NRU :: Browsing by Author "Kamalha, Edwin"

Browsing by Author "Kamalha, Edwin"

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Antimicrobial and Antiviral Properties of Metal Nanoparticles and Their Potential Use in Textiles: A Review
(University of Oradea Fascicle of Textiles, Leatherwork, 2021) Nonsikelelo Sheron, Mpofu; Mwasiagi, Josphat Igadwa; Nganyi, Eric Oyondi; Kamalha, Edwin
Recent global trends have put an emphasis on the importance of hygiene in all sectors including textiles. Antimicrobial and antiviral finishes are used in textiles to control bacteria, moulds, fungi and viruses on the textile substrate. Metal nanoparticles have been shown to posess antimicrobial and antiviral properties and can potentially be used in textiles for the production of fabrics with these functions. The aim of this paper is to explore the different antimicrobial and antiviral properties possessed by zinc oxide nanoparticles, titanium dioxide nanoparticles, silver nanoparticles and copper nanoparticles and their potential use in textiles. The challenges associated with these metal nanoparticles have also been assessed. Most of the metal nanoparticles studied display antibacterial properties against gram-negative Escherichia Coli and Pseudomonas Aeruginosa as well as gram-positive Staphylococcus aureus. Antiviral activities were also observed against Herpes Simplex Virus Type 1 (HSV-1), H1N1 influenza, poliovirus and foot and mouth disease. Although the metal nanoparticles showed potential for use as antimicrobial and antiviral finishes for textile substrates, environmental concerns have been raised on their use as they tend to be toxic during use and also produce a harmful washing effluent. Future studies should focus on the mitigation of the toxicity challenges associated with the use of metal nanoparticles.
Classification and Measure of Quantitative Difference between Polyester and Cotton Fabrics Based on Sensory Analysis
(FLINS, 2016) Kamalha, Edwin; Koehl, Ludovic; Campagne, Christine
In this study we compare cotton and polyester (Polyethylene terephthalate) (PET) sensory attributes, as a precursor for sensory modification of polyester, for cotton replacement. We systematically identify the key sensory attributes that distinguish cotton from polyester fabrics. Rank Aggregation, Principal Component Analysis (PCA), Agglomerative Hierarchical Clustering (AHC), and the measure of distances are used to process elicited data.
Clustering and Classification of Cotton Lint Using Principle Component Analysis, Agglomerative Hierarchical Clustering, and K-Means Clustering
(Journal of Natural Fibers, 2017) Kamalha, Edwin; Kiberu, Jovan; Nibikora, Ildephonse; Igadwa Mwasiagi, Josphat; Omollo, Edison
Cotton from the three cotton growing regions of Uganda was characterized for 13 quality parameters using the High Volume Instrument (HVI). Principal Component Analysis (PCA), Agglomerative Hierarchical Clustering (AHC) and k-means clustering were used to model cotton quality parameters. Using factor analysis, cotton yellowness and short fiber index were found to account for the highest variability. At 5% significance level, the highest correlation (0.73) was found between short fiber index and yellowness. Based on Cotton Outlook’s world classification and USDA Standards, the cotton under test was deemed of high and uniform quality, falling between Middling and Good Middling grades. Our suggested classification integrates all lint quality parameters, unlike the traditional methods that consider selected parameters.
The Comfort Dimension: a Review of Perception in Clothing
(Journal of sensory studies, 2013) Kamalha, Edwin; Zeng, Yongchun; Mwasiagi, Josphat I.; Kyatuheire, Salome
For a clothing system, comfort is a fundamental necessity. In this paper, basic definitions and elements of clothing comfort and the general research trends were reviewed. In particular, understanding comfort of textile materials, its relevance to clothing choice and some assessment methods have been discussed. The impact of fabric and clothing attributes on clothing comfort was explored. Psychological, physical and physiological perceptions of clothing comfort were reviewed, including subjective and objective modes of assessment. A thorough discussion of handle comfort was presented, including assessment methods. Statistical presentations from selected comfort studies were also reviewed. Other sensory comfort properties particularly acoustic and appearance were also mentioned. From the aforementioned reviews, it was noted that the main focus for most researchers has been on sensorial and thermal comfort.
Construction of a prediction model for body dimensions used in garment pattern making based on anthropometric data learning
(The Journal of The Textile Institute, 2017) Liu, Kaixuan; Wang, Jianping; Kamalha, Edwin; Li, Victoria; Zeng, Xianyi
Using artificial intelligence to predict body dimensions rather than measuring them physically is a new research direction in apparel industry. If implemented, this technology can reduce costs and improve efficiency. In this paper, we proposed a back propagation artificial neural network (BP-ANN) model to predict pattern making-related body dimensions by inputting few key human body dimensions. In order to construct the proposed model, anthropometric measurements of 120 young females from the northeastern region of China were collected. The data were then used for training and the proposed model. The results showed that the prediction of the developed BP-ANN model is more accurate and stable than that of linear regression (LR) model. As great as the LR model was at pattern making, the BP-ANN model is even better. In the future, the precision of the proposed model can be further improved if the size of the learning data increases. The proposed method can be especially useful in making garment pattern for form-fitting clothing.
Cotton-elastane ring core spun yarn: A review
(Research & Reviews on Polymer, 2013) Tayari Akankwasa, Nicholus; Siddiqui, Qasim; Kamalha, Edwin; Ndlovu, Llyod
The quest for highly stretchable fabrics with good and lasting handle properties such as absorbance, feel, and comfort has inspired researchers to constantly involve in blending of natural and artificial fibres. One of the commonly used methods of blending is core yarn spinning. Core spun yarn structure consists of two components; the sheath and the core. Normally, a continuous multifilament yarn is used as a core while cotton staple fibres are used to cover the filament. Cotton staple fibres have been a favourite choice for the sheath of core spun yarns because of their aesthetic properties. Cotton is known for its commendable absorbance properties, comfort feel among other unique properties that can hardly be found in most man-made fibres. On the other hand, most filaments used like Lycra, polyester, and spandex, among others possess stretching/extensible properties and they are also responsible for the tensile properties of the resulting yarn. This reviewfocused on structural properties, end use, and the important spinning parameters of Cotton/Lycra, Cotton/spandex, Cotton/Polyester elastic core spun yarns.
Fit evaluation of virtual garment try-on by learning from digital pressure data
(Knowledge-Based Systems, 2017) Liu, Kaixuan; Zeng, Xianyi; Bruniaux, Pascal; Wang, Jianping; Kamalha, Edwin; Tao, Xuyuan
Presently, garment fit evaluation mainly focuses on real try-on, and rarely deals with virtual try-on. With the rapid development of E-commerce, there is a profound growth of garment purchases through the internet. In this context, fit evaluation of virtual garment try-on is vital in the clothing industry. In this paper, we propose a Naive Bayes-based model to evaluate garment fit. The inputs of the proposed model are digital clothing pressures of different body parts, generated from a 3D garment CAD software; while the output is the predicted result of garment fit (fit or unfit). To construct and train the proposed model, data on digital clothing pressures and garment real fit was collected for input and output learning data respectively. By learning from these data, our proposed model can predict garment fit rapidly and automatically without any real try-on; therefore, it can be applied to remote garment fit evaluation in the context of e-shopping. Finally, the effectiveness of our proposed method was validated using a set of test samples. Test results showed that digital clothing pressure is a better index than ease allowance to evaluate garment fit, and machine learning-based garment fit evaluation methods have higher prediction accuracies.
FTIR and WAXD Study of Regenerated Silk Fibroin
(Advanced Materials Research, 2013) Kamalha, Edwin; Zheng, Yuansheng; Zeng, Yongchun; Fredrick, Mutua N.
In this study, regenerated Bombyx Mori (B. Mori ) silk fibroin from two aqueous solvents was analyzed for structural deviations. Results from Fourier transform infrared spectroscopy (FTIR) and Wide angle x-ray diffraction (WAXD) implied great alteration in the secondary structure, crystallinity and molecular weight due to the regeneration process.
Fuzzy classification of young women's lower body based on anthropometric measurement
(International Journal of Industrial Ergonomics, 2016) Liu, Kaixuan; Wang, Jianping; Tao, Xuyuan; Zeng, Xianyi; Bruniaux, Pascal; Kamalha, Edwin
The traditional method of body classification is discrete, using crisp and rather dichotomous classification methods; there are many shortcomings for ergonomic design of clothing products by this method. This paper proposes a fuzzy method to classify lower body shapes based on triangular fuzzy numbers. By using factor analysis and correlation analysis, we found that the height, the waist girth, and the difference of hip-waist are crucial dimensions to represent lower body shape. We then classified the lower body shape into three categories according to the difference of hip-to-waist, and finally used the membership of triangular fuzzy numbers to represent the lower body shapes. Results show that the fuzzy method of body classification can more accurately represents body information than the traditional method without increasing the number of body types. Additionally, we established that the mean of the height, waist girth and hip girth of the young women of northeast China increased by about 0.8 cm, 1.5 cm and 1.4 cm respectively compared with ten years ago. Relevance to industry: Anthropometric data is the basis of garment pattern design, and body classification is a necessary precondition for developing a garment size system. These research achievements will add value to the pattern design of young women's lower body clothing, the development of new sizing systems and related industries.
Garment Fit Evaluation Using Machine Learning Technology
(Springer, 2018) Liu, Kaixuan; Zeng, Xianyi; Bruniaux, Pascal; Tao, Xuyuan; Kamalha, Edwin; Wang, Jianping
Presently, garment fit evaluation mainly focuses on real try-on and rarely deals with virtual try-on.With the rapid development of e-commerce, there is a profound growth of garment purchases through the Internet. In this context, fit evaluation of virtual garment try-on is vital in the clothing industry. In this chapter, we propose a Naive Bayes-based model to evaluate garment fit. The inputs of the proposed model are digital clothing pressures of different body parts, generated from a 3D garment CAD software, while the output is the predicted result of garment fit (fit or unfit). To construct and train the proposed model, data on digital clothing pressures and garment real fit was collected for input and output learning data, respectively. By learning from these data, our proposed model can predict garment fit rapidly and automatically without any real try-on; therefore, it can be applied to remote garment fit evaluation in the context of e-shopping. Finally, the effectiveness of our proposed method was validated using a set of test samples. Test results showed that digital clothing pressure is a better index than ease allowance to evaluate garment fit, and machine learning-based garment fit evaluation methods have higher prediction accuracies.
Helicobacter pylori among patients with symptoms of gastroduodenal ulcer disease in rural Uganda
(Infection Ecology & Epidemiology, 2015) Tsongo, Lawrence; Nakavuma, Jessica; Mugasa, Claire; Kamalha, Edwin
To meet key millennium development goals, the rural population needs to be reached for health assessment and service delivery. Gastroduodenal ulcer disease is a common ailment affecting the health of people in Uganda. A cross-sectional study was conducted at Bwera Hospital in Kasese district of western Uganda, to establish the prevalence and predisposing factors of Helicobacter pylori among gastroduodenal ulcer disease patients. Methods: A sample of 174 patients with symptoms of gastroduodenal ulcer disease was purposively obtained. Using two laboratory test methods, the prevalence of H. pylori among these patients was determined. A structured questionnaire was administered to participants to establish their demographic background and selected aspects of their lifestyle. Finally, the results obtained by enzyme-linked immunosorbent assay (ELISA) and immunochromatographic rapid test (IRT) were compared. Results: We established the prevalence of H. pylori as 29.9% (52/174) by ELISA and 37.4% (65/174) by IRT. Cigarette smoking, poor sanitation, and lack of formal education were the significant predisposing factors with p-values B0.05. The two tests gave identical results in 87.9% of the patients. Discussion: The prevalence of H. pylori by IRT and ELISA test methods was similar to what has been reported elsewhere in developed countries; but was lower than previously reported in developing countries including Uganda. The previous studies in Uganda were carried out in the urban population and on young children; and some used antibody-detection methods only, therefore leading to different prevalence as a result of difference in study population and methods.
A mixed human body modeling method based on 3D body scanning for clothing industry
(International Journal of Clothing Science and Technology, 2017) Liu, Kaixuan; Wang, Jianping; Zhu, Chun; Kamalha, Edwin; Hong, Yan; Zhang, Junjie; Dong, Min
The purpose of this paper is to propose a relatively simple and rapid method to create a digital human model (DHM) to serve clothing industry. Design/methodology/approach – Human body’s point cloud is divided into hands, foots, head and torso. Then forward modeling method is used to model hands and foots, photo modeling method is used to model head and reverse modeling method is used to model torso. After that, hands, foots, head and torso are integrated together to get a static avatar. Next, virtual skeleton is bound to the avatar. Finally, a lifelike digital human body model is created by the mixed modeling method (MMM). Findings – In allusion to the defect of the three-dimension original data of human body, this paper presented an MMM, with which we can get a realistic digital human body model with accurate body dimensions. The DHM can well meet the needs of fashion industry. Practical implications – The DHM, which is got by the MMM, can be well applied in the field of virtual try on, virtual fashion design, virtual fashion show and so on. Originality/value – The originality of the paper lies in the integration of forward modeling, reverse modeling and photo modeling to present a novel method of human body modeling.
Nanotechnology and Carbon Nanotubes; A Review of Potential in Drug Delivery
(Macromolecular Research, 2012) Kamalha, Edwin; Shi, Xiangyang; Mwasiagi, Josphat I.; Zeng, Yongchun
The need for affordable health care costs and the quest for better modes of treatment have increased research in novel drug delivery techniques. Efficient drug delivery systems (DDS) are judged on their ability to perform controlled and targeted drug delivery. Several nanomaterials such as carbon nanotubes (CNTs) are widely being investigated for biomedical use due to their unique properties, as well as several functional groups and incorporated targeting molecules. This review looked at nanotechnology as an emerging field in drug delivery. Several studies and findings with regards to the current functionalization of CNTs for drug delivery were explored. The conclusion reviewed the key notes.
Optimization Design of Cycling Clothes’ Patterns Based on Digital Clothing Pressures
(Fibers and Polymers, 2016) Liu, Kaixuan; Kamalha, Edwin; Wang, Jianping; Agrawal, Tarun-Kumar
Enormous research has focused on the analysis of garment wear-comfort using clothing pressure; however, optimization of clothing pressure based garment comfort has remained elusive. In this context, we propose a new method to optimize cycling clothes’ patterns based on the difference of static-to-dynamic clothing pressure (DSDCP). Firstly, we mapped 53 measuring points on an upper cycling garment on which we measured garment pressures in both static and dynamic conditions. We then analyzed DSDCP to find the rightful garment patterns to adjust according to the analyzed results. A garment optimization degree (OD) is proposed to carry out a quantitative analysis for garment comfort optimization. Finally, two upper cycling garments were made according to the original patterns and optimized patterns. A comparative analysis through cyclist wear trials of the cycling garments to test the optimization effect was done. Results show that our proposed method improves dynamic wear comfort significantly. Moreover, the optimized upper cycling garment, offers additional improvement of dynamic wear comfort.
Parametric design of garment flat based on body dimension
(International Journal of Industrial Ergonomics, 2018) Liu, Kaixuan; Zeng, Xianyi; Wang, Jianping; Tao, Xuyuan; Xu, Jun; Jiang, Xiaowen; Ren, Jun; Kamalha, Edwin; Agrawal, Tarun-Kumar; Bruniaux, Pascal
Garment flats have a wide application in product development production and designing stages. However, the traditional drawing methods of garment flat are very time-consuming, and need professional drawing skills. In this paper, a parametric design method was proposed based on body dimension to draw garment flats. The relations among human body, flats and garment show that a garment flat has a close relation with human body and real garment. Graphic analysis shows that a garment flat is constrained by two kinds of parameters: geometric and dimensional parameters. Then, the parametric relation model between garment flat and human body dimensions was constructed. According to the parametric relation model, all the dimensions of a garment flat can be represented by several dimensional parameters and style parameters. Finally, an application program (JFRS, 2016) based on the proposed method was developed to generate garment flats. The result shows that the proposed method is more effective than traditional methods. Moreover, the engineering design methods have been successfully applied to improve design efficiency in artistic design in this research. This is a novel research idea in the field of fashion design, and could be further applied in other design domains.

Browsing by Author "Kamalha, Edwin"

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