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Football (soccer) stands as the world's most popular sport, enthralling millions of fans globally. Within the dynamic sphere of modern football, gaining comprehensive insights into the nuanced technical and physical demands placed on players is pivotal for performance optimization. This paper introduces an innovative deep learning-powered image classification algorithm for recognizing football player activities directly from videos and images. Our pioneering approach harnesses the synergistic capabilities of convolutional neural networks (CNNs) and graph convolutional networks (GCNs) to decipher intricate spatial–temporal patterns in player poses and motions. The methodology employs a hybrid CNN and GCN architecture. The CNN leverages consecutive convolutional and pooling layers to automatically extract discriminative visual features from input frames capturing player poses. The GCN models' skeletal joints as graph nodes with bones as edges, performing graph convolutions to aggregate spatial and temporal information from neighboring body parts. This enables capturing localized pose dynamics. The complementary CNN and GCN outputs are fused through fully connected layers to classify player activities based on both visual appearances and pose configurations. The model is trained end to end on richly annotated football video data using a multi-class cross-entropy loss. Data augmentation and regularization techniques enhance robustness. Extensive experiments validate the proposed architecture's effectiveness, achieving 97.4% accuracy, 96% precision, 95.5% recall, 95.4% F1-score, 0.90 Matthews correlation, and 93% specificity in classifying 17 complex football activities significantly higher than previous benchmarks. Detailed ablation studies confirm the contributions of the CNN, GCN, and fused model components. The work represents a major advance in leveraging deep neural networks for accurate and granular analysis of sports performances. [ABSTRACT FROM AUTHOR]

Herein, we produced POT polymer-based tungsten (IV) oxide, (WO2), cerium (IV) oxide, (CeO2) and iron (III) oxide (Fe2O3) novel composite materials by emulsion polymerization and one pot blending techniques. UV–Vis analysis confirmed various electronic transitions in π–π* and n–π* levels. FT-IR spectra showed the integration of reinforcement particles within the polymer matrix by the engagement of free functionalities of the polymer by the metal oxide moieties. SEM analysis described the diverse morphology (spherical, pellets, porous and rod-shaped) of the synthesized materials while the complete dispersion of reinforcement particles in the polymer matrix. Extensive cyclic voltammetry studies were done and the materials were found to be used as electroactive agents as they deliver reversible anodic and cathode peaks. The materials are less resistive toward the mobility of ions thus offering good electrical and storage properties. The prepared are proposed to be efficient in electrode and capacitors production technologies. [ABSTRACT FROM AUTHOR]

A finite element–based thermomechanical modeling approach is developed in this study to provide a prediction of the mesoscale melt pool behavior and part-scale properties for AlSi10Mg alloy. On the mesoscale, the widely adopted Goldak heat source model is used to predict melt pool formed by laser during powder bed fusion process. This requires the determination of certain parameters as they control temperature distribution and, hence, melt pool boundaries. A systematic parametric approach is proposed to determine parameters, i.e., absorption coefficient and transient temperature evolution. The simulation results are compared in terms of morphology of melt pool with the literature results. Considering the part-scale domain, there is increasing demand for predicting geometric distortions and analyzing underlying residual stresses, which are highly influenced by the mesh size and initial temperature setup. This study aims to propose a strategy for evaluating the correlation between the mesh size and the initial temperature to provide correct residual stresses when increasing the scale of the model for efficiency. The outcomes revealed that the predicted melt pool error produced by optimal Goldak function parameters is between 5 and 12%. On the part-scale, the finite element model is less sensitive to mesh size for distortion prediction, and layer-lumping can be used to increase the speed of simulation. The effect of large time increments and layer lumping can be compensated by appropriate initial temperature value for AlSi10Mg. The study aids practitioners and researchers to establish and validate design for additive manufacturing within the scope of desired part quality metrics. [ABSTRACT FROM AUTHOR]

Humidity sensors have gained tremendous attention due to their practical applications in the pharmaceutical industry, food processing, biomedical applications, microelectronics, and meteorology. Herein, a polymer-based multifunctional humidity sensor (PANI-Bi-ZnO) has been fabricated. This study describes a polymer-based capacitive-type humidity sensor that has excellent repeatability, negligible hysteresis (0.5% RH at 60% RH), quick response (8 s) and relaxation times (20 s), high stability (30 days), high sensitivity, and good linearity in a wide humidity detection range of 10–90% RH and has become increasingly significant for applications involving industrial control and environmental monitoring. Moreover, the fabricated sensor possesses a highly reliable/stable output performance that remains constant after multiple test cycles. The current work also provides a cost-effective method to fabricate high-performance humidity sensors. The designed humidity sensor would be an excellent choice for measuring a variety of applications in the field of humidity.Graphical abstract: Humidity sensors have gained tremendous attention due to their practical applications in the pharmaceutical industry, food processing, biomedical applications, microelectronics, and meteorology. Herein, a polymer-based multifunctional humidity sensor (PANI-Bi-ZnO) has been fabricated. This study describes a polymer-based capacitive-type humidity sensor that has excellent repeatability, negligible hysteresis (0.5% RH at 60% RH), quick response (8 s) and relaxation times (20 s), high stability (30 days), high sensitivity, and good linearity in a wide humidity detection range of 10–90% RH and has become increasingly significant for applications involving industrial control and environmental monitoring. Moreover, the fabricated sensor possesses a highly reliable/stable output performance that remains constant after multiple test cycles. The current work also provides a cost-effective method to fabricate high-performance humidity sensors. The designed humidity sensor would be an excellent choice for measuring a variety of applications in the field of humidity. [ABSTRACT FROM AUTHOR]

In this study, a 9-elements hybrid MIMO (multiple input multiple output) antennas system is developed for 5G Smartphone communication.The designed MIMO system is composed of two different antenna parts i.e. the multi-band antenna element, and the eight-elements single-band antenna array. The multi-band antenna element encompasses the GSM 0.9/1.8/1.9 GHz (2G bands), UMTS 2.1 GHz (3G bands), LTE 2.3/2.5 GHz (4G bands), GPS, and WLAN 2.4/5 GHz, while the single-band antenna array covers the C-band (3400–3600 MHz) allocated for 5G cellular communcation. The model of the designed system has been manufactured and the simulation results are validated by conducting experiments with the fabricated prototype. High isolation levels have been observed between the elements. The designed antenna systems showed consistent radiation characteristics with a peak gain value of 5.5 dBi, and efficiency of as high as 90%. Furthermore, good MIMO performance parameters, such as the envelop correlation coefficient (ECC) less than 0.13, and 40 bps/Hz channel capacity have been observed over the desired bandwidth. Owing to the salient performance characteristics, the proposed antenna system could be used in modern mobile communications. [ABSTRACT FROM AUTHOR]

Implementing additive manufacturing in an industry, particularly for critical applications of lightweight aluminum (AlSi10Mg), requires part properties that are both accurate and precise to conform to the intent of a robust design. In this experimental study, the objective was to evaluate anisotropy in part properties (i.e., flatness, surface roughness, surface porosity, surface hardness, pre-hole shrinkage, drilling thrust force, and thread-stripping force) when the part orientation (i.e., print inclination and recoater angle) was independently changed. This study developed and investigated an innovative procedure for determining anisotropy in part properties. The part properties were evaluated by designing specific features on a tailor-made flat plate. The replicas of the aluminum plate were additively manufactured at varying orientations using two commercial EOS parameter sets for the laser-based powder bed fusion technique. Conventional measurement equipment was used to analyze all the part properties, except the thread-stripping force, which was measured using a custom-made setup. All the part properties indicated a considerable degree of anisotropy, excluding the drilling thrust force. The printing parameters dictate the significance of the anisotropy. The anisotropy in flatness and pre-hole shrinkage decreases with an increased substrate temperature and a decrease in energy input and thermal gradient. The presence of surface overlapping contours in the scan strategy and an increased energy input can reduce anisotropy in surface roughness and hardness. No significant anisotropy was detected when the recoater angle was changed. This study helps designers establish and substantiate design for additive manufacturing that is within the limits of appropriate anisotropy for a robust design. [ABSTRACT FROM AUTHOR]

The aim of this paper is to admit and stabilize T–S descriptive with time delays. We present some general conditions for the uniqueness and existence in terms of the impulse-free solution for delayed T–S fuzzy systems. Thus, we establish and obtain in terms of strict linear matrix inequalities new sufficient conditions for the stability of T–S fuzzy systems and delayed T–S fuzzy systems by constructing the Lyapunov–Krasovskii functional and applying the generalized Itô formula. Furthermore, a novel algorithm for real-time adjustment of controller membership functions is designed based on a gradient descent strategy to obtain superior H ∞ performance. By using non-PDC fuzzy control mechanism instead of conventional non-PDC control scheme, the performance of interference reduction can be effectively improved. [ABSTRACT FROM AUTHOR]

In this study, zinc oxide (ZnO) nanoparticles and their thin film were synthesized using co-precipitation and spin coating techniques, respectively. Spherical nanoparticles measuring 10–120 nm and thin film having particle with a diameter of 10–100 nm were synthesized. The electrical properties of the synthesized nanoparticles were evaluated using the KEITHLEY semiconductor characterization system. The structure, phase identification, and morphology of the nanoparticles investigated by X-ray diffraction, Raman, and scanning electron microscope techniques were employed. The results confirmed that the ZnO nanoparticles had a hexagonal wurtzite structure. Additionally, gas sensing measurements were conducted using a locally made sensing chamber. The response of nanoparticles and their thin film were observed at varying concentrations of methane gas in the chamber. Response of the thin film as sensor is greater, fast and consistent as compared to nanoparticles sensor. Our study reveals best sensor having response (Ra/Rg) of 1.37 for 100 ppm of CH4 at 140 °C as compared to previous reported studies. [ABSTRACT FROM AUTHOR]

The current research work demonstrates a simple, fast, and sensitive colorimetric approach for visual and spectroscopic detection of mercury (Hg (II)) ions using silver nanoparticles. The compound, N-(3,5-bis(trifluoromethyl)phenyl)-2-(4-chlorophenyl) hydrazine carbothioamide (ThAm), is synthesized, characterized and reacted with AgNO3 in the presence of sodium borohydride (NaBH4) used as reducing agent to produce AgNPs having mean particle size of approximately 11 nm. The stability of nanoparticles (NPs) is studied at different conditions such temperature, time, pH and salt concentration. The NPs are characterized by commonly available techniques including UV–Visible spectroscopy, atomic force microscopy (AFM), Fourier transformed infrared spectroscopy (FTIR) and thermogravimetric/differential analyzer (TG/DTA). The AgNPs are selective to detect Hg (II) among the sixteen metal ions considered in this study. The yellow color of AgNPs solution disappears quickly by addition of Hg (II), along with a substantial variation in surface plasmon resonance band (SPRB). The limit of detection (LOD) is 2.2 µM and that of quantification (LOQ) 7.5 µM. The sensor also responded to the trace amount of Hg (II) ions in spiked water samples and in human blood plasma. Recoveries study of spiked real water samples was in range of 95–98%. [ABSTRACT FROM AUTHOR]

Background & Aims: Drought stress negatively affects wheat crop production worldwide. Selection of drought tolerant varieties and application of silicon (Si) can help to uplift the crop production. The present investigation was aimed to screen drought tolerant wheat varieties by evaluating the potential of Si fertilization.Study was conducted in two sets of experiments, in first (hydroponic) investigation two wheat varieties out of eleven were screened out based upon agronomic parameters, membrane stability, potassium (K+) distribution and tolerance index. The screened varieties were then subjected to different silicon fertilizers under water deficit pot conditions in second experiment and impact of Si sources was monitored via agronomic, physiological and biochemical attributes.Faisalabad-08 and Anaj-17 were best performing varieties in tested parameters. The silica fertilizer application improved the growth, physiological, biochemical and ionic attributes under water deficit and increased the grain yield of crop. Among tested sources, silicic acid proved best as compared to other silicates in terms of ameliorating the osmotic stress. The silicic acid application improved the root and shoot growth parameters i.e. increased plant height by 13% and grain yield by 43%, relative water contents (30%), membrane stability (46%), antioxidant activity (up to 64%), organic solutes production and silicification of cell wall by increasing Si uptake by 9 folds.It was observed that combined use of tolerant varieties and silica fertilizer as silicic acid can uplift plant growth and production under water deficit conditions. Further field investigations are recommended to check crop economics of applied treatments.Methods: Drought stress negatively affects wheat crop production worldwide. Selection of drought tolerant varieties and application of silicon (Si) can help to uplift the crop production. The present investigation was aimed to screen drought tolerant wheat varieties by evaluating the potential of Si fertilization.Study was conducted in two sets of experiments, in first (hydroponic) investigation two wheat varieties out of eleven were screened out based upon agronomic parameters, membrane stability, potassium (K+) distribution and tolerance index. The screened varieties were then subjected to different silicon fertilizers under water deficit pot conditions in second experiment and impact of Si sources was monitored via agronomic, physiological and biochemical attributes.Faisalabad-08 and Anaj-17 were best performing varieties in tested parameters. The silica fertilizer application improved the growth, physiological, biochemical and ionic attributes under water deficit and increased the grain yield of crop. Among tested sources, silicic acid proved best as compared to other silicates in terms of ameliorating the osmotic stress. The silicic acid application improved the root and shoot growth parameters i.e. increased plant height by 13% and grain yield by 43%, relative water contents (30%), membrane stability (46%), antioxidant activity (up to 64%), organic solutes production and silicification of cell wall by increasing Si uptake by 9 folds.It was observed that combined use of tolerant varieties and silica fertilizer as silicic acid can uplift plant growth and production under water deficit conditions. Further field investigations are recommended to check crop economics of applied treatments.Results: Drought stress negatively affects wheat crop production worldwide. Selection of drought tolerant varieties and application of silicon (Si) can help to uplift the crop production. The present investigation was aimed to screen drought tolerant wheat varieties by evaluating the potential of Si fertilization.Study was conducted in two sets of experiments, in first (hydroponic) investigation two wheat varieties out of eleven were screened out based upon agronomic parameters, membrane stability, potassium (K+) distribution and tolerance index. The screened varieties were then subjected to different silicon fertilizers under water deficit pot conditions in second experiment and impact of Si sources was monitored via agronomic, physiological and biochemical attributes.Faisalabad-08 and Anaj-17 were best performing varieties in tested parameters. The silica fertilizer application improved the growth, physiological, biochemical and ionic attributes under water deficit and increased the grain yield of crop. Among tested sources, silicic acid proved best as compared to other silicates in terms of ameliorating the osmotic stress. The silicic acid application improved the root and shoot growth parameters i.e. increased plant height by 13% and grain yield by 43%, relative water contents (30%), membrane stability (46%), antioxidant activity (up to 64%), organic solutes production and silicification of cell wall by increasing Si uptake by 9 folds.It was observed that combined use of tolerant varieties and silica fertilizer as silicic acid can uplift plant growth and production under water deficit conditions. Further field investigations are recommended to check crop economics of applied treatments.Conclusion: Drought stress negatively affects wheat crop production worldwide. Selection of drought tolerant varieties and application of silicon (Si) can help to uplift the crop production. The present investigation was aimed to screen drought tolerant wheat varieties by evaluating the potential of Si fertilization.Study was conducted in two sets of experiments, in first (hydroponic) investigation two wheat varieties out of eleven were screened out based upon agronomic parameters, membrane stability, potassium (K+) distribution and tolerance index. The screened varieties were then subjected to different silicon fertilizers under water deficit pot conditions in second experiment and impact of Si sources was monitored via agronomic, physiological and biochemical attributes.Faisalabad-08 and Anaj-17 were best performing varieties in tested parameters. The silica fertilizer application improved the growth, physiological, biochemical and ionic attributes under water deficit and increased the grain yield of crop. Among tested sources, silicic acid proved best as compared to other silicates in terms of ameliorating the osmotic stress. The silicic acid application improved the root and shoot growth parameters i.e. increased plant height by 13% and grain yield by 43%, relative water contents (30%), membrane stability (46%), antioxidant activity (up to 64%), organic solutes production and silicification of cell wall by increasing Si uptake by 9 folds.It was observed that combined use of tolerant varieties and silica fertilizer as silicic acid can uplift plant growth and production under water deficit conditions. Further field investigations are recommended to check crop economics of applied treatments. [ABSTRACT FROM AUTHOR]

Technique for Order preference by Similarity to Ideal Solution (TOPSIS) is a Multi Attribute Decision Making (MADM) technique employed in diverse disciplines for the prioritization of alternative options/solutions to a problem. Test vector compaction for analog fault detection is a field which is witnessing continuous growth and experimentation. This study suggests a novel TOPSIS-based approach for the compaction of analog test vector to be constituted from test signals achieved by an exhaustive search method. The compacted test vector can help to reduce the test costs while at the same time enabling the test designer to base the compaction methodology on objectively obtained deterministic data. [ABSTRACT FROM AUTHOR]

Security and privacy have been continuously compromised in the modern multimedia network by various signal processing attacks. As a result, digital data owners are losing copyright protection, data security, and content authentication. A secure and robust digital watermarking scheme must protect digital works from the copyright and neutralize and counteract these potential threats. However, the existing audio watermarked strategies based on discrete wavelet transform face robustness issues relating to external attacks, and the embedding of unencrypted watermarks (text, image, and voice) easily violates security. Besides, these schemes failed to achieve a balance between the conflicting watermarking parameters, embedding capacity, and imperceptibility. As a solution, a robust dual-domain twofold encrypted image-in-audio watermarking scheme is proposed that initially exploits the binary image through Arnold encryption and Bose–Chaudhuri–Hocquenghem codes. Thus, it improves the watermark image's security, and intruders can't extract the watermark information directly. Prior to watermark embedding, both the encrypted image and the host audio signal are decomposed by dual-tree complex wavelet transforms , short-time Fourier transform, and singular value decomposition. It gives back two matrices, one for the encrypted image and the other for the host audio signal. The singular values of the matrices are used for embedding purposes. These threefold transformations improve capacity, imperceptibility, and complimentary level robustness against various digital signal processing attacks. The proposed system is evaluated experimentally based on improved security, robustness, embedding capacity, and imperceptibly compared to existing audio watermarking approaches. [ABSTRACT FROM AUTHOR]

In this article, we propose a new source separation method in which the dual-tree complex wavelet transform (DTCWT) and short-time Fourier transform (STFT) algorithms are used sequentially as dual transforms and sparse nonnegative matrix factorization (SNMF) is used to factorize the magnitude spectrum. STFT-based source separation faces issues related to time and frequency resolution because it cannot exactly determine which frequencies exist at what time. Discrete wavelet transform (DWT)-based source separation faces a time-variation-related problem (i.e., a small shift in the time-domain signal causes significant variation in the energy of the wavelet coefficients). To address these issues, we utilize the DTCWT, which comprises two-level trees with different sets of filters and provides additional information for analysis and approximate shift invariance; these properties enable the perfect reconstruction of the time-domain signal. Thus, the time-domain signal is transformed into a set of subband signals in which low- and high-frequency components are isolated. Next, each subband is passed through the STFT and a complex spectrogram is constructed. Then, SNMF is applied to decompose the magnitude part into a weighted linear combination of the trained basis vectors for both sources. Finally, the estimated signals can be obtained through a subband binary ratio mask by applying the inverse STFT (ISTFT) and the inverse DTCWT (IDTCWT). The proposed method is examined on speech separation tasks utilizing the GRID audiovisual and TIMIT corpora. The experimental findings indicate that the proposed approach outperforms the existing methods. [ABSTRACT FROM AUTHOR]