Abstract: Identifying influential actors within social networks is pivotal for optimizing information flow and mitigating the spread of both rumors and viruses. Several methods have emerged to pinpoint these influential entities in networks, represented as graphs. In these graphs, nodes correspond to individuals and edges indicate their connections. This study focuses on centrality measures, prized for their straightforwardness and effectiveness. We divide structural centrality into two categories: local, considering a node’s immediate vicinity, and global, accounting for overarching path structures. Some techniques blend both centralities to highlight nodes influential at both micro and macro levels. Our paper presents a novel centrality measure, accentuating node degree and incorporating the network’s broader features, especially paths of different lengths. Through Spearman and Pearson correlations tested on seven standard datasets, our method proves its merit against traditional centrality measures. Additionally, we employ the susceptible–infected–recovered (SIR) model, portraying virus spread, to further validate our approach. The ultimate influential node is gauged by its capacity to infect the most nodes during the SIR model’s progression. Our results indicate a notable correlative efficacy across various real-world networks relative to other centrality metrics. Full article

This survey represents the first endeavor to assess the clarity of the dermoscopic language by a chatbot, unveiling insights into the interplay between dermatologists and AI systems within the complexity of the dermoscopic language. Given the complex, descriptive, and metaphorical aspects of the dermoscopic language, subjective interpretations often emerge. The survey evaluated the completeness and diagnostic efficacy of chatbot-generated reports, focusing on their role in facilitating accurate diagnoses and educational opportunities for novice dermatologists. A total of 30 participants were presented with hypothetical dermoscopic descriptions of skin lesions, including dermoscopic descriptions of skin cancers such as BCC, SCC, and melanoma, skin cancer mimickers such as actinic and seborrheic keratosis, dermatofibroma, and atypical nevus, and inflammatory dermatosis such as psoriasis and alopecia areata. Each description was accompanied by specific clinical information, and the participants were tasked with assessing the differential diagnosis list generated by the AI chatbot in its initial response. In each scenario, the chatbot generated an extensive list of potential differential diagnoses, exhibiting lower performance in cases of SCC and inflammatory dermatoses, albeit without statistical significance, suggesting that the participants were equally satisfied with the responses provided. Scores decreased notably when practical descriptions of dermoscopic signs were provided. Answers to BCC scenario scores in the diagnosis category (2.9 ± 0.4) were higher than those with SCC (2.6 ± 0.66, p = 0.005) and inflammatory dermatoses (2.6 ± 0.67, p = 0). Similarly, in the teaching tool usefulness category, BCC-based chatbot differential diagnosis received higher scores (2.9 ± 0.4) compared to SCC (2.6 ± 0.67, p = 0.001) and inflammatory dermatoses (2.4 ± 0.81, p = 0). The abovementioned results underscore dermatologists’ familiarity with BCC dermoscopic images while highlighting the challenges associated with interpreting rigorous dermoscopic images. Moreover, by incorporating patient characteristics such as age, phototype, or immune state, the differential diagnosis list in each case was customized to include lesion types appropriate for each category, illustrating the AI’s flexibility in evaluating diagnoses and highlighting its value as a resource for dermatologists. Full article

Ubiquitin-specific protease 14 (USP14), one of the three major proteasome-associated deubiquitinating enzymes (DUBs), is known to be activated by the AKT-mediated phosphorylation at Ser432. Thereby, AKT can regulate global protein degradation by controlling the ubiquitin-proteasome system (UPS). However, the exact molecular mechanism of USP14 activation by AKT phosphorylation at the atomic level remains unknown. By performing the molecular dynamics (MD) simulation of the USP14 catalytic domain at three different states (inactive, active, and USP14-ubiquitin complex), we characterized the change in structural dynamics by phosphorylation. We observed that the Ser432 phosphorylation induced substantial conformational changes of USP14 in the blocking loop (BL) region to fold it from an open loop into a β-sheet, which is critical for USP14 activation. Furthermore, phosphorylation also increased the frequency of critical hydrogen bonding and salt bridge interactions between USP14 and ubiquitin, which is essential for DUB activity. Structural dynamics insights from this study pinpoint the important local conformational landscape of USP14 by the phosphorylation event, which would be critical for understanding USP14-mediated proteasome regulation and designing future therapeutics. Full article

Functionalization by noble metal catalysts and the construction of heterojunctions are two effective methods to enhance the gas sensing performance of metal oxide-based sensors. In this work, we adopt the porous ZIF-8 as a catalyst substrate to encapsulate the ultra-small Pt nanoparticles. The Pt/ZnO-In₂O₃ hollow nanofibers derived from Pt/ZIF-8 were prepared by a facile electrospinning method. The 25PtZI HNFs sensor possessed a response value of 48.3 to 100 ppm HCHO, 2.7 times higher than the pristine In₂O₃, along with rapid response/recovery time (5/22 s), and lower theoretical detection limit (74.6 ppb). The improved sensing properties can be attributed to the synergistic effects of electron sensitization effects and catalytic effects of Pt nanoparticles, and the high surface O⁻ absorbing capability of heterojunctions. The present study paves a new way to design high performance formaldehyde gas sensors in practical application. Full article

Theories of category learning have typically focused on how the underlying category structure affects the category representations acquired by learners. However, there is limited research as to how other factors affect what representations are learned and utilized and how representations might change across the time course of learning. We used a novel “5/5” categorization task developed from the well-studied 5/4 task with the addition of one more stimulus to clarify an ambiguity in the 5/4 prototypes. We used multiple methods including computational modeling to identify whether participants categorized on the basis of exemplar or prototype representations. We found that, overall, for the stimuli we used (schematic robot-like stimuli), learning was best characterized by the use of prototypes. Most importantly, we found that relative use of prototype and exemplar strategies changed across learning, with use of exemplar representations decreasing and prototype representations increasing across blocks. Full article

Forest road planning incorporates crucial strategies essential for sustainable timber extraction, minimizing environmental impacts and ensuring safe access to forest regions. This paper presents a literature review conducted to examine publications related to forest roads to ultimately filter and evaluate the information on the incorporation of classification systems in the planning strategies for forest roads. Using the Scopus database to gather publications, various data points were mapped, such as temporal distribution of publications, citation metrics, keyword inputs and other bibliometric markers. Through the bibliometric visualization software VOSviewer 1.6.19, this study determined that over the years, the forest road research subject has gained increasing attention with different shifts in focus. However, upon investigating the application of systems of classification implemented on forest road networks, it became evident that this approach is not a recent innovation and there is scarce documentation and development regarding this planning strategy. The information collected also reveals that this type of classification can be found more in technical documents, like design manuals. This outcome suggests that the subject under study is not relevantly covered in forest-related journals, but rather by institutions aiming to identify region-specific needs and develop corresponding systems accordingly. Full article

Background: Long COVID, characterized by a persistent symptom spectrum following SARS-CoV-2 infection, poses significant health, social, and economic challenges. This review aims to consolidate knowledge on its epidemiology, clinical features, and underlying mechanisms to guide global responses; Methods: We conducted a literature review, analyzing peer-reviewed articles and reports to gather comprehensive data on long COVID’s epidemiology, symptomatology, and management approaches; Results: Our analysis revealed a wide array of long COVID symptoms and risk factors, with notable demographic variability. The current understanding of its pathophysiology suggests a multifactorial origin yet remains partially understood. Emerging diagnostic criteria and potential therapeutic strategies were identified, highlighting advancements in long COVID management; Conclusions: This review highlights the multifaceted nature of long COVID, revealing a broad spectrum of symptoms, diverse risk factors, and the complex interplay of physiological mechanisms underpinning the condition. Long COVID symptoms and disorders will continue to weigh on healthcare systems in years to come. Addressing long COVID requires a holistic management strategy that integrates clinical care, social support, and policy initiatives. The findings underscore the need for increased international cooperation in research and health planning to address the complex challenges of long COVID. There is a call for continued refinement of diagnostic and treatment modalities, emphasizing a multidisciplinary approach to manage the ongoing and evolving impacts of the condition. Full article

Selecting appropriate climate change scenarios is crucial, as it influences the outcomes of climate change impact studies. Several storylines could be used to investigate the sensitivity of water resource schemes to weather variability and improve policymakers’ adaptation strategies. This study proposes a comprehensive and generic methodology for assessing the future climate change impact on semi-arid and arid zones at the basin scale by comparing delta perturbation scenarios to the outcomes of seven collections of GCMs (general circulation models). The findings indicate that the two scenarios predicted nearly identical declines in average reservoir discharges over a monthly timescale. Consequently, their maximum values are almost similar. The projected decrease in the streamflow for the period 2080–2099 is approximately 48%—the same as the ratio from the delta perturbation scenario of Future₁₆ (a 30% precipitation decrease and a 30% potential evapotranspiration increase). Furthermore, delta perturbation scenarios allow the impacts of model sensitivity to climate change to be clearly identified in relation to GCM scenarios. Delta perturbation scenarios allow for an extensive collection of possible climate changes at the regional scale. In addition, delta perturbation scenarios are simpler to create and use; therefore, they might complement GCM scenarios. Full article

In the context of ever-increasing water demand and pressures on natural resources, efficient water management is becoming a major priority for contemporary society. Since nitrogen and phosphorus, as essential nutrients, play a crucial role in the dynamics of aquatic ecosystems, but excessive concentrations can cause eutrophication of receptors, they need to be eliminated as completely as possible while respecting the principles of a sustainable economy, efficiency, and quality. In this study, the efficiency of optimizing the technological process of wastewater treatment by dosing FeCl₃ 40% solution to reduce nitrogen and phosphorus concentrations in treated water was investigated. The results obtained revealed that the use of this type of flocculant resulted in an increase in the efficiency of the removal process of total N by an average of 35.57 mg/L and total P by an average of 3.89 mg/L. Also, the results, which are interpreted by mathematical modeling, show that the optimal use of FeCl₃ 40% solution leads to a significant reduction in pollutants, well below the maximum permitted values (according to Romanian regulations, the maximum value for total phosphorus is 2 mg/L and total nitrogen is 15 mg/L for localities with a population between 10,000 and 100,000 inhabitants). This technical approach not only improves the quality of treated water but also contributes to minimizing the impact on aquatic ecosystems and promotes the principles of circular economy in water resource management. By optimizing the dosage of FeCl₃ 40% solution in the treatment process, the efficiency of the coagulation and flocculation processes is maximized, thus providing a viable and sustainable solution for reducing the environmental impact of nitrogen and phosphorus and promoting responsible and sustainable water resource management. Full article

With ageing, the risk of frailty increases, becoming a common condition that exposes older people to an increased risk of multiple adverse health outcomes. In Valencia (Spain), the ValueCare project develops and applies a value-based care approach that addresses the multidimensional nature of frailty by implementing integrated and personalized care to tackle psychosocial frailty. A pre–post controlled design with a baseline measurement at inclusion, at the end of implementation and a follow-up measurement after 6 months of intervention. In Valencia (Spain), 120 participants over 65 years of age are recruited from primary care centres to receive the ValueCare comprehensive and personalised care plan according to the results and are compared with 120 participants receiving “usual care”. An assessment questionnaire is designed using validated instruments, and a personalised care plan is developed specifically for each participant based on the results obtained. The study protocol has been registered under the ISRCTN registration number ISRCTN25089186. Addressing frailty as a multidimensional and multifactorial risk condition requires the development and implementation of comprehensive assessments and care. In this context, this study will provide new insights into the feasibility and effectiveness of a value-based methodology for integrated care supported by ICT for older people experiencing frailty. Full article

With increasing air and sea temperatures, the thermodynamic environments over the oceans are becoming more favourable for the development of intense tropical cyclones (TCs) with rapid intensification (RI). The South China coastal region consists of highly densely populated cities, especially over the Pearl River Delta (PRD) region. Intense TCs maintaining their strength or the RI of TCs close to the coastal region can present substantial forecasting challenges and have significant potential impacts on the coastal population. This study investigates the effect of sea-surface and sub-surface temperatures and salinity on the intensification of five TCs, namely Super Typhoon Hato in 2017, Super Typhoon Mangkhut in 2018, and Typhoon Talim, Super Typhoon Saola, and Severe Typhoon Koinu in 2023, which have significantly affected the South China coastal region and triggered high TC warning signals in Hong Kong in the past few years. This analysis utilised the Hong Kong Observatory’s TC best-track and intensity data, along with sea temperature and salinity profiles generated using the China Ocean ReAnalysis version 2 (CORA2) product from the National Marine Data and Information Service of China. It was found that high sea-surface temperatures (SST) of 30 °C or above for a depth of about 20 m, low sea-surface salinity (SSS) levels of 33.8 psu or below for a depth of at least 20 m, and strong salinity stratification of at least 0.6 psu per 100 m depth might offer useful hints for predicting the RI of TCs over the western North Pacific and the South China Sea (SCS) in operational forecasting, while noting other contributing environmental factors and synoptic flow patterns conducive to RI. This study represents the first documentation of sub-surface salinity’s impact on some intense TCs traversing the SCS during 2017–2023 based on an observational study. Our aim is to supplement operational techniques for forecasting RI with some quantitative guidance based on upper-level ocean observations of temperatures and salinity, on top of well-known but more rapidly changing dynamical factors like low-level convergence, weak vertical wind shear, and upper-level divergent outflow, as forecasted with numerical weather prediction models. This study will also encourage further research to refine the analysis of quantitative contributions from different RI factors and the identification of essential features for developing AI models as one way to improve the forecasting of TC RI before the TC makes landfall near the PRD, with due consideration given to the effect of freshwater river discharge from the Pearl River. Full article

The widespread availability of tools to collect and share spatial data enables us to produce a large amount of geographic information on a daily basis. This enormous production of spatial data requires scalable data management systems. Geospatial architectures have changed from clusters to cloud architectures and more parallel and distributed processing platforms to be able to tackle these challenges. Peer-to-peer (P2P) systems as a backbone of distributed systems have been established in several application areas such as web3, blockchains, and crypto-currencies. Unlike centralized systems, data storage in P2P networks is distributed across network nodes, providing scalability and no single point of failure. However, managing and processing queries on these networks has always been challenging. In this work, we propose a spatio-temporal indexing data structure, DSTree. DSTree does not require additional Distributed Hash Trees (DHTs) to perform multi-dimensional range queries. Inserting a piece of new geographic information updates only a portion of the tree structure and does not impact the entire graph of the data. For example, for time-series data, such as storing sensor data, the DSTree performs around 40% faster in spatio-temporal queries for small and medium datasets. Despite the advantages of our proposed framework, challenges such as 20% slower insertion speed or semantic query capabilities remain. We conclude that more significant research effort from GIScience and related fields in developing decentralized applications is needed. The need for the standardization of different geographic information when sharing data on the IPFS network is one of the requirements. Full article

In this paper, an interesting γ′-carbon 1,6-conjugate addition for phosphine-catalyzed α-succinimide substituted allenoates has been disclosed. A wide array of substrates was found to participate in the reaction, resulting in the production of diverse 4-diarylmethylated 3,4-disubstituted maleimides with satisfactory to outstanding yields. Furthermore, a plausible mechanism for the reaction was proposed by the investigators. Full article

Potassium–oxygen batteries (KOBs) are a promising energy storage technology with high theoretical energy density, low overpotential and a long cycle life. The cathode microstructure plays a significant role in the electrochemical performance of KOB. In this article, hierarchical porosity was introduced to commercially available carbon paper cathodes by thermal pretreatment in air at different pretreatment times. This pretreatment modifies the properties, such as surface area, defects, oxygen functional groups, etc. The discharge performance was determined at three different current densities, i.e., 0.1 mA/cm², 0.5 mA/cm², and 1.0 mA/cm². It has been found that an increase in specific surface area with the introduction of micropores and mesopores is beneficial for the improvement in the discharge capacity by enabling homogeneous discharge product, KO₂ distribution and high degrees of pore filling over the volume of the cathode. A reduction in the discharge overpotentials was observed, which is attributed to the introduction of oxygenic functional groups and defects. Samples treated for the longest pretreatment time of 24 h showed the highest discharge capacity of 5 mAh/cm² and lowest discharge overpotential of 0.03 V. Full article

Eucommia ulmoides Oliver with rich active components, such as flavonoids, lignans, polysaccharides, is used as a medicinal plant. Unfortunately, its popularization and cultivation are limited due to its low-temperature sensitivity. In this study, we aimed to explore the effect of different doses of ultraviolet-B (UV-B) radiation (UV-1, UV-2, and UV-3) and low-temperature (LT) stress, both applied individually and in combination, on the photosynthetic properties, biochemical parameters, and the contents of salicylic acid in E. ulmoides plants. The results showed that UV-B radiation alone significantly reduced photosynthetic performance and soluble total sugar content, as well as causing increases in soluble protein, proline, and superoxide anion content and antioxidant activity including SOD, POD, CAT, total phenol, and total flavonoid content. The leaf thickness and photosynthetic parameters significantly increased, as well as a significant decrease in SOD activity and soluble sugar, proline, and superoxide anion content after 14 days of none-UV-B radiation exposure. UV-B combined with LT significantly improved photosynthetic properties, Chl content, and soluble sugar content but significantly decreased proline content. Principal component analysis showed that salicylic acid was the key factor in improving LT tolerance, and UV-2 radiation showed the best LT resistance. We aim to provide new ideas and a theoretical basis for the directional cultivation and LT stress tolerance research of E. ulmoides. Our findings demonstrate that the combined effect was more positively helpful in improving the ability to resist LT tolerance via the improvement of photosynthetic ability and the increase in soluble sugar and salicylic acid content in E. ulmoides. Full article

(1) Background: The human microbiota is essential for maintaining a healthy body. The gut microbiota plays a protective role against pathogenic bacteria. Probiotics are live microorganisms capable of preventing and controlling gastrointestinal and balancing the immune system. They also aid in better nutrients and vitamins absorption. Examples of natural probiotic cultures are kefir and kombucha. (2) Methods: Therefore, the aim of this review was to address the beneficial properties of probiotic kefir and kombucha using a Boxplot analysis to search for scientific data in the online literature up to January 2024: (Latin American and Caribbean Health Sciences (LILACS), PubMed, Medical Literature Analysis (MED-LINE), Science Direct, Google Scholar/Google Academic, Bioline Inter-national and Springer Link). Boxplots showed the summary of a set of data “Index Terms—Keywords” on kefir and kombucha in three languages (English, Portuguese and Spanish). (3) Results: Google Scholar was the database with the highest number of articles found, when the search for the keywords used in the study (containing ~4 × 10⁶–~4 million articles available). This was Followed by the Science Direct database, containing ~3 × 10⁶–~3 million articles available, and the BVS databases—Biblioteca Virtual de Saúde (Virtual Health Library) e Lilacs, both containing a value of ~2 × 10⁶–~2 million articles available. The databases containing the smallest number of articles found were Nutrients and Medline, both containing a value of ≤0.1 × 10⁶–≤100 thousand articles. (4) Conclusions: Scientific studies indicate that kefir and kombucha certainly contain various functional properties, such as antimicrobial, antitumor, anticarcinogenic and immunomodulatory activity, in addition to having a microbiological composition of probiotic bacteria and yeasts. Kefir and kombucha represent key opportunities in the food and clinic/medical fields. Full article

A community engaged research (CER) approach was used to provide an exposure assessment of poly- and perfluorinated (PFAS) compounds in North Carolina residential drinking water. Working in concert with community partners, who acted as liaisons to local residents, samples were collected by North Carolina residents from three different locations along the Cape Fear River basin: upper, middle, and lower areas of the river. Residents collected either drinking water samples from their homes or recreational water samples from near their residence that were then submitted by the community partners for PFAS analysis. All samples were processed using weak anion exchange (WAX) solid phase extraction and analyzed using a non-targeted suspect screening approach as well as a quantitative approach that included a panel of 45 PFAS analytes, several of which are specific to chemical industries near the collection site locations. The non-targeted approach, which utilized a suspect screening list (obtained from EPA CompTox database) identified several PFAS compounds at a level two confidence rating (Schymanski scale); compounds identified included a fluorinated insecticide, a fluorinated herbicide, a PFAS used in polymer chemistry, and another that is used in battery production. Notably, at several locations, PFOA (39.8 ng/L) and PFOS (205.3 ng/L) were at levels that exceeded the mandatory EPA maximum contaminant level (MCL) of 4 ng/L. Additionally, several sites had detectable levels of PFAS that are unique to a local chemical manufacturer. These findings were communicated back to the community partners who then disseminated this information to the local residents to help empower and aid in making decisions for reducing their PFAS exposure. Full article

A simple dynamic system with dry friction is studied theoretically and numerically. Models of systems including dry friction are not easily obtained, as defining the relationship between the friction force and the relative velocity presents a significant challenge. It is known that friction forces exhibit notable discontinuities when there is a change in the direction of motion. Additionally, when the relative motion ceases, the friction force can assume any value within a certain range. In the literature, numerous models of dry friction are presented, and most of them assume a biunivocal dependency of the friction force with respect to relative velocity. The dynamic system considered here is a tilted rod with spherical ends, initially at rest. Dry friction forces are evident at the contact point with the horizontal plane. The ball–plane contact highlights the rolling friction or/and sliding friction. The problem is theoretically solved after adopting one of the two cases of friction: rolling friction or sliding friction. The nonlinear differential equations of motion have been derived, along with expressions for the magnitude of the normal reaction and the friction force. The results of the model are displayed graphically for three different sets of values for the coefficient of friction. It is revealed that there is a critical value of the coefficient of friction that determines the transition from rolling to sliding regimes. To validate the theoretical model, dynamic simulation software was utilised. The excellent match between the theoretical predictions and the results from the numerical simulation confirms the accuracy of the proposed analytical solution. Full article

This study aimed to investigate effects of long-term probiotic supplementation on gut microbiota and growth performance in health weaned piglets. The non-probiotic group (N-PrB) was fed only a basal diet, while the probiotic group (PrB) was fed a basal diet + probiotic combination (E. faecium 1.6 × 10⁸ CFU/g, B. subtilis 2.0 × 10⁸ CFU/g, S. cerevisiae 3.0 × 10⁸ CFU/g). The probiotics combination was provided to the PrB, mixing with the basal diet in 5 kg/ton. As a result, the PrB exhibited significantly improved weight gain compared to the N-PrB (p = 0.00991). In the gut microbiome analysis, the PrB exhibited a significant increasing tendency of α-diversity compared to those of the N-PrB (p < 0.01). In the bacterial relative abundance changes in bacteria comprising the gut microbiota, Ruminococcaceae (p = 0.00281) and Prevotella (p = 0.00687) tended to significantly increase in the PrB, but decreased in the N-PrB. The Eubaterium coprostanoligenes group exhibited an increasing tendency in both groups, but tended to increase more significantly in the PrB compared to the N-PrB (p = 0.00681). Muribaculaceae tended to significantly increase in the N-PrB, but decreased in the PrB (p = 0.002779). In this study, significant differences on the gut microbiome were found according to the probiotics supplementation in the weaned piglets and these gut microbiome changes appeared to improve the growth performance. Full article

This paper offers a brief yet comprehensive comparative analysis of historical and contemporary racial authoritarian violence in the United States and Brazil. Utilizing Black feminist historian and literary scholar Saidiya Hartman’s theorization of the “afterlife of slavery” and Michael Dawson’s linked fate, I examine how the processes of racialization and the racial logics of subordination have and continue to shape the contours of Black life in the United States and in Brazil. Moreover, in this work, I interrogate the afterlife of George Floyd and the afterlives of Black Brazilian victims and survivors of racial authoritarian violence; the political, transnational, and symbolic impacts of Floyd’s death; and Diasporic understandings of linked fate on racial authoritarian violence between Black communities in the United States and in Brazil. Full article

Visits to forests can improve human health and well-being through various mechanisms. They can support the immune system, promote physical activity, and restore stress and attention fatigue. Questions remain about how perceived qualities in forests important to support such salutogenic, i.e. health-promoting, benefits can be represented in forest simulation tools to allow quantitative analyses, e.g., long-term projections or trade-off analyses with other forest functions, such as biodiversity conservation, wood production, etc. Questions also remain about how different forest management regimes might impact such perceived qualities in forests. Here, we defined three types of salutogenic forest characteristics (SFCs), referred to as Deep, Spacious, and Mixed forest characteristics, respectively. We did so by using the perceived sensory dimension (PSD) model, which describes and interrelates more fundamental perceived qualities of recreational outdoor environments that are important to support people’s health and well-being. We identified proxy variables for the selected PSD models in boreal forest stands and compared the effect of five different management regimes on both individual PSD models and the derived SFCs when projecting a forest landscape 100 years into the future. Our results suggest combinations of protection (set-aside) and variations of continuous cover forestry as the most promising strategies to achieve these salutogenic properties in the long-term future. Depending on the SFC in focus and the specific management regime used, between 20% and 50% of the landscape could support associated properties in the long term (100 years). This might impact how forests should be managed when salutogenic outcomes are considered alongside, e.g., wood production and other forest contributions. Full article

In the modern world, the evolution of the internet supports the automation of several tasks, such as communication, education, sports, etc. Conversely, it is prone to several types of attacks that disturb data transfer in the network. Efficient attack detection is needed to avoid the consequences of an attack. Traditionally, manual attack detection is limited by human error, less efficiency, and a time-consuming mechanism. To address the problem, a large number of existing methods focus on several techniques for better efficacy in attack detection. However, improvement is needed in significant factors such as accuracy, handling larger data, over-fitting versus fitting, etc. To tackle this issue, the proposed system utilized a Random Grove Blend in Weighted MLP (Multi-Layer Perceptron) Layers to classify network attacks. The MLP is used for its advantages in solving complex non-linear problems, larger datasets, and high accuracy. Conversely, it is limited by computation and requirements for a great deal of labeled training data. To resolve the issue, a random info grove blend and weight weave layer are incorporated into the MLP mechanism. To attain this, the UNSW–NB15 dataset, which comprises nine types of network attack, is utilized to detect attacks. Moreover, the Scapy tool (2.4.3) is utilized to generate a real-time dataset for classifying types of attack. The efficiency of the presented mechanism is calculated with performance metrics. Furthermore, internal and external comparisons are processed in the respective research to reveal the system’s better efficiency. The proposed model utilizing the advantages of Random Grove Blend in Weighted MLP attained an accuracy of 98%. Correspondingly, the presented system is intended to contribute to the research associated with enhancing network security. Full article