving practical issues related to the design of psychological and pedagogical tools for individualizing learning and evaluating their educational effectiveness.

Effectiveness of Self-Instructional module on knowledge regarding Latchkey children among working mother's

3. To find an association between the pre-test knowledge scores and selected demographic variables. Methodology: Research design: -Pre-experimental study. In which one group pretest and post test method is planned for research study. Groups Pre test Intervention Post test,60 working mothers in colleges, Bangalore. Structured knowledge questionnaire consist of 30 Structured knowledge questionnaire on the basis of multiple choice questions on knowledge of latchkey children are utilized as a tool to collect the data from working mother's at B.E.S Degree College and B.E.S. Pre-University College, Jayanagar, Bangalore. Results: Regarding effectiveness of SIM, the overall mean knowledge score in the pre-test was 45.66 % and 80.93 % in the post test with enhancement of 35 % and it was significant at 5% level. Analysis of socio-demographic variables showed that none of demographic variable are significant associated with knowledge score at 5% level (P>0.05). Conclusion: The findings of this study support the need for nurses to conduct the health education to increase the knowledge of working mothers in B.E.S Degree College and B.E.S. Pre- University College, Jayanagar, Bangalore. And had a remarkable increase in the knowledge regarding latchkey children when compared to their previous knowledge, prior to the implementation of the Self-instructional module. Thus the student researcher recommends further studies in these areas to improve knowledge regarding latchkey children.

Descriptive Study to Assess the Knowledge about Benefits of Kangaroo Mother Care among Mothers of Newborn in Banasankari Referral Hospital, Bangalore

Kangaroo mother care is a special way of caring newborns by skin to skin contact. It promotes their bodily condition and glowing being by efficient thermal control, breast feeding and bonding among mother and child. Objectives: The main aim of the study is to assess the knowledge of mothers of newborn regarding kangaroo mother care. Methods: The study was conducted by using descriptive research design. 30 subjects were selected by using convenient sampling technique. The structured knowledge questionnaire was administered and data were collected. Data analysis descriptive and inferential statistical technique was used. Results: The overall knowledge level were majority 27(90%) have inadequate knowledge and 3(10%) have moderate knowledge and none of them had adequate knowledge on benefits of kangaroo mother care. The findings reveal that mean knowledge of sample were found to be 34.1% only and standard deviation value was 4.81. Conclusion: The study which is helpful in an increasing the knowledge level of the mother of infant regarding kangaroo mother care.

Critical Literacy In An EFL Learning Virtual Course

The objective of the present investigation is related to describing how a group of intermediate-level students responds to a pedagogical implementation of critical literacy in an online EFL course at a language institute. The study has a qualitative approach and descriptive level. The sample consisted of six female students, all of them 15 and 16-year-old high school students; with a command of the English language at an intermediate level B1. This study considers four data collection instruments: classroom observations - video recordings and teachers' diaries, semi-structured open interviews with the aim of capturing the representations, thoughts, and conceptions that students have built on social problems through the approach of critical literacy implemented to teach English in a virtual learning environment. Among the main findings is that from the development of multimodal literacy, students achieved more structured knowledge in arguments; also more autonomous learning as well as a clear increase in interaction and consensus among students; finally, the mastery of the sources and the collection of information for learning increased. Overall, participants responded effectively to the development of critical literacy skills, through a gradual and satisfactory learning process.

Rich Event Modeling for Script Event Prediction

Script is a kind of structured knowledge extracted from texts, which contains a sequence of events. Based on such knowledge, script event prediction aims to predict the subsequent event. To do so, two aspects should be considered for events, namely, event description (i.e., what the events should contain) and event encoding (i.e., how they should be encoded). Most existing methods describe an event by a verb together with a few core arguments (i.e., subject, object, and indirect object), which are not precise enough. In addition, existing event encoders are limited to a fixed number of arguments, which are not flexible enough to deal with extra information. Thus, in this paper, we propose the Rich Event Prediction (REP) framework for script event prediction. Fundamentally, it is based on the proposed rich event description, which enriches the existing ones with three kinds of important information, namely, the senses of verbs, extra semantic roles, and types of participants. REP contains an event extractor to extract such information from texts. Based on the extracted rich information, a predictor then selects the most probable subsequent event. The core component of the predictor is a transformer-based event encoder that integrates the above information flexibly. Experimental results on the widely used Gigaword Corpus show the effectiveness of the proposed framework.

A KNOWLEDGE-BASED IDEATION APPROACH FOR BIO-INSPIRED DESIGN

AbstractBio-inspired design (BID) involves generating innovative ideas for engineering design by drawing inspiration from natural biological phenomena and systems, using a form of design-by-analogy. Despite its many successes, BID approaches encounter research challenges including unstructured data and existing models that hinder comprehension and processing, limited focus on finding biological knowledge compared to defined problems, and insufficient guidance of the ideation process with algorithms. This paper proposes a knowledge-based approach to address the challenges. The approach involves transforming unstructured data into structured knowledge, including information about natural sources, their benefits, and applications. The structured knowledge is then used to construct a semantic network, enabling designers to retrieve information for BID in two ways. Furthermore, a three-step ideation method is developed to encourage divergent thinking and explore additional potential solutions by drawing inspiration and utilizing knowledge. The knowledge-based BID approach is implemented as a tool and design cases are conducted to illustrate the process of applying this tool for BID.