Process Information Research Articles

An Intrusion Detection Model Based on Extra Trees Algorithm with Dimensionality Reduction and Oversampling

With the advancement of the university information process, more and more application systems are running on the campus network, and the information system becomes larger and more complex. With the rapid growth of network users and the popularization and deepening of computer knowledge, the campus network has been transformed from an experimental network for education and scientific research into an operational network that attaches equal importance to education, scientific research, and service. As the most important transmission carrier of digital information, how to ensure its security has become an urgent issue for colleges and universities. Therefore, this paper uses advanced intrusion detection technology to design the corresponding model to solve the security problem of the campus network. When traditional machine learning algorithms train network intrusion data sets, they are prone to problems such as too many feature dimensions, overfitting, and imbalance of data sets, which lead to lower accuracy and low time efficiency of intrusion detection algorithms. In order to solve the above problems, this paper proposes an intrusion detection model based on Extra Trees, which uses linear discriminant analysis to reduce the dimension of data, then uses oversampling to reduce the influence of imbalance of sample categories of the network intrusion dataset, and finally uses Extra Trees algorithm to train the model. The experimental results show that after LDA reduction and oversampling, using the Extra Trees classification model can improve the overall recognition performance of imbalanced data sets under multi-classification and satisfy the network intrusion detection.

Federated knowledge distillation for enhanced insulator defect detection in resource‐constrained environments

AbstractInsulator defect detection is crucial for the stable operation of power systems. It has become a mainstream research direction to realise insulator defect detection based on the combination of line images captured by UAVs and deep learning techniques. However, the existing high‐quality insulator defect detection models still face problems such as relying on massive‐labelled data and huge model parameters. Especially on resource‐constrained devices, it becomes a challenge to strike a balance between model lightweighting and performance. Although the knowledge distillation technique provides a solution for model lightweighting, the loss of information in the distillation process leads to the performance degradation of small models, which in turn creates a paradox between lightweighting and performance. Hence, an insulator defect detection method based on federated knowledge distillation is proposed. The method not only realises the lightweighting of the model, but also effectively improves the model performance by collaboratively training the model through the federated learning approach. Moreover, the asynchronous aggregation approach and model freshness mechanism designed in the method further enhance the training efficiency and collaborative effect. The experimental results show that the detection accuracy and efficiency of this paper's method on public datasets are significantly better than the benchmark algorithm.

Public Opinion Formation in the Digital Age : A Review of Literature

The digital age has brought significant changes in the way people access and process information. Social media and other online platforms have become a major source of information and public opinion. This study aims to review the literature on public opinion formation in the digital age. This study uses the literature review method to analyze literature relevant to the research topic. A literature review shows that the digital age has had a significant impact on the formation of public opinion. Social media and other online platforms have become the primary means for individuals to access information, share ideas, and exchange opinions. This has led to changes in the way public opinion is formed and disseminated. The formation of public opinion in the digital age is a complex and dynamic phenomenon. Social media and other online platforms have an important role to play in shaping public opinion. A better understanding of the process of forming public opinion in the digital age is needed to develop effective communication strategies and build a more democratic society.

Data stream solution for decision-making processes: a general and adaptive system for decision support

ABSTRACT With the rise of new data generation processes and availability rates, new challenges appear linked with the information and pattern extraction for decisional processes. In these contexts, decision support systems (DSS) need to incrementally integrate the data flows to provide readable, understandable and meaningful conclusions. This research presents a novel adaptive DSS that offers updated and explainable knowledge for decision makers, especially in uncertain decision scenarios. Also, this work explores applications of this technology in some social fields, aiming to analyse the potential contribution of machine learning, combined with adaptive decision systems, in society.

Comparative analysis of spatial transport characteristics of spring cold-front-type sandstorms in the Hexi Corridor

AbstractIn this study, we investigate the spatial transport characteristics of cold-front-type sandstorms with different intensities in the Hexi Corridor based on the hourly observation data from 13 ground-based meteorological stations in the Hexi Corridor, the data in the upper and lower layers from the Meteorological Information Comprehensive Analysis And Process System, and the three-dimensional aerosol observation data of the Vertical Feature Mask product obtained from the Cloud-Aerosol Lidar with Orthogonal Polarization of the United States. The results show that the influence range and horizontal transport distance of cold-front-type sandstorms in the Hexi Corridor are determined by the intensity, thickness and width of the upper-level troughs and the intensity of cold fronts. Generally, cold fronts pass through the Hexi Corridor from noon to evening and stay in this region for a long time or move slowly, which is favorable to the horizontal long-distance transport of sandstorms. The intensity of the 200 hPa upper-level jets is directly proportional to both the influence range and transport distance of sandstorms which primarily occur on the left side of the exit area of an upper-level jet. The strengthening of upper-level jets induces the formation of the vertical circulation cell at middle and low levels. The ascending branch of the circulation cell lifts sand-dust particles from the surface to the upper layers, and the descending branch transports upper-level momentum to the near-surface. This circulation situation increases the near-surface wind speed and forms sandstorms. The occurrence time and descending branch of the secondary circulation cell caused by upper-level jets are important indicators for predicting the occurrence time and falling area of sandstorms. Dust aerosols are mainly concentrated at a height of 2–6 km,.,and they can reach the height of 12 km. When the dust is concentrated at the height of 2–8 km, and the wind speed of 500 hPa and 300 hPa reaches 28 and 32 m s− 1 or above respectively, the cold front sandstorm can realize the long distance transport of thousands of kilometers.

The Effectiveness of Using Sondet Smart Augmented Reality Based Application to Improve Sound Understanding for Hearing Impairment Special School Students in Central Java

Hearing impairment children are individuals who have lost the ability to hear, thereby hampering the process of information through their hearing, whether they use hearing aids or not. This research will test the effectiveness of using the Sondet Smart Augmented Reality based application in improving sound understanding for hearing impairment children. This research uses a quantitative approach with experimental techniques to test the use of the Sondet Smart Augmented Reality based application. The research subjects involved 124 hearing impairment students attending special schools in Central Java, then these students were divided into two groups, control and experimental groups. The research results were calculated using SPSS with the Chi Square test resulting in a asymp-sig calculation of 0.010 using alpha of 0.05, so asymp-sig. < 0.05. Therefore, the use of the sondet application to improve the sound understanding of hearing impairment students in Central Java has proven to be effective in increasing students' sound understanding.

Toward Cosmological Simulations of the Magnetized Intracluster Medium with Resolved Coulomb Collision Scale

We present the first results of one extremely high-resolution, nonradiative magnetohydrodynamical cosmological zoom-in simulation of a massive cluster with a virial mass of M vir = 2.0 × 1015 solar masses. We adopt a mass resolution of 4 × 105 M ⊙ with a maximum spatial resolution of around 250 pc in the central regions of the cluster. We follow the detailed amplification process in a resolved small-scale turbulent dynamo in the intracluster medium (ICM) with strong exponential growth until redshift 4, after which the field grows weakly in the adiabatic compression limit until redshift 2. The energy in the field is slightly reduced as the system approaches redshift zero in agreement with adiabatic decompression. The field structure is highly turbulent in the center and shows field reversals on a length scale of a few tens of kiloparsecs and an anticorrelation between the radial and angular field components in the central region that is ordered by small-scale turbulent dynamo action. The large-scale field on megaparsec scales is almost isotropic, indicating that the structure formation process in massive galaxy cluster formation suppresses any memory of both the initial field configuration and the amplified morphology via the turbulent dynamo. We demonstrate that extremely high-resolution simulations of the magnetized ICM are within reach that can simultaneously resolve the small-scale magnetic field structure, which is of major importance for the injection of and transport of cosmic rays in the ICM. This work is a major cornerstone for follow-up studies with an on-the-fly treatment of cosmic rays to model in detail electron-synchrotron and gamma-ray emissions.

A Mechanistic Study of Enterprise Digital Intelligence Transformation, Innovation Resilience, and Firm Performance

Enterprise Digital Intelligence Transformation is based on the Digital Conversion of information and process service upgrading, further touching the enterprise’s core business, with the goal of building a new business model of Digital Intelligence Transformation at a higher level. Based on dynamic capability theory, this paper conducts an in-depth study on the mechanism of enterprise Digital Intelligence Transformation and firm performance. This paper selects manufacturing companies listed in China’s Shanghai and Shenzhen A-shares from 2013 to 2022 as the research sample, and analyzes and tests the sample data using empirical research methods in order to explore the actual impact of Digital Intelligence Transformation on firm performance, including the specific pathways of action and moderating effects. This study helps enterprises to positively face the megatrend of Digital Intelligence Transformation and upgrading and the challenges it brings, and to grasp the new opportunities in the digital era. This study finds that enterprises carry out digital empowerment transformation and development strategies, and implement information Digital Conversion, service upgrading, and Digital Intelligence Transformation to promote firm performance to different degrees. Enterprise innovation resilience has a mechanism effect between information digitalization conversion enterprise performance and process service upgrading enterprise performance. The higher the environmental uncertainty, the greater the positive contribution of information digitalization to firm performance. Digital Conversion is the base and service upgrading is the process. The current sample enterprises have limited years of data collection, and most of them have only carried out the strategic implementation of Digital Conversion or servitization, and have not reached the high-level stage of digital and intellectual transformation. Therefore, it is found that enterprise innovation resilience has not yet shown a significant role mechanism effect between digital–intelligent transformation and enterprise performance at present. And environmental uncertainty has not yet shown a significant moderating effect in the stage of Servitization Upgrading and digital–intelligent transformation. The marginal contributions of this paper are mainly reflected in the following: (1) This study introduces the dynamic capability theory to explore the role of Digital Intelligence Transformation (Digital Conversion + service upgrading) on enterprise performance. (2) This paper investigates the role of Digital Intelligence Transformation in influencing the performance of enterprises from the Digital Conversion and service upgrading phases, and enriches the relevant role and regulatory mechanisms. (3) This study provides new ideas and strategic suggestions on Digital Intelligence Transformation for enterprises with different factor intensities, at different stages of development, and in different regions.

Accurate prediction of antibody function and structure using bio-inspired antibody language model.

In recent decades, antibodies have emerged as indispensable therapeutics for combating diseases, particularly viral infections. However, their development has been hindered by limited structural information and labor-intensive engineering processes. Fortunately, significant advancements in deep learning methods have facilitated the precise prediction of protein structure and function by leveraging co-evolution information from homologous proteins. Despite these advances, predicting the conformation of antibodies remains challenging due to their unique evolution and the high flexibility of their antigen-binding regions. Here, to address this challenge, we present the Bio-inspired Antibody Language Model (BALM). This model is trained on a vast dataset comprising 336 million 40% nonredundant unlabeled antibody sequences, capturing both unique and conserved properties specific to antibodies. Notably, BALM showcases exceptional performance across four antigen-binding prediction tasks. Moreover, we introduce BALMFold, an end-to-end method derived from BALM, capable of swiftly predicting full atomic antibody structures from individual sequences. Remarkably, BALMFold outperforms those well-established methods like AlphaFold2, IgFold, ESMFold and OmegaFold in the antibody benchmark, demonstrating significant potential to advance innovative engineering and streamline therapeutic antibody development by reducing the need for unnecessary trials. The BALMFold structure prediction server is freely available at https://beamlab-sh.com/models/BALMFold.

Facilitating the sharing of electrophysiology data analysis results through in-depth provenance capture.

Scientific research demands reproducibility and transparency, particularly in data-intensive fields like electrophysiology. Electrophysiology data is typically analyzed using scripts that generate output files, including figures. Handling these results poses several challenges due to the complexity and iterative nature of the analysis process. These stem from the difficulty to discern the analysis steps, parameters, and data flow from the results, making knowledge transfer and findability challenging in collaborative settings. Provenance information tracks data lineage and processes applied to it, and provenance capture during the execution of an analysis script can address those challenges. We present Alpaca (Automated Lightweight Provenance Capture), a tool that captures fine-grained provenance information with minimal user intervention when running data analysis pipelines implemented in Python scripts. Alpaca records inputs, outputs, and function parameters and structures information according to the W3C PROV standard. We demonstrate the tool using a realistic use case involving multichannel local field potential recordings of a neurophysiological experiment, highlighting how the tool makes result details known in a standardized manner in order to address the challenges of the analysis process. Ultimately, using Alpaca will help to represent results according to the FAIR principles, which will improve research reproducibility and facilitate sharing the results of data analyses.Significance Statement Sharing electrophysiology data analysis results is challenging, especially in collaborative environ-ments. The results can be understood and interpreted only with the accurate description of the individual analysis steps, the parameters and the data flow, which can be achieved by storing the results together with detailed provenance information. We implemented the Alpaca toolbox to capture provenance during the execution of Python scripts, a typical implementation in pipelines that analyze electrophysiology datasets. Alpaca provides an easy and lightweight solution to record the relevant details of the analysis, facilitating sharing the results.

Enhancement of silicon vacancy fluorescence intensity in silicon carbide using a dielectric cavity

Over the past decades, spin qubits in silicon carbide (SiC) have emerged as promising platforms for a wide range of quantum technologies. The fluorescence intensity holds significant importance in the performance of quantum photonics, quantum information process, and sensitivity of quantum sensing. In this work, a dual-layer Au/SiO2 dielectric cavity is employed to enhance the fluorescence intensity of a shallow silicon vacancy ensemble in 4H-SiC. Experimental results demonstrate an effective fourfold augmentation in fluorescence counts at saturating laser power, corroborating our theoretical predictions. Based on this, we further investigate the influence of dielectric cavities on the contrast and linewidth of optically detected magnetic resonance (ODMR). There is a 1.6-fold improvement in magnetic field sensitivity. In spin echo experiments, coherence times remain constant regardless of the thickness of dielectric cavities. These experiments pave the way for broader applications of dielectric cavities in SiC-based quantum technologies.

Modeling the dissemination of privacy information in online social networks

AbstractDriven by the rapid development of information technology, online social networks (OSNs) have experienced a fast development in recent years, allowing increasingly more people to share and spread information over OSNs. The rapid rise of OSN platforms such as Facebook and Twitter is sufficient evidence of such development. As one type of information, privacy information can also be created and disseminated over an OSN, posing a severe threat to individual privacy. This article attempts to construct a model for disseminating privacy information in OSNs and to analyze the model by simulating the dissemination process of privacy information in OSNs. First, we establish network models that exhibit the main characteristics of OSNs. Second, by considering the factors related to social relationships, especially intimacy between users and the attention of users to the privacy subject, we derive the parameters for privacy information dissemination models in OSNs. Third, based on the theory of information dissemination dynamics, we construct a model for information dissemination that conforms to the properties of privacy information. We also present some experimental results based on the constructed model and analyze the characteristics of privacy information dissemination. Fourth, we study and verify the various properties of the model through a set of experiments. The proposed model provides the opportunity to better understand the dynamics of privacy information dissemination in OSNs and the effect of user behavior on dissemination.

Epithelial-to-mesenchymal transition and NF-kB pathways are promoted by a mutant form of DDB2, unable to bind PCNA, in UV-damaged human cells

BackgroundDNA-Damaged Binding protein 2 (DDB2) is a protein involved in the early step of Nucleotide Excision Repair. Recently, it has been reported that DDB2 is involved in epithelial-to-mesenchymal transition (EMT), key process in tumour invasiveness and metastasis formation. However, its role is not completely known.MethodsBoyden chamber and cell adhesion assays, and ICELLigence analysis were performed to detect HEK293 adhesion and invasion. Western blotting and gelatine zymography techniques were employed to assess the EMT protein levels and MMP enzymatic activity. Immunofluorescence analysis and pull-down assays facilitated the detection of NF-kB sub-cellular localization and interaction.ResultsWe have previously demonstrated that the loss of DDB2-PCNA binding favours genome instability, and increases cell proliferation and motility. Here, we have investigated the phenotypic and molecular EMT-like changes after UV DNA damage, in HEK293 clones stably expressing DDB2Wt protein or a mutant form unable to interact with PCNA (DDB2PCNA−), as well as in HeLa cells transiently expressing the same DDB2 constructs. Cells expressing DDB2PCNA− showed morphological modifications along with a reduced expression of E-cadherin, an increased activity of MMP-9 and an improved ability to migrate, in concomitance with a significant upregulation of EMT-associated Transcription Factors (TFs), whose expression has been reported to favour tumour invasion. We observed a higher expression of c-Myc oncogene, NF-kB, both regulating cell proliferation and metastatic process, as well as ZEB1, a TF significantly associated with tumorigenic potential and cell migratory ability. Interestingly, a novel interaction of DDB2 with NF-kB was detected and found to be increased in cells expressing the DDB2PCNA−, suggesting a direct modulation of NF-kB by DDB2.ConclusionThese results highlight the role of DDB2-PCNA interaction in counteracting EMT since DDB2PCNA− protein induces in HEK293 transformed cells a gain of function contributing to the acquisition of a more aggressive phenotype.

Service Browser in Linux Environment

The key features of using web browsers and service browsers as clients of information systems are considered. A minimal set of methods has been defined that is sufficient for the effective support of client functioning. A comparison is made of the main methods that a browser used as a universal means of providing client applications should include. The basic steps of the service-browser algorithm are presented. The service browser has the full range of necessary ways to process information from the client. At the same time, it is more lightweight than a web browser. However, well-known service browsers operate in a Windows environment, which limits the scope of use. The possibility of transferring and using a C#-based service browser from a Windows environment to a Linux environment is considered. The base problems with the transfer are described. Migration methods are proposed. Using the example of the service module "System Manager", which is actually identical in both systems, a comparative analysis of the work was carried out. In order to estimate only the operating time of the service-browser components, a unified database management system is used. The launch of the main modules in the Linux environment is somewhat faster, which is explained by the features of GTK widgets. At the same time, in the Windows environment, it is much easier to develop systems with a complex graphical interface due to a richer palette of visual components. Existing web browsers are quite cumbersome and contain many functions that may be unnecessary for the development of information systems. A compact solution that includes all the necessary methods for use in the client is to use a service-browser. This paper proposes a method for building service browsers in the Linux environment based on the C# language and the Mono package, taking into account the developed additional components.

Conventional Radiography Assessment of the Pediatric Knee: Pearls and Pitfalls.

Knee pain is one of the most common indications for radiography in the evaluation of musculoskeletal disorders in children and adolescents. According to international guidelines, knee radiographs should be obtained when there is the suspicion of an effusion, limited motion, pain to palpation, inability to bear weight, mechanical symptoms (such as "locking"), and persistent knee pain after therapy. When indicated, radiographs can provide crucial information for the clinical decision-making process. Because of the developmental changes occurring in the knee during growth, the assessment of knee radiographs can be challenging in children and adolescents. Radiologists unfamiliar with the appearance of the knee on radiographs during skeletal maturation risk overcalling or overlooking bone lesions. Image acquisition techniques and parameters should be adapted to children. This article describes the most common challenges in distinguishing pathology from the normal appearance of knee radiographs in the pediatric population, offering some pearls and pitfalls that can be useful in clinical practice.

Strategic analysis and recommendations of the Sociedad Española de Patología Digestiva (SEPD) regarding population-based screening programs for colorectal cancer in Spain.

population-based screening programs are effective to reduce colorectal cancer-related mortality and incidence. However, given their complex development, sound organization and design do not warrant success. This study provides a strategic analysis of the Spanish programs, as well as recommendations in an attempt to contribute to their optimization. a multidisciplinary panel of researchers, supported by the Sociedad Española de Patología Digestiva (SEPD), has performed a SWOT (strengths, weaknesses, opportunities and threats) analysis, from which a proposal of recommendations was developed; their adequacy was judged using an adapted version of the RAND/UCLA method. 5 weaknesses, 3 threats, 5 strengths and 5 opportunities were identified, and a total of 15 recommendations were developed emphasizing aspects with room for improvement in program orientation, particularly the need to increase participation, fight variability and inequities, improve information processes and systems quality, ensure specific, adequate funding, and evaluate health results. promoting an operational collaboration framework between all the public health and care levels involved should facilitate effective communication with society regarding the benefits of taking part in population screening programs while persuading decision and policy makers of the critical importance of taking an active, determined stance regarding its implementation.

BLOOD BANK MANAGEMENT STSTEM

The Blood Bank Management System (BBMS) is a comprehensive software solution designed to streamline and automate the operations of blood banks and transfusion centers. This system provides a centralized platform for managing blood inventory, donor information, blood testing, and distribution processes, thereby enhancing operational efficiency and ensuring timely access to safe blood products for patients.

Transnational review on the use of information and communication technologies and technoscience in healthcare:Their impact onthe autonomy and governance of individuals and communities.

The impact and use of Information and Communication Technologies (ICTs) in healthcare settings has been increasing since 2019. This is greatly due to the COVID-19 pandemic. But beyond accommodating an extraordinary and complex situation in terms of healthcare services, or beyond replacing personalised care delivered by healthcare professionals (HCPs), has there been a process of information and consultation for communities and HCPs? Do we have the basic requirements needed to make such use commonplace in health care? What will the impact be on communities and their governance? Have we arrived here by consensus or by imposition? Our purpose has been to conduct a transnational analysis by approaching communities, social actors, and healthcare professionals in three territories in a pilot study following a qualitative methodology. The aim being to discover the potential impact of such measures beyond the right to health and if such measures are compatible with the purpose of population settling in rural areas. Furthermore, to identify if this entails a conflict of value and priorities or if we need new ethical reviews both for communities and healthcare professionals.

Developing a Tool for Assessing the Process of Seeking Health Information: Online Think-Aloud Method.

Nursing students can access massive amounts of online health data to drive cutting-edge evidence-based practice in clinical placement, to bridge the theory-practice gap. This activity requires investigation to identify the strategies nursing students apply to evaluate online health information. Online Think-Aloud sessions enabled 14 participants to express their cognitive processes in navigating various educational resources, including online journals and databases, and determining the reliability of sources, indicating their strategies for information-seeking, which helped to create this scoring system. Easy access and user convenience were clearly the instrumental factors in this behavior, which has troubling implications for the lack of use of higher-quality resources (e.g., from peer-reviewed academic journals). The identified challenges encountered during resource access included limited skills in the critical evaluation of information credibility and reliability, signaling a requirement for improved information literacy skills. Participants acknowledged the importance of evidence-based, high-quality information, but faced numerous barriers, such as restricted access to professional and specialty databases, and a lack of academic skills training. This paper develops and critiques a Performative Tool for assessing the process of seeking health information using an online Think-Aloud method, and explores factors and strategies contributing to evidence-based health information access and utilization in clinical practice, aiming to provide insight into individuals' information-seeking behaviors in online health contexts.

Reinterpretation of Salodik Group Performance Based on Facies and Diagenesis Approaches to Classify Reservoir Quality

An integrated study of several methods to characterize a carbonate reservoir provides a comprehensive result on carbonate facies and diagenesis. Therefore, a study on the Tertiary carbonate reservoir at the East Arm of Sulawesi area, Banggai – Sula Basin, is intended to determine the Salodik Group carbonate reservoir facies and diagenesis. Moreover, the purpose of this study is to determine the intensity and implication of syn-depositional or post-depositional processes, and to provide the reservoir final properties values, such as porosity and permeability to classify the reservoir quality. The methods of the study are based on carbonate fieldwork mapping to obtain samples on distributed traverses. Further analyses are the laboratory works to determine facies and diagenesis features on a more detailed scale. This study shows several facies, dominantly classified into reefal packstone, planktonic foraminifera packstone-wackestone, large foram packstone-mudstone, skeletal packstone-wackestone, planktonic-large foraminifera packstone-wackestone, and large foraminifera-red algae packstone. The dominant diagenesis processes are cementation and dissolution. Moreover, meteoric vadose and meteoric phreatic are predominantly the main diagenesis environment of Salodik Group formations. Furthermore, the dominant diagenesis stage is Eogenetic. The post-depositional process or the diagenetic processes, provides a more significant impact on carbonate reservoir properties than the syn-depositional process as shown on lithofacies texture. However, in general, from the younger to the oldest formation of Salodik Group, this shows a decreasing trend of reservoir properties due to the dominantcementation process in the oldest formation. Overall, the reservoir quality referring to porosity value is classified as negligible to excellent. While, based on permeability data, it is classified as the tight to good reservoir.