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Predicting the Stitch Density of Finished Fabrics Using Weft Blended Grey Knit Fabrics

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Journal of Textile Science and Technology 2024年第3期10卷 51-63页

作者： Kazi Md. Elias mohammad obaidur rahman H. M. Zakir Hossain Department of Physics Jahangirnagar University Savar Bangladesh Jute Textile Wing Bangladesh Jute Research Institute Dhaka Bangladesh

Stitch density is one of the critical quality parameters of knit fabrics. This parameter is closely related to other physical quality parameters like fabric weight, fabric tightness factor, fiber types, blend ratio, yarn diameter and linear density, and fabric structure. Selecting stitch density (wales per inch, course per inch) is essential to getting the appropriate fabric weight and desired quality. Usually, no rules or assumptions exist to get the desired stitch density in the finished fabric stage. Fifteen types of blended knit fabrics were prepared to conduct the study. The varying percentages of cotton, polyester, and elastane are incorporated in the blends. Regression analysis and regression ANOVA tests were done to predict the stitch density of finished fabrics. A suitable regression equation is established to get the desired results. The study also found that the stitch density value in the finished stage fabric decreases by approximately 15% compared to the stitch density in the grey fabric stage. This study will help the fabric manufacturers get the finished fabric stitch density in advance by utilizing the grey fabric stitch density data set. The author expects this research to benefit the knitting and dyeing industry, new researchers, and advanced researchers.

关键词： Wales per Inch Course per Inch Stitch Density Blended Knit Fabric

Mechanical and Electrical Properties of Some Sn-Zn Based Lead-Free Quinary Alloys

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Chemical Modification on Woven Jute and Nonwoven Wet-Laid Glass Fiber Sheet Reinforced Poly-(ε-Caprolactone) Composites

Materials Sciences and Applications（材料科学与应用期刊） 2024年第7期 213页

作者： Shihab Uddin Md.Abdul Gafur Suraya Sabrin Soshi mohammad obaidur rahman

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Open Journal of Composite Materials 2021年第4期11卷 63-81页

作者： mohammad Muzammel Hossen mohammad obaidur rahman BGMEA University of Fashion & Technology (BUFT) Dhaka Bangladesh

High-moisture regains nature of cellulosic fibers considered one of the critical drawbacks for jute-based applications. To minimize this by developing better interfacial adhesion, a hydrophobic nonwoven wet-laid glass fiber sheet used the woven jute fabric in this experiment. For this purpose, woven jute fabric was categorized into untreated, silane, alkali, and alkali-silane combined treatment then compounded with the solution of polycaprolactone (PCL). Fabrication of composites performed the following sandwich method based on different hot-pressing time with temperature for detecting a prominent fabrication parameter. Surface treated jute fibers characterized using FTIR spectroscopy. Hence, the mechanical and thermal properties of composites were investigated to find the consequence of chemical treatments into woven jute fabric. Alkali-silane combined chemical treatments resulting in improved 48.38% of tensile strength over untreated optimized composites. Scanning electron microscope (SEM) used for displaying interfacial adhesion between fiber and polymer matrix. Besides, further investigation demonstrated due to the combined chemical treatment of alkali-silane optimized composites significantly enhance

关键词： Woven Jute Fabric Polycaprolactone Compression Molding Surface Modification Mechanical Properties

Effect of Strain Rate on Tensile Behavior of Sn-9Zn-xAg-ySb;{(x, y) = (0.2, 0.6), (0.2, 0.8), (0.6, 0.2), (0.8, 0.2)} Lead-Free Solder Alloys

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Materials Sciences and Applications 2023年第4期14卷 273-283页

作者： Shihab Uddin Md. Abdul Gafur mohammad obaidur rahman Department of Physics Jahangirnagar University Savar Dhaka Bangladesh Pilot Plant and Process Development Centre Dhaka Bangladesh

The tensile properties of Sn-9Zn-xAg-ySb;{(x, y) = (0.2, 0.6), (0.2, 0.8), (0.6, 0.2), (0.8, 0.2)} lead-free solders were investigated. All the test samples were annealed at 150°C for 1 hour. The tests are carried out at room temperature at the strain rate of 4.17 × 10-3 s-1, 20.85 × 10-3 s-1, and 208.5 × 10-3 s-1. It is seen that the tensile strength increases and the ductility decrease with increasing the strain rate over the investigated range. From the strain rate change test results, the strain sensitivity values are found in the range of 0.0831 to 0.1455 due to the addition of different alloying elements.

关键词： Lead-Free Solder Strain Rate Strain Sensitivity Ductility Tensile Properties

Studying the Effect of Polyester Fiber Blend Ratio and Pilling Cycle on Blended Knit Fabrics

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Journal of Textile Science and Technology 2023年第4期9卷 227-243页

作者： Kazi Md. Elias mohammad obaidur rahman H. M. Zakir Hossain Testing Laboratory Textile Testing Services Ltd. Gazipur Bangladesh Department of Physics Jahangirnagar University Dhaka Bangladesh Jute Textile Wing Bangladesh Jute Research Institute Dhaka Bangladesh

Pilling is a severe concern for blended fabrics. The aesthetic look and smoothness are the buyers’ prime requirements. The main focus of the study was to see the pilling behavior from various percentages of polyester fiber blend ratio as well as the different pilling cycles on blended fabrics. The cotton, polyester, and elastane prepared the study fabrics. These fabrics are (90% Cotton/5% Polyester/5% Elastane, 90% Cotton/6% Polyester/4% Elastane, 90% Cotton/7% Polyester/3% Elastane, 90% Cotton/8% Polyester/2% Elastane, and 90% Cotton/9% Polyester/1% Elastane, 85% Cotton/10% Polyester/5% Elastane, 85% Cotton/11% Polyester/4% Elastane, 85% Cotton/12% Polyester/3% Elastane, 85% Cotton/13% Polyester/2% Elastane, and 85% Cotton/ 14% Polyester/1% Elastane, 80% Cotton/15% Polyester/5% Elastane, 80% Cotton/16% Polyester/4% Elastane, 80% Cotton/17% Polyester/3% Elastane, 80% Cotton/18% Polyester/2% Elastane, and 80% Cotton/19% Polyester/1% Elastane). The selected polyester blend ratios were 5%, 6%, 7%, 8%, 9%, 10%, 11%, 12%, 13%, 14%, 15%, 16%, 17%, 18% and 19% respectively. The study used the Martindale pilling tester with 2000, 5000, and 7000 cycles, respectively. The evaluation followed the ISO 12945-2:2000. The study findings are that the polyester fiber blend ratio did not influence the pilling grade on blended fabrics for pilling cycles 2000, and the pilling grade remained constant at 4 - 5. The pilling grade started to deteriorate in pilling cycle 5000 for the fabrics 85%C/10%P/5%E, 85%C/11%P/4%E, 85%C/12%P/3%E, 85%C/ 13%P/2%E, 85%C/14%P/1%E showed the pilling grade 4, and the fabrics made from 80%C/15%P/5%E, 80%C/16%P/4%E, 80%C/17%P/3%E, 80%C/ 18%P/2%E, 80%C/19%P/1%E showed the pilling grade 4, 3, 3, 3, and 3 respectively. For the pilling cycles 7000, the pilling grade further deteriorated for the fabrics 80%C/15%P/5%E, 80%C/16%P/4%E, 80%C/17%P/3%E, 80%C/ 18%P/2%E, 80%C/19%P/1%E showed the pilling grade 3, 3, 2, 2, and 2 respectively. The study finds the dominance o

关键词： Pilling Cotton Polyester Elastane Blended Knit Fabric

Predicting Bursting Strength Behavior of Weft Knitted Fabrics Using Various Percentages of Cotton, Polyester, and Spandex Fibers

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Journal of Textile Science and Technology 2023年第4期9卷 273-290页

The bursting strength is an essential quality parameter of knit fabric. The fabric structure, weight, types of fibers, and fiber blend proportion influence the bursting strength parameter. The tenacity of polyester fiber is better than cotton and spandex. The study focused on predicting knit fabric bursting strength test value using different fibers (cotton, polyester, and spandex) with varying percentages of the blend ratio. This study used fifteen categories of blended fabrics. The Pearson Correlation and the hypothetical ANOVA regression analysis were conducted to do the statistical significance test. The experimental result reveals that the bursting strength test result increased with the increased percentage of polyester and suggested a suitable regression equation. The dominance of the polyester fiber was observed throughout the experiment, i.e., the higher the polyester blend proportion, the higher the bursting strength value. The inclusion of polyester in blends can reduce the cost of fabric. The developed prediction model or equation can help the fabric manufacturer make appropriate decisions regarding getting the expected bursting strength. The researcher hopes that the findings from this study will motivate new researchers, advanced researchers, and the textile manufacturing industry.

关键词： Kilopascal Prediction Bursting-Strength Blended Fabric Cotton Polyester Spandex

Effect of Bismuth Addition on Structure and Mechanical Properties of Tin-9Zinc Soldering Alloy

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Materials Sciences and Applications 2015年第9期6卷 792-798页

作者： Muhommad Abdul Wadud M. A. Gafur Md. Rakibul Qadir mohammad obaidur rahman Department of Physics Jahangirnagar University Savar Bangladesh PP&PDC BCSIR Dhaka Bangladesh

Sn-Zn based solder is a possible replacement of Pb solder because of its better mechanical properties. The alloys need to be studied and explored to get a usable solder alloy having better properties. In this work eutectic Sn-9Zn and three Tin-Zinc-Bismuth ternary alloys were prepared and investigated their microhardness and mechanical properties. Microhardness, tensile strength and elastic modulus increase with Bi addition while ductility decreases with Bi addition.

关键词： Lead Free Solder Alloy Eutectic Alloy Microhardness

Thermal Behavior and Magnetic Properties of Nd-Fe-B Based Exchange Spring Nanocomposites Nd4-xTbxFe83.5Co5Cu0.5Nb1B6(x = 0, 0.2, 0.4, 0.6, 0.8 and 1) Melt-Spun Ribbons

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Advances in Materials Physics and Chemistry 2017年第6期7卷 223-241页

作者： Palash Chandra Karmaker mohammad obaidur rahman Nguyen Huy Dan Samia Islam Liba Per Nordblad Dilip Kumar Saha Sheikh Manjura Hoque Materials Science Division Atomic Energy CenterDhakaBangladesh Department of Physics Jahangirnagar UniversityDhakaBangladesh Institute of Materials Science Vietnam Academy of Science and TechnologyHanoiVietnam Solid State Physics Department of Engineering ScienceUppsala UniversityUppsalaSweden

Co-rich Nd-Fe-B nanocomposite ribbons with Tb substituted have been fabricated by single roller melt spinning technique of Nd4-xTbxFe83.5Co5Cu0.5Nb1B6 (x = 0, 0.2, 0.4, 0.6, 0.8 and 1) alloys in an argon (Ar) atmosphere at a circumferential speed of 40 m/s. According to the differential scanning calorimeter (DSC) traces the nanocomposite samples have been annealed at different temperatures like 675°C, 687°C, 700°C, 712°C and 725°C for 10 min. Crystallization behavior was studied by X-ray diffraction in which it was found that the XRD patterns are characterized by broad diffused pattern which demonstrate the amorphous state of materials. The ribbon samples were also characterized by vibration sample magnetometer (VSM) and Mössbauer spectroscopy at as-cast and annealed condition. Co-rich and Tb substitution has significantly enhanced the value of coercivity (Hc) and maximum energy product (BH)max. Highest value of Hc and (BH)max has been obtained as 2.36 kOe and 6.11 MGOe for the sample annealed at 700°C for 10 min with higher concentration of Tb. The M-H hysteresis loops show extremely soft natures which do not possess any area. We have found reduced remanent ratio (Mr/Ms) up to 0.49 at optimal annealing temperature 700°C. However, with the annealing of the samples in the above mentioned temperature, evolution of large coercivity was observed due to the formation of exchange couple hard and soft nanocrystal composites. We have investigated the variation of Curie temperature (Tc) with annealing temperature of the melt spun ribbon samples. Mossbauer spectroscopy was carried out to study the hyperfine parameters such as hyperfine field, hyperfine field distribution for full width half maximum (FWHM) and isomer shift of Fe species of these two phases.

关键词： Coercivity Maximum Energy Product Remanent Ratio Nanocomposite Hard and Soft Phases

Detecting anomalies in blockchain transactions using machine learning classifiers and explainability analysis

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BLOCKCHAIN-RESEARCH AND APPLICATIONS 2024年第3期5卷 106-122页

作者： Hasan, mohammad rahman, mohammad Shahriar Janicke, Helge Sarker, Iqbal H. Premier Univ Dept Comp Sci & Engn Chitagong 4000 Bangladesh United Int Univ Dept Comp Sci & Engn Dhaka 1212 Bangladesh Cyber Secur Cooperat Res Ctr Perth 6027 Australia Edith Cowan Univ Ctr Securing Digital Futures Perth 6027 Australia

As the use of blockchain for digital payments continues to rise, it becomes susceptible to various malicious attacks. Successfully detecting anomalies within blockchain transactions is essential for bolstering trust in digital payments. However, the task of anomaly detection in blockchain transaction data is challenging due to the infrequent occurrence of illicit transactions. Although several studies have been conducted in the field, a limitation persists: the lack of explanations for the model's predictions. This study seeks to overcome this limitation by integrating explainable artificial intelligence (XAI) techniques and anomaly rules into tree-based ensemble classifiers for detecting anomalous Bitcoin transactions. The shapley additive explanation (SHAP) method is employed to measure the contribution of each feature, and it is compatible with ensemble models. Moreover, we present rules for interpreting whether a Bitcoin transaction is anomalous or not. Additionally, we introduce an under-sampling algorithm named XGBCLUS, designed to balance anomalous and non-anomalous transaction data. This algorithm is compared against other commonly used under-sampling and over-sampling techniques. Finally, the outcomes of various tree-based single classifiers are compared with those of stacking and voting ensemble classifiers. Our experimental results demonstrate that: (i) XGBCLUS enhances true positive rate (TPR) and receiver operating characteristic-area under curve (ROC-AUC) scores compared to state-of-the-art under-sampling and over-sampling techniques, and (ii) our proposed ensemble classifiers outperform traditional single tree-based machine learning classifiers in terms of accuracy, TPR, and false positive rate (FPR) scores.

关键词： Anomaly detection Blockchain Bitcoin transactions Data imbalance Data sampling Explainable AI Machine learning Decision tree Anomaly rules