Awareness Of Content Research Articles

Making exploratory search engines using qualitative case studies: a mixed method implementation using interviews with Detroit Artisans

Abstract Search engine algorithms are increasingly subjects of critique, with evidence indicating their role in driving polarization, exclusion, and algorithmic social harms. Many proposed solutions take a top-down approach, with experts proposing bias-corrections. A more participatory approach may be possible, with those made vulnerable by algorithmic unfairness having a voice in how they want to be “found.” By using a mixed methods approach, we sought to develop search engine criteria from the bottom-up. In this project we worked with a group of 16 African American artisanal entrepreneurs in Detroit Michigan, with a majority female and all from low-income communities. Through regular in-depth interviews with select participants, they highlighted their important services, identities and practices. We then used causal set relations with natural language processing to match queries with their qualitative narratives. We refer to this two-step process-- deliberately focusing on social groups with unaddressed needs, and carefully translating narratives to computationally accessible forms--as a “content aware” approach. The resulting content aware search outcomes place themes that participants value, in particular greater relationality, much earlier in the list of results when compared with a standard Web search. More broadly, our use of participatory design with “content awareness” adds evidence to the importance of addressing algorithmic bias by considering who gets to address it; and, that participatory search engine criteria can be modeled as robust linkages between interviews and semantic similarity using causal set relations.

Mental mathematics knowledge for teaching of ‘high gain’ pre-service teachers

Background: Initial teacher education (ITE) research in South Africa shows gaps in pre-service teachers’ (PSTs) primary mathematics knowledge.Aim: We study the mental mathematics understandings and teaching experiences of three PSTs who achieved high gains for learners they taught mental mathematics to using the Mental Starters Assessment Project (MSAP) jump strategy materials.Setting: The three PSTs, from one urban university, taught the jump strategy to Grade 3 classes in three different Gauteng schools.Methods: Learner pre- and post-tests around the taught unit provided the basis for categorising the three ‘high gain’ PSTs. Extended interviews with each PST were then transcribed. Initial grounded analyses of these data were subsequently overlaid with categories drawn from the mathematical knowledge for teaching literature.Results: All three PSTs indicated relatively strong common content knowledge of jump strategies and connected specialised content knowledge. They also exhibited strong awareness of the MSAP content. They differed in how they saw the relationship between fluency, calculation and equivalence tasks.Conclusion: The study’s findings indicate the need for more explicit attention to the connection between mental maths fluencies and strategic calculation in ITE.Contribution: The study points to ways in which mental mathematics can be understood and taught for strong learning gains.

51069 Temporal coordination of the CORE Exams promotes organization of a boards review curriculum enhancing residents’ preparation, confidence, and awareness of content

51069 Temporal coordination of the CORE Exams promotes organization of a boards review curriculum enhancing residents’ preparation, confidence, and awareness of content

LUD-YOLO: A novel lightweight object detection network for unmanned aerial vehicle

Autonomous execution of tasks by unmanned aerial vehicles (UAVs) relies heavily on object detection. However, object detection in most images presents challenges such as complex backgrounds, small targets, and obstructions. Additionally, the limited computing speed and memory of the UAV processor affects the accuracy of conventional object detection algorithms. This paper proposes LUD-You Only Look Once (YOLO), a small and lightweight object detection algorithm for UAVs based on YOLOv8. The proposed algorithm introduces a new multiscale feature fusion mode that solves the degradation in feature propagation and interaction through the introduction of upsampling in the feature pyramid network and the progressive feature pyramid network. The application of the dynamic sparse attention mechanism in the Cf2 module achieves flexible computing allocation and content awareness. Furthermore, the proposed model is optimized to be sparse and lightweight, making it possible to deploy on UAV edge devices. Finally, the effectiveness and superiority of LUD-YOLO were verified on the VisDrone2019 and UAVDT datasets. The results of ablation and comparison experiments show that compared with the original algorithm, LUDY-N and LUDY-S have shown excellent performance in various evaluation indexes, indicating that the proposed improvement strategies make the model have better robustness and generalization. Moreover, compared with multiple other popular competitors, the proposed improvement strategies enable LUD-YOLO to have the best overall performance, providing an effective solution for UAVs object detection while balancing model size and detection accuracy.

Digital Literacy In Detecting Hoaxes In Instagram Media (Analysis Study Of Communication Science Students, State Islamic University Of North Sumatra)

Abstract This article explores the urgency of digital literacy in detecting hoaxes on social media, especially Instagram, among students of Communication Sciences of the State Islamic University of North Sumatra (UINSU). This research identifies crucial problems in the spread of false information or hoaxes that have the potential to divide society and damage information integrity. This study uses a qualitative methodology, this research adopts an ethnographic approach and a constructive paradigm to gain a deep understanding of how students perceive and respond to the information they find on social media. The location of this study is Campus 4 Tuntungan UINSU, and the resource persons were selected through purposive sampling based on their experience and activeness in using Instagram as well as their involvement in digital literacy issues. Primary data sources are obtained from in-depth interviews and participatory observations, while secondary data sources include relevant document studies. The data analysis technique used is the Miles, Huberman, and Saldana analytical model which includes data reduction, data presentation, and conclusion drawn. The validity test of the data was carried out through source triangulation. The results of the study show that even though students have access to digital literacy tools, there is still a tendency to trust and spread unverified content. The conclusion of the study emphasizes that digital literacy is not only important as a tool to verify information and avoid the spread of hoaxes, but also as a means to increase critical awareness of media content.

BPN-YOLO: A Novel Method for Wood Defect Detection Based on YOLOv7

The detection of wood defect is a crucial step in wood processing and manufacturing, determining the quality and reliability of wood products. To achieve accurate wood defect detection, a novel method named BPN-YOLO is proposed. The ordinary convolution in the ELAN module of the YOLOv7 backbone network is replaced with Pconv partial convolution, resulting in the P-ELAN module. Wood defect detection performance is improved by this modification while unnecessary redundant computations and memory accesses are reduced. Additionally, the Biformer attention mechanism is introduced to achieve more flexible computation allocation and content awareness. The IOU loss function is replaced with the NWD loss function, addressing the sensitivity of the IOU loss function to small defect location fluctuations. The BPN-YOLO model has been rigorously evaluated using an optimized wood defect dataset, and ablation and comparison experiments have been performed. The experimental results show that the mean average precision (mAP) of BPN-YOLO is improved by 7.4% relative to the original algorithm, which can better meet the need to accurately detecting surface defects on wood.

Examining how early experiences in oncology settings influence nurses' career decisions.

The transition from nursing student to newly registered nurse is a complex process, and subsequent recruitment to cancer nursing posts can be challenging. This article details a service evaluation that aimed to describe the experiences of nursing students on placement and newly registered nurses or nursing associates working in a specialist cancer centre, and how these experiences might influence their future career aspirations. To gather data, the authors undertook a focus group with nursing students ( n= 8) and interviewed newly registered nurses or nursing associates ( n= 19). The data revealed four themes: navigating the nursing student experience; motivation to work in oncology; transition to staff nurse; and looking ahead. The service evaluation identified that education providers often lack awareness of cancer-specific content and career pathways. It also found that some aspects of cancer care, such as gaining specialist skills in systemic anticancer therapy, require particular attention since they were often anxiety-provoking for newly registered nurses.

Analysis of packaging design its colour coding and labelling of contained sugar in dairy and cereal products

The purpose of developing the colour coding system is to create better awareness and help consumers monitor and understand the sugar content of foods. Our research focused on food products (dairy products and cereal products on the Slovenian market) that contain so-called hidden sugars, as these can cause many health risks. The aim of the study was to raise awareness of the sugar content in dairy products and cereals through a packaging design with a uniform labelling and coding system. During the process of this research, few answers were provided to the following questions: How can a labelling system be designed to be clear and impartial, what is the hierarchy and layout of food information on packaging, and how can the system be coherently integrated with existing packaging? The impact of the information design on the consumer in the food packaging industry, which helps in further execution, was analysed. Based on the research, variants of a multi-colour labelling system were created, differing in primary information graphics, colour, placement and formats. The packaging for an imaginary brand and the placement of the code system were designed. Finally, the packaging design was implemented in the 3D models for each food group. The result of this research is a collection of packaging models with a labelling system that informs consumers about sugar content, facilitates decision-making and helps them control their food intake. The colour-coded labels were applied to the packaging in a uniform and coherent manner, which can provide sufficient attention and information.

Farmers’ Awareness of Millets in the Marathwada region

Historically, millets have been integral to diets, offering not only a plethora of health benefits but also contributing to environmental conservation through low water and input requirements. The International Year of Millets, declared by the United Nations for 2023 at the initiative of the Government of India, aims to raise awareness, increase production, and promote consumption of millets. This research explores the awareness and consumption of millets among the farmers of the Marathwada region. The study revealed that Great Millet and Pearl Millet garnered high awareness, while Little Millet, Proso Millet, and Kodo Millet exhibited lower awareness among the respondents. The data also showcased varying awareness of millet nutritional content, with 44.12 per cent having a medium overall awareness. Consumption behaviours unveiled diverse frequency patterns for different millets, with 40.91 per cent at a medium overall consumption level. Consumption patterns of the respondents depicted preferences for staple millet-based items. Reasons for consumption/non-consumption highlighted taste and health as major motivators. Respondents suggested measures like training programs, online resources, and awareness campaigns to boost millet usage. These findings provide a comprehensive understanding of the complex interplay between awareness, consumption patterns, and influencing factors, offering valuable insights for stakeholders aiming to promote millet adoption within communities.

Psychometric Properties of the Turkish Version of the Algorithmic Media Content Awareness (AMCA) Scale

Psychometric Properties of the Turkish Version of the Algorithmic Media Content Awareness (AMCA) Scale

IMPLEMENTATION OF GRAPHIC INTERCHANGED FORMAT (GIF) –ENHANCED LEARNING MATERIALS (ELM) TO THE PERFORMANCE OF STUDENTS IN PHYSICAL EDUCATION OF BALIBAGO INTEGRATED HIGH SCHOOL

Current educational trends, the emergence of the knowledge society, societal changes, and globalization influenced the higher education at the greater level and thus resulted in a quality education and quality assurance, the transformation of the education system and changes in teaching and learning approaches like virtual learning and more technologically enhanced learning like the GIF-ELM. Among a wide range of GIF’s has been introduced to academic institutions and industries. As revealed in this study, the thirty-five (35) teachers who are utilizing GIF-ELM, agreed that the level of effectiveness of the GIF-ELM when it comes to Accuracy, Significance, and Presentation is highly effective. The Enhanced Students Performance after using GIF-ELM is found also highly effective. Diversity refers to the diversification and multiple dimensions in information transmission of technology that will enhance the performance of the Grade 8 students, the results revealed that it is Highly Effective. With this, the utilization of learning materials using GIF-ELM stimulate students’ concentration and awareness of the learning contents. The same viewpoint was stated in stressing that the presence of suitable learning material is a necessity for a smooth process of sharing information between the teacher and learners.

Innovating by prompting: How to facilitate innovation in the age of generative AI

This article focuses on how recent advances in artificial intelligence (AI), particularly chatbots based on large language models (LLMs), such as ChatGPT, can be used for innovation purposes. The article begins with a brief overview of the development and characteristics of generative AI (GenAI). Elaborating on the implications of GenAI, we provide examples to demonstrate four mechanisms of LLMs: translation, summarization, classification, and amplification. These mechanisms inform a framework that highlights how LLMs enable the creation of innovative solutions for organizations through capacities in two dimensions: context awareness and content awareness. The strength of LLMs lies in the combination of capacities in both these dimensions, which enables them to comprehend and amplify content. Four managerial suggestions are presented, ranging from starting out with small-scale projects and data exploration, to scaling through integration efforts and educating prompt engineers. By presenting the framework, recommendations, and examples of use cases in various contexts, the article contributes to the emerging literature on GenAI and innovation.

PharmaCORE: Optimizing medical pharmacology education with an innovative instructional dashboard

What was the educational challenge? Diminishing emphasis on pharmacology education in medical schools has resulted in a concerning lack of prescribing knowledge among physician graduates. These concerns mirror our graduates’ expressed dissatisfaction with the structure and quality of pharmacology educational experiences over the past 5 years. What was the solution? PharmaCORE, a web-based instructional dashboard, was developed as an interactive faculty development tool to enhance integration and instruction of pharmacology content in pre-clinical curriculum at a US medical school. How was the solution implemented? PharmaCORE was introduced in Spring 2022 for instructors teaching pharmacology in the pre-clinical curriculum. Instructors used the dashboard to assess coverage of specific drug topics throughout the curriculum and to apply tailored, learner-centered teaching strategies to optimize learner engagement and comprehension. What lessons were learned that are relevant to a wider global audience? The initial assessment indicated that the dashboard was user-friendly and positively influenced instructor awareness of pharmacology content and learner-centered teaching. This faculty development approach underscores the importance of skill-based mapping and maintaining learner-centered teaching standards to address other integrated subjects and broader curricular challenges. What are the next steps? This study lays the foundation for the broader applicability of instructional dashboards in tracking and addressing curricular challenges across pharmacology and other science subjects. Future steps include more personalized feedback for instructors, creating a student-accessible version, and ongoing monitoring of maintenance measures like milestone exams.

A convolutional neural network based on noise residual for seam carving detection

Seam carving is a method of resizing images based on content awareness. It can realize image retargeting while retaining the main content of the image. However, it may also be maliciously used to tamper with images, such as changing image semantic content by object removal. Therefore, seam carving detection has become important in image forensics. In this paper, a noise residual-based deep learning method is proposed to detect seam carving images. We try to learn the local noise in-consistency of images to recognize them. Firstly, a noise residual extraction segment is used to learn local noise features in the image, and a noise augmentation module is designed to enrich the features, which leverages the noise features extracted from a steganalysis rich model filter to discover the noise in-consistency between authentic and tampered regions. Then, through the feature dimensionality reduction section, the features are further learned and the size of feature maps are reduced. Finally, the output is obtained through global average pooling and a fully-connected layer. A careful testing strategy is further proposed, which greatly improves the detection performance, especially for seam carving with small scaling ratios. The experimental results demonstrate that our method achieves state-of-the-art performance at various scales, and has good robustness and generalization compared with other methods.

Enhancing ESP Learning: Investigating Students' Perspectives on Real-Time Written Corrective Feedback Delivery via Google Docs

The present research aims to investigate the practice of real-time or synchronous written corrective feedback (SWCF) delivery via Google Docs as a platform to deliver feedback, known as a linguistic feedback tool (LiFT) in ESP (English for Specific Purposes) classes, students’ preferences and viewpoints of SWCF. The research employed a qualitative case study involving 15 students from an advanced English correspondence course in a non-English department of a private university in Depok, West Java, Indonesia. Open-ended questionnaires, document analysis, and semi-structured interviews were used to gather the data. The findings revealed that auto-generated and human feedback are used to deliver SWCF via Google Docs, inferring that those features can build students' awareness of language aspects, content, and context in composing professional documents. Direct feedback was delivered more frequently, regarding the learning time efficiency and the students’ ability to identify errors. Further, the students preferred frequent SWCF, direct and indirect feedback, and correcting delivery methods. Finally, they considered that SWCF delivered via Google Docs assists them in improving letter accuracy. Their preferences and viewpoints might allow the lecturer to choose appropriate feedback delivery strategies and material reinforcement. The present research implies a balanced use of auto-generated and human feedback from LiFT in SWCF delivery. Evaluating the effectiveness of SWCF delivery via Google Docs for different levels of achievers in ESP classes might be a potential area of future research. Other LiFTs’ infusion into ESP classes is also worth researching to provide language instructors with alternative applications for SWCF delivery.

Effectiveness of Social Media as Perceived by the Graduate School Students in the University of Baguio

Social media platforms significantly transformed the flow of communication of a company's product or service brand to its target market. This study aims to determine the effectiveness of social media marketing among graduate school students at the University of Baguio. This paper utilizes a descriptive quantitative-qualitative evaluation survey with a questionnaire checklist and an informal interview. Further, this study deploys the convenience sampling method in determining the 74 respondents from graduate school students and 1 Dean. The quantitative aspect of the data is measured using frequency, percentage, weighted mean, and ranking. The findings reveal that Facebook emerged as the most popular social networking platform. The very high influence of social media creates attention, visibility, and awareness of subject content. The increase in enrollment is a confirmation of the effectiveness of social media marketing produced by institutions. Strategic initiatives related to the marketing and promotion of the Graduate School under the School of Business Administration and Accountancy deal with the 4Ps—Product, Place, Price, and Promotion.

Sociocultural Pressures, Internalization, and Body Esteem in Congenitally Blind, Late-Blind, and Sighted Men and Women

Introduction: Visual experience has a substantial effect on how individuals construct a template of their own bodies in space. Whether the absence of total or partial visual exposure in individuals of both genders allows the buffering of harmful effects has yet to be tested. This study examined the role of vision among congenitally blind and later blind subjects for the expression of body esteem and sociocultural attitudes toward appearance. Methods: Participants comprised 101 subjects, 53 sighted and 48 visually impaired men and women. For the purpose of the study, we took into consideration congenitally blind, late blind, and typically sighted individuals. The Sociocultural Attitudes toward Appearance Questionnaire-3 (SATAQ-3) and the Body-Esteem Scale Questionnaire (BESQ) were used as measures. Results: Although congenitally blind, late blind, and typically sighted individuals showed similar awareness of media content and beauty ideals, typically sighted women displayed higher pressure to conform and had higher levels of social comparison. Congenitally blind women placed less emphasis on mass media as an influential aspect of their body perception and showed reduced internalization of beauty ideals and higher levels of body esteem. Moreover, men with visual impairments considered siblings and family to be the most influential information sources for their own body perception, while showing reduced levels of athlete internalization. Discussion: In this research, it was identified that the absence of sight influences an individual's body image beyond its physical, metric representation. Susceptibility to detrimental messages linked to sociocultural standards of attractiveness is interiorized by individuals with and without visual impairments, regardless of their gender. Implications for Practitioners: Further studies on body esteem and sociocultural pressures could enable practitioners to better understand how to support individuals with visual impairments in coping with an unhealthy social environment and with feelings of unhappiness related to their appearance.

Conscious perception of fear in faces: Insights from high-density EEG and perceptual awareness scale with threshold stimuli

Contrary to the extensive research on processing subliminal and/or unattended emotional facial expressions, only a minority of studies have investigated the neural correlates of consciousness (NCCs) of emotions conveyed by faces. In the present high-density electroencephalography (EEG) study, we first employed a staircase procedure to identify each participant's perceptual threshold of the emotion expressed by the face and then compared the EEG signals elicited in trials where the participants were aware with the activity elicited in trials where participants were unaware of the emotions expressed by these, otherwise identical, faces. Drawing on existing knowledge of the neural mechanisms of face processing and NCCs, we hypothesized that activity in frontal electrodes would be modulated in relation to participants' awareness of facial emotional content. More specifically, we hypothesized that the NCC of fear seen on someone else's face could be detected as a modulation of a later and more anterior (i.e., at frontal sites) event-related potential (ERP) than the face-sensitive N170. By adopting a data-driven approach and cluster-based statistics to the analysis of EEG signals, the results were clear-cut in showing that visual awareness of fear was associated with the modulation of a frontal ERP component in a 150–300 msec interval. These insights are dissected and contextualized in relation to prevailing theories of visual consciousness and their proposed NCC benchmarks.

Does the Australian school system and curriculum support young people to become active and informed citizens?

AbstractDoes the Australian school system and curriculum support students to become active and informed’ members of the community, which is a key aspiration of the Australian school system set out in the Alice Springs (Mparntwe) Education Declaration? We address this question by drawing on the Australian National Assessment Program (NAP) civics and citizenship data. The NAP data measures Year 6 and Year 10 students’ awareness of civics and citizenship content as well as their participation in civics and citizenship-related activities at school. The data suggests that students are being informed about social, political and economic issues, but there are differences between students with respect to their active engagement in civics and citizenship related activities at school deriving from their parents’ educational level and age group. But the curriculum is also at issue here. The prescriptive Australian Curriculum framework has a heavy emphasis on academic learning particularly during the secondary years, which sidelines active participation in civics and citizenship education. Furthermore, the Australian Curriculum constrains teachers in their ability to enact a truly negotiated curriculum that is meaningful to students and may enhance their sense of being part of the community and citizens of a democratic society.

The role of governance mechanisms in trust-building strategies: A comparative analytical study in public and private banks

The study aims to build a model that enhances trust-building for public and private banks to compare and determine the significant differences between public and private banks, by testing the impact of governance mechanisms (transparency, accountability, justice, independence, and social responsibility) (Agere, 2000) on trust-building strategies (trust and trust building, people management, work relations, training and development, leadership practices, and communications) (Ngalo, 2011; Stone et al., 2005), to indicate the level of employees’ awareness of the theoretical contents of the two variables and their importance to banking work, with the aim of improving performance. The main question is the role of governance mechanisms in supporting trust-building strategies. The questionnaire was distributed to two stratified random samples, the first in public banks consisting of 62 individuals and the second in private banks consisting of 61 individuals. It followed the descriptive analytical comparative approach. One of the most important results is that there are significant differences between the two samples, and the weight is weighted in favor of public banks in relation to trust-building strategies with customers. Despite the use of outdated working methods, the conclusions pointed to the tangible role of governance mechanisms in supporting trust-building strategies.