Information Processing Research Articles

Human-computer interaction interface design of flight simulator based on situation awareness.

To meet the comprehensive requirements of drivers for Human-Computer Interaction (HCI) during operation and to enhance situation awareness (SA), this paper proposes a design and evaluation method for flight simulator HCI interfaces grounded in SA. Firstly, the widely adopted Endsley's SA model, which comprehensively covers processes relevant to individual drivers was selected as the foundational framework. The study concentrates on flight, cruise, and landing scenarios within the simulator, analyzing and restructuring the information architecture of the HCI interface. Secondly, a self-assessment scale was developed based on the three-level model of information processing for SA to measure drivers' SA cognitive levels. The core scenarios of the simulation training were analyzed to establish a design-making process. Thirdly, invite participants were invited to engage in simulated driving sessions on the flight simulator, where their SA cognitive levels were assessed. An analysis of detail features was performed on samples with high SA cognitive levels. Subsequently, drivers' requirements for the control layout features of the HCI interface design were gathered through surveys. The design detail features of the HCI interface associated with high SA cognitive levels were identified and synthesized into four distinct dimensions to guide the detailed design process. Finally, participants engaged in simulated driving using the finalized interface design, and their SA cognitive levels were reassessed. The results demonstrated that the HCI interface design derived from this method significantly improved SA cognitive levels compared to the original design.

Building a valuable professional development course: instructor effort vs. perceived student value of activities in an online biotechnology course

Providing undergraduate and graduate students with the appropriate preparation for transitioning to careers in their field after graduation is a key goal of higher education institutions, with many programs employing professional development workshops or courses to assist students and provide hands-on skills in this area. Although a wide variety of activities could benefit students, instructor and career specialist time is limited. Here, we describe an online biotechnology professional development course for undergraduate and graduate students, covering career exploration and the job search process, and the students’ perceptions of the activities offered based on survey data. Overall response to the course was positive, with students at various stages of their education indicating appreciation of most of the course assignments. Interestingly, students ranked the activities that took the most instructor time, namely review of application materials, mock interviews, and career panels, as the most valuable for their personal development. The career exploration aspects of the course influenced students to be open to new possibilities. However, students struggled to make time to complete the assignments for a fully online, largely asynchronous course. Discussion of the value of the course activities, their relevance to social cognitive career theory and cognitive information processing, and suggestions for smooth implementation are provided.

The Evolution of Data Visualization Tools and Their Impact on Business Decision-Making : A Historical Analysis

This article examines the transformative evolution of data visualization tools and their profound impact on business decision-making processes. Through a comprehensive analysis of historical developments, theoretical frameworks, and technological advancements, the article explores how visualization tools have progressed from basic manual charts to sophisticated AI-powered analytical platforms. The investigation encompasses the cognitive foundations of visual information processing, the emergence of first-generation Business Intelligence tools, and the current landscape of modern visualization platforms. Particular attention is given to the integration of artificial intelligence in data visualization, including automated generation, pattern recognition, and predictive analytics capabilities. The article presents both quantitative and qualitative assessments of these tools' impact on organizational decision-making, highlighting significant improvements in decision speed, accuracy, and user engagement. The article reveal substantial benefits in terms of ROI, decision-making efficiency, and organizational adoption patterns. The article concludes by examining emerging trends, including the potential of extended reality technologies and edge computing, while acknowledging current limitations and providing recommendations for future research directions in this rapidly evolving field.

The Interplay Between Managerial Cognition, Earliness of Internationalization, and Post-internationalization Speed: A Qualitative Study of Experiential and Analytical Information Processing

The Interplay Between Managerial Cognition, Earliness of Internationalization, and Post-internationalization Speed: A Qualitative Study of Experiential and Analytical Information Processing

Learning Languages in the 21st Century: the Digital and Ai Transformation

The article deals with the problem of the learning languages in the 21st century: the digital and AI transformation. The aim of this article is to explore and clarify the transformative impact of digital technologies on foreign language teaching. This article explores the evolution of language learning from classroom-based methods to the incorporation of digital instruments, Artificial Intelligence (AI), and Information and Communication Technologies (ICT). Digital tools such as language learning applications, online dictionaries, multimedia resources, and language exchange platforms have made language acquisition more accessible and engaging. AI technologies introduce intelligent tutoring systems, personalized learning experiences, and advanced language processing capabilities, while ICT tools like Learning Management Systems (LMS) and virtual classrooms facilitate effective communication and information processing. The benefits of these advancements are multifaceted, including increased accessibility and flexibility, enhanced engagement and motivation, personalized learning paths, and improved collaboration and communication. However, challenges such as the digital divide, variability in resource quality, data privacy concerns, and the need for continuous teacher training must be addressed. Looking ahead, future trends such as augmented and virtual reality, blockchain technology, AI-driven content creation, IoT integration, and multimodal learning experiences promise to further transform the landscape of language education. These innovations will pave the way for more immersive and interconnected language learning experiences, contributing to a more multilingual global society.

Analysis of Interconnectedness in Indian Subcontinent Remittances from the Gulf Cooperation Countries

Indian subcontinent is a major remittance receiver. With similar labor market characteristics, their workers go to same host countries. Therefore, their labor is substitutable for each other with high degree of connectedness with direct consequences on remittance inflows. Yet, due to social and political considerations in host countries, substitution may not take place. The issue is an empirical question. We study interactions of remittance inflows into India, Pakistan, Bangladesh and Sri Lanka via frequency connectedness. We find a low degree of spillovers across countries, i.e., dynamics of remittance inflows in each country are largely explained by internal factors, not due to spillovers from other countries. That is, remittance inflows in these countries are essentially independent. We also observe that information processing is faster in the short-run than the long-run indicating that market participants are aware of dynamics in other markets. The findings have policy implications for unemployment and foreign exchange.

Rapid sensorimotor adaptation to auditory midbrain silencing in free-flying bats.

Echolocating bats rely on rapid processing of auditory information to guide moment-to-moment decisions related to echolocation call design and flight path selection. The fidelity of sonar echoes, however, can be disrupted in natural settings due to occlusions, noise, and conspecific jamming signals. Behavioral sensorimotor adaptation to external blocks of relevant cues has been studied extensively, but little is known about adaptations that mitigate internal sensory flow interruption. How do bats modify their sensory-guided behaviors in natural tasks when central auditory processing is interrupted? Here, we induced internal sensory interruptions by reversibly inactivating excitatory neurons in the inferior colliculus (IC) using ligand-activated inhibitory designer receptors exclusively activated by designer drugs (DREADDs). Bats were trained to navigate through one of three open windows in a curtain to obtain a food reward, while their echolocation and flight behaviors were quantified with synchronized ultrasound microphone and stereo video recordings. Under control conditions, bats reliably steered through the open window, only occasionally contacting the curtain edge. Suppressing IC excitatory activity elevated hearing thresholds, disrupted overall performance in the task, increased the frequency of curtain contact, and led to striking compensatory sensorimotor adjustments. DREADDs-treated bats modified flight trajectories to maximize returning echo information and adjusted sonar call design to boost detection of obstacles. Sensorimotor adaptations appeared immediately and did not change over successive trials, suggesting that these behavioral adaptations are mediated through existing neural circuitry. Our findings highlight the remarkable rapid adaptive strategies bats employ to compensate for internal sensory interruptions to effectively navigate their environments.

Functional localization of the human auditory and visual thalamus using a thalamic localizer functional magnetic resonance imaging task

Abstract Functional magnetic resonance imaging (fMRI) of the auditory and visual sensory systems of the human brain is an active area of investigation in the study of human health and disease. The medial geniculate nucleus (MGN) and lateral geniculate nucleus (LGN) are key thalamic nuclei involved in the processing and relay of auditory and visual information, respectively, and are the subject of blood-oxygen-level-dependent (BOLD) fMRI studies of neural activation and functional connectivity in human participants. However, localization of BOLD fMRI signal originating from neural activity in MGN and LGN remains a technical challenge, due, in part, to the poor definition of boundaries of these thalamic nuclei in standard T1-weighted and T2-weighted magnetic resonance imaging sequences. Here, we report the development and evaluation of an auditory and visual sensory thalamic localizer (TL) fMRI task that produces participant-specific functionally-defined regions of interest (fROIs) of both MGN and LGN, using 3 Tesla multiband fMRI and a clustered-sparse temporal acquisition sequence, in less than 16 minutes of scan time. We demonstrate the use of MGN and LGN fROIs obtained from the TL fMRI task in standard resting-state functional connectivity (RSFC) fMRI analyses in the same participants. In RSFC analyses, we validated the specificity of MGN and LGN fROIs for signals obtained from primary auditory and visual cortex, respectively, and benchmarked their performance against alternative atlas- and segmentation-based localization methods. The TL fMRI task and analysis code (written in Presentation and MATLAB, respectively) have been made freely available to the wider research community.

A New Method of Intelligent Fault Diagnosis of Ship Dual-Fuel Engine Based on Instantaneous Rotational Speed

Ship engine misfire faults not only pose a serious threat to the safe operation of ships but may also cause major safety accidents or even lead to ship paralysis, which brings huge economic losses. Most traditional fault diagnosis methods rely on manual experience, with limited feature extraction capability, low diagnostic accuracy, and poor adaptability, which make it difficult to meet the demand for high-precision diagnosis. To this end, a fusion intelligent diagnostic model—ResNet–BiLSTM—is proposed based on a residual neural network (ResNet) and a bidirectional long short-term memory network (BiLSTM). Firstly, a multi-scale decomposition of the instantaneous rotational speed signal of a ship’s engine is carried out by using the continuous wavelet transform (CWT), and features containing misfire fault information are extracted. Subsequently, the extracted features are fed into the ResNet–BiLSTM model for learning. Finally, the intelligent diagnosis of ship dual-fuel engine misfire faults is realized by the classifier. The model combines the advantages of ResNet18 in image feature extraction and the capability of BiLSTM in temporal information processing, which can efficiently capture the time-frequency features and dynamic changes in the fault signal. Through comparison experiments with fusion models AlexNet–BiLSTM, VGG–BiLSTM, and the existing AlexNet–LSTM and VGG–LSTM models, the results show that the ResNet–BiLSTM model outperforms the other models in terms of diagnostic accuracy, robustness, and generalization ability. This model provides an effective new method for intelligent diagnosis of ship dual-fuel engine misfire faults to solve the traditional diagnostic methods’ limitations.

Design and implementation of broadband optical vortices in photonic crystal slabs

We propose and discuss a simple method to generate broadband optical vortices, utilizing the inherent topological vortex structures of polarization around bound states in the continuum supported by a photonic crystal slab in the momentum space to induce the generation of vortex beams. Since the proposed structure is composed of silicon pillars arranged periodically, it lacks a true optical geometric center. It is insensitive to the position of the incident light and does not require a specific optical alignment process compared to traditional spiral phase plates. Furthermore, because it is composed of dielectric pillars, it can achieve vortex beam generation at any desired working wavelength. We also discuss the robustness of its structure, showing that it can be immune to certain manufacturing defects. Therefore, the proposed structure not only provides a new method for manipulating the angular momentum of photons but also has potential new applications in integrated optical information processing and optical tweezers.

PSYCHOLOGICAL READINESS OF SENIOR ADOLESCENTS FOR HIGHER EDUCATION UNDER WARTIME STRESS CONDITIONS

Introduction. Researchers have always paid close attention to an educational problem of the formation and the role of psychological readiness of adolescents and students for studying at higher education institutions. After the start of a large-scale Russian military invasion in February 2022, this aspect has become particularly acute and relevant. The aim of this reveiw article is to examine the role of key subsystems of psychological readiness among students in higher education institutions under the influence of wartime conditions. Materials and methods. Based on professional review articles, this study examines the primary factors shaping a psychological readiness of an individual for higher education. The importance of this work is heightened by the ways in which these processes are significantly altered—and in some cases, become multi-complementary—under the conditions of the Russian military invasion. The study draws on psychological research conducted by leading scientists, focusing primarily on findings from the past five years. Results. The psychological readiness of first-year students for studying at higher education institutions is closely tied to their psychological adaptation to new academic conditions. This readiness is crucial for shaping graduates into professionally skilled specialists equipped to work in relevant sectors of the national economy. Research indicates that developing psychological adaptation of students is not feasible without a foundational intellectual component of psychological readiness established in earlier stages. This foundation promotes students’ creativity, the formation of self-concept („I” concept), and heightened resilience to the challenges of studying in higher education during extreme wartime conditions. Without this structure of psychological readiness, achieving higher education becomes virtually unattainable. The next important component of the system of psychological readiness of adolescents for studying at higher education institutions is personal readiness. This is a rather complex and complementary system of individual knowledge and skills. It solves practical issues of optimizing the receipt and processing of information by a adolescent, as well as readiness to discuss the achieved results with peers, the importance of these processes for the formation of self-awareness of young men and women. The third important component of university students’ psychological readiness is the operating system. First of all, this concerns not only the issues of mastering professional knowledge and technologies, but also the ability to use them in the practical professional activities of students, and later adults. Conclusion. Thus, the psychological readiness of adolescent students significantly enhances their ability to succeed in higher education. It fosters greater adaptability and resilience, particularly under the challenging conditions of wartime, supporting students in navigating their studies more effectively.

Unlocking the potential of photoexcited molecular electron spins for room temperature quantum information processing

Abstract Future information processing technologies like quantum memory devices have the potential to store and transfer quantum states to enable quantum computing and networking. A central consideration in practical applications for such devices is the nature of the light-matter interface which determines the storage state density and efficiency. Here, we employ an organic radical, α,γ-bisdiphenylene-β-phenylallyl doped into an o-terphenyl host to explore the potential for using tuneable and high-performance molecular media in microwave-based quantum applications. We demonstrate that this radical system exhibits millisecond-long spin-lattice relaxation and microsecond-long phase memory times at room temperature, while also having the capability to generate an oscillating spin-polarized state using a co-dissolved photo-activated tetraphenylporphyrin moiety, all enabled by using a viscous liquid host. This latest system builds upon collective wisdom from previous molecules-for-quantum literature by combining careful host matrix selection, with dynamical decoupling, and photoexcited triplet-radical spin polarisation to realise a versatile and robust quantum spin medium.

Heralded pure single-photon sources using nanophotonic waveguides with quadratic and cubic nonlinearities

This paper presents, to our knowledge, a new approach in developing integrated pure heralded single-photon sources based on the interplay between the spontaneous four-wave mixing and sum-frequency generation parametric processes. We introduce a comprehensive quantum model to exploit this interplay in AlGaAs and LiNbO3 nanophotonic waveguides. The developed model is used to assess the performance of the sources based on the photon-pair generation and the associated spectral purity. We find that this approach can remarkably improve the spectral purity of low-pure generated photon pairs, relaxing the restrictions on the structure design and the used pump wavelength. In addition, it overcomes the current hurdles in implementing on-chip photon detectors operating at room temperature, paving the way for advanced applications in integrated quantum photonics and information processing.

Efficiency of International Law Mechanisms for Human Rights Protection in Education

Objectives. The study deals with international law mechanisms for human rights protection in education. The aim of the study is to analyse and evaluate the effectiveness of international law mechanisms for human rights protection in education. Theoretical Framework: The theoretical basis of the research was made up of the scientific works of scientists, quality and qualitative indicators of research, and the regulatory and legal framework. Methods: The research employed the method of comparison, visual graphic methods, a set of methods of processing, comprehension and interpretation of information. Results and Discussion: The study established the most common types of violations in the field of education, in particular: violation of the right of national minorities to education; impossibility of choosing the language of instruction; failure to provide inclusive education; discrimination against people with mental illness. Specific manifestations of the effectiveness of international law mechanisms for the human rights protection in the field of education are singled out, in particular: increasing public awareness and transparency of government activity, etc. Research Implications: The study gave grounds to draw the conclusions regarding the difficulty of proving the existence of violations in education. Attention is drawn to the subjectivity of the European Court of Human Rights (ECHR) and the ambiguous interpretation of norms enshrined in international legal acts. Originality/Value: The research is original, based on official data and the author's own conclusions, and has practical significance.

NEW ASPECTS OF CORE MICROTOMOGRAPHY

Compared to many other technologies of laboratory studies of core samples, the modern «digital core» technology is a rather young scientific and industrial direction, but for decades it has attracted close attention of a wide range of scientists and specialists of the oil and gas industry (geologists, sedimentologists, lithologists, geophysicists, developers, geological modelers, hydrodynamicists, physicists). For many specialists of practical sphere new methodical techniques and methods of such researches remain little known. If earlier computer X-ray microtomographs in the Russian Federation were the prerogative of only academic structures or service organizations, nowadays many subsoil users have started to equip their own laboratory and research centers with the corresponding specialized equipment, understanding that without these data it is hardly possible to build high-quality geological, petrophysical, tectonic-physical, rheological, hydrodynamic and geological-field models of the studied sediments, as well as to prepare progragmatic models of the studied sediments. In this article the authors made an attempt to study and analyze the current state of development of «digital core» technology.Using extensive factual material the accumulated experience of special studies in the field of full-size core tomography is summarized, estimates of absolute permeability of low-permeability complex sediments are made, results of studying cores in frozen and unfrozen state are given, detailed analysis of fracturing at different stages of sample preparation and ongoing studies is carried out, and specific problems for which a solution using the technology is expected in the near future are formulated In this article the positive and negative sides of poroset and direct methods of modeling of filtration properties by digital core model are studied. Particular attention is paid to the need for large-scale studies to obtain statistically reliable data samples, which can be used to select the most qualitative methods of research and application of algorithms for processing of initial geological and geophysical information.

Low power tactile sensory neuron using nanoparticle-based strain sensor and memristor

Endowing strain sensors with neuromorphic computing capabilities could permit the efficient processing of tactile information on the edge. The realization of such functionalities from a simple circuit without software processing holds promise for attaining skin-based perception. Here, leveraging the intrinsic neuronal plasticity of memristive neurons, various firing patterns induced by the applied strain were demonstrated. More specifically, tonic, bursting, transition from tonic to bursting, adaptive, and nociceptive activities were captured. The implementation of these patterns permits the facile translation of the analog pressure signals into digital spikes, attaining accurate perception of various tactile characteristics. The tactile sensory neuron consisting of an RC circuit was composed of a SiO2-based conductive bridge memristor exhibiting leaky integrate-and-fire properties and a Pt nanoparticles (NPs)-based strain sensor with a gauge factor of ∼270. A dense layer of Pt NPs was also used as the bottom electrode for the memristive element, yielding the manifestation of a threshold switching mode with a switching voltage of only ∼350 mV and an exceptional switching ratio of 107. Our work provides valuable insights for developing low power neurons with tactile feedback for prosthetics and robotics applications.

Machine Learning‐Based Wind Classification by Wing Deformation in Biomimetic Flapping Robots: Biomimetic Flexible Structures Improve Wind Sensing

Flying animals such as insects and birds have strain receptors on their wings. The functions and information processing capabilities of these strain receptors, however, are largely unknown. Herein, the potential ability of wing strain sensors to detect wind direction in flapping flight is experimentally explored. Seven strain gauges are attached to the biomimetic wing shafts of flexible wings. The wings flap through an electric mechanism emulating hovering flight in a wind tunnel with gentle wind, and a convolutional neural network model for wind direction classification is developed. The results show that with only one strain gauge, accurate wind classification is achieved using segmented data of ≈1 flapping cycle. Even with segmented data of only 0.2 flapping cycles, wind classification can be achieved with all seven strain gauges. Moreover, the use of wing shafts improves the classification accuracy, especially with shorter segmented data. Additional flapping phase information does not substantially improve classification performance. These results suggest that hovering animals determine the wind direction via strain sensing, which is useful for flight control. The implementation of wing strain sensors in flapping‐wing aerial robots may improve flight control ability.

Television and the Origins of Visual Pattern Recognition AI in Japan: a ‘Quest for a Seeing Machine’

Abstract This article traces the genealogy of contemporary data-driven computer vision to developments at the Japan Broadcasting Corporation (NHK) in the 1960s. Specifically, it examines NHK’s Visual and Auditory Information Science Unit and its role in the invention of the world’s first deep convolutional neural network. The use of television to collect viewer behaviour data enabled modelling of eye-brain information processing, in particular mechanisms of feature extraction. This, in turn, linked Fukushima Kunihiko’s formative work on signal compression to the development of a pattern recognition machine, resulting in the creation of the world’s first convolutional neural network. Recovering this history is important for two reasons. First, it helps counter a trend of ‘digital universalism’ that covertly homogenizes local differences into a single culture of artificial intelligence in the Cold-War-era US. Second, it reveals the largely ignored role of television in the genesis of digital image technologies and AI more broadly.

Perception of pointing gestures in 3D space.

Pointing gestures are often used to refer to distant referents by indicating in which vertical and horizontal direction the referent is located relative to the pointer. In the present manuscript, we address whether and how both dimensions interact when people spatially interpret pointing gestures, or whether both dimensions are processed independently as reflected in many current models. We found that both dimensions interact on different levels. First, cross-dimensional effects were found on a between-gestures level. That is, the perception of the vertical position implied by a pointing gesture depended on horizontal arm and finger orientation. Conversely, the horizontal interpretation depended on vertical arm and finger orientation. Second, we found cross-dimensional interactions on the level of intra-individual biases. That is, participants' horizontal perceptual biases in interpretations (e.g., perceiving a gesture as directed more rightward than others) were related to their vertical perceptual biases. Third, we found cross-dimensional interactions on the level of intra-individual variability. That is, the vertical and horizontal interpretations of the same pointing gestures were correlated within participants and gestures. Together, these findings indicate that human spatial pointing perception is based on configural processing of a gesture on different levels of information processing.

Impact of basic artificial intelligence (AI) course on understanding concepts, literacy, and empowerment in the field of AI among students

AbstractWith the development of information technologies and information processing methods, it is important to provide high‐quality education in the field of artificial intelligence (AI). The study aims to investigate the impact of an educational course on AI on the comprehension of concepts, literacy, and empowerment in the field of AI among students of higher educational institutions. The experiment involved 125 students from Hohai University in China. As a result of taking the training course, students were able to improve their understanding of concepts (increasing their average score from 6.33 to 9.69), literacy (from 2.94 to 3.99), and empowerment (from 3.90 to 4.04) in AI. The resulting data statistically confirmed the effectiveness of the developed course for improving confidence in the field of AI. The training module can be applied to improve confidence in the field of AI for students in various careers, as information competence is important these days and increases the success of graduates in employment. When it comes to further research, the encouraging results of this study suggest opportunities for promoting this training program among a diverse group of participants. To confirm the effectiveness of the developed course, it can be conducted among students in schools and other educational institutions, reducing it to even more basic if necessary.