Chunks Of Information Research Articles

Nurse perspectives on the assessment of emergency medicine residents: A qualitative study.

Multisource and 360-degree feedback are emerging methods in the medical education assessment literature. Nursing feedback in particular has been identified as a point of emphasis regarding what medical education leadership would most value for incorporating into their evaluations. There is no currently accepted tool for multisource feedback in the emergency department (ED). To answer this call, we conducted a qualitative study to elucidate nurse perspectives on evaluation of emergency medicine residents. We conducted individual semistructured interviews of ED nurses with experience working alongside residents via volunteer recruitment. Transcripts were coded independently by each author and then reviewed collaboratively to resolve differences. Codes were created by inductive thematic analysis and subsequently underwent constant comparison and classical content analysis. Recruitment continued until analysis of transcripts showed thematic saturation. We organized the interview transcript into chunks of information, arranging 407 quotes from the 10 interview transcripts into 17 codes and six themes regarding observable resident behaviors. Representative quotes and exemplar cases added detailed description to the meaning of these codes. The identified themes for observable resident behaviors included "general communication style," "medical knowledge," "efficiency," "patient communication," "nurse communication," and "professionalism." An additional 13 codes addressed the themes of barriers and catalysts for feedback. The identified themes on observable resident behaviors aligned well with prior literature and with the Accreditation Council for Graduate Medical Education (ACGME) Milestones. The interviews also highlighted nurse perspectives on barriers and catalysts for feedback that would be useful to incorporate into the design of an assessment tool.

DEVELOPING DIGITAL LEADERSHIP PRACTICES IN MILITARY: A WAY FORWARD

Military leadership today deals with a plethora of information related to its on-field and offthe-field operations that are complex in nature and needs critical thinking which can affect the decision-making process. Information overload is a phenomenon that creates uncertainty and ambiguity in decision-making. Losing direction is very likely in such situations as it could be an issue for the leadership to keep track of what needs to be contained and what needs to be discarded from the chunks of information received continuously. Building adaptive and agile leadership is imperative to technology adaption in the military as digital decision-making and a tech-savvy culture will be key attributes of the future. Adapting digital technologies will help fight and win wars in the digital era and military leadership must learn the digital leadership skills to win the fights driven by technology. With the future of warfare going digital, knowledge-based decision-making will be a valuable asset as these capabilities will become a necessity in times to come. Information control will play a pivotal role in digital leadership and digital leadership combined with the foresight and experience of the commanders can help tackle fifthgeneration warfare.

Markers of schizophrenia at the prosody/pragmatics interface. Evidence from corpora of spontaneous speech interactions.

The speech of individuals with schizophrenia exhibits atypical prosody and pragmatic dysfunctions, producing monotony. The paper presents the outcomes of corpus-based research on the prosodic features of the pathology as they manifest in real-life spontaneous interactions. The research relies on a corpus of schizophrenic speech recorded during psychiatric interviews (CIPPS) compared to a sampling of non-pathological speech derived from the LABLITA corpus of spoken Italian, which has been selected according to comparability requirements. Corpora has been intensively analyzed in the Language into Act Theory (L-AcT) frame, which links prosodic cues and pragmatic values. A cluster of linguistic parameters marked by prosody has been considered: utterance boundaries, information structure, speech disfluency, and prosodic prominence. The speech flow of patients turns out to be organized into small chunks of information that are shorter and scarcely structured, with an atypical proportion of post-nuclear information units (Appendix). It is pervasively scattered with silences, especially with long pauses between utterances and long silences at turn-taking. Fluency is hindered by retracing phenomena that characterize complex information structures. The acoustic parameters that give rise to prosodic prominence (f0 mean, f0 standard deviation, spectral emphasis, and intensity variation) have been measured considering the pragmatic roles of the prosodic units, distinguishing prominences within the illocutionary units (Comment) from those characterizing Topic units. Patients show a flattening of the Comment-prominence, reflecting impairments in performing the illocutionary activity. Reduced values of spectral emphasis and intensity variation also suggest a lack of engagement in communication. Conversely, Topic-prominence shows higher values for f0 standard deviation and spectral emphasis, suggesting effort when defining the domain of relevance of the illocutionary force. When comparing Topic and Comment-prominences of patients, the former consistently exhibit higher values across all parameters. In contrast, the non-pathological group displays the opposite pattern.

A secure framework for medical image by integrating watermarking and encryption through fuzzy based ROI selection

Security, secrecy, and authenticity problems have arisen as a result of the widespread sharing of medical images in social media. Copyright protection for online photo sharing is becoming a must. In this research, a cutting-edge method for embedding encrypted watermarks into medical images is proposed. The proposed method makes use of fuzzy-based ROI selection and wavelet-transformation to accomplish this. In the first step of the process, a fuzzy search is performed on the original picture to locate relevant places using the center region of interest (RoI) and the radial line along the final intensity. The suggested method takes a digital picture and divides it into 4×4 non-overlapping blocks, with the intent of selecting low information chunks for embedding in order to maximize invisibility. By changing the coefficients, a single watermark bit may be inserted into both the left and right singular SVD matrices. The absence of false positives means the suggested technique can successfully integrate a large amount of data. Watermarks are encrypted using a pseudorandom key before being embedded. Discrete wavelet transform saliency map, block mean method, and cosine functions are used to construct an adaptively-generated pseudo-random key from the cover picture. Images uploaded to social media platforms must have a high degree of invisibility and durability. These watermarking features, however, come with a price. The optimal scaling factor is used to strike a balance between the two in the proposed system. Furthermore, the suggested scheme’s higher performance is confirmed by comparison with the latest state-of-the-art systems.

Video steganography: recent advances and challenges

Video steganography approach enables hiding chunks of secret information inside video sequences. The features of video sequences including high capacity as well as complex structure make them more preferable for choosing as cover media over other media such as image, text, or audio. Video steganography is a prominent as well as the evolving field in the information security domain and significant number of video steganography methods are proposed in recent years. This article provides a comprehensive review of video steganography methods proposed in the literature. This article initially reviews various raw domain-based video steganography methods. In particular, the raw domain-based methods include spatial domain approaches such as least significant bits (LSB), transform domain-based methods such as discrete wavelet transform, discrete cosine transform, etc. Furthermore, the article looks into various compressed domain steganography methods. A critical comparative analysis is included in the article to analyze and contrast the steganography methods proposed in the literature. A brief description of various evaluation matrices for video steganography methods is provided in this article. Moreover, a brief introduction to steganalysis and video steganalysis is provided. The article concludes with a discussion focused on the limitations and challenges of the video steganography methods. Further, a brief insight into future directions in video steganography systems is provided.

Design of a micro-learning framework and mobile application using design-based research.

Traditional learning techniques have evolved slowly and have yet to adapt the course content delivery to today's students' approaches to acquiring new knowledge. However, micro-learning has become popular in e-Learning environments as a course design technique due to short attention spans, demand for small chunks of information, and time constraints. Hence, it has been selected for creating reading mobile applications provided to the nature of its learning approach. In order to describe the multiple iterations of design, development, and evaluation of this general framework, a methodology named Design-Based Research (DBR) is implemented. First, the article presents the abstract framework components and a cloud-based software architecture that allows a modular approach to creating such applications. The pathway developed through adapting the iPAC framework, which involves personalization, authenticity, and collaboration, is part of the methodology used to design the app under pedagogical and technological considerations. The process demanded the following phases: analysis and exploration, design and construction, evaluation and reflection, redesign and reconstruction, and final critical reflections. Four applied instruments also validate the framework implementation: The iPAC Rubric, an aphorisms checklist, a pre and post-test, a focus group, and a usability test taken by 28 students in a private university in Colombia. Findings indicated that Design-Based Research (DBR) methodology emerged as an appropriate tool to encounter the needs behind reading applications design due to its sequence of operations yields results successively closer to adequate usability standards and smooth implementation. They also reveal the positive impact of new types of texts on students' motivation and awareness toward other reading strategies and micro-learning. This impact indeed proved the proposed framework's effectiveness for designing micro-learning applications.

Deliberate ignorance—a barrier for information interventions targeting reduced meat consumption?

Objective Despite abundant information about negative consequences of consuming meat, consumption in many Western countries is many times higher than recommended. One possible explanation for this discrepancy is that people consciously decide to ignore such information—a phenomenon called deliberate ignorance. We investigated this potential barrier for information interventions aiming to reduce meat consumption. Methods In three studies, a total of 1133 participants had the opportunity to see 18 information chunks on negative consequences of meat consumption or to ignore part of the information. Deliberate ignorance was measured as the number of ignored information chunks. We assessed potential predictors and outcomes of deliberate ignorance. Interventions to reduce deliberate ignorance (i.e., self-affirmation, contemplation, and self-efficacy) were experimentally tested. Results The more information participants ignored, the less they changed their intention to reduce their meat consumption (r = −.124). This effect was partially explained by cognitive dissonance induced by the presented information. While neither self-affirmation nor contemplation exercises reduced deliberate ignorance, self-efficacy exercises did. Conclusion Deliberate ignorance is a potential barrier for information interventions aiming to reduce meat consumption and needs to be considered in future interventions and research. Self-efficacy exercises are a promising approach to reduce deliberate ignorance and should be further explored.

An EIM-based compression-extrapolation tool for efficient treatment of homogenized cross-section data

Nuclear reactor simulators implementing the widespread two-steps deterministic calculation scheme tend to produce a large volume of intermediate data at the interface of their two subcodes – up to dozens or even hundred of gigabytes – which can be so cumbersome that it hinders the global performance of the code. The vast majority of this data consists of “few-groups homogenized cross-sections”, nuclear quantities stored in the form of tabulated multivariate functions which can be precomputed to a large extent.It has been noticed in Tomatis (2021) that few-groups homogenized cross-sections are highly redundant — that is, they exhibit strong correlations, which paves the way for the use of compression techniques. We here pursue this line of work by introducing a new coupled compression/surrogate modeling tool based on the Empirical Interpolation Method, an algorithm originally developed in the framework of partial differential equations (Barrault et al., 2004). This EIM-compression method is based on the infinite norm ∥⋅∥∞, and proceeds in a greedy manner by iteratively trying to approximate the data and incorporating the chunks of information which cause the largest error. In the process, it generates a vector basis and a set of interpolation points, which provide an elementary surrogate model that can be used to approximate future data from little information. The algorithm is also very suitable for parallelization and out-of-core computation (processing of data too large for the computer RAM) and very easy to apprehend and implement.This method enables us to both efficiently compress cross-sections and spare a large fraction of the required lattice calculations. We investigate its performance on large realistic nuclear data replicating the notorious VERA benchmark (Godfrey, 2014) (20 energy groups, pin-by-pin homogenization, 10 particularized isotopes). Compression loss, memory savings and speed are analyzed both from a data-centric point of view in the perspective of applications in neutronics, and by comparison with an existing and widely-used method – stochastic truncated SVD – to assess mathematical efficiency. We discuss the usage of our surrogate model and its sensitivity to the choice of the training set. The method is shown to be competitive in terms of accuracy and speed, provide important memory savings and spare a large amount of physics code computation; all this could facilitate the adoption of fine-grain modelization schemes (pin-by-pin and many-groups homogenization, particularization of many isotopes) in industrial setups. A Github repository is available,11Link: https://github.com/Otruffinet/EIM_surrogates.git. which contains all the methods used for the article.

Amazon customer service: Big data analytics

“Amazon Big Data”, conducts a thorough analysis on the e-commerce industry using big data and how certain trends can affect the functioning of the organizations delving in the field. With the growth of e-commerce, there has been a significant rise of the online consumers’ footprint. Companies such as Amazon, Flipkart and other e-commercial platforms have accrued huge chunks of consumer information, especially since the start of the pandemic. In this industry, reviews and ratings given to a product play a crucial role in determining the sentiments of the customers associated towards making the final purchase. Such factors account for the brand’s sales and image. In today’s landscape, a careful customer goes through the ratings of the product, its reviews which serve as a medium of screening. In a tie between two similar products, customers purchase a product with higher ratings and better reviews. Therefore, this leads us to the development of an ideal rating metric that is significant for the sales of the product. Moreover, become a tool for product differentiation. This manuscript is a method to standardize the ratings of customers and preserve the sanctity of the data. We discuss models which are an amalgamation of customer ratings, their respective reviews and a sentiment scored derived from the same review. These models also help us define customer clusters with different personalities based on their reviews and ratings. In addition to this, customer segmentation is a future scope to deep dive into the sales data and understand the financial behavior of a customer.

Entropic Statistics: Concept, Estimation, and Application in Machine Learning and Knowledge Extraction

The demands for machine learning and knowledge extraction methods have been booming due to the unprecedented surge in data volume and data quality. Nevertheless, challenges arise amid the emerging data complexity as significant chunks of information and knowledge lie within the non-ordinal realm of data. To address the challenges, researchers developed considerable machine learning and knowledge extraction methods regarding various domain-specific challenges. To characterize and extract information from non-ordinal data, all the developed methods pointed to the subject of Information Theory, established following Shannon’s landmark paper in 1948. This article reviews recent developments in entropic statistics, including estimation of Shannon’s entropy and its functionals (such as mutual information and Kullback–Leibler divergence), concepts of entropic basis, generalized Shannon’s entropy (and its functionals), and their estimations and potential applications in machine learning and knowledge extraction. With the knowledge of recent development in entropic statistics, researchers can customize existing machine learning and knowledge extraction methods for better performance or develop new approaches to address emerging domain-specific challenges.

Construction Information Management: Benefits to the Construction Industry

This paper aimed to unveil the outcome of an appraisal of the systematic approach to construction information management. This was performed with a view of creating awareness of how information management can be beneficial through the management of the large chunk of information emanating from construction processes. This will improve the gathering, sharing, and storage of information for construction activities. The study implemented a quantitative survey approach with the aid of a questionnaire as the mechanism for data gathering from architects, civil engineers, quantity surveyors, mechanical and electrical engineers, construction managers, and project managers. Data analysis ensued with the aid of SPSS in which applicable measure of dispersal and inferential statistics were implemented. The study unveiled that information management is a major aspect of the construction procedure, and that, to achieve in construction, there must be a well-structured information system. Further findings revealed that the benefits of information management include the firm’s growth, organizational performance, enhanced market value, employee’s motivation, and quality service. The prowess of this study depends on the appraisal of the benefits of systematic management of construction information and how identification of the benefits can help to motivate construction companies.

Analysis of Computer Network Security Storage System Based on Cloud Computing Environment

A fundamental component of cloud computers from a business perspective is that users are allowed to use any desire and pay with a product that desire. Its cloud services were accessible anytime and anywhere consumers needed them. As a result, consumers are free to purchase whatever IT services they want, and they don't have to worry about how easy things can be managed. The remote server is used in a new information storage computing architecture that is considered an Internet generation. Ensuring security, material at resource providers' sites is a challenge that must be addressed in cloud technology. Thus, rather than reliance on a single provider for knowledge storing, this research implies developing construction for protection of knowledge stockpiling with a variation of operations, in which knowledge is scrambled and divided into numerous cipher frames and distributed across a large number of provider places. This support was applied to provide greater security, scalability, or reliability that was suggested according to the new structure. This paper, presented an encoded model for the cloud environment to improve security. The proposed model comprises the parity metadata for the database management provision to the provider. In the developed encoder chunks parity is not stored within the single resources with the provision of the available information chunks. The constructed security architecture in the RAID layer increases the dependability of the data with the deployment of the RAID 10 deployment. The developed RAID-based encoder chunks exhibit improved efficiency for the higher uptime at a minimal cost.

Unsourced Massive Random Access Scheme Exploiting Reed-Muller Sequences

The challenge in massive Machine Type Communication (mMTC) is to support reliable and instant access for an enormous number of machine-type devices (MTDs). In some particular applications of mMTC, the access point (AP) only has to know the messages received, but not where they source from, thus giving rise to the concept of unsourced random access (URA). In this paper, we propose a novel URA scheme exploiting the elegant properties of Reed-Muller (RM) sequences. Specifically, after dividing the message of an active user into several information chunks, RM sequences are used to carry those chunks, for exploiting the vast sequence space to improve the spectral efficiency, and their nested structure to enable reliable and efficient sequence detection. Next, we further explore a novel structural property of RM sequences for designing sparse patterns which carry part of the information and serve as the hints of coupling the information chunks of a single user. The factors affecting the performance of our slot-based RM detection are characterized. Besides, the complexity of the proposed message stitching method is analyzed and compared to the commonly used tree coding approach. Our simulation results verify the enhanced performance of the proposed URA scheme in error probability and computational complexity compared to the existing counterpart.

Eye movements during text reading align with the rate of speech production.

Across languages, the speech signal is characterized by a predominant modulation of the amplitude spectrum between about 4.3 and 5.5 Hz, reflecting the production and processing of linguistic information chunks (syllables and words) every ~200 ms. Interestingly, ~200 ms is also the typical duration of eye fixations during reading. Prompted by this observation, we demonstrate that German readers sample written text at ~5 Hz. A subsequent meta-analysis of 142 studies from 14 languages replicates this result and shows that sampling frequencies vary across languages between 3.9 Hz and 5.2 Hz. This variation systematically depends on the complexity of the writing systems (character-based versus alphabetic systems and orthographic transparency). Finally, we empirically demonstrate a positive correlation between speech spectrum and eye movement sampling in low-skilled non-native readers, with tentative evidence from post hoc analysis suggesting the same relationship in low-skilled native readers. On the basis of this convergent evidence, we propose that during reading, our brain's linguistic processing systems imprint a preferred processing rate-that is, the rate of spoken language production and perception-onto the oculomotor system.

Improvements in Multi-Document Abstractive Summarization using Multi Sentence Compression with Word Graph and Node Alignment

The present work proposes a scheme for multi-document abstractive text summarization using node-aligned Word Graph based representation of clustered sentences. In the first step, the proposed scheme uses SBERT embedding for representing the sentences as fixed-size vectors. The sentences belonging to the same cluster are then represented using Word Graph, in which words of different sentences are aligned based on their semantic and syntactic similarities. The advantage of the above representation is that it utilizes alignment information of words between pairs of similar sentences to merge nodes in the Word Graph, and thereby facilitating the generation of sentences with multiple chunks of information. A sentence scoring function assisted by an intensification function is used to measure the grammaticality and informativeness of the generated sentences. Integer Linear Programming has been used to make the final selection of the scored sentences for generating the abstract. Experiments conducted for the task of sentence fusion and multi-document summarization demonstrate superior performance in comparison with the state-of-the-art techniques available in the literature.

Signature Text,Image and Audio Hiding in a Color Image using Steganography and Cryptography

Data Transmission in network security is one of the foremost vital issues in today’s communication world. the end result of that’s that Data security has gained utmost importance because of the unprecedented increase within the data generated over the web, which could be a basic necessity of any application in information technology. The vigorous growth within the field of data communication has made information transmission much easier. But this kind of advancement has opened many possibilities of data being snooped. So, day-by-day maintaining of data security is becoming an inseparable part of computing and communication. In this report, we’ve got explored techniques that blend cryptography and steganography together. Steganography may be a specialty of science to manage and conceal a chunk of important information inside image, audio, video, or text documents. Steganography may be a method and study of composing a secret communication specified only the source and also the targeted beneficiary will realize the concealed information. the information concealed or covered process starts with the steganography method by identifying a network canopy and redundant parts, i.e. only permitted persons would be able to change without affecting the standard of that medium. The encoding method generates a Stego medium by substituting these redundant bits with the concealed message content. In this report, various approaches for information hiding using both cryptography and steganography is proposed keeping in mind two considerations-size of the encrypted object and degree of security. Here, signature image, text, audio information is kept hidden into a cover image using the private key of sender and receiver, which extracts the data from stego image employing a public key. This approach is often used for message authentication, message integrity, and non-repudiation purpose.

THE CORRELATION BETWEEN LANGUAGE AND REALITY

The correlation between language and reality is investigated in this article. The question whether language shapes the way we think or it is the reality which defines what we say is highly disputable. Any language is a complex structure of vocabulary and grammar which serves as the main means of communication, and with the help of which people can render their thoughts, achieve their goals, or simply socialize. The influence of language on our way of thinking can be observed on the example of the process of word formation in different languages or the usage of specific words, which describe phenomena common to this or that culture. However, at the same time, the reality influences lexicon as well and plays a significant role in building a culture. Moreover, grammatical categories of time and gender, which differ from language to language, may also affect the way people perceive the world. As for the category of gender, it may restrict human beings in the choice of adjectives they attribute to different entities, depending on the word being masculine or feminine. Meanwhile, the very essence of time vary from language to language, depending on it, speakers may give prominence to different chunks of information expressed in a sentence. To achieve these not only grammatical structures but also certain words may be used. Due to the differences in world images that speakers of different languages have, some cultural misunderstanding may arise. It has to be mentioned that a culture is a combination of values, moral principles, customers and traditions of a nation which are reflected in its language. Moreover, great emphasis was put on the process of acquiring a new language which has the power to alter human perception of the universe. Therefore, learning a foreign language a person as well studies its culture and begins to see the world from a different perspective. Thus, language has an impact on the human perception of the world, but at the same time, the reality has an influence on what we say.

Identification and conceptualization of procedural chunks in chess

When it comes to cognitive architecture and human information processing, chunks are one of the best known and most recognized constructs. Nevertheless, the nature of chunks is still very elusive, especially when it comes to chunks in procedural knowledge. This study deals with basic features of procedural information processing and examines the manifestation of chunks in procedural knowledge. The participants' task was to reconstruct sequences of chess moves. Chess was chosen as an experimental domain, because of its complexity, well-defined rules and standardized measure of chess player strength. From the results we conclude that short-term memory capacity is determined by the combination of the size and amount of procedural chunks recalled to the short-term memory. We have shown that on average, participants with more specialized knowledge operated faster and with larger chunks of procedural information than participants with less specialized knowledge. We have shown that in procedural information processing, the level of expertise and the sorting order of the retrieved information are important factors that influence the amount of procedural chunks retained in the short-term memory. Therefore, the capacity of short-term memory in complex situations cannot be expressed as a simple concept.

MEDIA EXAGGERATION AND INFORMATION CREDIBILITY: QUALITATIVE ANALYSIS OF FEAR GENERATION FOR COVID- 19 USING NVIVO

Present world is information-driven. News, information, facts, figures, data are the few terms which are pedalling the wheels of the present life and human being too. The digitalisation has transformed the media in different ways. Apart from the traditional media platforms like radio, newspaper, magazines, and television, the new and speedy news delivery platforms has made the information accessible in a few seconds. The online platform like Instagram, Twitter, Facebook, WhatsApp, and various other social media, has transformed the people behaviour and expectations. Now the information can be accessed, obtained anytime and anywhere. Media has played a tremendous part in Covid times too. It has helped to spread the information about this deadly infectious very quickly. Almost every media platform is bombarded with ample information regarding Covid updates like new cases, deaths, number of tests conducted, recovery rates, precautions to be followed, etc. People tend to believe every piece of information coming their way. It has been difficult to differentiate that which chunk of information is to be trusted and which is fake. This paper has presented the respondents' sentiment regarding the information which they have come across Covid times. The qualitative analysis has been conducted using NVIVO 12 to extract the respondents' viewpoint about the exaggeration of media on coronavirus disease.

Reading the Future from Body Movements –Anticipation in Handball

In speed-based sports that require fast reactions, the most accurate predictions are made once the players have seen the ball trajectory. However, waiting for the ball trajectory does not leave enough time for appropriate reactions. Expert athletes use kinematic information which they extract from the opponent’s movements to anticipate the ball trajectory. Temporal occlusion, where only a part of the full movement sequence is presented, has often been used to research anticipation in sports. Unlike many previous studies, we chose occlusion points in video-stimuli of penalty shooting in handball based on the domain-specific analysis of movement sequences. Instead of relying on randomly chosen occlusion points, each time point in our study revealed a specific chunk of information about the direction of the ball. The multivariate analysis showed that handball goalkeepers were not only more accurate and faster than novices overall when predicting where the ball will end up, but that experts and novices also made their decisions based on different kinds of movement sequences. These findings underline the importance of kinematic knowledge for anticipation, but they also demonstrate the significance of carefully chosen occlusion points.