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Quality assessment of different ozone treatments to extend shelf-life of banana (Musa acuminata)

Materials Today: Proceedings 2022年 65卷 2452-2455页

作者： Siriprom, Wichian Teanchai, Kanyakorn Chamchoi, Noppadon Faculty of Science at Si Racha Kasetsart University Si Racha campus Chonburi 20230 Thailand Material Science and Applied Physics Research Unit Faculty of Science at Si Racha Kasetsart University Si Racha campus Chonburi 20230 Thailand Forensic Science Faculty of Science and Technology Suan Sunandha Rajabhat University Bangkok 10300 Thailand

This study investigated the physicochemical parameters before and after ozone treatment of bananas (Musa acuminata) known as "Hom Thong" in Thailand. The effects of different durations of ozone exposure and storage temperatures were used to evaluate the effectiveness of ozone treatment in extending shelf life, as shown by the changes in surface morphology, peel color index, total titratable acidity, and weight loss of the Hom Thong sample. The duration of ozone exposure was 10 and 60 min every 4 h during an 18-day storage period at a flow rate of 15 L/min, while the storage temperatures were 18 and 30 °C (ambient temperature), respectively. The quality at the beginning of the storage period and after 3, 6, 9, 12, 15 and 18 days of storage was investigated using the physicochemical parameters. The result showed that the quality was better at 18 °C storage temperature, but the color index of the peel had changed rapidly. When the results were available on the 12 day of storage, mold growth started in the untreated sample but was absent in the Hom Thong sample treated with ozone. Therefore, it can be concluded that ozone treatment is an alternative process that can extend the shelf life of bananas (Hom Thong) with great potential. © 2022

关键词： Ozone

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Data-Driven Bandwidth Selection in Kernel Density Estimation via Unsupervised Learning 8th

Data-Driven Bandwidth Selection in Kernel Density Estimatio...

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8th International Symposium on Modelling and Implementation of Complex Systems, MISC 2024

作者： Guidoum, Arsalane Chouaib Henider, Amel Department of Mathematics and Computer Science Faculty of Sciences and Technology University of Tamanghasset Tamanghasset11000 Algeria Department of Finance and Actuarial National Higher School of Statistics and Applied Economics Kolea42003 Algeria

ISBN: (纸本)9783031821110

The selection of optimal bandwidth bw in Kernel Density Estimation (KDE) is crucial for accurate density estimation. Traditional methods, such as unbiased and biased cross-validation and their variants, often suffer from performance and computational limitations. This study presents a novel, data-driven approach to bandwidth selection using unsupervised machine learning techniques. Synthetic samples are generated from the original data, a comprehensive set of statistical parameters is calculated, and bandwidth is estimated using a rule-of-thumb [2]. Feature importance is assessed through random forests (RF) to identify the most influential factors in bandwidth selection. Various unsupervised learning models are then applied to predict the optimal bandwidth for the original sample bwos. The results demonstrate that this machine learning-based approach achieves superior accuracy and computational efficiency compared to traditional cross-validation methods. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Adversarial machine learning

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Improved Mechanical Properties and Use of Rice Husk-Reinforced Recycled Thermoplastic Composite in Safety Helmets 2nd

Improved Mechanical Properties and Use of Rice Husk-Reinforc...

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2nd International Conference on Materials, Design and Manufacturing for Sustainable Environment, ICMDMSE 2022

作者： Al-Talib, Ammar A. Chen, Ruey Shan Natarajan, Elango Chai, Ashley Denise Faculty of Engineering Technology and Built Environment UCSI University Kuala Lumpur56000 Malaysia Department of Applied Physics Faculty of Science and Technology The National University of Malaysia Selangor Bangi43600 Malaysia

ISBN: (纸本)9789811930522

Recycled thermoplastics have inferior mechanical properties as compared to virgin thermoplastics. It limits application of recycled thermoplastics in industrial and domestic parts. In this research, abundance of rice husk fibre in the form of agricultural waste was utilised to reinforce and increase mechanical properties of recycled high-density polyethylene and polyethylene terephthalate composite (rHDPE/rPET). Rice husk (RH) fibres (70 wt%)-reinforced recycled thermoplastic composite was fabricated through a two-step extrusion process and hot press moulding technique. The tensile strength and elastic modulus were increased by 4.95% and 162.65% as compared with pure recycled thermoplastic blend. Water absorption and swelling of the composite was analysed by immersing it in water for 4 weeks of time. Furthermore, the applicability of rHDPE/rPET/RH composite in safety helmet was analysed using finite element analysis. The analysis according to EN397 standard reports that RH-reinforced recycled thermoplastic is safer than virgin recycled plastic. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Water absorption

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Effect of Co^(2+)substitution in B-sites of the perovskite system on the phase formation,microstructure,electrical and magnetic properties of Bi0.5(Na0.68K0.22Li0.10)0.5TiO3 ceramics

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International Journal of Minerals,Metallurgy and Materials 2022年第9期29卷 1798-1808页

作者： Pamornnarumol Bhupaijit Chonnarong Kaewsai Tawat Suriwong Supree Pinitsoontorn Surirat Yotthuan Naratip Vittayakorn Theerachai Bongkarn Department of Physics Faculty of ScienceNaresuan UniversityPhitsanulok 65000Thailand School of Renewable Energy and Smart Grid Technology Naresuan UniversityPhitsanulok 65000Thailand Research Center for Academic Excellence in Applied Physics Faculty of ScienceNaresuan UniversityPhitsanulok 65000Thailand Institute of Nanomaterials Research and Innovation for Energy(IN-RIE) Khon Kaen UniversityKhon Kaen 40002Thailand Department of Chemistry School of ScienceKing Mongkut's Institute of Technology LadkrabangBangkok 10520Thailand

Bi_(0.5)(Na_(0.68)K_(0.22)Li_(0.10))_(0.5)Ti_(1-x)Co_(x)O_(3) lead-free perovskite ceramics(BNKLT-xCo,x=0,0.005,0.010,0.015 and 0.020)were fabricated via the solid-state combustion technique.A small-amount of Co^(2+)ion substitution into Ti-sites led to modification of the phase formation,microstructure,electrical and magnetic properties of BNKLT *** rhombohedral and tetragonal phases were observed in all samples using the X-ray diffraction(XRD)*** Rietveld refinement revealed that the rhombohedral phase increased from 39%to 88%when x increased from 0 to *** average grain size increased when x *** increasing x,more oxygen vacancies were generated,leading to asymmetry in the bipolar strain(S-E)hysteresis *** the composition of x=0.010,a high dielectric constant(ε_(m))of 5384 and a large strain(S_(max))of 0.23%with the normalized strain (d*_(33))of 460 pm·V^(-1) were *** BNKLT-0Co ceramic showed diamagnetic behavior but all of the BNKLT-xCo ceramics exhibited paramagnetic behavior,measured at 50 K.

关键词： BNKLT-xCo dielectric ferroelectric strain magnetic

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Characterization of YBa2Cu4O8superconductor prepared by using YBa2Cu3O7-xand CuO via solid state reaction technique with heating under ordinary oxygen pressure 4

Characterization of YBa2Cu4O8superconductor prepared by usin...

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4th International Conference on Separation technology, ICoST 2023

作者： Min Cheong, Choon Kien Chen, Soo Faculty of Computer Science & Information Technology Universiti Malaya Kuala Lumpur57100 Malaysia School of Engineering INTI International College Penang 11900 Malaysia Department of Physics Faculty of Science Universiti Putra Malaysia Selangor Darul Ehsan Serdang43300 Malaysia

The aim and objective of this study is to investigate the material synthesis and superconducting properties of YBa2Cu4O8(Y-124) synthesized from YBa2Cu3O7-x(Y-123) and CuO powders. A commercial Y-123 and CuO powders were used to synthesize polycrystalline Y-124 employing the conventional solid state reaction method with heating at 1 atm oxygen pressure. Sodium nitrate was used as catalytic enhancer during the chemical reaction. The samples were subjected to twice sintering at 815 °C for 24 h with intermittent grinding. Analysis of the x-ray diffraction (XRD) data showed that Y-124 phase is dominance (81.1 wt%) in the samples with the presence of Y-123, and CuO as secondary phases. The thermogravimetric curve shows a small oxygen loss at ∼400 °C and rapid oxygen loss above ∼850 °C. Scanning electron microscope (SEM) images revealed that the samples had irregular grain shapes ranging in size from a few micrometers to fractions of a micrometer. The four-point-probe method was used to measure superconducting transition temperature (Tc). The samples exhibited a dual superconducting transition with the onset Tcof around 77 K and 87 K, respectively. This is consistent with the co-existence of superconducting phase Y-124 and Y-123. This two-level Tccharacteristic of the sample gave potential application in multiples industries, including electronics, transportation, and data storage and processing. This study demonstrates how efficient and optimal conditions can be used to produce the Y-124 phase. © 2024 Elsevier Ltd. All rights reserved.

关键词： Copper oxides

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Deep Learning and SVM-Based Approach for Indian Licence Plate Character Recognition

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computers, Materials & Continua 2023年第1期74卷 881-895页

作者： Nitin Sharma Mohd Anul Haq Pawan Kumar Dahiya B.R.Marwah Reema Lalit Nitin Mittal Ismail Keshta Department of Electronics&Communication Engineering Chandigarh UniversityMohali140413India Department of Computer Science College of Computer and Information SciencesMajmaah University11952Al-MajmaahSaudi Arabia Department of Electronics&Communication Engineering DCRUST Murthal131039India Department of Transportation Engineering IITKanpur208016Uttar PradeshIndia Department of Computer Science Applications PIETSmalkha132102India Skill Faculty of Science and Technology Shri Vishwakarma Skill UniversityPalwal121102India Computer Science and Information Systems Department College of Applied SciencesAlMaarefa UniversityRiyadhSaudi Arabia

Every developing country relies on transportation,and there has been an exponential expansion in the development of various sorts of vehicles with various configurations,which is a major component strengthening the automobile *** is a developing country with increasing road traffic,which has resulted in challenges such as increased road accidents and traffic oversight *** the lack of a parametric technique for accurate vehicle recognition,which is a major worry in terms of reliability,high traffic density also leads to mayhem at checkpoints and toll plazas.A system that combines an intelligent domain approach with more sustainability indices is a better way to handle traffic density and transparency *** Automatic Licence Plate Recognition(ALPR)system is one of the components of the intelligent transportation system for traffic *** study is based on a comprehensive and detailed literature evaluation in the field of *** major goal of this study is to create an automatic pattern recognition system with various combinations and higher accuracy in order to increase the reliability and accuracy of identifying digits and alphabets on a car *** research is founded on the idea that image processing opens up a diverse environment with allied fields when employing distinct soft techniques for *** properties of characters are employed to recognise the Indian licence plate in this *** licence plate recognition,more than 200 images were analysed with various parameters and soft computing techniques were *** comparison to neural networks,a hybrid technique using a Convolution Neural Network(CNN)and a Support Vector Machine(SVM)classifier has a 98.45%efficiency.

关键词： Intelligent transportation system automatic license plate recognition system neural network random forest convolutional neural network support vector machine

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AI-Enhanced Virtual Twin Modelling for Strengthening IoT Software Security Protocols 1

AI-Enhanced Virtual Twin Modelling for Strengthening IoT Sof...

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1st International Conference on Software, Systems and Information technology, SSITCON 2024

作者： Kumara, Bharath Barmola, Pareshwar Prasad Arora, Renuka Parikh, Swapnil M Maranan, Ramya Ramaiah University of Applied Science Department of Electronics and Communication Engineering Bengaluru India Graphic Era Deemed to Be University Department of Computer Science and Engineering Dehradun India Jagannath University Department of Computer Science and Engineering Haryana India Parul Institute of Engineering and Technology Parul University Faculty of Computer Science and Engineering Vadodara India Simats Saveetha School of Engineering Department of Research and Innovation Chennai India

ISBN: (纸本)9798350352931

To fortify security mechanisms in software systems for the Internet of Things (IoT), this article presents a framework for AI-Enhanced Virtual Twin Modelling. In order to track and examine the actions of IoT devices in real-time, the suggested method makes use of virtual twin technology that is combined with machine learning techniques. Automated response generation, continuous threat assessment, and anomaly detection are made possible by creating a digital clone of the actual IoT network using the virtual twin paradigm. By combining deep learning models like CNNs and LSTMs, it becomes easier to forecast possible security risks in network traffic data by seeing intricate spatial and temporal patterns. When tested in a virtual Internet of Things (IoT) setting, the suggested framework outperforms conventional rule-based approaches by a wide margin, reducing reaction time by 35% while achieving an accuracy of 9 6. 2 %in threat identification. © 2024 IEEE.

关键词： Risk assessment

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First principle study of X2GaAgCl6 (X = Cs, Rb) double perovskites: structural, mechanical, vibrational, electronic, optical, SLME, thermoelectric, and thermodynamic properties for solar cell applications

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Environmental science and Pollution Research 2024年第24期31卷 34881-34895页

作者： Rehman, Zia Ur Rehman, Muhammad Awais Khan, Muhammad Rashid Rehman, Bushra Sikiru, Surajudeen Rizwan, Muhammad Chafi, Mohammed Usman, Muhammad Department of Mathematics Namal University 30Km Talagang Road Mianwali42250 Pakistan Institute of Physics University of Silesia Ul 75 Pulku Piechoty 1 Chorzów41-500 Poland Department of Environmental Science Quaid-I-Azam University Islamabad Islamabad45320 Pakistan School of Physics and Materials Studies Faculty of Applied Science Universiti Teknologi Mara Selangor Shah Alam40450 Malaysia School of Physical Sciences University of the Punjab Lahore Pakistan LIPE Higher School of Technology Hassan II University of Casablanca Oasis Morocco Department of Applied Mechanics School of Mathematics and Physics University of Science and Technology Beijing Beijing China

The structural, mechanical, vibrational, electronic, optical, SLME, thermoelectric, and thermodynamic properties of X2GaAgCl6 (X = Cs, Rb), a double perovskite material, were computed by employing Density Functional Theory (DFT). CASTEP and Quantum ESPRESSO were used to perform first-principles calculations. X2GaAgCl6 possesses a cubic structure with the space-group symmetry Fm-3 m. The lattice parameters of Cs2GaAgCl6 and Rb2GaAgCl6 were optimized using the energy-volume curves, resulting in values of 7.357 Å and 7.365 Å, respectively. The population analysis confirmed the charge transfer among transition metals and halogen atoms. The stability of crystal X2GaAgCl6 (X = Cs, Rb) is effectively demonstrated by analyzing phonon dispersion curves with no negative frequencies. The band structure calculations indicated the semiconducting nature of compounds with energy gaps of 0.96 eV and 0.88 eV for Cs2GaAgCl6 and Rb2GaAgCl6, respectively. The optical characteristics results confirm that the examined materials are suitable for devices working, primarily in the electromagnetic spectrum’s visible region. SLME results showed that Cs2GaAgCl6 has 30% and Rb2GaAgCl6 has 27% efficiency, respectively, suggesting their use in photovoltaics. The thermoelectric properties of X2GaAgCl6 (X = Cs, Rb) were calculated by using the BoltzTraP code in the temperature range of 300 to 800 K. The quasi-harmonic Debye model was applied to calculate the thermodynamic characteristics. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Density functional theory

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Universality of random-site percolation thresholds for two-dimensional complex noncompact neighborhoods

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Physical Review E 2024年第3期109卷 034108-034108页

作者： Krzysztof Malarz AGH University Faculty of Physics and Applied Computer Science al. Mickiewicza 30 30-059 Kraków Poland

The phenomenon of percolation is one of the core topics in statistical mechanics. It allows one to study the phase transition known in real physical systems only in a purely geometrical way. In this paper, we determine thresholds pc for random-site percolation in triangular and honeycomb lattices for all available neighborhoods containing sites from the sixth coordination zone. The results obtained (together with the percolation thresholds gathered from the literature also for other complex neighborhoods and also for a square lattice) show the power-law dependence pc∝(ζ/K)−γ with γ=0.526(11), 0.5439(63), and 0.5932(47), for a honeycomb, square, and triangular lattice, respectively, and pc∝ζ−γ with γ=0.5546(67) independently on the underlying lattice. The index ζ=∑iziri stands for an average coordination number weighted by distance, that is, depending on the coordination zone number i, the neighborhood coordination number zi, and the distance ri to sites in the ith coordination zone from the central site. The number K indicates lattice connectivity, that is, K=3, 4, and 6 for the honeycomb, square, and triangular lattice, respectively.

关键词： Percolation Phase transitions Finite-size scaling Monte Carlo methods

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WSports-50: An Image Dataset for Women’s Sport Action Classification 4th

WSports-50: An Image Dataset for Women’s Sport Action Class...

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4th International Conference on Frontiers in Computing and Systems, COMSYS 2023

作者： Ray, Palash Bera, Asish Krejcar, Ondrej Bhattacharjee, Debotosh Nasipuri, Mita Department of Computer Science and Engineering Haldia Institute of Technology West Bengal Haldia India Department of Computer Science and Information Systems BITS Pilani Rajasthan Pilani India Center for Basic and Applied Science Faculty of Informatics and Management University of Hradec Kralove Rokitanskeho 62 Hradec Kralove500 03 Czech Republic Department of Computer Science and Engineering Jadavpur University West Bengal Kolkata India

ISBN: (纸本)9789819726134

Sport action recognition is an interesting area in computer vision. Categorization of sport actions, representing difficult and complex body postures, is regarded as a fine-grained visual classification problem. The Convolutional Neural Networks (CNNs) have attained enhanced performance over conventional feature descriptors in recognizing various sport activities. In general, though decent improvement has been gained using deep learning for sport action recognition, however, recognition of women’s sport activities is not widely explored. Even, no benchmark dataset depicting women’s sport action with sufficient variations is available yet for study. Hence, fine-grained image classification of diverse sport categories involving female/women athletics requires immediate research attention. To overcome this limitation, this paper proposes an image dataset comprising worldwide popular 50 sport categories of women players only. A simple deep learning model is proposed that extracts the high-level deep features using a backbone CNN. Then, these features are pooled from a collection of regular regions representing local discriminative information. The spatial pyramid pooling is applied for mining semantic information and enhancing feature aggregation for classification. The proposed method has achieved satisfactory performance on the Women Sports dataset using four standard backbone CNNs. Moreover, our method has achieved better accuracy on the Yoga-82 pose recognition dataset with a significant margin, e.g., 11.6% gain using ResNet-50 base CNN. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Classification (of information)

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