GOBI NALLATHAMBI, BHARGAVI RAM THIMMIAH^*

Journal of Polymer Materials, Vol.37, No.3-4, pp. 189-200, 2020, DOI:10.32381/JPM.2020.37.3-4.6

Abstract The aim of this study is to optimize the process parameters of alkali treated Saharan aloe vera cactus fibres using of Box-behnken experimental design. The Saharan aloe vera cactus fibres were treated with different concentration of NaOH, soaking time and temperature which affect the properties of fibres and plays main role in removal of lignin, hemicellulose, pectin and wax content. The chemical composition of untreated and treated fibres was analyzed by standard methods. XRD result shows the improvement in the crystallinity index of fibres due to alkali treatment. ATR-FTIR analysis shows that hemicellulose and lignin were decreased in all alkali… More >

NEETU TRIPATHI, DIBYENDU S. BAG^*, MAYANK DWIVEDI

Journal of Polymer Materials, Vol.40, No.3-4, pp. 227-269, 2023, DOI:10.32381/JPM.2023.40.3-4.8

Abstract Over the last three decades, there has been considerable interest in the captivating mechanical properties displayed by auxetic materials, highlighting the advantages stemming from their distinct negative Poisson's ratio. The negative Poisson's ratio observed in auxetic polymeric materials is a result of the distinctive geometries of their unit cells. These unit cells, encompassing structures such as chiral, re-entrant, and rotating rigid configurations, are carefully engineered to collectively generate the desired auxetic behaviour. This comprehensive review article explores the field of auxetic polymeric materials, offering a detailed exploration of their geometries, fabrication methods, mechanical properties, and characterisation. The diverse applications of… More >

Ralph L. Webb

Frontiers in Heat and Mass Transfer, Vol.2, No.2, pp. 1-5, 2011, DOI:10.5098/hmt.v2.2.3001

Abstract This paper discusses the “Inlet Temperature Difference” (ITD) based heat-exchanger (and its variants) design methodology frequently used by designers of electronic heat sinks. The methodology is at variance with the accepted methodology recommended in standard heat-transfer text books – the “Log-Mean Temperature Difference” (LMTD), or the equivalent “effectiveness-NTU” design method. The purpose of this paper is to evaluate and discuss the ITD based design methodology and its deficiencies. The paper shows that the ITD based method is an approximation at best. Variants of the method can lead to either under or over prediction of the heat transfer rate. Its shortcomings… More >

Yatim Lailun Ni’mah¹, Afaf Baktir², Dewi Santosaningsih³, Suprapto Suprapto^1,*

Journal of Renewable Materials, Vol.12, No.2, pp. 245-258, 2024, DOI:10.32604/jrm.2023.045514

Abstract Silver nanoparticles (AgNPs) synthesized using tartaric acid as a capping agent have a great impact on the reaction kinetics and contribute significantly to the stability of AgNPs. The protective layer formed by tartaric acid is an important factor that protects the silver surface and reduces potential cytotoxicity problems. These attributes are critical for assessing the compatibility of AgNPs with biological systems and making them suitable for drug delivery applications. The aim of this research is to conduct a comprehensive study of the effect of tartaric acid concentration, sonication time and temperature on the formation of silver nanoparticles. Using Response Surface… More > Graphic Abstract

Uma Ramasamy^*, Sundar Santhoshkumar

Journal of Intelligent Medicine and Healthcare, Vol.2, pp. 1-14, 2024, DOI:10.32604/jimh.2023.046995

Abstract More than 140 autoimmune diseases have distinct autoantibodies and symptoms, and it makes it challenging to construct an appropriate model using Machine Learning (ML) for autoimmune disease. Arthritis-related autoimmunity requires special attention. Although many conventional biomarkers for arthritis have been established, more biomarkers of arthritis autoimmune diseases remain to be identified. This review focuses on the research conducted using data obtained from clinical laboratory testing of real-time arthritis patients. The collected data is labelled the Arthritis Profile Data (APD) dataset. The APD dataset is the retrospective data with many missing values. We undertook a comprehensive APD dataset study comprising four… More >

Runlian Zhang^1,*, Rui Shu¹, Yongzhuang Wei¹, Hailong Zhang², Xiaonian Wu¹

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1911-1927, 2023, DOI:10.32604/cmc.2023.041187

Abstract S-boxes can be the core component of block ciphers, and how to efficiently generate S-boxes with strong cryptographic properties appears to be an important task in the design of block ciphers. In this work, an optimized model based on the generative adversarial network (GAN) is proposed to generate 8-bit S-boxes. The central idea of this optimized model is to use loss function constraints for GAN. More specially, the Advanced Encryption Standard (AES) S-box is used to construct the sample dataset via the affine equivalence property. Then, three models are respectively built and cross-trained to generate 8-bit S-boxes based on three… More >

Cut Rahmawati^1,2,*, Lia Handayani³, Muhtadin⁴, Muhammad Faisal⁴, Muhammad Zardi¹, S. M. Sapuan⁵, Agung Efriyo Hadi⁶, Jawad Ahmad⁷, Haytham F. Isleem⁸

Journal of Renewable Materials, Vol.11, No.10, pp. 3751-3767, 2023, DOI:10.32604/jrm.2023.028987

Abstract Waste Glass (WGs) and Coir Fiber (CF) are not widely utilized, even though their silica and cellulose content can be used to create construction materials. This study aimed to optimize mortar compressive strength using Response Surface Methodology (RSM). The Central Composite Design (CCD) was applied to determine the optimization of WGs and CF addition to the mortar compressive strength. Compressive strength and microstructure testing with Scanning Electron Microscope (SEM), Fourier-transform Infrared Spectroscopy (FT-IR), and X-Ray Diffraction (XRD) were conducted to specify the mechanical ability and bonding between the matrix, CF, and WGs. The results showed that the chemical treatment of… More > Graphic Abstract

B. Ramesh, Kuruva Lakshmanna^*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2513-2528, 2023, DOI:10.32604/cmes.2023.028944

Abstract Major chronic diseases such as Cardiovascular Disease (CVD), diabetes, and cancer impose a significant burden on people and healthcare systems around the globe. Recently, Deep Learning (DL) has shown great potential for the development of intelligent mobile Health (mHealth) interventions for chronic diseases that could revolutionize the delivery of health care anytime, anywhere. The aim of this study is to present a systematic review of studies that have used DL based on mHealth data for the diagnosis, prognosis, management, and treatment of major chronic diseases and advance our understanding of the progress made in this rapidly developing field. Type 2… More > Graphic Abstract

Jingang Kim, Suengbum Lim, Taejin Lee^*

Computer Systems Science and Engineering, Vol.47, No.1, pp. 471-490, 2023, DOI:10.32604/csse.2023.038413

Abstract AI-related research is conducted in various ways, but the reliability of AI prediction results is currently insufficient, so expert decisions are indispensable for tasks that require essential decision-making. XAI (eXplainable AI) is studied to improve the reliability of AI. However, each XAI methodology shows different results in the same data set and exact model. This means that XAI results must be given meaning, and a lot of noise value emerges. This paper proposes the HFD (Hybrid Feature Dropout)-based XAI and evaluation methodology. The proposed XAI methodology can mitigate shortcomings, such as incorrect feature weights and impractical feature selection. There are… More >

Mohamed Abouhawwash^1,2, S. Sridevi³, Suma Christal Mary Sundararajan⁴, Rohit Pachlor⁵, Faten Khalid Karim⁶, Doaa Sami Khafaga^6,*

Computer Systems Science and Engineering, Vol.47, No.1, pp. 239-253, 2023, DOI:10.32604/csse.2023.037812

Abstract One of the significant health issues affecting women that impacts their fertility and results in serious health concerns is Polycystic ovarian syndrome (PCOS). Consequently, timely screening of polycystic ovarian syndrome can help in the process of recovery. Finding a method to aid doctors in this procedure was crucial due to the difficulties in detecting this condition. This research aimed to determine whether it is possible to optimize the detection of PCOS utilizing Deep Learning algorithms and methodologies. Additionally, feature selection methods that produce the most important subset of features can speed up calculation and enhance the effectiveness of classifiers. In… More >