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Flexible strain sensors in textiles are attractive for sensing human body posture changes. Knitted compression garments used in various medical applications can be a suitable choice for such smart applications. However, compression stockings haven't been scientifically described for such applications. In this study, smart knitted stockings have been engineered using plain, honeycomb, and birdeye structures. Acrylic, lycra, and conductive polyamide coated with silver colloidal particles were used to architect sensors. The stockings were employed to develop a correlation between strain-indued electrical resistance variations with interface pressure between clothing and wearer's body. Moreover, thermo-physiological comfort and serviceability characterization were carried out to ensure the comfortable wearing of stockings. Decreasing the percentage of Lycra and increasing the percentage of conductive yarn increased the electrical resistance variations with changing body circumference. Increasing the circumference of the fabric increased the pressure exertion phenomenon causing an increase in electrical resistance owing to the yarns being apart from each other. The comfortability of stockings had a parabolic trend, decreasing yarn accumulation enhanced the comfort i.e., air permeability was enhanced due to tuck stitch porosities in honeycomb structures. [ABSTRACT FROM AUTHOR]

With the rapid development of industrialization and urbanization, the impact of noise on people's health has become an increasingly serious issue, but it is still a challenge for the reducing the noise due to its complex property. Textiles with many loose porous structures have gained much significant attentions, thus chenille yarns with plush fibers on the surface, and polyester monofilament were chosen to fabricate the integrated knitting yarns, and their fundamental and mechanical properties were fully evaluated. The results showed that the diameter and braiding angle of the blended yarns decreased with the increase of pitch, resulting in a linear correlation of R2 > 0.8. The breaking strength values of the 3 + 1 series were much lower than that of the 4 + 1 series, while the force utilization rates of the 3 + 1 series were much higher than that of the 4 + 1 series, with a force utilization rate of 98%. Moreover, the dynamic friction coefficient of the 3 + 1 series integrated yarns were much lower than that of the 4 + 1 series, and that of the 4 + 1 series integrated yarns exhibited the lowest bending stiffness, indicating that these two kinds of yarns were the most suitable for the potential application of sound absorption. [ABSTRACT FROM AUTHOR]

Yarn input tension (YIT) during knitting has a profound impact on fabric quality. Modern high-speed circular knitting machines are mostly equipped with positive feed system, where a predetermined length of yarn is supplied to knitting zone. Several contributing factors affect YIT and keeping YIT in precise setting is a complex phenomenon. A plethora of studies addressed yarn tensile analysis for different knitting systems. However, a comprehensive description of generated YIT for a positive storage feed based circular weft knitting machine is still missing. This study aimed to navigate YIT mathematically through a model development by analyzing yarn tensile forces for different zones of yarn path in dynamic knitting operation. The model revealed several YIT contributing variables. After evaluating the governing equation, the impact of different variables, and their interdependence have also been discussed. The predicted YIT supported the actual YIT with a mean percentage error of around 10%. [ABSTRACT FROM AUTHOR]

Perhaps it is apt that people who knit and sew are drawn to solving puzzles, including fictional and actual crimes. The word clew is an archaic spelling of our modern-day clue. It is derived from the old English cliwen or cleowen, meaning a ball of thread. It may also be a nod to the ball of yarn that Theseus used to escape from the minotaur's labyrinth in Greek legend. Without his clew, Theseus would have no clue how to escape the labyrinth. Its modern-day association with detective work first began with Edgar Allen Poe's detective C. Auguste Dupin who followed 'clues' to solve his crimes and was popularized by Arthur Conan Doyle's Sherlock Holmes stories. In the past, and more recently fictional and real-life detectives follow clues to solve crimes, and many of them are crafty. This article considers how adaptative the mediums of knitting and sewing are when they are freed from their utilitarian or creative purpose and instead becomes a device to solve crimes. [ABSTRACT FROM AUTHOR]

Copyright of Wool Textile Journal is the property of National Wool Textile Science & Technology Information Center and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Recent stitch-based simulation methods permit effective and realistic simulation for the planar structure of warp-knitted fabrics. However, simulating the warp-knitted fully formed jacquard fabric with a specific shape remains a challenge. Characteristics of diversity and complexity of this kind of fabric greatly raise the simulation difficulty. We propose a new modeling and simulation method based on the mesh model with complex shapes. We start from the analysis of the double needle bed warp-knitting technique, and establish a three-dimensional fabric mesh model, producing a finer stitch placement on a double needle bed knitted structure. Due to the deformation date derived from the jacquard pattern, stitches are placed at the actual locations. The used stitches forming the fully formed products are rendered according to the jacquard pattern. Using the two-dimensional plates and corresponding three-dimensional objects as input models to define the shape of the warp-knitted products, stitches are transferred from two to three-dimensional model objects by spatial mapping. The interface of our modeling system allows for designing complex jacquard patterns and selecting specific models for warp-knitted products. The method we propose leads to a visible design process with results visualization, which is convenient for designers to modify the knitting parameters covering knitting information and jacquard pattern before the product is knitted. The simulation method can be applied to the rapid design of the warp-knitted boa, which can reduce duplicate sampling, shorten the design process, and save raw material costs. Further research will be carried out in the future to improve this simulation method. [ABSTRACT FROM AUTHOR]

Camouflage in textiles is a pattern orchestrated using different materials and designs, primarily used for armed forces clothing for not to be detected by enemies in variable environments. Wearer comfort is the central perspective while developing textiles; however, no significant literature exists on the comfort assessment of knitted camouflage fabrics. Hence this research experimentally investigates the effect of the fabric structure and the material type on the comfort and mechanical performance properties of the engineered knitted camouflage fabrics. Fabrication of camouflage patterns, i.e. snow, desert, forest camouflage, and plain rib (control sample), was done using different combinations of Polyester, Cotton, and Tencel through jacquard knitting. Characterization of comfort and mechanical properties were performed to predict the influence of input parameters, for finding the best knitting structures and materials and exploring the scientific reason behind behaviours of jacquard knitted camouflage fabrics. Comfort and performance attributes were influenced by changing material and knitting parameters i.e. mean air permeability was 5% higher, and thermal resistance was 21% lower for forest camouflage as compared to desert and snow camouflage due to yarn movements in jacquard patterns. Similarly, the mechanical properties also showed to be affected by changing experimental parameters. [ABSTRACT FROM AUTHOR]

Three-dimensional knitted uppers for footwear enhance ergonomic properties and fit compared to conventional flat panels. The knitting process for these elements represents a bottleneck in footwear production because flat-knitting machines must knit the uppers individually, which limits production capacity. This study explores ways to optimize knitting processes for 3D uppers. The focus is on reducing production time while maintaining product quality, ensuring a precise fit, and minimizing material waste. A series of experiments conducted on a base sneaker model implemented techniques to streamline knitting operations. These techniques were later adapted to other footwear types, including ankle boots, loafers, and sandals, to meet the unique requirements of each design. These optimizations include replacing traditional operations, such as overlocking or stitch decreases, with more efficient methods, such as open loops, as well as eliminating costly-to-manufacture elements. The results show significant reductions in production time while maintaining the fit and functional integrity of the uppers. These findings demonstrate both the technical feasibility and economic impact of these optimizations, offering valuable insights for the large-scale adoption of knitting technology in the footwear industry. [ABSTRACT FROM AUTHOR]

This paper presents volumetric homogenization, a spatially varying homogenization scheme for knitwear simulation. We are motivated by the observation that macro-scale fabric dynamics is strongly correlated with its underlying knitting patterns. Therefore, homogenization towards a single material is less effective when the knitting is complex and non-repetitive. Our method tackles this challenge by homogenizing the yarn-level material locally at volumetric elements. Assigning a virtual volume of a knitting structure enables us to model bending and twisting effects via a simple volume-preserving penalty and thus effectively alleviates the material nonlinearity. We employ an adjoint Gauss-Newton formulation[Zehnder et al. 2021] to battle the dimensionality challenge of such per-element material optimization. This intuitive material model makes the forward simulation GPU-friendly. To this end, our pipeline also equips a novel domain-decomposed subspace solver crafted for GPU projective dynamics, which makes our simulator hundreds of times faster than the yarn-level simulator. Experiments validate the capability and effectiveness of volumetric homogenization. Our method produces realistic animations of knitwear matching the quality of full-scale yarn-level simulations. It is also orders of magnitude faster than existing homogenization techniques in both the training and simulation stages. [ABSTRACT FROM AUTHOR]

Additive manufacturing, and particularly the cold spray technology for additive manufacturing (CSAM), is fast becoming a key technology to produce components in an efficient and environmentally friendly manner. This method usually requires a final rectification to generate specific surface topographies. The novelty of this paper is related to the capabilities of the CSAM technique to control the surface topography of the samples. Thus, this work investigates the topography of CSAM samples and its correlation with the processing parameters. Pure Al and Ti samples were manufactured following two different deposition strategies: traditional and metal knitting. This last strategy constitutes a promising alternative for CSAM to obtain near-net-final shape components. The topography was analyzed by confocal microscopy considering the form, waviness, and roughness components. Moreover, the microstructure and mechanical properties of the samples were also investigated in order to assure reliable freestanding CSAM deposits. Results showed that the waviness was controlled by the spraying line spacing, and that the waviness and roughness profiles of the metal knitting samples presented the largest wavelengths regardless the material. The metal knitting method generated samples with higher thickness and porosity than the traditional strategy, while the mechanical properties at the local scale were not varied. The study highlights the CSAM technology potential for controlling the deposit's surface topography. [Display omitted] • Al and Ti CSAM samples were obtained by traditional and metal knitting strategies. • Surface topography correlation with CSAM processing factors. • The waviness texture component is controlled by the spraying line spacing. • The metal knitting strategy creates the largest waviness and roughness wavelengths. • Metal knitting creates thicker samples, with higher porosity, and similar E and H 0. [ABSTRACT FROM AUTHOR]

Abstract Textile electrode is capable of measuring the myoelectric potentials of skeletal muscles such as electromyography (EMG), owing to their outstanding low weight, flexibility, breathability, and comfort properties. Nonetheless, textile surfaces often exhibit intermittent adhesion between the electrode surface and the skin, which can result in fluctuations in electrical resistivity due to the inherent characteristics of textiles. This study aimed to suggest the solutions to improve adhesive of textile electrode for the improvement of electrode performance with high quality signal by minimizing these intermittent contacts. For this, an adhesive intermediate, two different conductive materials, between the skin and the textile electrode was introduced to improve the instability skin contact, respectively. To assess the impact of various adhesive intermediates on knitted electrodes, two different types of adhesive intermediates were utilized: a conductive hydrogel-based adhesive intermediate and a conductive paste-based adhesive intermediate. Moreover, the durability of knitted electrodes with adhesive intermediate was evaluated by assessing the changes of signal quality during drying time for 180 min. As a results of sEMG measurement, it was confirmed that the sEMG signal was stably detecting by applying the adhesive intermediate. Both types of adhesive intermediate significantly increased the signal acquisition performance of knitted electrodes by more than threefold. After five washing cycle, the knitted electrodes with two types of adhesive intermediate maintained approximately 80% of their initial SNR values. Therefore, the use of the adhesive intermediate presented in this study not only improves the performance of the electrode but also ensures reusability.

Textile electrode is capable of measuring the myoelectric potentials of skeletal muscles such as electromyography (EMG), owing to their outstanding low weight, flexibility, breathability, and comfort properties. Nonetheless, textile surfaces often exhibit intermittent adhesion between the electrode surface and the skin, which can result in fluctuations in electrical resistivity due to the inherent characteristics of textiles. This study aimed to suggest the solutions to improve adhesive of textile electrode for the improvement of electrode performance with high quality signal by minimizing these intermittent contacts. For this, an adhesive intermediate, two different conductive materials, between the skin and the textile electrode was introduced to improve the instability skin contact, respectively. To assess the impact of various adhesive intermediates on knitted electrodes, two different types of adhesive intermediates were utilized: a conductive hydrogel-based adhesive intermediate and a conductive paste-based adhesive intermediate. Moreover, the durability of knitted electrodes with adhesive intermediate was evaluated by assessing the changes of signal quality during drying time for 180 min. As a results of sEMG measurement, it was confirmed that the sEMG signal was stably detecting by applying the adhesive intermediate. Both types of adhesive intermediate significantly increased the signal acquisition performance of knitted electrodes by more than threefold. After five washing cycle, the knitted electrodes with two types of adhesive intermediate maintained approximately 80% of their initial SNR values. Therefore, the use of the adhesive intermediate presented in this study not only improves the performance of the electrode but also ensures reusability. [ABSTRACT FROM AUTHOR]

The work aims to construct a complete electronic slogging system in order to enrich the characteristics of pattern and get large slogging movement distance. Herein, first, the knitting principle of double tricot machine is studied, and the conclusion is drawn that the looping process is composed of the swing of guide bar and the slogging of guide bar. Second, taking the RD4N tricot machine as the research object, the minimum overlap angle of 25° and the minimum underlap angle of 80° are obtained, which occur on the GB1 and GB4 bar, respectively. Third, discussions are carried out over the scheme and principles of the slogging system, the controller, servo motor, etc., are analyzed and designed, an electronic slogging execution program is drafted, and the electronic cam curve adopts the non-dwell corrected trapezoidal acceleration motion curve, which completely meets the requirements of production. The actual test proves the smooth operation, precise slogging, and fast response of the control systems. [ABSTRACT FROM AUTHOR]

While reaction-diffusion processes are utilized in multiple scientific fields, these phenomena have seen limited practical application in the polymer industry. Although self-regulating processes driven by parallel reaction and diffusion can lead to patterned structures, most polymeric products with repeating subunits are still prepared by methods that require complex and expensive instrumentation. A notable, high-added-value example is surgical mesh, which is often manufactured by weaving or knitting. In our present work, we demonstrate how the polymer and the biomedical industry can benefit from the pattern-forming capabilities of reaction-diffusion. We would like to propose a self-regulating method that facilitates the creation of surgical meshes from biocompatible polymers. Since the control of the process assumes a thorough understanding of the underlying phenomena, the theoretical background, as well as a mathematical model that can accurately describe the empirical data, is also introduced and explained. Our method offers the benefits of conventional techniques while introducing additional advantages not attainable with them. Most importantly, the method proposed in this paper enables the rapid creation of meshes with an average pore size that can be adjusted easily and tailored to fit the intended area of application. [ABSTRACT FROM AUTHOR]

As an unarmed country, Iceland could not provide military assistance to Ukraine after Russia"s invasion. Public and private support for Ukraine was nonetheless abundant. This intervention explores the contributions made by the Icelandic public to the Ukrainian war effort. This support appeared in the form of knitting, displaying a very gendered logic of care. This started as a individualized effort but was quickly institutionalised and supported by the authorities, which also provided humanitarian, economic, and military support to Ukraine. While the intent of individuals appears to have been to provide personal assistance to those suffering the consequences of war, the act contributes to the militarisation of Icelandic society and the normalisation of war. [ABSTRACT FROM AUTHOR]

In view of the fa^ that hollow out has certain practical application in three-dimensional clothing cutting, but lacks systematic classification and theoretical summary, this paper starting from the application of hollowed-out in three-dimensional clothing cutting technology, according to techniques, hollowed-out can be divided into 10 categories; part modeling, cutting, breaking, punching, knitting, embroidery, patchwork, drawing, tearing burning. The application technologies of hollowing in three-dimensional cutting was summarized, including changing the texture and structure of materials, integration of fragmented materials, reduction treatment, darts transfer, shape segmentation, overlapping splicing, contour hollowing technology law, and its practical application in practical wear, dress, creative clothing, underwear was analyzed. Finally, the operation methods and skills of the hollowing in the three- dimensional cutting of clothing were applied to design an overlapping splicing hollowing suit. This paper can provide more creative reference for the application of hollowing method in garment three-dimensional cutting. [ABSTRACT FROM AUTHOR]

Speculative negative Poisson's ratio (NPR) materials exhibit an auxetic response to strain in a predetermined direction due to their unusual morphologies, making them highly suitable for various specialized applications. For the rationale, these materials have immense potential in various specialized contexts. In weft-knitted auxetic fabrics, uneven tension in the purl loops leads to the distinctive curling architecture. Due to their inherent curly structure and adaptability, weft-knitted fabrics are an excellent choice for emulating NPR materials. In this study, 3D weft-knitted auxetic fabrics were created using flatbed purl knitting technology. Two distinctive patterns, comprising knit and tuck stitches, were employed. The number of stitches per repeat (SPR) was varied to assess the impact of grid size on NPR behavior. Additionally, the variation in measurement points within standard-sized characterization specimens was analyzed, revealing slight differences in auxeticity. Increasing the SPR size initially enhanced NPR behavior, up to a certain limit, beyond which the trend declined. A significant shift in NPR was observed due to material variation and inter-yarn friction, with a 27% and 28% shift of Poisson's ratio was experienced above and below the mean, respectively. Poisson's ratio was also positively correlated with energy absorption, suggesting that the designed materials could be effective for protective and energy-absorbing applications. [ABSTRACT FROM AUTHOR]

Compared with the traditional mechanical knitting needle, the tubular magnetic suspension knitting needle has the advantages of no friction and flexible control. But the highspeed reciprocating motion of the needle needs to consume a lot of power. The winding temperature is difficult to suppress. The heat dissipation performance becomes the main obstacle restricting the power improvement. In this paper, an integral tubular electric knitting needle is proposed and studied. The heat dissipation area of the needle is increased by the annular thermosyphon in the motor housing. The heat dissipation performance is carefully studied by experiments, and the results show that the heat dissipation performance is obviously improved compared with the original design. Under the power of 17 W, after the annulus thermosyphon is started, the maximum temperature of the winding can be suppressed at about 107 °C. Boiling occurs only at certain points on the surface of the winding, which is related to the structural asymmetry in the winding manufacturing and epoxy injection processes. The heat dissipation performance is best when the winding is located at the bottom of the motor. The axial temperature difference is within 15 °C while the circumferential temperature difference is within 4 °C. [ABSTRACT FROM AUTHOR]

In order to meet the current expanding market demand for knitwear, high-speed automatic knitting machines with "one-line knit to shape" capability are widely used. However, the frequent emergence of floating-yarn stacking anomalies during the high-speed knitting process will seriously hinder the normal reciprocating motion of the needles and cause a catastrophic fracture of the whole machine needle plate, greatly affecting the efficiency of the knitting machines. To overcome the limitations of the existing physical-probe detection method, in this work, we propose a visual floating-yarn anomaly recognition framework based on a CNN-BiLSTM network with the knit feature sequence (CNN-BiLSTM-KFS), which is a unique sequence of knitting yarn positions depending on the knitting status. The sequence of knitting characteristics contains the head speed, the number of rows, and the head movements of the automatic knitting machine, enabling the model to achieve more accurate and efficient floating-yarn identification in complex knitting structures by utilizing contextual information from knitting programs. Compared to the traditional probe inspection method, the framework is highly versatile as it does not need to be adjusted to the specifics of the automatic knitting machine during the production process. The recognition model is trained at the design and sampling stages, and the resulting model can be applied to different automatic knitting machines to recognize floating yarns occurring in various knitting structures. The experimental results show that the improved network spends 75% less time than the probe-based detection, has a higher overall average detection accuracy of 93% compared to the original network, and responds faster to floating yarn anomalies. The as-proposed CNN-BiLSTM-KFS floating-yarn visual detection method not only enhances the reliability of floating-yarn anomaly detection, but also reduces the time and cost required for production adjustments. The results of this study will bring significant improvements in the field of automatic floating-yarn detection and have the potential to promote the application of smart technologies in the knitting industry. [ABSTRACT FROM AUTHOR]

Copyright of Cotton Textile Technology is the property of Cotton Textile Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Compression therapy can be successfully applied to the treatment of amputated limbs. Compression is known to speed healing and reduce the appearance of complex scars. This is particularly relevant as the number of amputations increases, especially during times of war, such as the current war in Ukraine. For the research presented in this article, compression knits of two pattern repeats and twelve structural variations each were created. We investigated how the compression generated by the knit is influenced by the main factors which theoretically could have an effect: knitting pattern, density of loops, speed of the wheel supplying elastomeric inlay-yarn into the knitting zone, and elongation resulting from the difference between the knitted limb cover and limb circumference. It was found that in the area of low elongations (up to 50%) of the investigated elastomeric knits, the speed of supply of the inlay-yarn does not have a significant influence on the compression. However, the effect of loop density and knitting elongation on the generated compression is significant and manifests linearly. In addition, the established equations can be used for compression prediction and knitting design according to the required compression class. [ABSTRACT FROM AUTHOR]

The JW Anderson patchwork cardigan from the spring/summer 2020 menswear collection has become an iconic fashion item during the COVID-19 pandemic. Worn by Harry Styles, the cardigan inspired a worldwide TikTok trend of crafting and DIY-ing a replica at home with over 90 million views to date. In response, JW Anderson published the pattern online and the V&A museum acquired the knitwear for its permanent collection. One year later, Olympic gold medallist Tom Daley was pictured knitting in the stands at the 2020 Olympic games – a craft he had picked up during the lockdowns. Both instances are challenging the notion of knitting and needlework as a feminine craft. In the past, men who embroidered, knitted or sewed their clothes were designated as infantile, effeminate and deviant from the hetero masculine norm. In today's post-pandemic climate, these associations are being challenged. Taking the cardigan and the resurgence of needlework as a case study, this article investigates the ways the COVID-19 pandemic influenced contemporary fashion consumption and re-stitched the meaning of male knitting. Focusing on the transformative aspects of slow fashion and gender fluidity in contemporary society, this article draws on a theoretical framework deriving from queer theory and sustainable fashion. Coined by Kate Fletcher, slow fashion encompasses a recalibration towards a focus on high-quality items over quantity and a slower production that does not exploit natural and human resources. Judith Butler's notion of gender performativity exposes gender as a social construct produced and maintained by a stylized repetition of acts, such as commonplace speech or nonverbal communication. Analysing the resurgence of male needlework through this critical lens, this article argues that it is the result of seismographic shifts within the contemporary fashion and popular culture that have been accelerated by the COVID-19 pandemic. Disrupting the fashion industry profoundly on a global scale, this article discusses how the pandemic can be seen as a catalyst for fashion in renegotiating masculinities. [ABSTRACT FROM AUTHOR]

Electronic textiles (e‐textiles) combine electronic functions (e.g., sensing, actuating, data processing) with textiles. E‐textiles are a platform technology with the potential for ubiquitous deployment in any application scenario where textiles can be found. E‐textiles have attracted significant research interests from materials and manufacturing process development to applications such as sports/fitness, healthcare, and workwear. While significant advances have been made in the research domain regarding the integration of electronic functionality, the technology is relatively immature and significant challenges remain in the manufacturing of commercialized e‐textile systems. This paper reviews the state of the art in e‐textile manufacturing including materials (e.g., yarns, inks), fabrication (e.g., weaving, knitting, printing), electronic integration and interconnections. This paper also reviews the key principles of textile sustainability and electronic waste (e‐wastemanagement, which provide useful guidance on e‐textile design and manufacturing to minimize their impact on the environment. Examples are given to demonstrate the early work toward sustainable e‐textiles. The remaining research challenges regarding scalable and sustainable manufacturing of e‐textiles are presented. [ABSTRACT FROM AUTHOR]

The feasibility of designing plated knit fabric made by simultaneous knitting of synthetic fibers and natural fiber yarn was studied. In designing this knit fabric, it is important to take account of the bending stiffness of the fibers. Data on the stiffness of various chemical and natural fibers are presented. The procedure was tested experimentally on fabrics from yarn containing polyacrylonitrile, polyester, wool, flax, and cotton fibers. [ABSTRACT FROM AUTHOR]

Copyright of Industria Textila is the property of Institutul National de Cercetare-Dezvoltare pentru Textile si Pielarie and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Fashion image captioning is a critical task in the fashion industry that aims to automatically generate product descriptions for fashion items. However, existing fashion image captioning models predict a fixed caption for a particular fashion item once deployed, which does not cater to unique preferences. We explore a controllable way of fashion image captioning that allows the users to specify a few semantic attributes to guide the caption generation. Our approach utilizes semantic attributes as a control signal, giving users the ability to specify particular fashion attributes (e.g., stitch, knit, sleeve) and styles (e.g., cool, classic, fresh) that they want the model to incorporate when generating captions. By providing this level of customization, our approach creates more personalized and targeted captions that suit individual preferences. To evaluate the effectiveness of our proposed approach, we clean, filter, and assemble a new fashion image caption dataset called FACAD170K from the current FACAD dataset. This dataset facilitates learning and enables us to investigate the effectiveness of our approach. Our results demonstrate that our proposed approach outperforms existing fashion image captioning models as well as conventional captioning methods. Besides, we further validate the effectiveness of the proposed method on the MSCOCO and Flickr30K captioning datasets and achieve competitive performance. [ABSTRACT FROM AUTHOR]

Automotive seating fabrics, that come into direct contact with the human body, which have increased requirements for their tactile comfort properties, but it is still a great challenge to clear the relationship between structures and its performances. Hence, 44 knitting fabrics with the different structural parameters were prepared first, and then the properties such as tactile, bending and compressive performance were tested, and the intrinsic correlation between their performance indexes and the structural properties was analyzed. The results showed that the toughness of the fabrics varied greatly, and the main score was concentrated on 75 to 90. As for the bending stiffness, the warp bending hysteresis of fabrics was concentrated in the range of 0–0.15 gf·cm cm−1, while that of the weft bending hysteresis was mainly concentrated in the range of 0–0.1 gf·cm cm−1. Moreover, the compression behaviors of fabrics were 0.7 to 1.5 gf·cm cm−2, 47.5 to 55% and 0.25 to 0.65, respectively. Tactile analysis of fabrics was carried out by establishing a comprehensive evaluation model, the average composite ratings of weft-plane fabrics, mesh fabrics, jacquard fabrics, and pile fabrics are 0.14, 0.176, 0.175, and 0.15, respectively. The mesh and jacquard fabrics were observed to have the better tactile comfort properties. In conclusion, the toughness, softness, and bending stiffness of the fabrics had a great influence on the tactile comfort, providing a reference for the development of automotive seat fabrics with good comfort performances. [ABSTRACT FROM AUTHOR]

Wearable products have significant applications in medical assistance, posture correction, and humancomputer interaction. In this study, we present a knitting method for a one-piece knitted embedded hang-needle sensor. This method involves simultaneously knitting conductive yarn into the sensing zone while creating the monitoring garment in a seamless manner. By implementing a tight hanging needle structure in the sensing zone design and adjusting knitting parameters, the effect of pre-stretching on the sensor caused by the base garment is minimized. Furthermore, integrating the sensing area of the hang-needle structure with the monitoring garment eliminates the need for additional sensor integration steps and simplifies the preparation process, resulting in reduced time and material costs. Moreover, the monitoring garment offers a comfortable wearing experience without any foreign body sensation and accurately captures the initial shoulder posture of the wearer. [ABSTRACT FROM AUTHOR]

Knitting interloops one-dimensional yarns into three-dimensional fabrics that exhibit behaviour beyond their constitutive materials. How extensibility and anisotropy emerge from the hierarchical organization of yarns into knitted fabrics has long been unresolved. We seek to unravel the mechanical roles of tensile mechanics, assembly and dynamics arising from the yarn level on fabric nonlinearity by developing a yarn-based dynamical model. This physically validated model captures the mechanical response of knitted fabrics, analogous to flexible metamaterials and biological fibre networks due to geometric nonlinearity within such hierarchical systems. Fabric anisotropy originates from observed yarn–yarn rearrangements during alignment dynamics and is topology-dependent. This yarn-based model also provides a design space of knitted fabrics to embed functionalities by varying geometric configuration and material property in instructed procedures compatible to machine manufacturing. Our hierarchical approach to build up a knitted fabric computationally modernizes an ancient craft and represents a first step towards mechanical programmability of knitted fabrics in wide engineering applications. [ABSTRACT FROM AUTHOR]

In numerous cultures, men are predominantly responsible for the profession and industry of weaving and knitting, while women are primarily responsible for domestic sewing and weaving, provided that they are conducted within the confines of the home. However, cultural critics contend that these works did not merely demonstrate feminine taste or love for the home; rather, they delineated the expectations placed on females to remain silent, obedient, and compliant. The objective of this article is to examine the works of contemporary Iranian women artists. Feminine language is intended to convey the experiences of women and to facilitate the comprehension and reception of women, as identified by Luce Irigaray. This article addresses the issue of how female visual artists have transformed knitting and sewing into a means of exploring the language of female identity. In order to address this inquiry, five art exhibitions were examined and analyzed, including “Tajali Ehsas (Manifestation of feeling),” “sew+zan,” “Women Create,” “Nakhsh (Design),” and “Pressbook,” using the methodologies of “Trend analysis” and “Event Study.”The findings demonstrate the evolution of the experiences of contemporary Iranian women artists from the 1990s to the 2020s. Sewing and knitting have been depicted as symbols of desirable femininity in the works of certain Iranian female painters, particularly during the “Tajali Ehsas (Manifestation of feeling)” event in the 1990s. However, in the wake of socio-cultural shifts, female artists have employed sewing and knitting as a critical and linguistic action to reevaluate the identity of women in artistic events such as the exhibition “sew+zan,” “Women Create,” and “Pressbook.” [ABSTRACT FROM AUTHOR]

Intelligent scheduling of knitting workshops is the key to realizing knitting intelligent manufacturing. In view of the uncertainty of the workshop environment, it is difficult for existing scheduling algorithms to flexibly adjust scheduling strategies. This paper proposes a scheduling algorithm architecture based on deep reinforcement learning (DRL). First, the scheduling problem of knitting intelligent workshops is represented by a disjunctive graph, and a mathematical model is established. Then, a multi-proximal strategy (multi-PPO) optimization training algorithm is designed to obtain the optimal strategy, and the job selection strategy and machine selection strategy are trained at the same time. Finally, a knitting intelligent workshop scheduling experimental platform is built, and the algorithm proposed in this paper is compared with common heuristic rules and metaheuristic algorithms for experimental testing. The results show that the algorithm proposed in this paper is superior to heuristic rules in solving the knitting workshop scheduling problem, and can achieve the accuracy of the metaheuristic algorithm. In addition, the response speed of the algorithm in this paper is excellent, which meets the production scheduling needs of knitting intelligent workshops and has a good guiding significance for promoting knitting intelligent manufacturing. [ABSTRACT FROM AUTHOR]

Textiles-oriented flexible strain sensors have been attractive in designing intelligent clothing materials to sense the human body postural changes. However, their efficacy towards sensing performance can be tailored through fabrication architectures variation. In this study knitted strain sensors have been engineered using novel double face fabric designs. Filament polyester, and conductive polyamide coated with silver colloidal particles were used to architect sensors. The sensors provide real-time electrical resistance variation as a sensing feature w.r.t mechanical changes happening in them. Two-dimensional strain testing and comfortability evaluations were carried out to ensure sensing performance and comfortable wearing longevity of sensors. Decreasing linking yarn accumulation per unit area increased the strain sensitivity i.e. changing knit stitches with tuck and miss the sensing capability increased 28% and 95%, respectively. Comfortability of sensors had a parabolic trend, decreasing yarn accumulation enhanced comfort up to tuck-linking courses. While increasing the percentage of conductive polyamide in the linking course improved strain sensitivity by 50%. The research presents such double-face intelligent strain sensors as a suitable solution to the long-term wearability of sensors with comfort. [ABSTRACT FROM AUTHOR]

Aiming at the trend of denim yarn and the deficiencies of the current dyeing, characteristics of denim colored yarn were simulated and a multi-colored yarn by vortex spinning was developed. Traditional ring spinning and air-jet vortex core-spun technology were combined. Short staple fibers were taken as core yarn instead of filament to achieve the color of core yarn, the thickness and twist direction could be adjusted. The twisting stress of the fibers was counteracted by combining the core yarn with the opposite twist direction of the outer layer fibers and selecting the corresponding twist coefficients during the spinning process. The use of uneven wrapping effect of the air-jet vortex spinning could highlight the unique exposed core effect, inner and outer layers could be used in different colors and ratios. The multi-colored yarn by vortex spinning coud be used for knitting and weaving, the rich color variation of multi-colored yarn by vortex spinning was suitable for the production of dye-free denim production. [ABSTRACT FROM AUTHOR]

To predict the number of foreign fibers on the fabric, USTER CLASSIMAT 5 yarn imperfection indicator with foreign fiber detection function was adopted, according to the appearance of foreign fibers (length, reflectivity), foreign fibers were classified. The correlation between the foreign fiber data detected by yarn imperfection indicator and the number of foreign fibers which observed manually on the corresponding knitted fabric was discussed. The test showed there's a strong correlation between the foreign fibers number of yarns detected by yarn imperfection indicator and observed manually on corresponding knitted fabrics. It is considered that the number of yarn foreign fiber can be used as the acceptance standard of yarn foreign fiber when knitting factory purchases yarn, combined with the foreign fiber requirements of cloth is conducive to rational use of yarn. [ABSTRACT FROM AUTHOR]

This study explored the creation of 3D printing knit-based structures. Furthermore, the study investigated the relationship between the mechanical performance of these structures and the changes in loop stitch design and 3D printing material. Effects on the mechanical properties of the 3D printing loop structure were evaluated with respect to loop stitch, loop head, loop leg and loop foot. This study analysed the mean differences between the values of independent variables, namely, loop stitch and print material and the values of two dependent variables (i.e. tensile strength and elongation at break) using a multivariate analysis of variance. The results revealed that the mechanical properties of the loop structure vary significantly depending on the loop stitch shape and printing material. Tensile strength is mainly affected by material, whereas elongation property is significantly affected by loop stitch shape. [ABSTRACT FROM AUTHOR]

Biobased nylon (PA56) not only has the same physical properties as nylon (PA6/PA66) but its production method is also more environmentally friendly. PA56 fabric has the advantages of moisture absorption, perspiration, high-temperature resistance, and flexibility, which have been widely studied by scientific researchers. Wool has the advantages of beauty, environmental protection, and anti-wrinkle. However, pure wool fabrics have low strength and are easy to shrink when washed, which has always been a problem. Hence, this work adopted the ring spinning method to prepare wool/PA56 blended yarn with wool content of 0, 10, 30, 50, 70, and 100 wt%. Thus, to examine the effects of different blending ratios and twists on yarn performance, PA56 was blended with wool. The results showed that findings indicate that yarn performance is influenced by both yarn twist and blending ratio. The yarn thickens and takes on more linear density as the blending ratio and yarn twist increase. As the wool ratio increases, the yarn's breaking stress and breaking strain decrease. It is obvious that the strength and elongation at break of pure PA56 yarn are 2.09 cN/Dtex and 33.92%, respectively. When the wool content was 100 wt%, the strength and elongation at break of the blended yarn were 0.66 cN/Dtex and 21.15%, respectively. With the amount of wool blending, the yarn hairiness index's H-value initially rises and subsequently falls. The percentage of blended wool reaches 50% at 2.14; less blending might exacerbate the yarn's stem, resulting in neps and unevenness features. The quality of the yarn improves as the blending percentage rises. The yarn has the advantages of resource saving, biodegradability, and environmental friendliness and has a broad application prospect in the automotive interior field. [ABSTRACT FROM AUTHOR]