Aspects Of Information Research Articles

Intelligent Logistics Warehousing Strategy Based on 5G Network and Cloud Computing in the Era of Big Data

ABSTRACTBased on the resource base of “cloud computing,” a super big data storage center was built to exchange data between companies, units, departments and businesses, management, customers and personnel, so as to ensure the timely and accurate reception of all aspects of information. Using radio frequency identification technology, barcode technology, GPS/GIS (Global Positioning System/Geographic Information System) technology, mobile communication technology, and 5G (5th Generation Mobile Communication Technology) network technology, a new business model was realized. At the same time, SOA (Service Oriented Architecture) structure was adopted to combine decentralized business and SOA architecture in the form of loose coupling, and dynamic binding was adopted to realize dynamic access of cloud logistics warehousing platform. Massive data were collected, analyzed, and preprocessed through big data technology and logistics facilities. Real‐time data transmission was realized through 5G network. At the same time, scene acquisition, modeling, analysis, control, feedback, and other technologies were applied to the logistics system to realize the intellectualization of logistics warehousing services. The receiving and sending business process of B2C (Business‐to‐Consumer) e‐commerce enterprises based on “cloud logistics warehousing” is to take the terminal shipper as the seller and the terminal consignee as the buyer. By integrating the information of all links in the logistics process into the “cloud” platform, various stakeholders can conduct information, capital, and other transactions on this platform, thus ensuring the quality of customer logistics services. The advantage of recognized logistics cloud warehouse is that its application value accounts for 43.1%. The scheme proposed in this paper can shorten the storage time of the warehouse, thus speeding up the operation of the warehouse; it can ensure the quality of each link, thus reducing the operating costs of the warehouse; it can increase the use space of the warehouse and save the manpower of the warehouse; it can improve the operation efficiency of the warehouse, thus improving the economic benefits.

Pain and psychological integration

ABSTRACT The scientific investigation of pain faces many challenges. I argue that one of the central challenges posed by pain – its inherent complexity and supposed idiosyncrasy – is best understood as an instance of a more general issue in the mind sciences: the problem of psychological integration. This label is not yet an explanation or account of the underlying challenge, but rather a more precise, empirically tractable formulation of the worry as it arises in multiple domains. In this paper I first lay out a more substantive account of psychological integration, focusing on both the informational and regulative aspects of psychological coordination and control, and then apply this conception to the peripheral and central elements of sensory pain processing.

Can encryption save lives? Secure messaging and its infrastructure as loci of convergence between cyber warfare and conventional warfare: The case of Ukraine

The controversies surrounding the right to privacy of individuals in a hyperconnected world are longstanding debates, where particular emphasis is placed on encryption technologies, which encode information by converting its original representations into alternative forms that computers cannot decipher, thus ensuring the security of communications. These technologies are at the heart of a public controversy, in which privacy advocates a clash with claims that encryption is a threat to general security as an enabler of subversive action. Recent developments in the armed conflict in Ukraine open up or renew questions such as: in times of war, what is the role of encryption and privacy technologies? How does armed conflict challenge existing threat models, what are the new risks for civil society? Can encryption save lives? This article addresses these questions by showing that encrypted messaging is the subject of convergence between the informational and physical aspects ‘in the field’ of war in the 21st century. The aim is to show how these messaging tools and the digital ecosystem that makes their deployment possible (interfaces, access providers, telecom operators) are now an integral part of a war and resistance infrastructure where the borders between cyber warfare and conventional warfare are becoming more and more blurred. However, we will also underline the limits of a tool-centred approach and demonstrate how, in the case of the war in Ukraine, physical threats to civilians and infrastructure damage mean that encrypted messaging is one among several innovative technical and social practices of holistic self-defence deployed by Ukrainians.

Pengaruh Memory Training Permainan Anagram terhadap Kognitif Lansia di Panti Jompo Sumber, Surakarta

Background: One of the problems experienced by the elderly is experiencing a decrease in cognitive abilities such as difficulty remembering, retrieving new information, focusing, making decisions and various aspects such as orientation, visual spatial, memory and language. The problem of cognitive decline will develop into dementia and will affect functional abilities and reduce the quality of life of the elderly. Prevention of cognitive decline in the elderly can be done with cognitive interventions in the form of memory training anagram games. Objectives: This study aims to determine the effect of anagram game memory training on cognitive abilities in the elderly. Methods: This study used a pre-experimental one group pre-test and post-test method with a total sample of 42 elderly people at Aisyiyah Sumber Solo Nursing Home. The research instrument used the Indonesian version of the Montreal Cogntive Assessment (MoCA-Ina). Three stages of the anagram game were given each intervention based on the research module that had been prepared. The data analysis method uses paired t-test with the previous stage, namely data normality test with Shapiro Wilk. Results: The paired t-test results showed that the sig value was <0.05. An increase in moCA-Ina scores occurred after being given anagram game memory training intervention (mean difference 2.48). Memory training of anagram games affects the cognitive abilities of the elderly at Aisyiyah Sumber Solo Nursing Home (????=0.000). The research sample was entirely female, 76.2% dominated by the early elderly age group, 90.5% low-level education. Conclusion: This study shows that memory training intervention in the form of anagram games has a significant effect on the cognitive abilities of the elderly. Keywords: Dementia, Memory, MoCA-Ina, Cognitive games

Проблема дуального характеру логіки (історико-логічний екскурс)

This paper argued that interpreting logic solely as a formal discipline is unjustified, as this science has always included a significant informal component related to its application in argumentative discourse. The Aristotelian paradigm, based on the subject-predicate approach to the logical-philosophical analysis of language, has influenced the history of logic significantly. The functional analysis of language introduced by Gottlob Frege marked a shift to the modern logical paradigm. This led to the rise of symbolic logic, disrupting the established balance between the formal and informal components of logical knowledge for a time. The application of the latest analytical methods in informal logic has enabled research in this field to meet contemporary scientific standards. This development helps restore the balance between the formal and informal aspects of general logic.

Data Processing of Used Car Export Service Flow Based on Zookeeper + Kafka

The used car export industry has shown a trend of rapid growth in recent years. The export of used cars involves data pertaining to vehicle information, market demand, logistics, customs, and numerous other aspects. These data are constantly generated in the form of streams, posing challenges to the data processing capabilities of service platforms. Traditional data processing methods struggle to meet the requirements of real-time and large-scale data processing, thus necessitating an efficient streaming data processing architecture. Based on this, this paper proposes a streaming data processing scheme for a used car export service platform utilizing Zookeeper and Kafka. It describes the architecture design and data processing flow, analyzes the advantages of the scheme in terms of reliability, scalability, and real-time performance, and demonstrates its effectiveness through experiments and case studies.

Framing in media and communication studies: A bibliometric analysis

This paper presents a comprehensive bibliometric analysis of framing and frame theory in media and communication studies, utilizing Web of Science (WOS) data from 2014 to 2023. Framing, as a critical concept in media discourse, shapes public perception by highlighting specific aspects of information while downplaying others. Despite its central role in political communication, news framing, and social media research, there is a notable gap in better incorporating linguistic perspectives, particularly metaphor framing, within the existing literature. Using VOSviewer, this study analyzes co-occurrence networks and thematic clusters to map the evolving landscape of framing research. The results reveal key areas of focus, including political communication, science communication, and identity politics on social media platforms, while also highlighting the underrepresentation of linguistic approaches. This analysis not only identifies influential authors and institutions but also underscores the need for further integrating cognitive linguistic theories, such as metaphor framing, to deepen our understanding of how media discourse constructs reality. The paper concludes by suggesting directions for future research, calling for more interdisciplinary studies to explore the complex mechanisms underlying media framing.

A step-by-step definition of a reference architecture for cyber ranges

Being on the advent of Industry 5.0, organizations have been progressively incorporating information technology into their formerly air-gapped operational technology architectures. This coalescence has nevertheless amplified the attack surface, ringing the bells of preparedness. In this direction, Cyber Ranges (CRs) have cropped up as a valuable and attractive solution, providing a diverse perspective on reinforcing the overall cybersecurity stance. However, there exists a significant literature gap in attempts to define a complete approach for CR design, development, evaluation, and operation as per the up-to-date guidelines. To address this shortcoming, this work introduces the first to our knowledge overarching, fine-grained reference architecture for CR. This is done by adopting a three-step, systematic methodology. First, we scrutinize contemporary guidelines to extract an abstract architectural model that structurally entrenches the foundations of CR reference architecture. Then, we percolate and pinpoint common functionalities and capabilities of existing CRs, towards delineating the functional and informational aspects of the reference architecture. Finally, we devise an evaluation formula that approximates the conformance of a CR with the state-of-the-art. Through the latter step, we impart a unified means of identifying the most appropriate components to implement the structural, functional, and informational aspects of a CR. Overall, this work can be seen as an attempt towards CR unification and standardization, therefore it is anticipated to serve as a basis and point of reference for multiple stakeholders at varying levels.

Мирон Пилипович Деркач (1931–2012). Той, що почав розмовляти з комп’ютером…

Myron Derkach is a world-class scientist in the field of biophysics and informational aspects of speech communication – analysis, synthesis and recognition of speech signals. He is the founder of the scientific direction, who formulated the principles of the deductive strategy of auditory language perception. In 1976, he created one of the first biophysics departments in Ukraine on the basis of the biological faculty of Ivan Franko University of Lviv. Dr. Myron Derkach is the author of the first university textbooks in Ukrainian on biophysics and mathematical methods in biology, which have not lost their relevance to this day.

Crime Type Identification Using High-Order Deep Residual Network with Multiple Attention Algorithm

ABSTRACT Crime type identification is crucial for improving public safety through more accurate prevention and efficient responses. However, practical applications often suffer from a significant lack of effective samples features, making it difficult to focus on the most informative aspects during identification. This study addresses these challenges by proposing a novel crime type identification method that leverages a deep neural network enhanced with multiple attention mechanisms. The approach includes a tailored data processing method involving target encoding to convert categorical data into numerical form, L 2 normalizer to standardize data and ensure balanced feature contribution, and variance threshold feature selection to remove low-variance features. Additionally, a High-Order Deep Residual Network with Multiple Attention (HO-ResNet-MA) is developed, featuring an optimized Huta68 block (Huta-6(8)-MA ResBlock) with an enhanced Contextual Transformer (CoT) unit for local attention and a queue-and-exclusion layer for global attention. To validate the effectiveness of the proposed method, homicide reports data and Chicago crimes data are processed and fed into the crime type identification model, resulting in accuracies of over 84.1% and 99.5%, respectively. This study makes contributions to the field of crime analysis by validating the practical applicability of these approaches, and enhancing the efficiency of public safety workers.

RF sensing enabled tracking of human facial expressions using machine learning algorithms

Automatic analysis of facial expressions has emerged as a prominent research area in the past decade. Facial expressions serve as crucial indicators for understanding human behavior, enabling the identification and assessment of positive and negative emotions. Moreover, facial expressions provide insights into various aspects of mental activities, social connections, and physiological information. Currently, most facial expression detection systems rely on cameras and wearable devices. However, these methods have drawbacks, including privacy concerns, issues with poor lighting and line of sight blockage, difficulties in training with longer video sequences, computational complexities, and disruptions to daily routines. To address these challenges, this study proposes a novel and privacy-preserving human behavior recognition system that utilizes Frequency Modulated Continuous Wave (FMCW) radar combined with Machine Learning (ML) techniques for classifying facial expressions. Specifically, the study focuses on five common facial expressions: Happy, Sad, Fear, Surprise, and Neutral. The recorded data is obtained in the form of a Micro-Doppler signal, and state-of-the-art ML models such as Super Learner, Linear Discriminant Analysis, Random Forest, K-Nearest Neighbor, Long Short-Term Memory, and Logistic Regression are employed to extract relevant features. These extracted features from the radar data are then fed into ML models for classification. The results show a highly promising classification accuracy of 91%. The future applications of the proposed work will lead to advancements in technology, healthcare, security, and communication, thereby improving overall human well-being and societal functioning.

Teachers' beliefs about the relevance of the mathematic curriculum given emerging societal crises and knowledge demands

In an era inundated with statistical and mathematical information through various media channels, members of the public must grasp these concepts if they are to understand global developments like public health crises and climate change. In this study, we explored teachers' beliefs about the relevance of the curriculum in the context of the COVID pandemic and sought to identify, from their perspectives, the changes needed to improve its relevance. We had 56 teachers participate in an online survey, eight of whom were also interviewed later. Our findings revealed that participants believed the curriculum helped prepare learners to understand certain aspects of the pandemic-related information. However, they noted that the information was more complex than mere mathematical calculations might be, so required a careful coordination of appropriate mathematical and contextual relationships. Many teachers suggested changes focused on providing more opportunities for learners to engage with real-life applications of mathematics. There were variations in teachers' perspectives on curriculum content, with some emphasizing the importance of broader cognitive processes while others focused on specific topics. These differences were influenced by factors such as teaching experience, educational background, and teaching phase.

TCellR2Vec: efficient feature selection for TCR sequences for cancer classification.

Cancer remains one of the leading causes of death globally. New immunotherapies that harness the patient's immune system to fight cancer show promise, but their development requires analyzing the diversity of immune cells called T-cells. T-cells have receptors that recognize and bind to cancer cells. Sequencing these T-cell receptors allows to provide insights into their immune response, but extracting useful information is challenging. In this study, we propose a new computational method, TCellR2Vec, to select key features from T-cell receptor sequences for classifying different cancer types. We extracted features like amino acid composition, charge, and diversity measures and combined them with other sequence embedding techniques. For our experiments, we used a dataset of over 50,000 T-cell receptor sequences from five cancer types, which showed that TCellR2Vec improved classification accuracy and efficiency over baseline methods. These results demonstrate TCellR2Vec's ability to capture informative aspects of complex T-cell receptor sequences. By improving computational analysis of the immune response, TCellR2Vec could aid the development of personalized immunotherapies tailored to each patient's T-cells. This has important implications for creating more effective cancer treatments based on the individual's immune system.

The open effective field theory of inflation

In our quest to understand the generation of cosmological perturbations, we face two serious obstacles: we do not have direct information about the environment experienced by primordial perturbations during inflation, and our observables are practically limited to correlators of massless fields, heavier fields and derivatives decaying exponentially in the number of e-foldings. The flexible and general framework of open systems has been developed precisely to face similar challenges. Building on previous work, we develop a Schwinger-Keldysh path integral description for an open effective field theory of inflation, describing the possibly dissipative and non-unitary evolution of the Goldstone boson of time translations interacting with an unspecified environment, under the key assumption of locality in space and time. Working in the decoupling limit, we study the linear and interacting theory in de Sitter and derive predictions for the power spectrum and bispectrum that depend on a finite number of effective couplings organised in a derivative expansion. The smoking gun of interactions with the environment is an enhanced but finite bispectrum close to the folded kinematical limit. We demonstrate the generality of our approach by matching our open effective theory to an explicit model. Our construction provides a standard model to simultaneously study phenomenological predictions as well as quantum information aspects of the inflationary dynamics.

Generación renovable eólica y fotovoltaica en Ecuador: Una revisión sistemática de literatura

INTRODUCTION. Photovoltaic and wind renewable generation has grown exponentially in recent years worldwide, in Ecuador this technology has not been the exception, as several photovoltaic and wind power plants have been installed, increasing the generation of renewable energy. OBJECTIVE. This article presents a systematic review of the literature on operational photovoltaic and wind power plants in Ecuador, offering a perspective on the renewable sources connected to the national energy system. METHOD. Through a bibliographic search in the Scopus database, 8 publications were obtained that met the eligibility criteria, in addition to reports issued by government entities, to ensure that the information and technical aspects are accurate. RESULTS. The documentary analysis allows us to know the current status of photovoltaic and wind power plants, identifying their installed capacity, technology used, and operational characteristics. DISCUSSION AND CONCLUSIONS. The information collected provides a solid basis for understanding the current status and development prospects of photovoltaic and wind power generation in Ecuador. Despite certain limitations related to the availability of data in open sources, it was possible to obtain significant information on the main renewable plants in the country. These results serve as a basis for future research aimed at the expansion and optimization of renewable energies in the national context..

Understanding the Importance of Email Etiquette and Addressing Email Communication Challenges Among BTVI Students

Email serves as a communication channel for students in higher educational institutions to interact with teachers on course materials, assignments, and impending tests and seek guidance on personal or academic concerns. The present research examines student-instructor email communication, explicitly identifying the problematic elements in students' emails that hinder effective communication. The study examines a sample of 50 email communications composed and sent by first-year students to their instructors at Bright Technical and Vocational Institute (BTVI) in Kurdistan. Textual analysis is a valuable method for investigating research inquiries across several disciplines. The study findings demonstrated that informal aspects of student email exchanges include the usage of slang, overuse of capitalization, unconventional spelling, symbols, and emoticons. Lack of adherence to email etiquette norms and grammatical errors. These elements indicate a need for more understanding of formality, professionalism, and the decorum expected in a university atmosphere. Thus, it is advisable to implement pedagogical intervention to develop the necessary abilities for composing and comprehending emails. Providing education and assistance on the protocols and norms of email communication may enhance students' capacity to effectively and professionally interact via email in (BTVI), hence fostering good practices and increasing future employment prospects.

A socially interactive communication skills training for competent health educators

Abstract Background Every contact with expectant and new parents can be a “teachable moment” for promoting the health of mother-baby-family; yet, healthcare providers may not effectively perform their educational role. Previous studies have described various setting-specific challenges. Procedural knowledge, resulting in lack of confidence and avoidance, is a universal theme, challenging current communications skills training. Given the evolving role of midwives under the new Cyprus National Healthcare System, there is need for innovative practices. Objectives “Baby Buddy Communicators” designed, implemented and piloted tested a socially interactive digital environment on the Edubreak platform, where practicing (N = 8) and in-training (N = 7) Midwives completed an 8-week iterative hybrid communication skills course along with service-users. Results Four situational-based scenarios were co-created with ‘holders of the experience’ tapping on key priorities (elective caesarean, breastfeeding challenges, baby in NICU, postnatal depression). Participants produced video artefacts of role-play consultations and engaged in peer-to-peer and service-user feedback via the in-built video annotations and blog writing tools. Deductive content analysis of the rich material using the 18-item Health Professionals Communications Skills (HPCS) scale identified recurrent patterns tapping on both informational aspects (e.g. incomplete information gathering, overload without assessing comprehension) as well as social skills (e.g. agenda setting, early reassurance, assertiveness). Conclusions This cross-sectoral transfer of social video from sports training to healthcare is a “proof of concept”. Inverted (i.e. making current practices visible) and experiential learning (e.g. feedforward) with cross-sectoral (service-user involvement) and cross-module dimensions (i.e. communication skills and evidence-based practice) provided the basis for evaluation and a source of shared learning and reflection. Key messages • Several areas of improvement in communication skills of maternal healthcare providers were identified while peer-to-peer and service-user feedback was a source of reflection. • The use of digital technology and social video allowed immersive role-playing, observation and constructive feedback loops providing a new paradigm in health communication skills training.

DuINet: A dual-branch network with information exchange and perceptual loss for enhanced image denoising

Image denoising is a fundamental task in image processing and low-level computer vision, often necessitating a delicate balance between noise removal and the preservation of fine details. In recent years, deep learning approaches, particularly those utilizing various neural network architectures, have shown significant promise in addressing this challenge. In this study, we propose DuINet, a novel dual-branch network specifically designed to capture complementary aspects of image information. DuINet integrates an information exchange module that facilitates effective feature sharing between the branches, and it incorporates a perceptual loss function aimed at enhancing the visual quality of the denoised images. Extensive experimental results demonstrate that DuINet surpasses existing dual-branch models and several state-of-the-art convolutional neural network (CNN)-based methods, particularly under conditions of severe noise where preserving fine details and textures is critical. Moreover, DuINet maintains competitive performance in terms of the LPIPS index when compared to deeper or larger networks such as Restormer and MIRNet, underscoring its ability to deliver high visual quality in denoised images.

Culinary medicine in type 2 diabetes management: co-designing the Cook2DIAbeat training program

Abstract Background Type 2 diabetes (hereinafter diabetes) stands among the top ten drivers of disease burden. Globally, more than 59 million adults are living with diabetes with a projection of 15% increase by 2045. The Cook2DIAbeat project aims to develop a tailor-made nutrition training program based on culinary medicine, for patients with diabetes to achieve lifelong dietary changes. The aim of the present work was to reveal potential drivers and barriers related to lifelong dietary modifications. Methods The study was implemented in February-July 2023 in Spain, Belgium, Greece, and Cyprus. A mixed-method co-design methodology was conducted: co-creation sessions with individuals with diabetes, family members, and healthcare professionals, and an online survey with patients with diabetes. Results In total, 23 health professionals and 25 patients and family members participated in the co-creation sessions, and 212 patients in the online survey. Patients and health professionals recognized the added value of the culinary approach for diabetes management. The main perceived barriers for changing dietary habits included difficulties accessing reliable and non-conflicting information, lack of time, emotional and psychological issues, and limited social support. Individuals at an advanced age and of low socioeconomic status seem to demand specific educational approaches addressing the actual challenges of their daily life. Conclusions The study indicated that training should provide reliable information and address psychosocial aspects. The translation of the dietary guidelines through the culinary medicine approach seems to be well-received by the target group. Last, the content needs to be tailored to suit the specific age group and socioeconomic background of the patients. Key messages • Reliability, practicability are three key characteristics of a nutrition training program in diabetes management. • Cultural and socioeconomic barriers needs to be taken into consideration.

The problem of knowing future phenomena

The paper is devoted to the problem of epistemic conditions of cognition of future phenomena.The problem is that the cognizable aspects of information are based on the evolutionary mechanisms of adaptation of the body, which are reduced in humans, and on the rational principles of human cognition, which are mixed with irrational prophecies. The solution is to separate the heuristic possibilities of theory from empirical guesses and consider the structures of theoretical knowledge that process information about possible and impossible facts.The aim of the paper is to discover a mental act directed at the future, which cannot be reduced to extrapolating the past and varying alternatives. The conditions of the possibility of knowing about the reality of the future as a mode of time, and the idea of a specific event in the future are split.The following hypothesis is considered: cognition of the future is based on thinking about the possible and necessary relations of an object to an integral system including a subject.The attitude of the mind towards the future is not a cognitive act like receiving information, the source of which is problematic. This is not animal foresight, not divination, not planning. Cognition is understood not as a perception of the objective properties of a phenomenon, but as its construction according to the rules of the organization of consciousness. In general, the future is not knowable, but there are types of phenomena other than the causal concept of cognition that justify information about the future. Theoretical knowledge of the predispositions of a situation involving an object is proactive. The subject of prediction is not only the truth about the future, but also a judgment about what exactly will not happen. This limitation narrows the scope of possible alternatives. The elementary acts of realizing that an event is not yet happening have been investigated by the phenomenology of Buddhism. They are directed at the stages of the same process. The conclusion from content of one temporal interval to content of another interval is based on theoretical constructions that do not have spatiotemporal characteristics. Information about the future is limited by theoretical knowledge of the holistic situation and the properties of the object that arise as a result of its inclusion in this situation.