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Because textured contact lenses obscure the iris’s natural texture, they pose a serious threat to the accuracy of iris recognition systems and may make identity theft possible. Therefore, this work proposes a reliable method for textured contact lens detection that uses efficient global texture descriptors and effective feature selection with classification techniques. Run-Length and Zernike Moments are effective global texture descriptors that have been extracted from preprocessed iris images that were acquired from the IIIT-D CLI dataset. To improve classification performance, Ant Colony Optimization (ACO) was used to decrease the dimensionality of the feature vectors. Support Vector Machine (SVM) and Logistic Regression (LOG), two classifiers, have been evaluated with different descriptor pairings. According to findings from experiments, Zernike features optimized by ACO and paired with LOG produced the greatest accuracy of 98.04%, greatly surpassing previous methods. The efficacy of the presented approach for safe and dependable iris-based biometric systems is demonstrated by its exceptional results with regard to accuracy, recall, precision, and F1-score.

Human gesture image recognition is the process of identifying, deciphering, and classifying human gestures in images or video frames using computer vision algorithms. These gestures can vary from the simplest hand motions, body positions, and facial emotions to complicated gestures. Two significant problems affecting the performance of human gesture picture recognition methods are ambiguity and invariance. Ambiguity occurs when gestures have the same shape but different orientations, while invariance guarantees that gestures are correctly classified even when scale, lighting, or orientation varies. To overcome this issue, hand-crafted features can be combined with deep learning to greatly improve the performance of hand gesture image recognition models. This combination improves the model’s overall accuracy and dependability in identifying a variety of hand movements by enhancing its capacity to record both shape and texture properties. Thus, in this study, we propose a hand gesture recognition method that combines Reset50 model feature extraction with the Tamura texture descriptor and uses the adaptability of GAM to represent intricate interactions between the features. Experiments were carried out on publicly available datasets containing images of American Sign Language (ASL) gestures. As Tamura-ResNet50-OptimizedGAM achieved the highest accuracy rate in the ASL datasets, it is believed to be the best option for human gesture image recognition. According to the experimental results, the accuracy rate was 96%, which is higher than the total accuracy of the state-of-the-art techniques currently in use.

New computer-aided design and computer-aided manufacturing (CAD-CAM) materials have been reported to have suitable mechanical and physical properties for endocrown restorations. However, there is a lack of literature on evaluating the retention of endocrown using these materials. This in vitro study aimed to compare the retention of endocrowns fabricated from 3 different CAD-CAM materials. Sixty human mandibular third molars were divided into 3 groups ( n  = 20) according to the material used: (e.max CAD, Ivoclar AG, Schaan, Liechtenstein), (HC, Shofu, Koyoto, Japan), and (Brilliant Crios, Coltene, Altstätten, Switzerland) ( n  = 20). Specimens were stored in distilled water at 37 °C for 1 week and subjected to 5000 thermal cycles. A universal testing machine (5500R/1123, Instron, Norwood, USA) was used to measure the tensile force. All results were statistically analyzed using one-way ANOVA (α = 0.05), and different failure modes were demonstrated. The results revealed that e. max CAD showed the highest mean tensile force value (402.35 ± 15.812) N, and the lowest mean tensile force value was for Brilliant Coris (118.90 ± 12.430) N ( P  < .001). It is concluded that e.max CAD endocrowns showed the highest tensile force values after thermocycling in comparison to other materials with a significant difference, which may have a promising impact on the survival of endocrown restorations.

Statement of problem Immediate dentin sealing (IDS) is used to improve bonding of indirect restoration. However, interaction between polyether impressions may affect the future bonding of indirect restoration. So, digital impressions with IDS may have a better impact on microleakage. Purpose The current in vitro study aimed to investigate the effect of using digital impression versus polyether impression and different dentin sealing techniques on the microleakage of lithium disilicate onlays. Material and methods A total of 60 identically sized human mandibular molars were allocated into two groups ( n  = 30): group DI, which uses a digital impression, and group CI, which uses a polyether impression. After preparation of all teeth for onlay, based on the dentin sealing technique, these groups were further divided into three subgroups ( n  = 10): subgroups I, II, and III. Dentin sealing was postponed in subgroup I prior to cementation. Immediate dentin sealing was applied prior to impression processes in subgroups II and III, plus cavity design optimization (CDO) for subgroup III. All teeth received e.max CAD onlay restoration (Ivoclar Vivadent, Schaan, Liechtenstein). The specimens were exposed to thermocycling with bath temperatures of 5 °C and 55 °C for a total of 5000 cycles. The specimens were then submerged in 0.5% aqueous Rhodamine B dye for 48 h. Buccolingual sections were examined under confocal microscopy. Microleakage was scored (0–3). Data were analyzed using the Scheirer–Ray–Hare test (α = 0.05). Results Microleakage was significantly lower in DI than CI ( P =.0046). Delayed dentin sealing (subgroup I) showed significantly higher microleakage than IDS (subgroup II) and IDS + CDO (subgroup III) ( P <.001), with no significant difference between IDS and IDS + CDO. Conclusions Digital impressions were associated with significantly lower microleakage compared to polyether impressions. IDS, with or without CDO, significantly reduced microleakage compared to delayed sealing. Clinical implications Combining digital impressions with IDS may enhance the marginal seal and longevity of ceramic onlays.

Background Occlusal veneer had been evaluated for mechanical properties using lithium disillicate. However, studies evaluating the mechanical properties of occlusal veneer with different preparation designs and ceramic materials are lacking. So, this in vitro study aimed to evaluate the fracture resistance of occlusal veneers with two designs fabricated from two different ceramic materials. Material and methods Fourty mandibular third molars were distributed to 2 groups ( n  = 20) according to preparation design: group (O) anatomical occlusal reduction and group (OA) anatomical occlusal and 1 mm axial reduction. Each group was additionally subdivided into two subgroups ( n  = 10) according to ceramic materials; in subgroup X, lithium disilicate (e.max CAD, Ivoclar AG, Schaan, Liechtenstein) was used, and in subgroup S, zirconia-reinforced lithium silicate (ZLS) (Vita Suprinity, VitaZahnfabrik, Bad Säckingen, Germany) was used. All specimens were cemented with a light-cure resin cement (Choice 2, Bisco, Schaumburg, USA). 5000 thermocycles were applied to all specimens with both temperatures of 5 °C and 55 °C in two water baths; the dwell time was 30s at each bath, and the transfer time was 10s. Then all specimens were subjected to a fatigue simulation under dynamic loading of 200 N for 250,000 cycles. A universal testing machine (5500R/1123, Instron, Norwood, USA) was used to evaluate the fracture strength with a crosshead speed of 1 mm/min. All data were analyzed statistically by using a two-way ANOVA, and for some violations of assumptions, these results were compared with those obtained by the nonparametric test (Scheirer Ray Hare) (α = 0.05). Results A statistically significantly higher fracture resistance in the ‘OA’ (3389 N) compared to the ‘O’ (2787 N) group regardless of the ceramic material ( P  < .001) and a statistically significantly higher fracture resistance in the ‘X’ (3295 N) compared to the ‘S’ (2881 N) regardless of the preparation design ( P  = .015). Conclusions For occlusal veneers, all preparation designs and materials (such as Vita Suprinity and e.max CAD) had clinically acceptable fracture resistance values that were greater than the maximal biting forces. On the other hand, the e.max CAD with occlusal veneer, including axial reduction design, demonstrated the maximum fracture resistance value. Finally, no relationship between fracture strength and mode of failure was found. Clinical implications Proper preparation design and the use of dental materials with high fracture resistance are key factors in extending the life of occlusal veneer restorations. The highest fracture resistance was demonstrated by lithium disilicate glass-ceramic occlusal veneers with axial preparation, which may increase the clinical longevity of teeth restored with occlusal veneers.

Background Many monolithic machined materials have been introduced and provided a suitable mechanical and physical properties for inlay restorations. However, there is shortage in the studies evaluating the marginal adaptation using these materials. Purpose This study aimed to compare the effect of fabricating inlay restorations from 3 different CAD-CAM materials on marginal gaps before and after thermocycling. Materials and methods Sixty human premolars were randomly divided into 3 groups (n = 20) according to the material used: (e.max CAD, Ivoclar AG, Schaan, Liechtenstein), (HC, Shofu, Koyoto, Japan) and (Brilliant Crios, Coltene, Altstätten, Switzerland) (n = 20). A scanning electron microscope (SEM) (JSM- 6510 lv, JEOL, Tokyo, JAPAN) was used to for measuring the marginal gaps after cementation of inlay restorations. The magnification was adapted to 250x. Marginal gaps were revaluated with SEM after thermocycling. The temperatures of baths were 5 and 55 °C was applied for a total of 5000 cycles. All data were statistically analyzed by using ANCOVA to demonstrate if there were any statistically significant differences between the gap measures after thermocycling of the three independent (unrelated) groups. A Bonferroni adjustmen was used to perform post hoc analysis (α = 0.05). Results Post-intervention marginal gap was statistically significantly lower in group EX (110.8 μm) which was statistically significant compared with group SF (112.5 μm) (mean difference=-1.768, P  = .007) and group BR (113 μm) (mean difference=-2.272, P  = .001), however, in. comparing SF and BR groups, there was no significant difference (mean difference=-0.5, P  = .770). Conclusions Thermocycling affected the marginal gaps of composite based restoration and resin-modified ceramics widely. However, it had a very small effect on glass ceramics marginal adaptation. Clinical implications The marginal gaps of CAD-CAM inlays varied according to material used (ceramic based, combination, or resin based). Thermocycling has a minor effect on the marginal adaptation of lithium disilicate glass-ceramic inlays, where it affected the margin of resin-modified ceramic and composite based inlays greatly. Using lithium disilicate glass-ceramic might improve the clinical longevity of inlay restored teeth.

Steganography is the technique for secretly hiding messages in media such as text, audio, image, and video without being discovered. Image is one of the most essential media for concealing data, making it hard to identify hidden data not visible to the human eye. In general, the cover image and the encrypted image are symmetrical in terms of dimension size, resolution, and qualities. This makes the difference difficult to perceive with the human eye. As a result, distinguishing between the two symmetric images required the development of methods. Steganalysis is a technique for identifying hidden messages embedded in digital material without having to know the embedding algorithm or the “non-stego” image. Due to their enormous feature vector dimension, which requires more time to calculate, the performance of most existing image steganalysis classification (ISC) techniques is still restricted. Therefore, in this research, we present a steganalysis classification method based on one of the texture features chosen, such as segmentation-based fractal texture analysis (SFTA), local binary pattern (LBP), and gray-level co-occurrence matrix (GLCM). The classifiers employed include Gaussian discriminant analysis (GDA) and naïve Bayes (NB). We used a public database in our proposed method and applied it to IStego100K datasets to be able to assess its performance. The experimental results reveal that in all classifiers, the SFTA feature surpassed all of the texture features, making it a great texture feature for image steganalysis classification. In terms of feature dimension and classification accuracy (CA), a comparison was made between the suggested SFTA-based GDA approach and various current ISC methods. The outcomes of the comparison are obvious show that the proposed method surpasses current methods.

Background Conventional full-coverage crowns are used after endodontic treatment to enhance the fracture toughness of these teeth. However, these crowns lead to extensive loss of tooth structure. Continuous trials to develop a biomimetic conservative direct restorative material that can be used as a dentine substitute led to the development of the short fiber reinforced resin composite. Methods Fifty extracted intact upper premolar teeth were selected. Ten teeth serve as positive control without any treatment (Group 1). The remaining forty teeth were received root canal therapy. Standardized MOD cavities were prepared in 30 teeth of them, then they were randomly divided into three groups: Group 2: teeth received no coronal restorations; Group 3: MOD cavities restored with packable short fiber reinforced composite (EverX Posterior), followed by 2 mm nanocomposite; and Group 4: MOD cavities restored with flowable short fiber reinforced composite (EverX Flow), followed by 2 mm nanocomposite. For the remaining ten teeth, MOD cavities were prepared, and cusps were reduced to receive ceramic overlays (CeraSmart 270). After thermocycling, fracture load is applied using the Instron Universal machine until samples fracture. Fracture loads were recorded, and fracture mode was evaluated. All data were subjected to statistical analysis. Results Teeth restored with CeraSmart 270 overlays and those restored with high aspect ratio short fiber-reinforced resin composite recorded the highest resistance to fracture with no significant differences between them. Conclusions EverX Posterior may be considered a conservative substitute for indirect overlays to restore endodontically treated teeth with MOD cavities. Clinical relevance Clinically, using fiber reinforced composite as a substitute for indirect restorations preserves the tooth structure and provides proper resistance to fracture.

Background Restoring first permanent molars after endodontic treatment in children is challenging. Improved mechanical properties and adhesion of ceramic materials have led to the emergence of endocrown as a conservative and esthetic restorative option for endodontically treated molars in adults and offer dentists a restorative treatment for endodontically treated first permanent molars in children. The purpose of this study was clinical and radiographic evaluation of both endocrowns fabricated from 2 different materials and SSCs restoring endodontically treated first permenant molars in children over one year. Methods Thirty children were selected (18 girls and 12 boys) with an age range of 10–13 years old, with an endodontically treated first molar. Children were randomly divided into 3 groups: PMC group (restored with preformed SSCs), EMX group (restored with litium disilicate endocrown), and COP group (restored with indirect reinforced composite endocrown) ( n  = 10). Evaluation was done in terms of parent satisfaction, radiograph (base line and 12 months), the restoration survival after 12 months, plaque index (PI), and gingival index (GI) at base line, 6 months, and 12 months.The data were analyzed using the Kruskal-Wallis H-test, which was used to compare an ordinal variable, and Friedman’s test was used to compare an ordinal variable ( P  ≤.050). Results Parent satisfaction showed statistically significant differences between PMC (mean rank = 7.5) and both EMX and COP (mean rank = 19.5) ( P  <.001), but not between the EMX and COP groups ( P  = 1.00). At 6 and 12 months, the PMC group’s PI values were statistically significantly higher than those of the EMX and COP groups ( P  =.001 and P  <.001, respectively). The GI values of the EMX and COP groups did not change significantly through different intervals ( P  = 1.000 and P  =.135, respectively), whereas the GI values of the PMC group did ( P  =.050). At various intervals, it was found that there was no significant difference in the GI values between the three groups. Conclusions The survival rates of endorowns and SSCs were comparable. Compared to SSCs, endocrowns demonstrated a higher parental satisfaction, less plaque buildup, and improved gingival response. Trial registration The study protocol was retrospectively registered on Clinical Trials under No. (NCT06432049-29/05/2024).

A significant quantity of malware is created on purpose every day. Users of smartphones and computer networks now mostly worry about malware. These days, malware detection is a major concern in the cybersecurity area. Several factors can impact malware detection performance, such as inappropriate features and classifiers, extensive domain knowledge, imbalanced data environments, computational complexity, and resource usage. A significant number of existing malware detection methods have been impacted by these factors. Therefore, in this paper, we will first identify and determine the best features and classifiers and then use them in order to propose the malware detection method. The comparative strategy and proposed malware detection procedure consist of four basic steps: malware transformation (converting images of malware from RGB to grayscale), feature extraction (using the ResNet-50, DenseNet-201, GoogLeNet, AlexNet, and SqueezeNet models), feature selection (using PCA method), classification (including GDA, KNN, logistic, SVM, RF, and ensemble learning), and evaluation (using accuracy and error evaluation metrics). Unbalanced Malimg datasets are used in experiments to validate the efficacy of the results that were obtained. According to the comparison findings, KNN is the best machine learning classifier. It outperformed the other classifiers in the Malimg datasets in terms of both accuracy and error. In addition, DenseNet201 is the best pretrained model in the Malimg dataset. Therefore, the proposed DenseNet201-KNN methods had an accuracy rate of 96% and a minimal error rate of 3.07%. The proposed methods surpass existing state-of-the-art approaches. The proposed feature extraction is computationally quicker than most other methods since it uses a lightweight design and fewer feature vector dimensions.