Vulpes Vulpes Research Articles

Apex predators can structure ecosystems through trophic cascades: Linking the frugivorous behaviour and seed dispersal patterns of mesocarnivores

Abstract Current global change scenarios demand knowledge on how anthropogenic impacts affect ecosystem functioning through changes in food web structure. Frugivorous mesocarnivores are a key link in trophic cascades because, while their abundance and behaviour are usually controlled by apex predators, they can provide high‐quality seed‐dispersal services to plant communities. Thus, the recent rewilding of large carnivores worldwide can trigger cascading effects for plants. We investigated the top‐down effects of an apex predator (Iberian lynx Lynx pardinus) on seed‐dispersal services mediated by two mesocarnivore species (red fox Vulpes vulpes and stone marten Martes foina) at the plant community level by comparing areas with and without lynx in a Mediterranean mountain range in Southern Spain. We collected scats of mesocarnivores (n = 1575) to assess frugivory and seed dispersal of 15 plant species over two consecutive fruiting seasons and two habitat types (open and forest). Specifically, we assessed the effect of lynx presence on (i) seed occurrence and fleshy‐fruit biomass per scat, (ii) number of scats containing seeds and (iii) diversity of dispersed seeds. The quantity and diversity of dispersed seeds drastically decreased under predation risk for both mesocarnivore's species. Seed dispersal by stone martens was negatively affected by the presence of lynx, with a marked reduction in the number of scats with seeds (93%) and the diversity of dispersed seeds (46%). Foxes dispersed 68% fewer seeds in open habitats when coexisting with lynx, probably leading to differential contributions to seed‐dispersal effectiveness among habitats. Our study reveals a novel trophic cascade from apex predators to plant communities. The behavioural responses of frugivorous mesocarnivores to predation risk and the reduction in the intensity of their faecal deposition pattern are probably related to their lower abundance when co‐occurring with apex predators. While rewilding apex predators is a successful conservation tool, attention should be paid to cascading effects across food webs, particularly where frugivore megafauna is missing and mesocarnivores provide unique services to plants. Read the free Plain Language Summary for this article on the Journal blog.

Urbanization does not affect red foxes’ interest in anthropogenic food, but increases their initial cautiousness

Abstract Human presence and activities have profoundly altered animals' habitats, exposing them to greater risks but also providing new opportunities and resources. The animals’ capacity to effectively navigate and strike a balance between risks and benefits is crucial for their survival in the Anthropocene era. Red foxes (Vulpes vulpes), adept urban dwellers, exhibit behavioral plasticity in human-altered environments. We investigated variations in detection frequency on trail cameras and the behavioral responses (explorative, bold and fearful) of wild red foxes living along an urbanization gradient when exposed to a metal bin initially presented clean and then filled with anthropogenic food. All fox populations displayed an increased interest and similar explorative behavioral responses towards the anthropogenic food source, irrespective of the urbanization gradient. Despite no impact on explorative behaviors, foxes in more urbanized areas initially showed heightened fear towards the empty bin, indicating increased apprehension toward novel objects. However, this fear diminished over time, and in the presence of food, urban foxes displayed slightly reduced fear compared to their less urban counterparts. Our results highlight foxes' potential for adaptability to human landscapes, additionally underscoring the nuanced interplay of fear and explorative behavioral response of populations living along the urbanization gradient.

Successful invasion: camera trap distance sampling reveals higher density for invasive raccoon dog compared to native mesopredators

AbstractMonitoring population parameters of invasive species gains importance as these species continue to expand all over the world. Monitoring of invasive mammalian mesopredators is, however, complicated due to their nocturnal and secretive behaviour. In the European Union, the most common invasive mesopredator is the raccoon dog (Nyctereutes procyonoides), which causes concerns for native species, such as endangered waterfowl that may be subject to nest predation. We studied the density of mesopredators in southern Finland with wildlife cameras, using methodology of distance sampling. We deployed in total of 175 camera traps around 11 (spring 2020) and 16 (spring 2021) lakes or wetlands. We inferred densities for raccoon dogs, and for native mesopredators the red fox (Vulpes vulpes) and the European badger (Meles meles) for comparison. Raccoon dogs were found to have higher overall as well as site-specific densities (about 3.7 ind./km2) than badgers (1.2 ind./km2) and red foxes (0.6 ind./km2). The raccoon dogs also were present at every study wetland, while badgers were not found at all sites. The red fox showed more diurnal activity compared to raccoon dogs and badgers. Camera trap distance sampling enabled us to provide a density estimates on a rather small spatial and temporal scale for species of similar size and movement speed. It could therefore prove valuable as a long-term monitoring option, as climate trends are likely to further enable raccoon dog expansion. Currently this invasive species appears to be the most common mesopredator around wetlands in the southern boreal zone of southern Finland.

Lynxes and foxes among hyenas, bears and humans. Unit 3 of the Cova del coll Verdaguer Upper Pleistocene site (Barcelona, Iberian Peninsula)

Zooarchaeological and palaeontological assemblages, especially those located in karst cavities, are usually the product of the activity of several taphonomic biological agents. This is also the case of the Upper Pleistocene site of Cova del Coll Verdaguer (Barcelona, Iberian Peninsula), where hyenas accumulated most of the ungulates, bears used the cave to hibernate and for birthing cubs, and humans occasionally visited the cave. The main aim of this study is to investigate the role played by medium-sized mammalian carnivores in the formation of Unit 3 (the Sala Sal de Llop chamber). For this purpose, we analysed Lynx pardinus and Vulpes vulpes remains, on the one hand, and leporid remains, on the other, applying different taphonomic (breakage and surface modifications) zooarchaeological (skeletal parts frequencies, age at death) and spatial methods (GIS, geostatistics, refits). Regarding medium-sized carnivores, the results indicate a predominance of adult individuals, a fairly complete anatomical representation (especially in the case of the lynx), the refitting of several elements (in the case of the lynx, many of them clustered in the same area), and the presence of tooth marks on some remains. This data points to the natural death of these animals inside the cave, and suggests they were subsequently scavenged by other carnivores. With respect to leporids, adult individuals predominate, the most abundant elements are innominate bones and those from the distal segment of the appendicular skeleton, and there is evidence of carnivore damage on several remains. In accordance with these results, the leporid assemblage is interpreted mainly as a non-ingested assemblage caused by the feeding activity of the Iberian lynx and, to a lesser extent, the red fox. Thus, the combination of all these analyses indicates that the medium-sized terrestrial carnivores did not play a merely passive role, but were also accumulators and modifying agents, at least in terms of the leporid remains. Although ungulates are not the focus of this study, we have also discussed the potential role of Iberian lynx and red fox in accumulating and modifying them. This work adds to previously published studies indicating that Cova del Coll Verdaguer is the product of mixed occupations of different carnivore taxa, suggesting that lynxes and foxes used the cave as a safe place to rest, transport their prey and consume it. Therefore, this study will shed more light on the relationships between human groups and different carnivore taxa at Cova del Coll Verdaguer and, by extension, in the European Upper Pleistocene, demonstrating that the study of fossil collections can contribute significantly towards extending our knowledge on past carnivore and human behaviour.

Matheuristics for mixed-model assembly line balancing problem with fuzzy stochastic processing time

Our work aims to investigate methods for solving the mixed-model assembly line balancing problem (MALBP) under uncertainty with the objective of minimizing the number of workstations. Specifically, we model task processing time as fuzzy stochastic variables (FRVs) due to the inherent uncertainties and variations in the manufacturing environment. Additionally, we introduce a ranking method for FRVs and propose a mathematical model to address MALBP. The recently developed Red Fox Optimization (RFO) algorithm is also discretized for the first time to support solving this problem. Finally, matheuristic algorithms combine a metaheuristic such as the popular Genetic Algorithm (GA), Particle Swarm Optimization (PSO), or the Discretized Red Fox Optimization (DRFO) algorithm with the Mixed-Integer Programming (MIP) model to generate the best solution in a reasonable time. Our comparative results demonstrate that the GA-MIP combination outperforms the others in both objective value and computational time.

The low survival rate of European hare leverets in arable farmland: evidence from the predation experiment.

The low survival rate of leverets may significantly contribute to steep population declines and slow recovery of European hares (Lepus europaeus). However, the leveret survival rate in farmlands with different landscape structures is poorly understood, and the existing evidence comes mainly from Western Europe. In this study, we explored the survival of leveret hare dummies along linear semi-natural habitats in homogeneous Central European arable farmland during the main part of the European hare reproduction period (March-April) in 2019 and 2020. The survival rate of hare leverets during the 14-day period was only 22.2%, and all predation events were recorded during the first six days of the experiment. Mammalian predators were responsible for 53.1% of predation events, avian predators for 40.8%, and agricultural operations for 6.1%. The red fox (Vulpes vulpes) was the dominant predator in our study area and was the primary cause of leveret dummy mortality (32.7%), but it also had the highest use-intensity and visit frequency of all of the study plots. Predation by avian predators was associated with patches of lower vegetation height and cover (such as plowed fields) and during daylight hours, whereas the opposite was true for mammalian predators. We propose that improving the habitat quality of arable landscapes by increasing the proportion and quality of extensively used non-farmed habitats (e.g., set-asides, wildflower areas, extensive meadows, fallow land, and semi-natural habitats on arable land) providing cover and shelter for leverets could be an effective management measure for reducing predation risk on leverets.

Understanding intra-guild dynamics: Do presence of red foxes and yellow-throated martens shape ecology of leopard cats in the lesser Himalayas?

Understanding intra-guild dynamics: Do presence of red foxes and yellow-throated martens shape ecology of leopard cats in the lesser Himalayas?

Ptičja influenca u divljih kanida

The risk of cross-species transmission of infectious diseases and zoonoses has increased due to the adaptive evolution of pathogens and anthropogenic landscape changes. A current example is the avian influenza (AI) virus, which can infect not only avian species but also mammals. In these species, infections are often associated with severe neurological symptoms. AI viruses are primarily not well adapted to mammalian hosts and are not efficiently transmitted among them. To accomplish this, AI viruses must acquire adaptations or mutations that contribute to replication efficiency and virulence in mammals. The exact combination and interaction of mutations that result in optimal adaptation to mammals is still unknown and may vary between host species and virus subtypes. The globally increasing number of infected birds with highly pathogenic AI (HPAI) increases the likelihood of contact between birds and mammals, especially wildlife. One reason for the adaptation of HPAI to mammals is theexposure of wild mammals to infected birds or their carcasses. According to the current data, wild canids, such as red foxes, are among the most infected mammals. However, infections caused by neurotropic viruses, as well as HPAI, have been scarcely studied or not at all in jackals. Since jackals are scavengers that have spread rapidly in Europe and Croatia in recent years, surveillance of AI virus infection in these canids is of the utmost importance. Furthermore, interactions between wild carnivores and domestic animals are of concern, as infections with HPAI pose a public health threat due to the increased risk of mammalian adaptation.

Effect of skull morphology on fox snow diving

Certain fox species plunge-dive into snow to catch prey (e.g., rodents), a hunting mechanism called mousing. Red and arctic foxes can dive into snow at speeds ranging between 2 and 4 m/s. Such mousing behavior is facilitated by a slim, narrow facial structure. Here, we investigate how foxes dive into snow efficiently by studying the role of skull morphology on impact forces it experiences. In this study, we reproduce the mousing behavior in the lab using three-dimensional (3D) printed fox skulls dropped into fresh snow to quantify the dynamic force of impact. Impact force into snow is modeled using hydrodynamic added mass during the initial impact phase. This approach is based on two key facts: the added mass effect in granular media at high Reynolds numbers and the characteristics of snow as a granular medium. Our results show that the curvature of the snout plays a critical role in determining the impact force, with an inverse relationship. A sharper skull leads to a lower average impact force, which allows foxes to dive head-first into the snow with minimal tissue damage.

Comprehensive Quality Evaluation Model of College Students Based on Deep Learning

Evaluating college students' quality in higher education institutions is significant for promoting enhancement and innovation in teaching and learning practices. Conventional evaluation strategies mainly depend on subjective evaluation, which limits their ability to capture the multifaceted characteristics of students. In this study, we developed a distinct deep learning (DL) architecture by combining the Convolutional Deep Belief Network and Red Fox Optimization (CDBN-RFO) to evaluate college students' quality. Initially, a database containing academic performance records, extracurricular activities, and other relevant information is collected and fed into the system. Then, the database was preprocessed to make it an appropriate format for subsequent analysis. Further, the proposed CDBN-RFO was created, and the CDBN was trained using the preprocessed database to understand the patterns and relations within data for evaluating college students' quality. Subsequently, the RFO approach was deployed to fine-tune the CDBN hyperparameters to their finest range, which increases the overall system performance. Subsequently, the RFO optimized the CDBN training process by fine-tuning its parameters to the optimal range, enhancing overall evaluation performance. The developed framework was modeled using Python software, and the results were analyzed, including accuracy, error, computational time, etc. Also, a comparative analysis was done with conventional algorithms, which validated that the proposed strategy outperformed them in accuracy.

Heating load prediction in buildings using decision tree machine learning method

In recent years, the burgeoning imperative of energy-efficient building management practices has surged dramatically, underscoring an urgent mandate for comprehensive studies that integrate cutting-edge optimization algorithms with precise heating load forecasting techniques. These studies are not merely endeavors; they represent concerted efforts to increase building energy efficiency and address mounting concerns regarding sustainability and resource utilization. In the intricate domain of heating, ventilation, and air conditioning (HVAC) systems, energy optimization challenges are being meticulously confronted through rigorous exploration and the application of innovative problem-solving methodologies. This pioneering study introduces groundbreaking methodologies by seamlessly integrating two state-of-the-art optimization algorithms— the Red Fox Optimization and the Golden Eagle Optimizer— with the Decision Tree model. This fusion is aimed at enhancing the accuracy of heating load predictions and streamlining HVAC system optimization processes, marking a significant leap toward achieving heightened energy efficiency and operational efficacy in building management practices. The study emphasizes the significance of precise heating load prediction in advancing energy efficiency, realizing cost savings, and fostering environmental sustainability in building management. Furthermore, it delves into the multifaceted impact of various building features on heating load, encompassing variables such as glazing area, orientation, height, relative compactness, roof area, surface area, and wall area. These insights furnish actionable intelligence for refined decision-making processes in both building design and operation. Based on the results, the DT single model experienced the weakest performance among the three models, with R2 = 0.975 and RMSE = 1.608. The model DTFO (DT + FOX) achieves an extraordinary R2 value of 0.996 and RMSE value of 0.961 for heating load prediction, surpassing the performance benchmarks set by other models. This achievement holds considerable promise for aiding engineers in crafting energy-efficient buildings, particularly within the swiftly evolving landscape of smart home technologies.

Economic valuation of a mesocarnivore's impact management.

Red foxes (Vulpes vulpes) have interacted with humans during their common history. We used a contingent valuation method to assess the economic value of the management of this mesocarnivore's negative impacts. We carried out face-to-face interviews with 746 Greek residents, using a multiple-bounded discrete choice approach to estimate willingness to pay (WTP) for red fox management under three impact situations: attack domestic animals, reduce game, carry disease. About 51.9%, 33.0%, and 81.1% of the respondents stated a mean WTP of €34.1, €44.9, and €72.1 for each situation, respectively. The total annual amounts of €18.7 million, €15.7 million, and €61.7 million could be collected from the target population for red fox management when they attack domestic animals, reduce game, and carry disease, respectively. Attitudes and likeability toward foxes were negatively associated while knowledge about foxes and fear of them were positively associated with WTP. The younger, richer, less educated, rural, farmers, hunters, and pet owners were generally more willing to pay for red fox management across situations. Females were more willing to pay for managing predation on domestic animals, while males were more willing to pay for managing predation on game. Our findings showed that the Greek residents highly value the management of red foxes in all impact situations and would be valuable for further advising the management process.

Following urban predators – long‐term snow‐tracking data reveals changes in their abundance and habitat use

AbstractUrban habitats differ from natural environments, however some predatory species have become established in cities across the globe. The aim of our study was to compare the occurrence of the red fox and the stone marten in Warsaw during three time periods (1976–1978, 2005–2008, 2015–2021) and in different habitats. Generalized linear models were used to show factors affecting the density indices of these two species (i.e., frequency of occurrence of tracks of each species recorded during snow tracking on linear transects). The frequency of occurrence of tracks of these two species on transects increased over time and was explained by habitat type and distance from the city centre. The frequency of fox tracks was higher in more‐natural habitats located far from the city centre. In the first period (1976–1978), this species was recorded only in forests and riparian areas. In the last period (2015–2021), its tracks were recorded frequently in built‐up areas and cemeteries. From the beginning of the first period, the stone marten was recorded in a wider range of habitats than the fox and it colonized all habitat types in the subsequent periods, but a statistically significant increase was observed only for cemeteries. The frequency of occurrence of stone marten tracks was lower than that of red fox tracks in most natural and seminatural habitats (forests, parks, riparian areas). No relationship between the occurrence of the red fox and the stone marten was found. We speculate that the growth of the urban red fox numbers was driven by an increase in the national population as a result of anti‐rabies vaccinations. In turn, the stone marten, being a synanthropic species, was present in the city centre from the beginning of the study, but it now occurs in a wider range of habitats.

Implications of tactile enrichment on the behaviour and whisker movements of four species of carnivorans

Caniformia include a range of aquatic, semi-aquatic and terrestrial species, which reveal diversity in their whisker arrangements and shape. Whisker movements play a crucial role in the perception of tactile information, allowing whiskered mammals to distinguish between shapes, sizes, and textures. Despite the significance of whisker movements in sensory perception, few studies have focussed on measuring whisker movements during tactile sensing. Whisker enrichment tasks have the potential to expand behavioural repertoires of animals in captivity and reduce stereotypical behaviours. However, despite whiskers being essential in guiding foraging and exploration in many mammalian species, tactile whisker enrichment tasks are rare. Here, we utilised a novel tactile enrichment device to investigate the whisker movements in four Caniform species in captivity, including two pinnipeds- South African fur seals (Arctocephalus pussilus) and harbour seals (Phoca vitulina), a mustelid – Eurasian otter (Lutra lutra), and a canid – red fox (Vulpes vulpes) during a texture discrimination task. This study is the first to explore the impact of tactile enrichment on the behavioural repertoire of caniforms in captivity and provides the first insight of whisker movements in South African fur seals. The introduction of the tactile enrichment device did not increase the behavioural repertoire, nor did it lead to an increase in stereotypical behaviours or aggression in any of the species. However, it did successfully encourage natural whisker movements in the pinnipeds and otter. The whisker amplitude measure was especially high in the South African fur seals. We suggest that such a complex, discrimination-based enrichment task might only be feasible for more trainable caniforms, such as pinnipeds, rather than more neophobic species, such as the red fox, which did not interact with the enrichment device throughout the study. Therefore, while our enrichment device increased natural whisker movements, an even simpler foraging task might encourage tactile sensing without the requirement for training, making tactile whisker enrichment available to a wider group of species.

Missing History of a Modern Domesticate: Historical Demographics and Genetic Diversity in Farm-bred Red Fox Populations.

The first record of captive bred red foxes (Vulpes vulpes) dates to 1896, when a breeding enterprise emerged in the provinces of Atlantic Canada. Because its domestication happened during recent history, the red fox offers a unique opportunity to examine the genetic diversity of an emerging domesticated species in the context of documented historical and economic influences. In particular, the historical record suggests that North American and Eurasian farm-bred populations likely experienced different demographic trajectories. Here, we focus on the likely impacts of founder effects and genetic drift given historical trends in fox farming on North American and Eurasian farms. A total of 15 mitochondrial haplotypes were identified in 369 foxes from 10 farm populations that we genotyped (n=161) or that were previously published. All haplotypes are endemic to North America. Although most haplotypes were consistent with eastern Canadian ancestry, a small number of foxes carried haplotypes typically found in Alaska and other regions of western North America. The presence of these haplotypes supports historical reports of wild foxes outside of Atlantic Canada being introduced into the breeding stock. These putative Alaskan and Western haplotypes were more frequently identified in Eurasian farms compared to North American farms, consistent with historical documentation suggesting that Eurasian economic and breeding practices were likely to maintain low-frequency haplotypes more effectively than in North America. Contextualizing inter- versus intra-farm genetic diversity alongside the historical record is critical to understanding of the origins of this emerging domesticate and the relationships between wild and farm-bred fox populations.

Multi-Objective Dynamic Economic and Emission Generation Scheduling of Coordinated Power System Considering Renewable Energy Sources and Pumped Storage Hydro Plants via Fuzzy Surrogate-Assisted Coronavirus Herd Immunity Optimization

Globally, the power generation from renewable energy sources (RES) has received considerable attention to reduce pollutant emissions and the total operating costs of power generation. In this context, this study aims to extend the multi-objective dynamic economic and emission dispatch (MODEED) problem by incorporating RES and pumped storage hydro plants. The complex constrained MODEED problem is solved by a fuzzy surrogate-assisted coronavirus herd immunity optimization (FSACHIO) algorithm in which a self-adaptive speed factor and Lévy flight mechanism are utilized to ensure populace diversity, prevent premature convergence and achieve an ideal stability among the exploration and exploitation of the algorithm. Surrogate worth tradeoff methodology is used to discover a solution that provides the optimal balance between the objectives such as operating expenses and emission pollutants. The performance of FSACHIO algorithm is validated on a small-scale and a large-scale test systems, involving 10-unit, and 40-unit test systems, and compared with that of the coronavirus herd immunity optimization, red fox optimizer, Remora optimization algorithm, and other erstwhile approaches. Besides, a fuzzy constraint handling method based on a dominance relationship is integrated to fulfill the restrictions of the MODEED problem. The simulation results reveal that: (i) the operating costs and emissions are reduced by 173785.54 $/day and 2992.1848 lb/day in the small-scale test system and by 6383.9903 $/day and 216631.4877 lb/day in the large-scale test system, respectively for the MODEED problem with the presence of RES and pumped storage hydro plants; (ii) the suggested approach may offer a well-distributed Pareto-optimal frontier and superior tradeoffs among the operating expenses and pollution objectives in comparison to the other approaches.

Distribution of Himalayan Red Fox (Vulpes vulpes) A New Neighbor to Humans in Lahaul & Spiti, Himachal Pradesh

Distribution of Himalayan Red Fox (Vulpes vulpes) A New Neighbor to Humans in Lahaul & Spiti, Himachal Pradesh

Carnivore guild utilization of hunter‐provided food sources in boreal forest

Scavenging is an alternative foraging strategy to predation for many carnivore species, as they shift between predation and scavenging in response to changes in resource availability. The use of carrion may lead to interspecific competition and is thus influenced by a risk–reward trade‐off to balance coexistence with guild‐members, where smaller species are expected to be more vigilant due to their vulnerability to larger competitors. We used cameras to investigate the utilization of viscera from the annual moose Alces alces hunt by four sympatric carnivore species: wolf Canis lupus, wolverine Gulo gulo, red fox Vulpes vulpes and pine marten Martes martes in south–central Scandinavia, in relation to body size and habitat. Red foxes had highest probability of visiting viscera sites in both open and forested habitats. Visits by both red foxes and pine martens were longer in open habitats, while number of visits or activity did not differ between habitats. For pine martens, the probability of visiting viscera sites was twice as high in forest compared to open habitat; consequently, red foxes showed the highest overall use of viscera. Red foxes were most vigilant, especially in open habitat, whereas wolverines and pine martens spent a higher proportion of time feeding. Increased vigilance of red foxes facilitates extended resources use in open habitat, while for pine martens, the risk–reward decision occurs before leaving forest cover and entering open habitats. Viscera were not used to a large extent by wolves or wolverines. Wolves are generally less prone to scavenging and wolverines probably use other food resources, more suitable for caching. Overall, competition did not prevent use of viscera, probably due to small‐scale temporal segregation and limited use by the larger carnivores. Consequently, this pulse of human‐subsidized food resources before winter may have important implications for the smaller facultative scavengers.Keywords: carrion use, interspecific competition, pine marten, red fox, wolf, wolverine

Automatic Testing Technology of BTB Liquid Crystal Display Advanced Fault Detection in Smart Meter for Smart Machine

In smart meter technology, the reliability of Backplane to Bezel (BTB) Liquid Crystal Displays (LCDs) is crucial for efficient functioning within intelligent grid systems. Defects in these LCD screens can significantly impact overall smart meter performance, necessitating effective detection methods for proper management and utilization. Current detection approaches, which combine manual and automatic methods based on machine vision, have shown unsatisfactory performance. This research addresses this challenge by proposing a novel method for advanced fault detection in BTB LCDs of smart meters, Automatic Testing Technology of BTB Liquid Crystal Display Advanced Fault Detection in Smart Meter for smart machine (BTB-LCD-FD- MCDSGAN) is proposed. The study begins by collecting datasets specifically tailored for LCD screen localization and defect detection. To enhance data quality, a Window Adaptive Extended Kalman Filter (WAEKF) is applied during preprocessing for noise removal. Feature extraction follows, utilizing Parameterized Multi Synchrosqueezing Transforms (PMST) with a primary focus on Gray Level Co-occurrence Matrix features. These extracted features serve as input for classification by a Multimodal Contrastive Domain Sharing Generative Adversarial Network (MCDSGAN), categorizing defects into five types likes normal display, no display, abnormal display, liquid crystal rupture, and incomplete display. Furthermore, the proposed method optimizes the MCDSGAN weight parameter using the Red Fox Optimization Algorithm (RFOA) to achieve accurate LCD fault defect prediction. The entire approach is implemented in Python, performance metrics likes accuracy, precision, recall, F-score, computational time are thoroughly analyzed. Performance of proposed BTB-LCD-FD-MCDSGAN approach attains 20.89%, 33.67% and 25.98% high accuracy, and 17.98%, 23.78% and 33.45% higher recall compared with existing methods such as automatic detection of display defects for smart meters depend on deep learning (AD-AM-DL), deep learning-enabled image content-adaptive field sequential color LCDs by mini-LED backlight (DL-AFSC-LCD) and new multi category defect detection method depend on convolutional neural network technique for TFT-LCD panels (MDF-CNN-LCD), methods respectively.

Bridging the Gap

Effective organization and retrieval of news content are heavily reliant on accurate news classification. While the mountainous research has been conducted in resourceful languages like English and Chinese, the researches on under-resourced languages like the Kurdish language are severely lacking. To address this challenge, we introduce a hybrid approach called RFO-CNN in this paper. The proposed method combines an improved version of red fox optimization algorithm (RFO) and convolutional neural network (CNN) for finetuning CNN’s parameters. Our model’s efficacy was tested on two widely used Kurdish news datasets, KNDH and KDC-4007, both of which contain news articles classified into various categories. We compared the performance of RFO-CNN to other cutting-edge deep learning models such as bidirectional long short-term memory networks and bidirectional encoder representations from transformers (BERT) transformers, as well as classical machine learning approaches such as multinomial naive bayes, support vector machine, and K-nearest neighbors. We trained and tested our datasets using four different scenarios: 60:40, 70:30, 80:20, and 90:10. Our experimental results demonstrate the superiority of the RFO-CNN model across all scenarios, outperforming the benchmark BERT model and other machine learning models in terms of accuracy and F1-score.