Different Forms Of Information Research Articles

MuLX-QA: Classifying Multi-Labels and Extracting Rationale Spans in Social Media Posts

While social media platforms play an important role in our daily lives in obtaining the latest news and trends from across the globe, they are known to be prone to widespread proliferation of harmful information in different forms leading to misconceptions among the masses. Accordingly, several prior works have attempted to tag social media posts with labels/classes reflecting their veracity, sentiments, hate content, etc. However, in order to have a convincing impact, it is important to additionally extract the post snippets on which the labelling decision is based. We call such a post snippet as the ‘rationale’. These rationales significantly improve human trust and debuggability of the predictions, especially when detecting misinformation or stigmas from social media posts. These rationale spans or snippets are also helpful in post-classification social analysis, such as for finding out the target communities in hate-speech, or for understanding the arguments or concerns against the intake of vaccines. Also it is observed that a post may express multiple notions of misinformation, hate, sentiment, etc. Thus, the task of determining (one or multiple) labels for a given piece of text, along with the text snippets explaining the rationale behind each of the identified labels is a challenging multi-label, multi-rationale classification task, which is still nascent in the literature. While transformer -based encoder-decoder generative models such as BART and T5 are well-suited for the task, in this work we show how a relatively simpler encoder-only discriminative question-answering (QA) model can be effectively trained using simple template-based questions to accomplish the task. We thus propose MuLX-QA and demonstrate its utility in producing (label, rationale span) pairs in two different settings: multi-class (on the HateXplain dataset related to hate speech on social media), and multi-label (on the CAVES dataset related to COVID-19 anti-vaccine concerns). MuLX-QA outperforms heavier generative models in both settings. We also demonstrate the relative advantage of our proposed model MuLX-QA over strong baselines when trained with limited data. We perform several ablation studies, and experiments to better understand the effect of training MuLX-QA with different question prompts, and draw interesting inferences. Additionally, we show that MuLX-QA is effective on social media posts in resource-poor non-English languages as well. Finally, we perform a qualitative analysis of our model predictions and compare them with those of our strongest baseline.

Application of Internet of Things and multimedia technology in English online teaching

This study aims to explore the application status of Internet of Things and multimedia technology in English online teaching and its optimization measures. The Internet of Things is a technology that connects objects together and realizes information exchange through the network, while multimedia technology refers to the integration and processing of different forms of information including text, images, sound, video and so on. Firstly, the development status of Internet of Things and multimedia technology at home and abroad, as well as the development trend and demand of online English teaching, are analyzed. Secondly, through a questionnaire survey, data on the teaching methods, content, student feedback, and teachers’ teaching methods and effects in English online teaching were collected. Through in-depth data analysis and empirical research, this paper discusses how to integrate the Internet of Things and multimedia technology to build a more efficient online English teaching model. On this basis, the problems existing in the Internet of Things and multimedia technology in English online teaching are summarized, such as uneven application of technology, lack of targeted teaching design, and insufficient interactivity. In response to these problems, a series of optimization measures are proposed, including balancing the application of technology, personalized teaching design, improving interactivity, cultivating independent learning ability and solving technical problems. Finally, the future development of English online teaching in the application of Internet of Things and multimedia technology is prospected, focusing on technological innovation and application, personalized and intelligent teaching, teaching mode and method innovation, teacher role change and evaluation system construction.

A hybrid interval evidential reasoning-regret decision making model and its application to the behavior of Chinese herbal medicine planting selection

This paper studies the optimal selection of planting Chinese Herbal Medicine (CHM), which has many attributes and stakeholders, and where some assessment information cannot be obtained directly from the official websites. The assessment information is categorized into two groups: precise and interval numbers that can be obtained from the official sites, and precise information obtained through expert surveys and questionnaires. A three-step group decision-making mechanism is proposed for the CHM problem. First, an analytical method based on interval evidence reasoning is formed to unify different forms of information into the same interval belief structure. Next, a model based on the geometric area method is formed to obtain the weights of the attributes. Third, the extended interval regret theory is used to rank the alternative solutions. Applying perceived utility value and the ranking of the alternatives, an optimal solution for planting CHM is found. Comparative and sensitivity analyses highlight the flexibility and reliability of the suggested solution. By evaluating the various parameters, decision-makers in CHM can prioritize their decisions for maximal benefit.

An Investigation of Graduate Students' Views on Information Literacy

Information literacy, which is defined as the ability to access, evaluate, use and communicate information in different forms, has a special importance in every period of individuals' lives. The competencies sought in an information literate individual vary according to the level of education they are in; a linear relationship is established between the level of education and the areas of competence. The rapid development of technology and the subsequent information explosion have revealed the importance of qualified information, and societies have started to need individuals who access the right information, use it, produce and share it, and use technology effectively in these processes. It has become imperative for individuals to access the most up-to-date and accurate information in their own professional field. Information literacy qualifications of graduate students are of great importance in terms of both the studies they will put forward and their self-development. This study was carried out to determine the views of graduate students studying at a university in the 2022-2023 academic year affiliated to the Institute of Educational Sciences on information literacy. The information literacy interview form developed by the researcher was used as a data collection tool. Information literacy interview form developed by the researcher was used as a data collection tool. Content analysis was used in the analysis of the views of 20 postgraduate students affiliated to the Institute of Educational Sciences.Graduate students' views on the dimensions of information literacy were examined in the context of knowing, accessing, evaluating, using, ethical/legal issues. When the results of the research are examined, it is seen that graduate students see information literacy as the ability to use the stages of information literacy, determine the information they need when they encounter a problem situation, the sources of access to information are mostly the internet, question the accuracy of the sources in evaluating information, use information for academic development, and point out the presence of unrealistic information as a problem. In line with these results, it is suggested that information literacy should be added to the content of the research methods in education course, which is one of the courses taken by graduate students, and students should develop the skills of questioning the authenticity of the information obtained from the internet that they use in their academic development.

How Shall TFEU Article 102 on Abuse of Dominant Position be Interpreted in the Digital Platform Economy?

In 2021, The European General Court issued its judgment in Case T-612/17 Google and Alphabet v Commission (Google Shopping). The case concerned whether Google had abused its dominant market position by favouring its own comparison shopping service on its general results pages while demoting the results from competing comparison shopping services. The General Court stated that Google’s conduct was not competition on the merits and thus it had breached Article 102 of the Treaty on the Functioning of the European Union (TFEU). This article discusses firstly this judgment and its consequences for the interpretation of Article 102 TFEU in digital platform economy markets. Secondly, this article takes on the issue of abuse of dominant position in digital markets and tries to find out what kind of conduct of digital platform companies should be prohibited by Article 102 TFEU. The purpose is to identify what kind of conduct should be seen as an abuse of dominance and how to legally assess such conduct. The ECJ judgment states that self-preferencing can constitute a breach of Article 102 TFEU and that this can be seen as a form of discrimination. Besides self-preferencing or discrimination there is also other conduct that can be abusive. These include personalised pricing, forced free riding and different forms of information based abusive conducts. It is not clear how this conduct relate to Article 102 TFEU, but it is clear that should this conduct be seen abusive, it will be difficult to determine the basis for this since well-established theories of harm are incompatible. In addition, when assessing the abusive nature of such conduct, an effects-based case-by-case approach is needed.

University Student Dropout Prediction Using Pretrained Language Models

Predicting student dropout from universities is an imperative but challenging task. Numerous data-driven approaches that utilize both student demographic information (e.g., gender, nationality, and high school graduation year) and academic information (e.g., GPA, participation in activities, and course evaluations) have shown meaningful results. Recently, pretrained language models have achieved very successful results in understanding the tasks associated with structured data as well as textual data. In this paper, we propose a novel student dropout prediction framework based on demographic and academic information, using a pretrained language model to capture the relationship between different forms of information. To this end, we first formulate both types of information in natural language form. We then recast the student dropout prediction task as a natural language inference (NLI) task. Finally, we fine-tune the pretrained language models to predict student dropout. In particular, we further enhance the model using a continuous hypothesis. The experimental results demonstrate that the proposed model is effective for the freshmen dropout prediction task. The proposed method exhibits significant improvements of as much as 9.00% in terms of F1-score compared with state-of-the-art techniques.

Involvement, depressive symptoms, and their associations with problems and unmet needs in caregivers of adult eating disorder patients

PurposeThis study aimed to examine the most important problems and needs caregivers of adult inpatients with eating disorders (EDs) are confronted with in their everyday lives. A further aim was to investigate the associations between problems, needs, involvement, and depression in carers.MethodsFifty-five caregivers of inpatients with EDs (26 anorexia nervosa, 29 bulimia nervosa) completed the Carers' Needs Assessment, Beck Depression Inventory, and the Involvement Evaluation Questionnaire. The relationships between variables were tested via multiple linear regressions and mediation analyses.ResultsThe most frequent problem reported by caregivers was a lack of information about the course and treatment of the illness and consequent disappointment, whereas their most frequently reported needs were different forms of information and counselling. Problems, unmet needs, and worrying were especially high in parents compared to other caregivers. Involvement mediated significantly between problems (b = 0.26, BCa CI [0.03, 0.49]) as well as unmet needs (b = 0.32, BCa CI [0.03, 0.59]) of caregivers and their depressive symptoms.ConclusionOur findings underline the importance of including the problems and needs of caregivers of adult eating disorder patients in the planning of family and community interventions, to support their mental health.Level of evidenceLevel III: Evidence obtained from cohort or case–control analytic studies.

Forward Guidance and Household Expectations

Abstract We compare causal effects of forward guidance about future interest rates on households’ expectations of inflation and nominal mortgage rates to the effects of communication about inflation in a randomized control trial using more than 20,000 U.S. consumers in the Nielsen Homescan Panel. We elicit consumers’ expectations, and then provide 22 different forms of information regarding past, current, and/or future interest rates and inflation. Information treatments about current or future interest rates all have similar and offsetting effects on interest rate and inflation expectations, yielding limited pass-through into perceived real rates. Information about mortgage rates has much more powerful effects on interest rate perceptions, with no offsetting effects on inflation expectations, thereby delivering much larger changes in perceived real rates. Revisions in perceived real rates causally lead to changes in the ex-post purchases of durable goods by households.

REIMAGINING END OF LIFE: ALTERNATIVE APPROACHES TO SERIOUS ILLNESS CARE CONVERSATIONS

Abstract Serious illness care conversations are intended to document and protect patients’ medical treatment wishes. In the outpatient management of chronic diseases, it has been difficult to pinpoint ideal timing for these conversations. The goal of this project is to analyze current practice within a VA health care system for identifying and referring veterans for palliative care services in the last years of life. To develop a targeted intervention, we relied on different forms of information to identify life events which should trigger a goals of care conversation, possibly even a formal palliative care referral. This study describes how we operationalized knowledge gained from: 1) Veteran community members via a project-dedicated engagement panel, 2) semi-structured interviews with providers, and 3) review of patients’ clinic notes written by clinicians during the last 5 years of life. Tapping into the knowledge and experience of multiple parties provided nuance and complexity to our approach to intervention development. From the Veteran community member engagement panel, we learned that trusting relationships were essential. Providers emphasized that having enough time during appointments and timing of the conversation during a patient’s disease trajectory were important. Finally, chart review indicated a need for broaching serious illness conversations early and throughout the duration of their care. The goal of an earlier intervention is to engage veterans when they are medically stable and prior to prolonged hospitalization. These findings structured our ongoing intervention that focuses on identifying and reaching out to Veterans with serious illnesses.

NATURAL GUJARATI LANGUAGE INTERFACE TO DIRECT RETRIEVAL FROM DIVERSE INDIAN AGRICULTURE SOURCES

A major part of India's economy is based on agriculture. Indian Government and private organizations offer a lot of different forms of information and knowledge to be beneficial to the agriculture community. It is essential that this information reaches to the needy in his own language with very little effort. At that time, when other helping hand is not accessible to answer them, Automated Digital solution is blessing to acquire solution of the agriculture stake holder’s questions related to agriculture facts, features and functionalities. And that to be provided as speedy direct retrieval, not the transformed or linked solution. In Agriculture AI is applied at different phases of the crop cultivation system, but as per the study and review, we do not have direct solution in mind. After the innovation, we have found and patented the solution in India (Shah and Pareek, A Mechanized Intellect Orchestration, Filed as Patent). Here, in this paper we have described the detail framework in Indian agriculture context. We have found the result of the retrieval through the proposed process and that’s significant to work towards this novice solution.

The use of visual presentations for integrated reports in the investment decision-making process

PurposeThis study aims to identify the effect of the format of a presentation and the form of information on the decision-making process of non-professional investors in Indonesia. Investor behaviors, including acquisition, evaluation, weighting, judgment, and allocation decisions, are explained explicitly after taking a look at the form of the information and the way it is conveyed in various presentation formats.Design/methodology/approachThis research used web-based experiments. It used a 2 × 2 between-subjects design. Eighty-nine selected students acted as surrogate investors. They were provided with company performance reports presented in different report formats (integrated versus non-integrated) and different forms of information (visual versus descriptive).FindingsThe results showed that information, when presented visually, is more influential on investment allocation decisions in Indonesia. In addition, the result of the post hoc test indicated that integrated reports are more influential than non-integrated reports.Research limitations/implicationsThe results of this study have significant implications for companies that publish financial and non-financial disclosures. The reports are required to be presented in an integrated and visual form in order to increase the investors' level of understanding so they can comprehend a company's performance holistically.Practical implicationsIt is necessary for Indonesian policymakers to create regulations regarding the presentation of financial and non-financial information in an integrated and visual way.Originality/valueThis study fills a gap in the literature on integrated reports by showing that the visualization of information in such reports increases the level of understanding that underpins investment decision-making. Furthermore, this study contributes to cognitive load theory by providing evidence that the kind of presentation of information that facilitates people's cognitive ability is not only in the narrative form but visual presentation also works.

Monetary Policy Communications and Their Effects on Household Inflation Expectations

We study how different forms of communication influence the inflation expectations of individuals in a randomized controlled trial. We first solicit individuals’ inflation expectations in the Nielsen Homescan panel and then provide eight different forms of information regarding inflation. Reading the actual Federal Open Market Committee (FOMC) statement has about the same average effect on expectations as simply being told about the Federal Reserve’s inflation target. Reading a news article about the most recent FOMC meetings results in a forecast revision which is smaller by half. Our results have implications for how central banks should communicate to the broader public.

Multi-granular hybrid information-based decision-making framework and its application to waste to energy technology selection

To achieve sustainable management of municipal solid waste, selecting an appropriate waste to energy (WTE) technology is pivotal. The WTE technology selection is a complicated issue because it involves a range of conflicting criteria and a rich diversity of stakeholders. Moreover, the complexity will be multiplied when considering that the preference information provided by different people with respect to different criteria takes different forms and granularities. To tackle the WTE technology selection problems with multi-granular hybrid information, this paper proposes a new group decision-making framework. The proposed framework provides a reasonable solution to the WTE technology selection problems through four stages. In the first stage, three information transformation mechanisms are established to transform information in different forms and granularities into unified belief structures. In the second stage, a symmetrical cross-entropy measure-based weight determination model is developed to calculate the criteria weights. In the third stage, by combining information transformation mechanisms and criteria weights, the analytical evidential reasoning algorithm is extended to generate group opinions. Finally, according to the generated group opinions, the expected utilities of alternatives are calculated to compare and rank the alternatives. To illustrate the implementation process of the proposed decision-making framework, an application about the WTE technology selection in China is performed. Besides, a comparative experiment is conducted to show the flexibility and reliability of our proposal.

Cross-modal semantic autoencoder with embedding consensus

Cross-modal retrieval has become a topic of popularity, since multi-data is heterogeneous and the similarities between different forms of information are worthy of attention. Traditional single-modal methods reconstruct the original information and lack of considering the semantic similarity between different data. In this work, a cross-modal semantic autoencoder with embedding consensus (CSAEC) is proposed, mapping the original data to a low-dimensional shared space to retain semantic information. Considering the similarity between the modalities, an automatic encoder is utilized to associate the feature projection to the semantic code vector. In addition, regularization and sparse constraints are applied to low-dimensional matrices to balance reconstruction errors. The high dimensional data is transformed into semantic code vector. Different models are constrained by parameters to achieve denoising. The experiments on four multi-modal data sets show that the query results are improved and effective cross-modal retrieval is achieved. Further, CSAEC can also be applied to fields related to computer and network such as deep and subspace learning. The model breaks through the obstacles in traditional methods, using deep learning methods innovatively to convert multi-modal data into abstract expression, which can get better accuracy and achieve better results in recognition.

Using Design and Graphic Design with Color Research in AI Visual Media to Convey

With the development of science and technology and social progress, people can reveal design information in different forms on a daily basis. The more common visual design information, the more important its development status. In visual communication design, the two most important factors are color and image. These two factors can play a great role and can attract the public’s attention. This article is based on AI technology to study the design of color matching and image application in visual media communication design, aiming to innovate the method of visual media communication design, breaking through the traditional color matching and image application, so as to better use color art in visual communication design and graphic art and design excellent works. First, this article elaborates on the concept, main components, and influencing factors of visual communication design and also introduces the application of AI technology, then designs a visual media communication design model based on AI technology, and finally analyzes the current status of visual media communication design, usage, and satisfaction. From the analytical analysis, it appears that the optical media interface is commonly used for packaging design, responding to 45.6%; it is used more in the film and television media industry, reaching 68%; 49% of the public are very satisfied with AI visual media communication design. The above data fully shows that the application of AI visual media communication design is very wide, and the color matching and image use are very prominent, and the public is willing to accept AI visual media communication design works.

Estimation of pre-dolomitisation porosity and permeability of a nummulitic carbonate reservoir rock using the Multi-Component Architecture Method (MCAM)

The fossiliferous Eocene carbonate reservoir interval of the offshore Hasdrubal Field has a diagenetic history in which dolomitisation of micrite-rich facies has significantly enhanced reservoir quality. Using published information on the diagenetic evolution, digital textural representations of the limestones and dolostones are created using the Multi-Component Architecture Method (MCAM). This technique allows integration of images at different length scales (e.g., SEM, micro-/nano- XRT) which provide different forms of information about the pre-dolomitisation rock, including textural and compositional factors, and the arrangements of preserved components. These digital representations of the dolostones, together with their now completely overprinted precursor micritic limestones, permit exploration of the impact on porosity and permeability of uncemented, partly cemented and biomoulds Nummulites, their number per unit volume, and their orientation (i.e., uniformly or randomly orientated) allowing investigation of the petrophysical consequences of different distributions, orientations and abundances of the matrix and fossiliferous components. Viable diagenetic pathways, which were identified by thin section analysis as well as data available in the literature, are linked to petrophysical property evolution. In this way MCAM permits investigation of earlier stages of the diagenetic processes which were overprinted by later diagenetic processes.

Children’s Reputation Management: Learning to Identify What Is Socially Valued and Acting Upon It

Much of what people do is motivated by a concern with social evaluation. We argue that the process of figuring out what others value and making effective use of this information presents significant cognitive challenges. These challenges include reasoning about the relevance of different forms of information and making inferences about the mental lives of others. They also include modifying one’s behavior in light of whatever personal qualities appear to be valued in an effort to appeal to different audiences. We argue that the foundations of many of the important skills needed to meet these challenges are already in place early during childhood, but that the challenges themselves persist well into adulthood.

An efficient image encryption scheme based on double affine substitution box and chaotic system

Privacy of information is one of the most important and unavoidable issues in our digitally advance era. A huge amount of information transmitted over different servers and networking protocols. The sphere of digitally advanced world is tied with information in different forms of facilitations, which includes online banking systems, ecommerce and many more. Providing the ease of access, anything online makes our confidential information open to different threats. Therefore, to enjoy ease of access and at the same time secure our digital information from theft, we need a robust information security system. In this article, we have designed a novel and an efficient security system, which provides secrecy to our digital information. The designed encryption scheme is fundamentally a combination of chaos and nonlinear confusion components. We have developed a new mechanism of adding confusion, namely S8 permutation of double affine transformation to construct 40320 new substitution boxes (S-boxes) having nonlinearity 112 from a single S-box. Moreover, nonlinear Lorenz dynamical system is utilized to select any three S-boxes from 40320 newly generated nonlinear components. To add diffusion in our proposed algorithm, we have utilized Chirikov discrete iterative map. The excellence of an offered digital image encryption has been examined and evaluated with standard benchmarks. The simulation results reveal that the quality of the image encryption passes all these tests and is comparable to current benchmarks.

Health literacy and information seeking and sharing during a public health crisis in China

ABSTRACT Understanding individual differences in communication behaviors is crucial to achieve strategical communication during a public health crisis. To advance this knowledge, the current study explored how Chinese publics with different levels of functional, communicative, and critical health literacy sought and shared information in different forms (i.e. traditional media, social media, and offline word-of-mouth communication) and from different sources (i.e. government, news agencies, health professionals, the company, and other publics) during the Quanjian crisis, a public health crisis happened in China. Findings suggest that higher functional and critical health literacy were associated with higher frequency of seeking and sharing information of almost all forms and sources. However, communicative health literacy was not associated with seeking and sharing information of most forms and sources. The study contributes to crisis communication literature and practice by suggesting health literacy, as an individual factor, can be used to identify influential publics in crisis information transmission. The study also adds to health literacy literature by suggesting the need to develop context-specific operationalizations of communicative health literacy.

Theoretical and methodological aspects of the development of children's intellectual and creative abilities on the basis of media education technologies

The article deals with the theoretical and methodological aspects of the development of intellectual and creative abilities of children based on media education technologies. The main approaches that have developed in the world of science to this issue are studied, and the differences between them are outlined.Media literacy is, in general, a set of skills and abilities that enable people to analyze, evaluate, and generate information in different forms, genres, and types of different media. It is based on a model that encourages a person to ask questions about what they see, read, and hear. Through media literacy, a person acquires the ability to analyze media texts and distinguish the true from the false, the important from the insignificant, the narrow approach from the broad approach.