Hasil untuk "Information theory"

S. Ross

Tim Bollerslev, R. Chou, Kenneth F. Kroner

Xiang Lou

In today's rapidly evolving digital society, the new media environment has profoundly reshaped the landscape of innovation and entrepreneurship among college students. Understanding and evaluating students' abilities in this context are crucial for universities, policymakers, and industries seeking to cultivate future leaders and innovators. However, traditional evaluation frameworks often struggle to address the multi-layered, uncertain, and dynamic nature of competencies in a media-driven environment. This study proposes a novel decision-making framework based on Tree Soft Set (TSS) theory to evaluate college students' innovation and entrepreneurship abilities comprehensively. The TSS model, by organizing evaluation criteria into hierarchical tree structures, captures complex relationships among competencies and adapts flexibly to overlapping and uncertain information. To further enhance the robustness of the model, Single-Valued Neutrosophic Sets (SVNS) are integrated, enabling better representation of truth, indeterminacy, and falsity degrees in expert judgments. The proposed evaluation model identifies critical dimensions such as creativity, opportunity recognition, risk management, technological adaptability, communication skills, and leadership under the influence of new media. Criteria weighting is determined using the SWARA method, while final ranking of student profiles is achieved via the MAIRCA method. Empirical application and sensitivity analyses validate the framework’s stability and effectiveness. The results provide actionable insights for educational institutions aiming to nurture innovation-driven talent in the digital era.

Jatto Esther Oluwayemi, Tella Adeyinka

The purpose of the article is to provide information professionals, including librarians, with a better understanding of the concepts and potential applications of artificial intelligence (AI) in library services. Scientific novelty. The article provides an overview of the literature on the readiness to implement artificial intelligence in library practice. It will go over the components of the Theory of Planned Behavior (TPB) model in connection with the management of library service delivery through AI tools. Lastly, a position on the preparedness of librarians for AI integration in university libraries will be adopted. Conclusions. The integration of artificial intelligence in Nigerian academic libraries is gaining momentum which has the potential to completely change how libraries function and provide services to their patrons. However, the readiness of librarians is crucial for successful implementation. This paper undertakes a review of the literature on how academic libraries in Nigeria are currently integrating AI and their readiness to use these tools. The results show that academic libraries in Nigeria are aware of the potential benefits of AI, but challenges like funding, infrastructure, and lack of expertise exist. To effectively use AI tools, librarians need to acquire new competencies and skills. Finally, the review offers suggestions for enhancing librarian readiness to fully exploit the potential of AI. In the Nigerian context, there is a notable scarcity of literature that has explored Librarians’ readiness to the adoption of artificial intelligence in an academic library: a literature review analysis of the current scope and necessary skills and competencies needed through qualitative research. As such, this study stands as a significant contribution to expanding our understanding of the topic.

Hao Luo, Shuo Yang, Nanxiang Zhang et al.

Background: Autism Spectrum Disorder (ASD) is a complex neurodevelopment disease characterized by impaired social and cognitive abilities. Despite its prevalence, reliable biomarkers for identifying individuals with ASD are lacking. Recent studies have suggested that alterations in the functional connectivity of the brain in ASD patients could serve as potential indicators. However, previous research focused on static functional-connectivity analysis, neglecting temporal dynamics and spatial interactions. To address this gap, our study integrated dynamic functional connectivity, local graph-theory indicators, and a feature-selection and ranking approach to identify biomarkers for ASD diagnosis. Methods: The demographic information, as well as resting and sleeping electroencephalography (EEG) data, were collected from 20 ASD patients and 25 controls. EEG data were pre-processed and segmented into five sub-bands (Delta, Theta, Alpha-1, Alpha-2, and Beta). Functional-connection matrices were created by calculating coherence, and static-node-strength indicators were determined for each channel. A sliding-window approach, with varying widths and moving steps, was used to scan the EEG series; dynamic local graph-theory indicators were computed, including mean, standard deviation, median, inter-quartile range, kurtosis, and skewness of the node strength. This resulted in 95 features (5 sub-bands × 19 channels) for each indicator. A support-vector-machine recurrence-feature-elimination method was used to identify the most discriminative feature subset. Results: The dynamic graph-theory indicators with a 3-s window width and 50% moving step achieved the highest classification performance, with an average accuracy of 95.2%. Notably, mean, median, and inter-quartile-range indicators in this condition reached 100% accuracy, with the least number of selected features. The distribution of selected features showed a preference for the frontal region and the Beta sub-band. Conclusions: A window width of 3 s and a 50% moving step emerged as optimal parameters for dynamic graph-theory analysis. Anomalies in dynamic local graph-theory indicators in the frontal lobe and Beta sub-band may serve as valuable biomarkers for diagnosing autism spectrum disorders.

Kamran Farajzadeh, Mohammad Taghi Taghavifard, Abbas Toloie Ashlaghi et al.

Purpose: Collecting data from users using conventional traditional methods, in order to achieve a specific purpose, is often expensive, time-consuming, and accompanied by disadvantages affecting the research results, the aim of the current research is to provide a model based on gamification in order to obtain the way of thinking of people through a case study of internet taxi applications in Iran (Snapp, Tapsi, and Carpino). Method: Research is applied in terms of aim and descriptive in terms of nature. Data collection was done by a researcher-made questionnaire, whose validity and reliability were confirmed based on expert opinion and Cronbach's alpha coefficient. The statistical population was all the users of the mentioned applications and members of Telegram, which was 180 people as a statistical sample. Findings: Comparing the results to determine the popularity of brands in the two methods was almost the same, in addition, the cost and time of using the proposed method was significantly less and the percentage of audience participation was higher. Conclusion: By presenting the proposed framework, the limitations of common data collection methods were removed and more accurate and higher quality data were used to understand people's thinking, it is also possible to use this method for all researchers.

Santha Vaithilingam, Li-Ann Hwang, Mahendhiran Nair et al.

<h4>Background</h4> Sporadic outbreaks of COVID-19 remain a threat to public healthcare, especially if vaccination levels do not improve. As Malaysia begins its transition into the endemic phase, it is essential to identify the key determinants of COVID-19 vaccination intention amongst the pockets of the population who are still hesitant. Therefore, focusing on a sample of individuals who did not register for the COVID-19 vaccination, the current study integrated two widely used frameworks in the public health domain—the health belief model (HBM) and the theory of reasoned action (TRA)—to examine the inter-relationships of the predictors of vaccination intention amongst these individuals. <h4>Methodology</h4> Primary data from 117 respondents who did not register for the COVID-19 vaccination were collected using self-administered questionnaires to capture predictors of vaccination intention amongst individuals in a Malaysian context. The partial least squares structural equation modeling (PLS-SEM) technique was used to analyze the data. <h4>Results</h4> Subjective norms and attitude play key mediating roles between the HBM factors and vaccination intention amongst the unregistered respondents. In particular, subjective norms mediate the relationship between cues to action and vaccination intention, highlighting the significance of important others to influence unregistered individuals who are already exposed to information from mass media and interpersonal discussions regarding vaccines. Trust, perceived susceptibility, and perceived benefits indirectly influence vaccination intention through attitude, indicating that one’s attitude is vital in promoting behavioral change. <h4>Conclusion</h4> This study showed that the behavioral factors could help understand the reasons for vaccine refusal or acceptance, and shape and improve health interventions, particularly among the vaccine-hesitant group in a developing country. Therefore, policymakers and key stakeholders can develop effective strategies or interventions to encourage vaccination amongst the unvaccinated for future health pandemics by targeting subjective norms and attitude.

Mohammad Hassan zadeh, HamidReza Mahmoodi, Davoud Haseli et al.

Objectives:This research aims to prioritize the actions of public libraries in Iran to increase the overall satisfaction of users based on the Kano model and the asymmetric performance effect.Methods: The research method is descriptive in terms of data collection and practical in terms of purpose. The statistical population of this research is the number of 10,000 public library users in Iran, of which 400 people were selected as a sample according to Morgan's table by random cluster sampling. The research tool is a questionnaire that was created and validated by the researcher. Data were analyzed with SPSS software. 23 versions were analyzed.Results: The results showed that the three features of public library services, social and cultural programs, promotion, and introduction of the library are among the basic services with low performance, and the feature of library costs is among the basic services with high performance. The characteristic of the library's fame and popularity is among the functional services with low performance, and the characteristics of librarians, equipment, and collections are among the group of functional services with high performance. The characteristics of ancillary services and social participation are among motivational services with low performance, and the characteristics of activity time, space, place, the feeling of comfort and security, and library system and software are among motivational services with high performance.Conclusions: Basic and low-performance functional services cause dissatisfaction with public libraries, which should be the first priority to increase user satisfaction. In the second priority, low-performance motivational services should be upgraded to high-performance, and in the last priority, the level of basic, functional, and high-performance motivational services should be maintained at the current level. This type of prioritization of actions in public libraries has been done by considering the two principles of highlighting negative performance compared to positive performance and also the ability to remember positive events against negative events.

Kaijun Wang, Yunchao Gong, Feng Hu

The hypergraph offers a platform to study structural properties emerging from more complicated and higher-order than pairwise interactions among constituents and dynamical behavior, such as the spread of information or disease. Considering the higher-order interaction between multiple nodes in the system, the mathematical model of infectious diseases spreading on simple scale-free networks is extended to hypernetworks based on hypergraphs. A SIS propagation model based on reaction process strategy in a universal scale-free hypernetwork is constructed, and the theoretical and simulation analysis of the model is carried out. Using mean field theory, the analytical expressions between infection density and hypernetwork structure parameters as well as propagation parameters in steady state are given. Through individual-based simulation, the theoretical results are verified and the infectious disease spread process under the structure of the hypernetwork and simple scale-free network is compared and analyzed. It becomes apparent that infectious diseases are easier to spread on the hypernetworks, showing the clear clustering characteristics of epidemic spread. Furthermore, the influence of the hypernetwork structure and model parameters on the propagation process is studied. The results of this paper are helpful in further studying the propagation dynamics on the hypernetworks. At the same time, it provides a certain theoretical basis for the current COVID-19 prevention and control in China and the prevention of infectious diseases in the future.

GuangDong Song, JiuLong Cheng, BinXin Hu et al.

Given the complex environment experienced in working mines, the vibration waves produced by processes such as rock fracture in deep formations usually show interference effects when monitored due to other signals, the so-called “clutter” in the signal, which are interfered with the clutter. At the same time, owing to the influence of system noise, the first arrival time and the arrival time difference values of the signals obtained cannot easily be determined accurately. The propagation model for the microseismic signals experienced and the discrimination method used to determine the first arrival wave type can be established using knowledge of the spatial geometry between the sensors used and the seismic source. Thus, the filtering of the actual from the abnormal wave signals is possible. Using the theory of signal cross-correlation in this work, a correction method for the arrival velocity of the first microseismic signal has been proposed and evaluated. By calculating the cross-correlation coefficient of the same source vibration signal and finding the position that corresponds to the maximum value of the cross-correlation coefficient, the arrival time difference between the signals seen in the two channels is obtained. Thus, the key conclusions can be drawn from the experiments carried out: when the signal-to-noise ratio of the original signal is low, the time difference can still be determined with high accuracy. Further, a wave velocity correction criterion has also been proposed, where the velocity correction of the S wave or the R wave can be realized by combining the spatial coordinate information on the blasting point and an algorithm representing the signal cross-correlation to arrival time difference is used.

C. L. Kang, C. L. Kang, T. N. Lu et al.

In point cloud data processing, smooth sampling and surface reconstruction are important aspects of point cloud data processing. In view of the current point cloud sampling method, the point cloud distribution is not uniform, the point cloud feature information is incomplete, and the reconstructed model surface is not smooth. This paper proposes a method of smoothing sampling processing and surface reconstruction using point cloud using moving least squares method. This paper first introduces the traditional moving least squares method in detail, and then proposes an improved moving least squares method for point cloud smooth sampling and surface reconstruction. In this paper, the algorithm is designed for the proposed theory, combined with C++ and point cloud library PCL programming, using voxel grid sampling and uniform sampling and moving least squares smooth sampling comparison, after sampling, using greedy triangulation algorithm surface reconstruction. The experimental results show that the improved moving least squares method performs point cloud smooth sampling more uniformly than the voxel grid sampling and the feature information is more prominent. The surface reconstructed by the moving least squares method is smooth, the surface reconstructed by the voxel grid sampling and the uniformly sampled data surface is rough, and the surface has a rough triangular surface. Point cloud smooth sampling and surface reconstruction based on moving least squares method can better maintain point cloud feature information and smooth model smoothness. The superiority and effectiveness of the method are demonstrated, which provides a reference for the subsequent study of point cloud sampling and surface reconstruction.

Jan Mölter, Geoffrey J. Goodhill

Information theory provides a powerful framework to analyse the representation of sensory stimuli in neural population activity. However, estimating the quantities involved such as entropy and mutual information from finite samples is notoriously hard and any direct estimate is known to be heavily biased. This is especially true when considering large neural populations. We study a simple model of sensory processing and show through a combinatorial argument that, with high probability, for large neural populations any finite number of samples of neural activity in response to a set of stimuli is mutually distinct. As a consequence, the mutual information when estimated directly from empirical histograms will be equal to the stimulus entropy. Importantly, this is the case irrespective of the precise relation between stimulus and neural activity and corresponds to a maximal bias. This argument is general and applies to any application of information theory, where the state space is large and one relies on empirical histograms. Overall, this work highlights the need for alternative approaches for an information theoretic analysis when dealing with large neural populations.

A. T. Tarlanov, Z. M. Kurbanismailov

The paper shows the approach and the result of taking into account the mutual influence of on-board subsystems of a complex technical object along the DC power supply circuits. Technical objects are understood as a mobile, energy-intensive vehicle, such as an aircraft, a surface or submarine vessel, or a railway locomotive with strong magnetic fields. The aim of the work is to create a simple and intuitive tool for mathematical modeling of the magnetic field vector at an arbitrarily specified observation point. The task is being solved in order to improve the accuracy of magnetic measurements on board, in particular, in navigation problems. On-board DC networks are considered, to which the approach of mathematical modeling is applied. The disadvantages of commercial programs of a similar purpose are noted. The binding of the objects under consideration to the general coordinate system is described. An analytical algorithm for calculating the magnetic field vector from the on-board cable network with a pronounced 3D trajectory is shown. Examples of visualization of the simulation results are given. An algorithm for calculating the induction vector based on the Biot-Savard law is considered. The algorithm for the analytical solution of the problem is described in detail. A specific power cable of the on-board network is considered. The cable is given by a set of straight conductors with current. The ways of future improvement of the created product with the transition from one observation point to the field map in a given three-dimensional zone of arbitrary position, volume and orientation are outlined. The obtained result is considered as an element of the procedure for achieving electromagnetic compatibility of energy-intensive and highly sensitive subsystems of a modern complex technical object.

Zhuo Ma, Yang Yang, Martin Kearns et al.

On-line partial discharge (PD) monitoring is being increasingly adopted to improve the asset management and maintenance of medium-voltage (MV) motors. This study presents a novel method for autonomous analysis and classification of motor PD patterns in situations where a phase-reference voltage waveform is not available. The main contributions include a polar PD (PPD) pattern and a fractal theory-based autonomous PD recognition method. PPD pattern that is applied to convert the traditional phase-resolved PD pattern into a circular form addresses the lack of phase information in on-line PD monitoring system. The fractal theory is then presented in detail to address the task of discrimination of 6 kinds of single source and 15 kinds of multi-source PD patterns related to motors, as outlined in IEC 60034. The classification of known and unknown defects is calculated by a method known as centre score. Validation of the proposed method is demonstrated using data from laboratory experiments on three typical PD geometries. This study also discusses the application of the proposed techniques with 24 sets of on-site PD measurement data from 4 motors in 2 nuclear power stations. The results show that the proposed method performs effectively in recognising not only the single-source PD but also multi-source PDs.

Sanjana Buć, Blaženka Divjak

The paper deals with influential factors of an organization’s environment in the initial phase of diffusion of innovations (DOI) within the organization. A qualitative research was carried out with two expert groups: one for the diffusion of e-learning as an innovation in a higher education institution and the other for the diffusion of the Building Information Modelling (BIM) in a Construction Industry. The research disclosed 20 common factors. The internal environment group covers management support, the attitude towards innovation, strategic planning and communication, motivation and expertize of employers, available resources and IT maturity level of an organization. The group of business environment factors consists of competitors, clients and partners, supply and demand balance on the specific market for goods and services. In the social environment group, three factors are recognized on the national level and two on the global levels. The holistic model combines the theory of DOI and the concept of absorption capacity.

Ania Medina Rodríguez , Esperanza Asencio Cabot, Nilda Ibarra López

The scientific-technical advances bring with them the need to prepare persons for its use and. This article is the result of the elaboration and application of a survey to measure the development of the informational skills in teachers of the Pedagogical Area at the Central University "Marta Abreu" of Las Villas, Cuba. Methods of the theoretical, empirical and mathematical-statistical level were applied for the analysis of data. The instrument was conceived from the theory of research methodology and the investigative experience of the authors. The application of this proposal favored the diagnosis of teachers, both from the work with scientific information and their computer skills, essential skills of a competent professional. The work, although is perfectible, will contribute to the elaboration of future proposals for the improvement of the teaching process in Higher Education.

Sehyun Tak, Sunghoon Kim, Young-Ji Byon et al.

Ideal configuration or layout of highways should resemble the actual demands for the roads represented by Origin-Destination (OD) information. It would be beneficial if existing highways can be evaluated for their configurational fitness against the current demands, and newly planned highways can carefully be designed in terms of their layouts and topologies that would reflect the demands. Analysis techniques used for complex networks in the matured field of network theory can be applied for the highway layout health monitoring against the current OD information. This paper proposes a methodology of measuring the fitness of existing highways by comparing their structural configuration against conceptual OD networks using well-established techniques in network theory for complex networks. In the first phase, this paper conducts an empirical analysis and finds that both structural highway network and OD network follow the "power law" distribution as they are weighted by capacity and traffic volume respectively. It is also found that the power law coefficient of the OD network dynamically changes throughout the day and week. In the second phase, a noble methodology of weighting and measuring the health, of structural highway networks against OD networks by means of comparing their power law coefficients is proposed. It is found that the proposed method is effective at detecting deviations from ideal structural configurations associated with actual demands.

van der Merwe, Christo H. J.

In terms of the theoretical framework of an influential recent model of Bible translation, Left Dislocation (=LD) can be regarded as a “communicate clue” that translators must try to interpretively resemble in their target text translation. This exploratory study investigates how twenty translations (fifteen English, three Afrikaans, one German, and one Dutch) have interpretively resembled (or not) nine prototypical constructions, and one less prototypical one, from the book of Genesis. It has been found that, firstly, translations on the formal equivalent pole tend to interpretively resemble LD constructions. If the LD tends to be very prototypical, this tendency is displayed even by some translations towards the functional equivalent pole. Secondly, even in the case of prototypical instances, translations on the functional equivalent pole, however, tend not to interpretively resemble the construction. In these cases, it could be argued that they are not serving the very goal that they as a rule want to accomplish—that is, to provide readers with a translation that is easy to read and process. Thirdly, the structure of English, Afrikaans and Dutch—in contrast to German—often appears to require a construal that does not formally reflect the pronominal resumption of the LD constituent in the matrix clause. Fronting the LD constituent is often used, and sometimes a pause after the fronted (i.e. then dislocated) constituent is signaled by means of a comma or a dash. These findings concur with those of some of the other papers in this volume. Resumption, for example, is not always the primary distinctive feature of a LD construction; a tonal pause between the LD and its matrix clause may also suffice. There are also historical explanations as to why some of the functions of fronting and LD constructions overlap.

S. D. Lavrov

The paper presents the experimental and theoretical study results of nonlinear optical properties of lithium niobate domain structures created by a focused electron beam. The presence of a second optical harmonic periodic signal in the locations of the domain structures is shown. The numerical simulation of the second harmonic optical power was done based on the model of Boyd. The possibility of determining the volumetric parameters of domain structures using nonlinear confocal optical microscopy is shown.

Nilgün Şen, Bayram YÜKSEL

The B3LYP/6-311++G(2df,2p) density functional theory (DFT) method was used to investigate molecular geometry and thermodynamic properties of RDX and RDX derivatives containing Al and B metals. The detonation velocity (D) and detonation pressure (P), estimated by using Kamlet–Jacobs and in literature equations, respectively. Total energies (Et), frontier orbital energy (EHOMO, ELOMO), energy gap (ΔELUMO–HOMO) and theoretical molecular density (ρ) were calculated with Spartan 14 software package program. It was shown that the presence of aluminum and boron atoms affects the good thermal stabilities. The results show that the composite RDX-Al, RDX-B derivatives have higher detonation performance and higher density than RDX. RDX-Al derivatives appeared to be superior to RDX-B mixtures in terms of these parameters. These results provide information on the moleculer design of new energetic materials.