Competency Assessment and Factors Associated with It among Health Professionals at Debre Birhan Health Science College

Background: Competency assessment has a key role in the assurance of quality professionals in every discipline. Competency assessment is a method by which we can verify that our employees are competent to perform tasks timely. To derive the greatest benefit from the application of competency assessment in the health professionals, we must be sure that we are addressing areas where our efforts are utilized to optimize the patient care. There is no research done on the competency assessment so far except the report send by Technical Vocational and Educational Training. Objectives: To assess knowledge, attitude and practice of health professionals towards competency assessment and factors were associated with competencies at Debre Birhan Health Science College, 2013. Methods: A facility based cross sectional study was conducted using interview technique. Study participants were all students taking competency assessment in all departments at Debre Berhan Health Science College in two rounds. The percentage of participants who were competent was computed. Factors associated with competency were assessed using bivariate and multivariable logistic regression. Results: Among the total participants (n = 287), (57.8 percent) were female. Among the (n = 287) study participants, 226 (78.7%) were competent. Of these, 88.5% of the candidates were learned at governmental institution. Predictors of competency were department of the respondent AOR [95%];0.05 [0.01, 0.45], expectation of the results [AOR (95% CI) = 0.13 (0.02, 0.85)], number of competency taken [AOR (95% CI) = 0.11 (0.01, 0.88)] and candidates’ knowledge of their right and obligations AOR [95%];3.7 [1.3, 10.3]. Conclusions: Significant numbers of candidates were not yet competent due to various factors at different level. Therefore, comprehensive work should be done on the instructors, students and the center to make the candidates competent.

Perceived stress among staff in Saudi Arabian dental colleges before and after an accreditation process: A cross-sectional study

BACKGROUND Accreditation processes are extensively employed to guarantee the quality of higher education institutions.However,this process can potentially generate a stressful atmosphere for staff,thus impacting their ability to perform optimally under pressure.AIM To examine the knowledge of the National Commission for Academic Assessment and Accreditation(NCAAA)and its effects on perceived stress among dental college staff before and after the program accreditation process.METHODS The present cross-sectional questionnaire-based study included 300 employees from three dental colleges.The same employees had to fill out the questionnaire 1 mo after the NCAAA process.RESULTS Approximately 51.33%of the included employees believed that NCAAA is essential to attract quality students to join the program before and after the program.A total of 44.67%felt that their stress was high before,and 31.33%had low stress levels before and after NCAAA.These findings were statistically significant(P≤0.05).CONCLUSION NCAAA raised the prestige of the institution and specific programmes and increased prospects to attract better students,staff,and money,according to the employees.In addition to their needed teaching,research,and other service responsibilities,this work requires a tremendous amount of faculty effort and may cause them stress.

Health Related Physical Fitness Measures: Reference Values and Predictive Equations for Saudi Female College Students

Health related-physical fitness (HRPF) is critical for maintaining and enhancing health and quality of life. Purposes: To estimate the reference values and predictive equations for frequently used clinical field HRPF measures in a sample of Saudi female college students aged 18 - 24 years. Methods: In this cross-sectional study, body fat percentage (BF %) was estimated. Curl-up test (CUT) and sit and reach test (SRT) were applied in 216 students. The Queen’s College Step Test (QCST) was used to predict maximal oxygen consumption (VO2 max). Physical activity (PA) level was also measured using International Physical Activity Questionnaire (IPAQ). Results: The mean of BF %, SRT, CUT, and predicted VO2 max were 23.98% ± 6.13%, 17.10 ± 7.50 cm, 28.17 ± 7.72 number/min, and 39.58 ± 4.01 ml/kg/min respectively. There was no significant effect of age on all HRPF measures except for BF % (F (6,215) = 3.25, p (6,215) = 4.01, p strated that BMI was the predictor for BF % and SRT and explained 65% and 4% of total variance respectively. IPAQ score, age, and height were the predictors of CUT counting 17% of total variance. While, BMI and IPAQ score were the predictors for VO2 max and explained 13% of the total variance. Conclusion: Reference values can be used clinically in the evaluation of HRPF, in the rehabilitation process as well as in designing a program to improve the HRPF for female college students with consideration of age, height, BMI, and PA level for a particular population.

Single-cell transcriptomic atlas of goat ovarian aging

Background The ovaries are one of the first organs that undergo degenerative changes earlier in the aging process,and ovarian aging is shown by a decrease in the number and quality of oocytes.However,little is known about the molecular mechanisms of female age-related fertility decline in different types of ovarian cells during aging,especially in goats.Therefore,the aim of this study was to reveal the mechanisms driving ovarian aging in goats at single-cell resolution.Results For the first time,we surveyed the single-cell transcriptomic landscape of over 27,000 ovarian cells from newborn,young and aging goats,and identified nine ovarian cell types with distinct gene-expression signatures.Functional enrichment analysis showed that ovarian cell types were involved in their own unique biological processes,such as Wnt beta-catenin signalling was enriched in germ cells,whereas ovarian steroidogenesis was enriched in granulosa cells(GCs).Further analysis showed that ovarian aging was linked to GCs-specific changes in the antioxidant system,oxidative phosphorylation,and apoptosis.Subsequently,we identified a series of dynamic genes,such as AMH,CRABP2,THBS1 and TIMP1,which determined the fate of GCs.Additionally,FOXO1,SOX4,and HIF1A were identified as significant regulons that instructed the differentiation of GCs in a distinct manner during ovarian aging.Conclusions This study revealed a comprehensive aging-associated transcriptomic atlas characterizing the cell typespecific mechanisms during ovarian aging at the single-cell level and offers new diagnostic biomarkers and potential therapeutic targets for age-related goat ovarian diseases.

The early life immune dynamics and cellular drivers at single-cell resolution in lamb forestomachs and abomasum

Background Four-chambered stomach including the forestomachs(rumen,reticulum,and omasum)and abomasum allows ruminants convert plant fiber into high-quality animal products.The early development of this four-chambered stomach is crucial for the health and well-being of young ruminants,especially the immune development.However,the dynamics of immune development are poorly understood.Results We investigated the early gene expression patterns across the four-chambered stomach in Hu sheep,at 5,10,15,and 25 days of age.We found that forestomachs share similar gene expression patterns,all four stomachs underwent widespread activation of both innate and adaptive immune responses from d 5 to 25,whereas the metabolic function were significantly downregulated with age.We constructed a cell landscape of the four-chambered stomach using single-cell sequencing.Integrating transcriptomic and single-cell transcriptomic analyses revealed that the immune-associated module hub genes were highly expressed in T cells,monocytes and macrophages,as well as the defense-associated module hub genes were highly expressed in endothelial cells in the four-stomach tissues.Moreover,the non-immune cells such as epithelial cells play key roles in immune maturation.Cell communication analysis predicted that in addition to immune cells,non-immune cells recruit immune cells through macrophage migration inhibitory factor signaling in the forestomachs.Conclusions Our results demonstrate that the immune and defense responses of four stomachs are quickly developing with age in lamb's early life.We also identified the gene expression patterns and functional cells associated with immune development.Additionally,we identified some key receptors and signaling involved in immune regulation.These results help to understand the early life immune development at single-cell resolution,which has implications to develop nutritional manipulation and health management strategies based on specific targets including key receptors and signaling pathways.

Pre‑hatch thermal manipulation of embryos and post‑hatch baicalein supplementation mitigated heat stress in broiler chickens

Background High environmental temperatures induce heat stress in broiler chickens,affecting their health and pro-duction performance.Several dietary,managerial,and genetics strategies have been tested with some success in mitigating heat stress(HS)in broilers.Developing novel HS mitigation strategies for sustaining broiler production is critically needed.This study investigated the effects of pre-hatch thermal manipulation(TM)and post-hatch baica-lein supplementation on growth performance and health parameters in heat-stressed broilers.Results Six hundred fertile Cobb 500 eggs were incubated for 21 d.After candling on embryonic day(ED)10,238 eggs were thermally manipulated at 38.5℃ with 55%relative humidity(RH)from ED 12 to 18,then transferred to the hatcher(ED 19 to 21,standard temperature)and 236 eggs were incubated at a controlled temperature(37.5℃)till hatch.After hatch,180-day-old chicks from both groups were raised in 36 pens(n=10 birds/pen,6 replicates per treatment).The treatments were:1)Control,2)TM,3)control heat stress(CHS),4)thermal manipulation heat stress(TMHS),5)control heat stress supplement(CHSS),and 6)thermal manipulation heat stress supplement(TMHSS).All birds were raised under the standard environment for 21 d,followed by chronic heat stress from d 22 to 35(32–33℃ for 8 h)in the CHS,TMHS,CHSS,and TMHSS groups.A thermoneutral(22–24℃)environment was maintained in the Control and TM groups.RH was constant(50%±5%)throughout the trial.All the data were analyzed using one-way ANOVA in R and GraphPad software at P<0.05 and are presented as mean±SEM.Heat stress significantly decreased(P<0.05)the final body weight and ADG in CHS and TMHS groups compared to the other groups.Embryonic TM significantly increased(P<0.05)the expression of heat shock protein-related genes(HSP70,HSP90,and HSPH1)and antioxidant-related genes(GPX1 and TXN).TMHS birds showed a significant increment(P<0.05)in total cecal volatile fatty acid(VFA)concentration compared to the CHS birds.The cecal microbial analysis showed significant enrichment(P<0.05)in alpha and beta diversity and Coprococcus in the TMHSS group.Conclusions Pre-hatch TM and post-hatch baicalein supplementation in heat-stressed birds mitigate the detrimental effects of heat stress on chickens’growth performance,upregulate favorable gene expression,increase VFA produc-tion,and promote gut health by increasing beneficial microbial communities.

Construction of a Computational Scheme for the Fuzzy HIV/AIDS Epidemic Model with a Nonlinear Saturated Incidence Rate

This work aimed to construct an epidemic model with fuzzy parameters.Since the classical epidemic model doesnot elaborate on the successful interaction of susceptible and infective people,the constructed fuzzy epidemicmodel discusses the more detailed versions of the interactions between infective and susceptible people.Thenext-generation matrix approach is employed to find the reproduction number of a deterministic model.Thesensitivity analysis and local stability analysis of the systemare also provided.For solving the fuzzy epidemic model,a numerical scheme is constructed which consists of three time levels.The numerical scheme has an advantage overthe existing forward Euler scheme for determining the conditions of getting the positive solution.The establishedscheme also has an advantage over existing non-standard finite difference methods in terms of order of accuracy.The stability of the scheme for the considered fuzzy model is also provided.From the plotted results,it can beobserved that susceptible people decay by rising interaction parameters.

Knockdown of the atypical protein kinase genes GhABC1K2-A05 and GhABC1K12-A07 make cotton more sensitive to salt and PEG stress

Activity of bc1 complex kinase(ABC1K)is an atypical protein kinase(aPK)that plays a crucial role in plant mitochondrial and plastid stress responses,but little is known about the responses of ABC1Ks to stress in cotton(Gossypium spp.).Here,we identified 40 ABC1Ks in upland cotton(Gossypium hirsutum L.)and found that the Gh ABC1Ks were unevenly distributed across 17 chromosomes.The GhABC1K family members included 35 paralogous gene pairs and were expanded by segmental duplication.The GhABC1K promoter sequences contained diverse cis-acting regulatory elements relevant to hormone or stress responses.The qRT-PCR results revealed that most Gh ABC1Ks were upregulated by exposure to different stresses.Gh ABC1K2-A05 and Gh ABC1K12-A07 expression levels were upregulated by at least three stress treatments.These genes were further functionally characterized by virus-induced gene silencing(VIGS).Compared with the controls,the Gh ABC1K2-A05-and Gh ABC1K12-A07-silenced cotton lines exhibited higher malondialdehyde(MDA)contents,lower catalase(CAT),peroxidase(POD)and superoxide dismutase(SOD)activities and reduced chlorophyll and soluble sugar contents under NaCl and PEG stress.In addition,the expression levels of six stress marker genes(Gh DREB2A,Gh SOS1,Gh CIPK6,Gh SOS2,Gh WRKY33,and Gh RD29A)were significantly downregulated after stress in the Gh ABC1K2-A05-and Gh ABC1K12-A07-silenced lines.The results indicate that knockdown of Gh ABC1K2-A05 and Gh ABC1K12-A07 make cotton more sensitive to salt and PEG stress.These findings can provide valuable information for intensive studies of Gh ABC1Ks in the responses and resistance of cotton to abiotic stresses.

Modulation of p75 neurotrophin receptor mitigates brain damage following ischemic stroke in mice

Stroke is a significant leading cause of death and disability in the United States(Tsao et al.,2022).Approximately 87% of strokes fall into the ischemic category,mainly caused by arterial blockage(Jayaraj et al.,2019).Although the only FDA-approved effective medication is tissue plasminogen activator(tPA),it should be administrated within 4.5 hours of ischemic stroke.Furthermore,tPA has been an integral part of managing acute ischemic stro ke.

There is more to the knee joint than just the quadriceps:A systematic review with meta-analysis and evidence gap map of hamstring strength,flexibility,and morphology in individuals with gradual-onset knee disorders

Background:Impairments in hamstring strength,flexibility,and morphology have been associated with altered knee biomechanics,pain,and function.Determining the presence of these impairments in individuals with gradual-onset knee disorders is important and may indicate targets for assessment and rehabilitation.This systematic review aimed to synthesize the literature to determine the presence of impairments in hamstring strength,flexibility,and morphology in individuals with gradual-onset knee disorders.Methods:Five databases(MEDLINE,Embase,CINAHL,SPORTDiscus,and Web of Science)were searched from inception to September 2022.Only studies comparing hamstring outcomes(e.g.,strength,flexibility,and/or morphology)between individuals with gradual-onset knee disorders and their unaffected limbs or pain-free controls were included.Meta-analyses for each knee disorder were performed.Outcome-level certainty was assessed using the Grading of Recommendations Assessment,Development,and Evaluation,and evidence gap maps were created.Results:Seventy-nine studies across 4 different gradual-onset knee disorders(i.e.,knee osteoarthritis(OA),patellofemoral pain(PFP),chondromalacia patellae,and patellar tendinopathy)were included.Individuals with knee OA presented with reduced hamstring strength compared to pain-free controls during isometric(standard mean difference(SMD)=-0.76,95%confidence interval(95%CI):-1.32 to-0.21)and concentric contractions(SMD=-0.97,95%CI:-1.49 to-0.45).Individuals with PFP presented with reduced hamstring strength compared to painfree controls during isometric(SMD=-0.48,95%CI:-0.82 to-0.14),concentric(SMD=-1.07,95%CI:-2.08 to-0.06),and eccentric contractions(SMD=-0.59,95%CI:-0.97 to-0.21).No differences were observed in individuals with patellar tendinopathy.Individuals with PFP presented with reduced hamstring flexibility when compared to pain-free controls(SMD=-0.76,95%CI:-1.15 to-0.36).Evidence gap maps identified insufficient evidence for chondromalacia patellae and hamstring morphology across all gradual-onset knee disorders.Conclusion:Our findings suggest that assessing and targeting impairments in hamstring strength and flexibility during rehabilitation may be recommended for individuals with knee OA or PFP.

Additively manufactured Ti–Ta–Cu alloys for the next-generation load-bearing implants

Bacterial colonization of orthopedic implants is one of the leading causes of failure and clinical complexities for load-bearing metallic implants. Topical or systemic administration of antibiotics may not offer the most efficient defense against colonization, especially in the case of secondary infection, leading to surgical removal of implants and in some cases even limbs. In this study, laser powder bed fusion was implemented to fabricate Ti3Al2V alloy by a 1:1 weight mixture of CpTi and Ti6Al4V powders. Ti-Tantalum(Ta)–Copper(Cu) alloys were further analyzed by the addition of Ta and Cu into the Ti3Al2V custom alloy. The biological,mechanical, and tribo-biocorrosion properties of Ti3Al2V alloy were evaluated. A 10 wt.% Ta(10Ta) and 3 wt.% Cu(3Cu) were added to the Ti3Al2V alloy to enhance biocompatibility and impart inherent bacterial resistance. Additively manufactured implants were investigated for resistance against Pseudomonas aeruginosa and Staphylococcus aureus strains of bacteria for up to 48 h. A 3 wt.% Cu addition to Ti3Al2V displayed improved antibacterial efficacy, i.e.78%–86% with respect to CpTi. Mechanical properties for Ti3Al2V–10Ta–3Cu alloy were evaluated, demonstrating excellent fatigue resistance, exceptional shear strength, and improved tribological and tribo-biocorrosion characteristics when compared to Ti6Al4V. In vivo studies using a rat distal femur model revealed improved early-stage osseointegration for alloys with10 wt.% Ta addition compared to CpTi and Ti6Al4V. The 3 wt.% Cu-added compositions displayed biocompatibility and no adverse infammatory response in vivo. Our results establish the Ti3Al2V–10Ta–3Cu alloy’s synergistic effect on improving both in vivo biocompatibility and microbial resistance for the next generation of load-bearing metallic implants.

Perception of dental appearance and aesthetic analysis among patients,laypersons and dentists

BACKGROUND Current concepts of beauty are increasingly subjective,influenced by the viewpoints of others.The aim of the study was to evaluate divergences in the perception of dental appearance and smile esthetics among patients,laypersons and dental practitioners.The study goals were to evaluate the influence of age,sex,education and dental specialty on the participants’judgment and to identify the values of different esthetic criteria.Patients sample included 50 patients who responded to a dental appearance questionnaire(DAQ).Two frontal photographs were taken,one during a smile and one with retracted lips.Laypersons and dentists were asked to evaluate both photographs using a Linear Scale from(0-10),where 0 represent(absolutely unaesthetic)and 10 represent(absolutely aesthetic).One-way analysis of variance(ANOVA)and t-test analysis were measured for each group.Most patients in the sample expressed satisfaction with most aspects of their smiles and dental appearance.Among laypersons(including 488 participants),47 pictures“with lips”out of 50 had higher mean aesthetic scores compared to pictures“without lips”.Among the dentist sample,90 dentists’perception towards the esthetic smile and dental appearance for photos“with lips”and“without lips”were the same for 23 out of 50 patients.Perception of smile aesthetics differed between patients,laypersons and dentists.Several factors can contribute to shape the perception of smile aesthetic.AIM To compare the perception of dental aesthetic among patients,laypersons,and professional dentists,to evaluate the impact of age,sex,educational background,and income on the judgments made by laypersons,to assess the variations in experience,specialty,age,and sex on professional dentists’judgment,and to evaluate the role of lips,skin shade and tooth shade in different participants’judgments.METHODS Patients sample included 50 patients who responded to DAQ.Two frontal photographs were taken:one during a smile and one with retracted lips.Laypersons and dentists were asked to evaluate both photographs using a Linear Scale from(0-10),where 0 represent(absolutely unaesthetic)and 10 represent(absolutely aesthetic).One-way ANOVA and t-test analysis were measured for each group.RESULTS Most patients in the sample expressed satisfaction with most aspects of their smiles and dental appearance.Among laypersons(including 488 participants),47 pictures“with lips”out of 50 had higher mean aesthetic scores compared to pictures“without lips”.Whereas among the dentist sample,90 dentists’perception towards the esthetic smile and dental appearance for photos“with lips”and“without lips”were the same for 23 out of 50 patients.Perception of smile aesthetics differed between patients,laypersons and dentists.CONCLUSION Several factors can contribute to shape the perception of smile aesthetic.

Outsmarting Android Malware with Cutting-Edge Feature Engineering and Machine Learning Techniques

The growing usage of Android smartphones has led to a significant rise in incidents of Android malware andprivacy breaches.This escalating security concern necessitates the development of advanced technologies capableof automatically detecting andmitigatingmalicious activities in Android applications(apps).Such technologies arecrucial for safeguarding user data and maintaining the integrity of mobile devices in an increasingly digital world.Current methods employed to detect sensitive data leaks in Android apps are hampered by two major limitationsthey require substantial computational resources and are prone to a high frequency of false positives.This meansthat while attempting to identify security breaches,these methods often consume considerable processing powerand mistakenly flag benign activities as malicious,leading to inefficiencies and reduced reliability in malwaredetection.The proposed approach includes a data preprocessing step that removes duplicate samples,managesunbalanced datasets,corrects inconsistencies,and imputes missing values to ensure data accuracy.The Minimaxmethod is then used to normalize numerical data,followed by feature vector extraction using the Gain ratio andChi-squared test to identify and extract the most significant characteristics using an appropriate prediction model.This study focuses on extracting a subset of attributes best suited for the task and recommending a predictivemodel based on domain expert opinion.The proposed method is evaluated using Drebin and TUANDROMDdatasets containing 15,036 and 4,464 benign and malicious samples,respectively.The empirical result shows thatthe RandomForest(RF)and Support VectorMachine(SVC)classifiers achieved impressive accuracy rates of 98.9%and 98.8%,respectively,in detecting unknown Androidmalware.A sensitivity analysis experiment was also carriedout on all three ML-based classifiers based on MAE,MSE,R2,and sensitivity parameters,resulting in a flawlessperformance for both datasets.This approach has substantial potential for real-world applications and can serve asa valuable tool for preventing the spread of Androidmalware and enhancing mobile device security.

Impacts of Future Changes in Heavy Precipitation and Extreme Drought on the Economy over South China and Indochina

Heavy precipitation and extreme drought have caused severe economic losses over South China and Indochina(INCSC)in recent decades.Given the areas with large gross domestic product(GDP)in the INCSC region are distributed along the coastline and greatly affected by global warming,understanding the possible economic impacts induced by future changes in the maximum consecutive 5-day precipitation(RX5day)and the maximum consecutive dry days(CDD)is critical for adaptation planning in this region.Based on the latest data released by phase 6 of the Coupled Model Intercomparison Project(CMIP6),future projections of precipitation extremes with bias correction and their impacts on GDP over the INCSC region under the fossil-fueled development Shared Socioeconomic Pathway(SSP5-8.5)are investigated.Results indicate that RX5day will intensify robustly throughout the INCSC region,while CDD will lengthen in most regions under global warming.The changes in climate consistently dominate the effect on GDP over the INCSC region,rather than the change of GDP.If only considering the effect of climate change on GDP,the changes in precipitation extremes bring a larger impact on the economy in the future to the provinces of Hunan,Jiangxi,Fujian,Guangdong,and Hainan in South China,as well as the Malay Peninsula and southern Cambodia in Indochina.Thus,timely regional adaptation strategies are urgent for these regions.Moreover,from the sub-regional average viewpoint,over two thirds of CMIP6 models agree that maintaining a lower global warming level will reduce the economic impacts from heavy precipitation over the INCSC region.

Differences in spring precipitation over southern China associated with multiyear La Ni?a events

Composite analyses were performed in this study to reveal the difference in spring precipitation over southern China during multiyear La Ni?a events during 1901 to 2015. It was found that there is significantly below-normal precipitation during the first boreal spring, but above-normal precipitation during the second year. The difference in spring precipitation over southern China is correlative to the variation in western North Pacific anomalous cyclone(WNPC), which can in turn be attributed to the different sea surface temperature anomaly(SSTA) over the Tropical Pacific. The remote forcing of negative SSTA in the equatorial central and eastern Pacific and the local air-sea interaction in the western North Pacific are the usual causes of WNPC formation and maintenance.SSTA in the first spring is stronger than those in the second spring. As a result, the intensity of WNPC in the first year is stronger, which is more likely to reduce the moisture in southern China by changing the moisture transport, leading to prolonged precipitation deficits over southern China. However, the tropical SSTA signals in the second year are too weak to induce the formation and maintenance of WNPC and the below-normal precipitation over southern China. Thus, the variation in tropical SSTA signals between two consecutive springs during multiyear La Ni?a events leads to obvious differences in the spatial pattern of precipitation anomaly in southern China by causing the different WNPC response.

Road Traffic Monitoring from Aerial Images Using Template Matching and Invariant Features

Road traffic monitoring is an imperative topic widely discussed among researchers.Systems used to monitor traffic frequently rely on cameras mounted on bridges or roadsides.However,aerial images provide the flexibility to use mobile platforms to detect the location and motion of the vehicle over a larger area.To this end,different models have shown the ability to recognize and track vehicles.However,these methods are not mature enough to produce accurate results in complex road scenes.Therefore,this paper presents an algorithm that combines state-of-the-art techniques for identifying and tracking vehicles in conjunction with image bursts.The extracted frames were converted to grayscale,followed by the application of a georeferencing algorithm to embed coordinate information into the images.The masking technique eliminated irrelevant data and reduced the computational cost of the overall monitoring system.Next,Sobel edge detection combined with Canny edge detection and Hough line transform has been applied for noise reduction.After preprocessing,the blob detection algorithm helped detect the vehicles.Vehicles of varying sizes have been detected by implementing a dynamic thresholding scheme.Detection was done on the first image of every burst.Then,to track vehicles,the model of each vehicle was made to find its matches in the succeeding images using the template matching algorithm.To further improve the tracking accuracy by incorporating motion information,Scale Invariant Feature Transform(SIFT)features have been used to find the best possible match among multiple matches.An accuracy rate of 87%for detection and 80%accuracy for tracking in the A1 Motorway Netherland dataset has been achieved.For the Vehicle Aerial Imaging from Drone(VAID)dataset,an accuracy rate of 86%for detection and 78%accuracy for tracking has been achieved.

Improving Video Watermarking through Galois Field GF(2^(4)) Multiplication Tables with Diverse Irreducible Polynomials and Adaptive Techniques

Video watermarking plays a crucial role in protecting intellectual property rights and ensuring content authenticity.This study delves into the integration of Galois Field(GF)multiplication tables,especially GF(2^(4)),and their interaction with distinct irreducible polynomials.The primary aim is to enhance watermarking techniques for achieving imperceptibility,robustness,and efficient execution time.The research employs scene selection and adaptive thresholding techniques to streamline the watermarking process.Scene selection is used strategically to embed watermarks in the most vital frames of the video,while adaptive thresholding methods ensure that the watermarking process adheres to imperceptibility criteria,maintaining the video's visual quality.Concurrently,careful consideration is given to execution time,crucial in real-world scenarios,to balance efficiency and efficacy.The Peak Signal-to-Noise Ratio(PSNR)serves as a pivotal metric to gauge the watermark's imperceptibility and video quality.The study explores various irreducible polynomials,navigating the trade-offs between computational efficiency and watermark imperceptibility.In parallel,the study pays careful attention to the execution time,a paramount consideration in real-world scenarios,to strike a balance between efficiency and efficacy.This comprehensive analysis provides valuable insights into the interplay of GF multiplication tables,diverse irreducible polynomials,scene selection,adaptive thresholding,imperceptibility,and execution time.The evaluation of the proposed algorithm's robustness was conducted using PSNR and NC metrics,and it was subjected to assessment under the impact of five distinct attack scenarios.These findings contribute to the development of watermarking strategies that balance imperceptibility,robustness,and processing efficiency,enhancing the field's practicality and effectiveness.

CLASSIFICATIONS OF DUPIN HYPERSURFACES IN LIE SPHERE GEOMETRY

This is a survey of local and global classification results concerning Dupin hypersurfaces in S^(n)(or R^(n))that have been obtained in the context of Lie sphere geometry.The emphasis is on results that relate Dupin hypersurfaces to isoparametric hypersurfaces in spheres.Along with these classification results,many important concepts from Lie sphere geometry,such as curvature spheres,Lie curvatures,and Legendre lifts of submanifolds of S^(n)(or R^(n)),are described in detail.The paper also contains several important constructions of Dupin hypersurfaces with certain special properties.

GRU Enabled Intrusion Detection System for IoT Environment with Swarm Optimization and Gaussian Random Forest Classification

In recent years,machine learning(ML)and deep learning(DL)have significantly advanced intrusion detection systems,effectively addressing potential malicious attacks across networks.This paper introduces a robust method for detecting and categorizing attacks within the Internet of Things(IoT)environment,leveraging the NSL-KDD dataset.To achieve high accuracy,the authors used the feature extraction technique in combination with an autoencoder,integrated with a gated recurrent unit(GRU).Therefore,the accurate features are selected by using the cuckoo search algorithm integrated particle swarm optimization(PSO),and PSO has been employed for training the features.The final classification of features has been carried out by using the proposed RF-GNB random forest with the Gaussian Naïve Bayes classifier.The proposed model has been evaluated and its performance is verified with some of the standard metrics such as precision,accuracy rate,recall F1-score,etc.,and has been compared with different existing models.The generated results that detected approximately 99.87%of intrusions within the IoT environments,demonstrated the high performance of the proposed method.These results affirmed the efficacy of the proposed method in increasing the accuracy of intrusion detection within IoT network systems.

Leveraging User-Generated Comments and Fused BiLSTM Models to Detect and Predict Issues with Mobile Apps

In the last decade, technical advancements and faster Internet speeds have also led to an increasing number ofmobile devices and users. Thus, all contributors to society, whether young or old members, can use these mobileapps. The use of these apps eases our daily lives, and all customers who need any type of service can accessit easily, comfortably, and efficiently through mobile apps. Particularly, Saudi Arabia greatly depends on digitalservices to assist people and visitors. Such mobile devices are used in organizing daily work schedules and services,particularly during two large occasions, Umrah and Hajj. However, pilgrims encounter mobile app issues such asslowness, conflict, unreliability, or user-unfriendliness. Pilgrims comment on these issues on mobile app platformsthrough reviews of their experiences with these digital services. Scholars have made several attempts to solve suchmobile issues by reporting bugs or non-functional requirements by utilizing user comments.However, solving suchissues is a great challenge, and the issues still exist. Therefore, this study aims to propose a hybrid deep learningmodel to classify and predict mobile app software issues encountered by millions of pilgrims during the Hajj andUmrah periods from the user perspective. Firstly, a dataset was constructed using user-generated comments fromrelevant mobile apps using natural language processing methods, including information extraction, the annotationprocess, and pre-processing steps, considering a multi-class classification problem. Then, several experimentswere conducted using common machine learning classifiers, Artificial Neural Networks (ANN), Long Short-TermMemory (LSTM), and Convolutional Neural Network Long Short-Term Memory (CNN-LSTM) architectures, toexamine the performance of the proposed model. Results show 96% in F1-score and accuracy, and the proposedmodel outperformed the mentioned models.