Search results for: driving techniques

Authors: Usama Shahid, Muhammad Zunnurain Hussain

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This research paper presents a comprehensive analysis of a sentiment analysis approach that employs valence and arousal as its foundational pillars, in comparison to traditional techniques. Sentiment analysis is an indispensable task in natural language processing that involves the extraction of opinions and emotions from textual data. The valence and arousal dimensions, representing the intensity and positivity/negativity of emotions, respectively, enable the creation of four quadrants, each representing a specific emotional state. The study seeks to determine the impact of utilizing these quadrants to identify distinct emotional states on the accuracy and efficiency of sentiment analysis, in comparison to traditional techniques. The results reveal that the valence and arousal-based approach outperforms other approaches, particularly in identifying nuanced emotions that may be missed by conventional methods. The study's findings are crucial for applications such as social media monitoring and market research, where the accurate classification of emotions and opinions is paramount. Overall, this research highlights the potential of using valence and arousal as a framework for sentiment analysis and offers invaluable insights into the benefits of incorporating specific types of emotions into the analysis. These findings have significant implications for researchers and practitioners in the field of natural language processing, as they provide a basis for the development of more accurate and effective sentiment analysis tools.

Keywords: sentiment analysis, valence and arousal, emotional states, natural language processing, machine learning, text analysis, sentiment classification, opinion mining

Procedia PDF Downloads 102

Authors: Titus Amodu Umoru

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The global economy today is full of sophistication. All over the world, business and marketing practices are undergoing an unprecedented transformation. In realization of this fact, the federal government of Nigeria has put in place a robust transformation agenda in order to put Nigeria in a better position to be a competitive player and in the process transform all sectors of its economy. New technologies, especially the internet, are the driving force behind this transformation. However, technology has inadvertently affected the way businesses are done thus necessitating the acquisition of new skills. In developing countries like Nigeria, citizens are still battling with effective application of those technologies. Obviously, students of business education need to acquire relevant business knowledge to be able to transit into the world of work on graduation from school and compete favourably in the labour market. Therefore, effective utilization of social media by both teachers and students can help extensively in empowering students with the needed skills. Social media which is described as a group of internet-based applications that build on the ideological foundations of Web 2.0, and which allow the creation and exchange of user-generated content, if incorporated into the classroom experience may be the needed answer to unemployment and poverty in Nigeria as beneficiaries can easily connect with existing and potential enterprises and customers, engage with them and reinforce mutual business benefits. Challenges and benefits of social media use in education in Nigeria universities were revealed in this study.

Keywords: business education, challenges, opportunities, utilization, social media

Procedia PDF Downloads 416

Authors: Abdal-Hafeez Alhussein

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Artificial Intelligence (AI) has become a transformative force in the field of information technologies, reshaping how data is processed, analyzed, and utilized across various domains. This paper explores the multifaceted applications of AI within information technology, focusing on three key areas: automation, scalability, and data-driven decision-making. We delve into how AI-powered automation is optimizing operational efficiency in IT infrastructures, from automated network management to self-healing systems that reduce downtime and enhance performance. Scalability, another critical aspect, is addressed through AI’s role in cloud computing and distributed systems, enabling the seamless handling of increasing data loads and user demands. Additionally, the paper highlights the use of AI in cybersecurity, where real-time threat detection and adaptive response mechanisms significantly improve resilience against sophisticated cyberattacks. In the realm of data analytics, AI models—especially machine learning and natural language processing—are driving innovation by enabling more precise predictions, automated insights extraction, and enhanced user experiences. The paper concludes with a discussion on the ethical implications of AI in information technologies, underscoring the importance of transparency, fairness, and responsible AI use. It also offers insights into future trends, emphasizing the potential of AI to further revolutionize the IT landscape by integrating with emerging technologies like quantum computing and IoT.

Keywords: artificial intelligence, information technology, automation, scalability

Procedia PDF Downloads 19

Authors: Ugochukwu Ejike Akpudo, Jank-Wook Hur

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The increasing demand for improved productivity, maintainability, and reliability has prompted rapidly increasing research studies on the emerging condition-based maintenance concept- Prognostics and health management (PHM). Varieties of fuel pumps serve critical functions in several hydraulic systems; hence, their failure can have daunting effects on productivity, safety, etc. The need for condition monitoring and assessment of these pumps cannot be overemphasized, and this has led to the uproar in research studies on standard feature extraction techniques for optimized condition assessment of fuel pumps. By extracting time-based, frequency-based and the more robust time-frequency based features from these vibrational signals, a more comprehensive feature assessment (and selection) can be achieved for a more accurate and reliable condition assessment of these pumps. With the aid of emerging deep classification and regression algorithms like the locally linear embedding (LLE), we propose a method for comprehensive condition assessment of electromagnetic fuel pumps (EMFPs). Results show that the LLE as a comprehensive feature extraction technique yields better feature fusion/dimensionality reduction results for condition assessment of EMFPs against the use of single features. Also, unlike other feature fusion techniques, its capabilities as a fault classification technique were explored, and the results show an acceptable accuracy level using standard performance metrics for evaluation.

Keywords: electromagnetic fuel pumps, comprehensive feature extraction, condition assessment, locally linear embedding, feature fusion

Procedia PDF Downloads 117

Authors: C. S. Seema, P. R. Prince

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The characterization of spatio-temporal inhomogeneities occurring in the ionospheric F₂ layer is remarkable since these variations are direct consequences of electrodynamical coupling between magnetosphere and solar events. The temporal and spatial variations of the F₂ layer, which occur with a period of several days or even years, mainly owe to geomagnetic and meteorological activities. The hourly F₂ layer critical frequency (foF2) over 23rd solar cycle (1996-2008) of three ionosonde stations (Wakkanai, Kokunbunji, and Okinawa) in northern hemisphere, which falls within same longitudinal span, is analyzed using continuous wavelet techniques. Morlet wavelet is used to transform continuous time series data of foF2 to a two dimensional time-frequency space, quantifying the time evolution of the oscillatory modes. The presence of significant time patterns (periodicities) at a particular time period and the time location of each periodicity are detected from the two-dimensional representation of the wavelet power, in the plane of scale and period of the time series. The mean strength of each periodicity over the entire period of analysis is studied using global wavelet spectrum. The quasi biennial, annual, semiannual, 27 day, diurnal and 12 hour variations of foF2 are clearly evident in the wavelet power spectra in all the three stations. Critical frequency oscillations with multi-day periods (2-3 days and 9 days in the low latitude station, 6-7 days in all stations and 15 days in mid-high latitude station) are also superimposed over large time scaled variations.

Keywords: continuous wavelet analysis, critical frequency, ionosphere, solar cycle

Procedia PDF Downloads 223

Authors: Kevin William Taylor

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This work used industry-standard practices and technologies as a foundation to explore current and future advancements in modularity for 3D environmental production. Covering environmental generation, and AI-assisted generation, this study investigated how these areas will shape the industries goal to achieve full immersion within augmented reality environments. This study will explore modular environmental construction techniques utilized in large scale 3D productions. This will include the reasoning behind this approach to production, the principles in the successful development, potential pitfalls, and different methodologies for successful implementation of practice in commercial and proprietary interactive engines. A focus will be on the role of the 3D artists in the future of environmental development, requiring adaptability to new approaches, as the field evolves in response to tandem technological advancements. Industry findings and projections theorize how these factors will impact the widespread utilization of augmented reality in daily life. This will continue to inform the direction of technology towards expansive interactive environments. It will change the tools and techniques utilized in the development of environments for game, film, and VFX. This study concludes that this technology will be the cornerstone for the creation of AI-driven AR that is able to fully theme our world, change how we see and engage with one another. This will impact the concept of a virtual self-identity that will be as prevalent as real-world identity. While this progression scares or even threaten some, it is safe to say that we are seeing the beginnings of a technological revolution that will surpass the impact that the smartphone had on modern society.

Keywords: virtual reality, augmented reality, training, 3D environments

Procedia PDF Downloads 124

Authors: Rejane Maria P. da Silva, Mariana X. Milagre, João Victor de S. Araujo, Leandro A. de Oliveira, Renato A. Antunes, Isolda Costa

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The Al-Cu-Li alloys are advanced materials for aerospace application because of their interesting mechanical properties and low density when compared with conventional Al-alloys. However, Al-Cu-Li alloys are susceptible to localized corrosion. The near-surface deformed layer (NSDL) induced by the rolling process during the production of the alloy and its removal by polishing can influence on the corrosion susceptibility of these alloys. In this work, the influence of surface preparation effects on the electrochemical activity of AA2098-T351 (Al–Cu–Li alloy) was investigated using a correlation between surface chemistry, microstructure, and electrochemical activity. Two conditions were investigated, polished and as-received surfaces of the alloy. The morphology of the two types of surfaces was investigated using confocal laser scanning microscopy (CLSM) and optical microscopy. The surface chemistry was analyzed by X-ray Photoelectron Spectroscopy (XPS) and energy dispersive X-ray spectroscopy (EDS). Global electrochemical techniques (potentiodynamic polarization and EIS technique) and a local electrochemical technique (Localized Electrochemical Impedance Spectroscopy-LEIS) were used to examine the electrochemical activity of the surfaces. The results obtained in this study showed that in the as-received surface, the near-surface deformed layer (NSDL), which is composed of Mg-rich bands, influenced the electrochemical behavior of the alloy. The results showed higher electrochemical activity to the polished surface condition compared to the as-received one.

Keywords: Al-Cu-Li alloys, surface preparation effects, electrochemical techniques, localized corrosion

Procedia PDF Downloads 160

Authors: S. Visetpotjanakit, C. Khrautongkieo

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Radiation monitoring in the environment and foodstuffs is one of the main responsibilities of Office of Atoms for Peace (OAP) as the nuclear regulatory body of Thailand. The main goal of the OAP is to assure the safety of the Thai people and environment from any radiological incidents. Various radioanalytical methods have been developed to monitor radiation and radionuclides in the environmental and foodstuff samples. To validate our analytical performance, several proficiency test exercises from the International Atomic Energy Agency (IAEA) have been performed. Here, the results of a proficiency test exercise referred to as the Proficiency Test for Tritium, Cobalt, Strontium and Caesium Isotopes in Seawater 2017 (IAEA-RML-2017-01) are presented. All radionuclides excepting ³H were analysed using various radioanalytical methods, i.e. direct gamma-ray counting for determining ⁶⁰Co, ¹³⁴Cs and ¹³⁷Cs and developed radiochemical techniques for analysing ¹³⁴Cs, ¹³⁷Cs using AMP pre-concentration technique and 90Sr using di-(2-ethylhexyl) phosphoric acid (HDEHP) liquid extraction technique. The analysis results were submitted to IAEA. All results passed IAEA criteria, i.e. accuracy, precision and trueness and obtained ‘Accepted’ statuses. These confirm the data quality from the OAP environmental radiation laboratory to monitor radiation in the environment.

Keywords: international atomic energy agency, proficiency test, radiation monitoring, seawater

Procedia PDF Downloads 172

Authors: Udayakumar Vee, Franck Quero

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Zwitterionic polymers generally have been viewed as a new class of antimicrobial and non-fouling materials. They offer a broad versatility for chemical modification and hence great freedom for accurate molecular design, which bear an equimolar number of homogenously distributed anionic and cationic groups along their polymer chains. This study explores the effectiveness of the auxetic zwitterion carboxylate/sulfonate hydrogel in the diabetic-induced mouse model. A series of silver metal-doped auxetic zwitterion carboxylate/sulfonate/vinylaniline copolymer hydrogels is designed via a 3D printer. Zwitterion monomers have been characterized by FT-IR and NMR techniques. The effect of changing the monomers and different loading ratios of Ag over zwitterion on the final hydrogel materials' antimicrobial properties and biocompatibility will be investigated in detail. The synthesized auxetic hydrogel has been characterized using a wide range of techniques to help establish the relationship between molecular level and macroscopic properties of these materials, including mechanical and antibacterial and biocompatibility and wound healing ability. This work's comparative studies and results provide new insights and guide us in choosing a better auxetic structured material for a broad spectrum of wound healing applications in the animal model. We expect this approach to provide a versatile and robust platform for biomaterial design that could lead to promising treatments for wound healing applications.

Keywords: auxetic, zwitterion, carboxylate, sulfonate, polymer, wound healing

Procedia PDF Downloads 142

Authors: Esther Chiramal, Kelvin Soh Boon Kai

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Explainable AI is a strong strategy implemented to understand complex black-box model predictions in a human-interpretable language. It provides the evidence required to execute the use of trustworthy and reliable AI systems. On the other hand, however, it also opens the door to locating possible vulnerabilities in an AI model. Traditional adversarial text attack uses word substitution, data augmentation techniques, and gradient-based attacks on powerful pre-trained Bidirectional Encoder Representations from Transformers (BERT) variants to generate adversarial sentences. These attacks are generally white-box in nature and not practical as they can be easily detected by humans e.g., Changing the word from “Poor” to “Rich”. We proposed a simple yet effective Grey-box cum Black-box approach that does not require the knowledge of the model while using a set of surrogate Transformer/BERT models to perform the attack using Explainable AI techniques. As Transformers are the current state-of-the-art models for almost all Natural Language Processing (NLP) tasks, an attack generated from BERT1 is transferable to BERT2. This transferability is made possible due to the attention mechanism in the transformer that allows the model to capture long-range dependencies in a sequence. Using the power of BERT generalisation via attention, we attempt to exploit how transformers learn by attacking a few surrogate transformer variants which are all based on a different architecture. We demonstrate that this approach is highly effective to generate semantically good sentences by changing as little as one word that is not detectable by humans while still fooling other BERT models.

Keywords: BERT, explainable AI, Grey-box text attack, transformer

Procedia PDF Downloads 138

Authors: Yeliz Karaca, Rana Karabudak

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Multifractal Denoising techniques are used in the identification of significant attributes by removing the noise of the dataset. Magnetic resonance (MR) image technique is the most sensitive method so as to identify chronic disorders of the nervous system such as Multiple Sclerosis. MRI and Expanded Disability Status Scale (EDSS) data belonging to 120 individuals who have one of the subgroups of MS (Relapsing Remitting MS (RRMS), Secondary Progressive MS (SPMS), Primary Progressive MS (PPMS)) as well as 19 healthy individuals in the control group have been used in this study. The study is comprised of the following stages: (i) L2 Norm Multifractal Denoising technique, one of the multifractal technique, has been used with the application on the MS data (MRI and EDSS). In this way, the new dataset has been obtained. (ii) The new MS dataset obtained from the MS dataset and L2 Multifractal Denoising technique has been applied to the K-Means and Fuzzy C Means clustering algorithms which are among the unsupervised methods. Thus, the clustering performances have been compared. (iii) In the identification of significant attributes in the MS dataset through the Multifractal denoising (L2 Norm) technique using K-Means and FCM algorithms on the MS subgroups and control group of healthy individuals, excellent performance outcome has been yielded. According to the clustering results based on the MS subgroups obtained in the study, successful clustering results have been obtained in the K-Means and FCM algorithms by applying the L2 norm of multifractal denoising technique for the MS dataset. Clustering performance has been more successful with the MS Dataset (L2_Norm MS Data Set) K-Means and FCM in which significant attributes are obtained by applying L2 Norm Denoising technique.

Keywords: clinical decision support, clustering algorithms, multiple sclerosis, multifractal techniques

Procedia PDF Downloads 171

Authors: Udayakumar Veerabagu, Franck Quero

Abstract:

Zwitterion carboxylate and sulfonate polymers generally have been viewed as a new class of antimicrobial and non-fouling materials. They offer a broad versatility for chemical modification and hence great freedom for accurate molecular design, which bear an equimolar number of homogenously distributed anionic and cationic groups along their polymer chains. This study explores the effectiveness of the auxetic zwitterion carboxylate/sulfonate hydrogel in the diabetic-induced mouse model. A series of silver metal-doped auxetic zwitterion carboxylate/sulfonate/vinylaniline copolymer hydrogels is designed via a 3D printer. Zwitterion monomers have been characterized by FT-IR and NMR techniques. The effect of changing the monomers and different loading ratios of Ag over zwitterion on the final hydrogel materials' antimicrobial properties and biocompatibility will be investigated in detail. The synthesized auxetic hydrogel has been characterized using a wide range of techniques to help establish the relationship between molecular level and macroscopic properties of these materials, including mechanical and antibacterial and biocompatibility and wound healing ability. This work's comparative studies and results provide new insights and guide us in choosing a better auxetic structured material for a broad spectrum of wound healing applications in the animal model. We expect this approach to provide a versatile and robust platform for biomaterial design that could lead to promising treatments for wound healing applications.

Keywords: auxetic, zwitterion, carboxylate, sulfonate, polymer, wound healing

Procedia PDF Downloads 157

Authors: A. S. V. Carvalho, J. Luis, L. S. O. Pires, J. M. Oliveira

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Additive manufacturing technologies (AM) experienced a remarkable growth in the latest years due to the development and diffusion of a wide range of three-dimensional (3D) printing techniques. Nowadays we can find techniques available for non-industrial users, like fused filament fabrication, but techniques like 3D printing, polyjet, selective laser sintering and stereolithography are mainly spread in the industry. Robocasting (R3D) shows a great potential due to its ability to shape materials with a wide range of viscosity. Industrial porcelain compositions showing different rheological behaviour can be prepared and used as candidate materials to be processed by R3D. The use of this AM technique in industry is very residual. In this work, a specific porcelain composition with suitable rheological properties will be processed by R3D, and a systematic study of the printing parameters tuning will be shown. The porcelain composition was formulated based on an industrial spray dried porcelain powder. The powder particle size and morphology was analysed. The powders were mixed with water and an organic binder on a ball mill at 200 rpm/min for 24 hours. The batch viscosity was adjusted by the addition of an acid solution and mixed again. The paste density, viscosity, zeta potential, particle size distribution and pH were determined. In a R3D system, different speed and pressure settings were studied to access their impact on the fabrication of porcelain models. These models were dried at 80 °C, during 24 hours and sintered in air at 1350 °C for 2 hours. The stability of the models, its walls and surface quality were studied and their physical properties were accessed. The microstructure and layer adhesion were observed by SEM. The studied processing parameters have a high impact on the models quality. Moreover, they have a high impact on the stacking of the filaments. The adequate tuning of the parameters has a huge influence on the final properties of the porcelain models. This work contributes to a better assimilation of AM technologies in ceramic industry. Acknowledgments: The RoboCer3D project – project of additive rapid manufacturing through 3D printing ceramic material (POCI-01-0247-FEDER-003350) financed by Compete 2020, PT 2020, European Regional Development Fund – FEDER through the International and Competitive Operational Program (POCI) under the PT2020 partnership agreement.

Keywords: additive manufacturing, porcelain, robocasting, R3D

Procedia PDF Downloads 163

Authors: Young Jae Choung, Seoung Bum Kim

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Statistical Process Control (SPC) is a popular technique for process monitoring. A widely used tool in SPC is a control chart, which is used to detect the abnormal status of a process and maintain the controlled status of the process. Traditional control charts, such as Hotelling’s T2 control chart, are effective techniques to detect abnormal observations and monitor processes. However, many complicated manufacturing systems exhibit nonlinearity because of the different demands of the market. In this case, the unregulated use of a traditional linear modeling approach may not be effective. In reality, many industrial processes contain the nonlinear and time-varying properties because of the fluctuation of process raw materials, slowing shift of the set points, aging of the main process components, seasoning effects, and catalyst deactivation. The use of traditional SPC techniques with time-varying data will degrade the performance of the monitoring scheme. To address these issues, in the present study, we propose a parameterless self-organizing map (PLSOM)-based control chart. The PLSOM-based control chart not only can manage a situation where the distribution or parameter of the target observations changes, but also address the nonlinearity of modern manufacturing systems. The control limits of the proposed PLSOM chart are established by estimating the empirical level of significance on the percentile using a bootstrap method. Experimental results with simulated data and actual process data from a thin-film transistor-liquid crystal display process demonstrated the effectiveness and usefulness of the proposed chart.

Keywords: control chart, parameter-less self-organizing map, self-organizing map, time-varying property

Procedia PDF Downloads 277

Authors: Pedro Ferraz-Gameiro

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Introduction: The Pellegrini-Stieda lesion is the result of post-traumatic calcification and/or ossification on the medial collateral ligament (MCL) of the knee. When this calcification is accompanied by gonalgia and limitation of knee flexion, it is called Pellegrini-Stieda syndrome. The pathogenesis is probably the calcification of a post-traumatic hematoma at least three weeks after the initial trauma or secondary to repetitive microtrauma. On anteroposterior radiographs, a Pellegrini-Stieda lesion is a linear vertical ossification or calcification of the proximal portion of the MCL and usually near the medial femoral condyle. Patients with Pellegrini-Stieda syndrome present knee pain associated with loss of range of motion. The treatment is usually conservative with analgesic and anti-inflammatory drugs, either systemic or intra-articular. Physical medicine and rehabilitation techniques associated with shock wave therapy can be a way of reduction of pain/inflammation. Patients who maintain instability with significant limitation of knee mobility may require surgical excision. Methods: Research was done using PubMed central using the terms Pellegrini-Stieda syndrome. Discussion/conclusion: Medical treatment is the rule, with initial rest, anti-inflammatory, and physiotherapy. If left untreated, this ossification can potentially form a significant bone mass, which can compromise the range of motion of the knee. Physical medicine and rehabilitation techniques associated with shock wave therapy are a way of reduction of pain/inflammation.

Keywords: knee, Pellegrini-Stieda syndrome, rehabilitation, shock waves therapy

Procedia PDF Downloads 142

Authors: Udeh Nneka Evelyn

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The shortcoming of traditional costing system in terms of validity, accuracy, consistency, and Relevance increased the need for modern management accounting system. Activity –Based Costing (ABC) can be used as a modern tool for planning, Control and decision making for management. Past studies on ABC system have focused on manufacturing firms thereby making the studies on service firms scanty to some extent. This paper reviewed the application and relevance of activity-based costing technique in service oriented business organizations by employing a qualitative research method which relied heavily on literature review of past and current relevant articles focusing on ABC. Findings suggest that ABC is not only appropriate for use in a manufacturing environment; it is also most appropriate for service organizations such as financial institutions, the healthcare industry and government organization. In fact, some banking and financial institutions have been applying the concept for years under other names. One of them is unit costing, which is used to calculate the cost of banking services by determining the cost and consumption of each unit of output of functions required to deliver the service. ABC in very basic terms may provide very good payback for businesses. Some of the benefits that relate directly to the financial services industry are: identification the most profitable customers: more accurate product and service pricing: increase product profitability: Well organized process costs.

Keywords: business, costing, organizations, planning, techniques

Procedia PDF Downloads 241

Authors: Ömer Tamer, Davut Avcı, Yusuf Atalay

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Novel picolinate complex of manganese(II) ion, [Mn(pic)2] [pic: picolinate or 2-pyridinecarboxylate], was prepared and fully characterized by single crystal X-ray structure determination. The manganese(II) complex was characterized by FT-IR, FT-Raman and UV–Vis spectroscopic techniques. The C=O, C=N and C=C stretching vibrations were found to be strong and simultaneously active in IR and spectra. In order to support these experimental techniques, density functional theory (DFT) calculations were performed at Gaussian 09W. Although the supramolecular interactions have some influences on the molecular geometry in solid state phase, the calculated data show that the predicted geometries can reproduce the structural parameters. The molecular modeling and calculations of IR, Raman and UV-vis spectra were performed by using DFT levels. Nonlinear optical (NLO) properties of synthesized complex were evaluated by the determining of dipole moment (µ), polarizability (α) and hyperpolarizability (β). Obtained results demonstrated that the manganese(II) complex is a good candidate for NLO material. Stability of the molecule arising from hyperconjugative interactions and charge delocalization was analyzed using natural bond orbital (NBO) analysis. The highest occupied and the lowest unoccupied molecular orbitals (HOMO and LUMO) which is also known the frontier molecular orbitals were simulated, and obtained energy gap confirmed that charge transfer occurs within manganese(II) complex. Molecular electrostatic potential (MEP) for synthesized manganese(II) complex displays the electrophilic and nucleophilic regions. From MEP, the the most negative region is located over carboxyl O atoms while positive region is located over H atoms.

Keywords: DFT, picolinate, IR, Raman, nonlinear optic

Procedia PDF Downloads 500

Authors: Daniel Ter Goon, Aanuoluwa O. Adedokun, Eyitayo Omolara Owolabi, Oladele Vincent Adeniyi, Anthony Idowu Ajayi

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Background: The unhealthy food choices and sedentary lifestyle of commercial drivers predisposes them to obesity and obesity related diseases. Yet, no attention has been paid to obesity burden among this high risk group in South Africa. This study examines the prevalence of obesity and its risk factors among commercial drivers in East London, South Africa. Methods: This cross-sectional study utilized the WHO STEP wise approach to screen for obesity among 403 drivers in Buffalo City Metropolitan Municipality (BCMM), South Africa. Anthropometric, blood pressure and blood glucose measurements were taken following a standard procedure. Overweight and obesity was defined as a body mass index (BMI) of 25.0 kgm⁻²–29.9 kg/m² and≥ 30 kg/ m², respectively. Bivariate and multivariate analysis were used to determine the prevalence and determinants of obesity. Result: The mean age of the participants was 43.3 (SD12.5) years, mean height (cm) and weight (kg) were 170.1(6.2cm) and 83(SD18.7), respectively. The prevalence of overweight and obesity was 34.0% and 38.0%, respectively. After adjusting for confounding factors, only age (OR 1.6, CI 1.0-2.7), hypertension (OR 3.6, CI 2.3-5.7) and non-smoking (OR 2.0, CI 1.3-3.1) were independent predictors of obesity. Conclusion: The prevalence of overweight and obesity is high among commercial drivers. Age, hypertension, and non-smoking were independent predictors of obesity among the sample. Measures aimed at promoting health and reducing obesity should be prioritized among this group.

Keywords: obesity and overweight, commercial taxi drivers, risk factors, South Africa

Procedia PDF Downloads 346

Authors: Basem Kamal Abasakhiroun Farag

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Fashion, like many other areas of design, has undergone numerous developments over the centuries. The aim of the article is to recognize and evaluate the importance of advanced technologies in fashion design and to examine how they are transforming the role of contemporary fashion designers by transforming the creative process. It also discusses how contemporary culture is involved in such developments and how it influences fashion design in terms of conceptualization and production. The methodology used is based on examining various examples of the use of technology in fashion design and drawing parallels between what was feasible then and what is feasible today. Comparison of case studies, examples of existing fashion designs and experiences with craft methods; We therefore observe patterns that help us predict the direction of future developments in this area. Discussing the technological elements in fashion design helps us understand the driving force behind the trend. The research presented in the article shows that there is a trend towards significantly increasing interest and progress in the field of fashion technology, leading to the emergence of hybrid artisanal methods. In summary, as fashion technologies advance, their role in clothing production is becoming increasingly important, extending far beyond the humble sewing machine.

Keywords: fashion, identity, such, textiles ambient intelligence, proximity sensors, shape memory materials, sound sensing garments, wearable technology bio textiles, fashion trends, nano textiles, new materials, smart textiles, techno textiles fashion design, functional aesthetics, 3D printing.

Procedia PDF Downloads 68

Authors: Walaa Hamed Mohamed Hamza

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Textile structures are the way in which the threading process of both thread and loom is done together to form the woven. Different methods of attaching the clothing and the flesh produce different textile structures, which differ in their surface appearance from each other, including so-called simple textile structures. Textile compositions are the basis of woven fabric, through which aesthetic values can be achieved in the textile industry by weaving threads of yarn with the weft at varying degrees that may reach the total control of one of the two groups on the other. Hence the idea of how art and design can be used using different textile structures under the modern techniques of pate de verre. In the creation of designs suitable for glass products employed in the interior architecture. The problem of research: The textile structures, in general, have a significant impact on the appearance of the fabrics in terms of form and aesthetic. How can we benefit from the characteristics of different textile compositions in different glass designs with different artistic values. The research achieves its goal by the investment of simple textile structures in innovative artistic designs using the pate de verre technique, as well as the use of designs resulting from the textile structures in the external architecture to add various aesthetic values. The importance of research in the revival of heritage using ancient techniques, as well as synergy between different fields of applied arts such as glass and textile, and also study the different and diverse effects resulting from each fabric composition and the possibility of use in various designs in the interior architecture. The research will be achieved that by investing in simple textile compositions, innovative artistic designs produced using pate de verre technology can be used in interior architecture.

Keywords: glass, interior architecture, pate de verre, textile structures

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Authors: Hamed Ahari, Behrouz Akbari Adreghani, Vadood Razavilar, Amirali Anvar, Sima Moradi, Hourieh Shalchi

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Considering the ever increasing population and industrialization of the developmental trend of humankind's life, we are no longer able to detect the toxins produced in food products using the traditional techniques. This is due to the fact that the isolation time for food products is not cost-effective and even in most of the cases, the precision in the practical techniques like the bacterial cultivation and other techniques suffer from operator errors or the errors of the mixtures used. Hence with the advent of nanotechnology, the design of selective and smart sensors is one of the greatest industrial revelations of the quality control of food products that in few minutes time, and with a very high precision can identify the volume and toxicity of the bacteria. Methods and Materials: In this technique, based on the bacterial antibody connection to nanoparticle, a sensor was used. In this part of the research, as the basis for absorption for the recognition of bacterial toxin, medium sized silica nanoparticles of 10 nanometer in form of solid powder were utilized with Notrino brand. Then the suspension produced from agent-linked nanosilica which was connected to bacterial antibody was positioned near the samples of distilled water, which were contaminated with Staphylococcus aureus bacterial toxin with the density of 10-3, so that in case any toxin exists in the sample, a connection between toxin antigen and antibody would be formed. Finally, the light absorption related to the connection of antigen to the particle attached antibody was measured using spectrophotometry. The gene of 23S rRNA that is conserved in all Staphylococcus spp., also used as control. The accuracy of the test was monitored by using serial dilution (l0-6) of overnight cell culture of Staphylococcus spp., bacteria (OD600: 0.02 = 107 cell). It showed that the sensitivity of PCR is 10 bacteria per ml of cells within few hours. Result: The results indicate that the sensor detects up to 10-4 density. Additionally, the sensitivity of the sensors was examined after 60 days, the sensor by the 56 days had confirmatory results and started to decrease after those time periods. Conclusions: Comparing practical nano biosensory to conventional methods like that culture and biotechnology methods(such as polymerase chain reaction) is accuracy, sensitiveness and being unique. In the other way, they reduce the time from the hours to the 30 minutes.

Keywords: exotoxin, nanobiosensor, recognition, Staphylococcus aureus

Procedia PDF Downloads 387

Authors: Pratyusha Das

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A paradigm shift has been noticed in the interpretation of DNA evidence for determining paternity. Sometimes DNA evidence has been accepted while sometimes it was rejected by the Indian Courts. Courts have forwarded various justifications for acceptance and rejection of such evidence through legal and scientific means. Laws have also been changed to accommodate the necessities of society. Balances between both the legal and scientific approaches are required, to make the best possible use of DNA evidence for the well-being of the society. Specifications are to be framed as to when such evidence can be used in the future by pointing out the pros and cons. Judicial trend is to be formulated to find out the present situation. The study of cases of superior courts of India using an analytical and theoretical approach is driving the questions regarding the shared identity of the legal and scientific approaches. To assimilate the differences between the two approaches, the basic differences between them have to be formulated. Revelations are required to access the favorable decisions using the DNA evidence. Reasons are to be forwarded for the unfavorable decisions and the approach preferred in such cases. The outcome of the two methods has to be assessed in relation to the parties to the dispute, the society at large, the researcher and from the judicial point of view. The dependability of the two methods is to be studied in relation to the justice delivery system. A highlight of the chronological study of cases along with the changes in the laws with the aid of presumptions will address the questions of necessity of a method according to the facts and situations. Address is required in this respect whether the legal and scientific forces converge somewhere pushing the traditional identification of paternity towards a fundamental change.

Keywords: cases, evidence, legal, scientific

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Authors: Azita Ramezani, Ghazal Mashhadiagha, Bahareh Sanabakhsh

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This study researches the combination of Random. Forest classifiers with large language models (LLMs) and natural language processing (NLP) to improve diagnostic accuracy in chest X-ray analysis using the Indiana University dataset. Utilizing advanced NLP techniques, the research preprocesses textual data from radiological reports to extract key features, which are then merged with image-derived data. This improved dataset is analyzed with Random Forest classifiers to predict specific clinical results, focusing on the identification of health issues and the estimation of case urgency. The findings reveal that the combination of NLP, LLMs, and machine learning not only increases diagnostic precision but also reliability, especially in quickly identifying critical conditions. Achieving an accuracy of 99.35%, the model shows significant advancements over conventional diagnostic techniques. The results emphasize the large potential of machine learning in medical imaging, suggesting that these technologies could greatly enhance clinician judgment and patient outcomes by offering quicker and more precise diagnostic approximations.

Keywords: natural language processing (NLP), large language models (LLMs), random forest classifier, chest x-ray analysis, medical imaging, diagnostic accuracy, indiana university dataset, machine learning in healthcare, predictive modeling, clinical decision support systems

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Authors: Taha Kadir Yesin, Hanyu Liu, Zhangfan Ding, Amit Singh, Qi Tian, Yuheng Zhang, Biswajyoti Borah, Junyu Chen, Anjali P. Kusumbe

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The skeletal structure and bone marrow endothelium collectively form a critical functional unit essential for bone development, health, and aging. At the core of osteogenesis and bone formation lies the dynamic process of angiogenesis. In this study, we reveal a potent endogenous anabolic NCAM1-14.3.3. ζδ-derived- Peptide interaction, which stimulates bone angiogenesis and osteogenesis during homeostasis, aging, and age-related bone diseases. Employing high-resolution imaging and inducible cell-specific mouse genetics, our results elucidate the pivotal role of the NCAM1-14.3.3.ζδ-derived-Peptide interaction in driving the expansion of Clec14a+ angiogenic endothelial cells. Notably, Clec14a+ endothelial cells express key osteogenic factors. The NCAM1-14.3.3.ζδ-derived-Peptide interaction in osteoblasts drives osteoblast differentiation, ultimately contributing to the genesis of bone. Moreover, the NCAM1-14.3.3.ζδ-derived-Peptide interaction leads to a reduction in bone resorption. In age-associated vascular and bone loss diseases, stimulating the NCAM1-14.3.3.ζδ-derived-Peptide interaction not only promotes angiogenesis but also reverses bone loss. Consequently, harnessing the endogenous anabolic potential of the NCAM1-14.3.3.ζδ-derived-Peptide interaction emerges as a promising therapeutic modality for managing age-related bone diseases.

Keywords: endothelial cell, NCAM1, Clec14a, 14.3.3.ζδ

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Authors: Najib Belhadj Messaoud, Slim Souissi

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The non-linear dynamic behavior of a single stage spur gear reducer is studied in this paper in transient regime. Driving and driver rotors are, respectively, powered by a motor torque Cm and loaded by a resistive torque Cr. They are supported by two identical Active Magnetic Bearings (AMBs). Gear excitation is induced by the motor torque and load variation in addition to the fluctuation of meshing stiff-ness due to the variation of input rotational speed. Three models of AMBs were used with four, six and eight magnets. They are operated by P.D controller and powered by control and bias currents. The dynamic parameters of the AMBs are modeled by stiffness and damping matrices computed by the derivation of the electromagnetic forces. The equations of motion are solved iteratively using Newmark time integration method. In the first part of the study, the model is powered by an electric motor and by a four strokes four cylinders diesel engine in the second part. The numerical results of the dynamic responses of the system come to confirm the significant effect of the transient regime on the dynamic behavior of a gear set, particularly in the case of engine acyclism condition. Results also confirm the influence of the magnet number by AMBs on the dynamic behavior of the system. Indeed, vibrations were more important in the case of gear reducer supported by AMBs with four magnets.

Keywords: motor, stiffness, gear, acyclism, fluctuation, torque

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Authors: Essam Amerian

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The aim of this study was to investigate the effects of improving waist-to-hip ratio (WHR) and visceral fat components on the health of shift workers in an offshore petrochemical company. A total of 100 male shift workers participated in the study, with an average age of 40.5 years and an average BMI of 28.2 kg/m². The study employed a randomized controlled trial design, with participants assigned to either an intervention group or a control group. The intervention group received a 12-week program that included dietary counseling, physical activity recommendations, and stress management techniques. The control group received no intervention. The outcomes measured were changes in WHR, visceral fat components, blood pressure, and lipid profile. The results showed that the intervention group had a statistically significant improvement in WHR (p<0.001) and visceral fat components (p<0.001) compared to the control group. Furthermore, there were statistically significant improvements in systolic blood pressure (p=0.015) and total cholesterol (p=0.034) in the intervention group compared to the control group. These findings suggest that implementing a 12-week program that includes dietary counseling, physical activity recommendations, and stress management techniques can effectively improve WHR, visceral fat components, and cardiovascular health among shift workers in an offshore petrochemical company.

Keywords: body composition, waist-hip-ratio, visceral fat, shift worker, work efficiency

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Authors: Maria Fonseca, Ana Branco, Joao Graca, Rui Mendes, Pedro Mimoso

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The present work is focused on the production of a carbon composite element for cycling through different techniques, namely, blow-molding and high-pressure resin transfer injection (HP-RTM). The main objective of this work is to compare both processes to produce carbon composite elements for the cycling industry. It is well known that the carbon composite components for cycling are produced mainly through blow-molding; however, this technique depends strongly on manual labour, resulting in a time-consuming production process. Comparatively, HP-RTM offers a more automated process which should lead to higher production rates. Nevertheless, a comparison of the elements produced through both techniques must be done, in order to assess if the final products comply with the required standards of the industry. The main difference between said techniques lies in the used material. Blow-moulding uses carbon prepreg (carbon fibres pre-impregnated with a resin system), and the material is laid up by hand, piece by piece, on a mould or on a hard male. After that, the material is cured at a high temperature. On the other hand, in the HP-RTM technique, dry carbon fibres are placed on a mould, and then resin is injected at high pressure. After some research regarding the best material systems (prepregs and braids) and suppliers, an element was designed (similar to a handlebar) to be constructed. The next step was to perform FEM simulations in order to determine what the best layup of the composite material was. The simulations were done for the prepreg material, and the obtained layup was transposed to the braids. The selected material was a prepreg with T700 carbon fibre (24K) and an epoxy resin system, for the blow-molding technique. For HP-RTM, carbon fibre elastic UD tubes and ± 45º braids were used, with both 3K and 6K filaments per tow, and the resin system was an epoxy as well. After the simulations for the prepreg material, the optimized layup was: [45°, -45°,45°, -45°,0°,0°]. For HP-RTM, the transposed layup was [ ± 45° (6k); 0° (6k); partial ± 45° (6k); partial ± 45° (6k); ± 45° (3k); ± 45° (3k)]. The mechanical tests showed that both elements can withstand the maximum load (in this case, 1000 N); however, the one produced through blow-molding can support higher loads (≈1300N against 1100N from HP-RTM). In what concerns to the fibre volume fraction (FVF), the HP-RTM element has a slightly higher value ( > 61% compared to 59% of the blow-molding technique). The optical microscopy has shown that both elements have a low void content. In conclusion, the elements produced using HP-RTM can compare to the ones produced through blow-molding, both in mechanical testing and in the visual aspect. Nevertheless, there is still space for improvement in the HP-RTM elements since the layup of the braids, and UD tubes could be optimized.

Keywords: HP-RTM, carbon composites, cycling, FEM

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Authors: Bilel Chalghaf, Mathieu Varin

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Forest characterization in Quebec, Canada, is usually assessed based on photo-interpretation at the stand level. For species identification, this often results in a lack of precision. Very high spatial resolution imagery, such as DigitalGlobe, and Light Detection and Ranging (LiDAR), have the potential to overcome the limitations of aerial imagery. To date, few studies have used that data to map a large number of species at the tree level using machine learning techniques. The main objective of this study is to map 11 individual high tree species ( > 17m) at the tree level using an object-based approach in the broadleaf forest of Kenauk Nature, Quebec. For the individual tree crown segmentation, three canopy-height models (CHMs) from LiDAR data were assessed: 1) the original, 2) a filtered, and 3) a corrected model. The corrected CHM gave the best accuracy and was then coupled with imagery to refine tree species crown identification. When compared with photo-interpretation, 90% of the objects represented a single species. For modeling, 313 variables were derived from 16-band WorldView-3 imagery and LiDAR data, using radiance, reflectance, pixel, and object-based calculation techniques. Variable selection procedures were employed to reduce their number from 313 to 16, using only 11 bands to aid reproducibility. For classification, a global approach using all 11 species was compared to a semi-hierarchical hybrid classification approach at two levels: (1) tree type (broadleaf/conifer) and (2) individual broadleaf (five) and conifer (six) species. Five different model techniques were used: (1) support vector machine (SVM), (2) classification and regression tree (CART), (3) random forest (RF), (4) k-nearest neighbors (k-NN), and (5) linear discriminant analysis (LDA). Each model was tuned separately for all approaches and levels. For the global approach, the best model was the SVM using eight variables (overall accuracy (OA): 80%, Kappa: 0.77). With the semi-hierarchical hybrid approach, at the tree type level, the best model was the k-NN using six variables (OA: 100% and Kappa: 1.00). At the level of identifying broadleaf and conifer species, the best model was the SVM, with OA of 80% and 97% and Kappa values of 0.74 and 0.97, respectively, using seven variables for both models. This paper demonstrates that a hybrid classification approach gives better results and that using 16-band WorldView-3 with LiDAR data leads to more precise predictions for tree segmentation and classification, especially when the number of tree species is large.

Keywords: tree species, object-based, classification, multispectral, machine learning, WorldView-3, LiDAR

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Authors: Paul Dunst, Ing. Tobias Hemsel, Ing. Habil. Walter Sextro

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The use of fine powders with high cohesive and adhesive properties leads to challenges during transport, mixing and dosing in industrial processes, which have not been satisfactorily solved so far. Due to the increased contact forces at the transporting parts (e. g. pipe-wall and transport screws), conventional transport systems and also vibratory conveyors reach their limits. Often, flowability increasing additives that need to be removed again in later process steps are the only option to achieve wanted transport results. A rather new ultrasound-assisted powder transport system showed to overcome some of the issues by manipulating the effective friction between powder and transport pipe. Within this contribution, the transport mechanism will be introduced shortly, together with preliminary transport results. As the tangential force of the transport pipe and the powder is the main influencing factor within the transport process, a test stand for measuring tangential forces of a powder-wall contact in the presence of an ultrasonic vibration orthogonal to the contact plane was built. Measurements for a sample powder show that the effective tangential force can already be significantly reduced at very low ultrasonic amplitude. As a result of the measurements, an empirical model for the relationship of tangential force, contact parameters and ultrasonic excitation is presented. This model was used to adjust the driving parameters of the powder transport system, resulting in better performance.

Keywords: powder transport, ultrasound, friction, friction manipulation, vibratory conveyor

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Authors: L. Freeborn

Abstract:

Recent years have seen an increasing number of neuroimaging studies related to language learning as imaging techniques such as fMRI and EEG have become more widely accessible to researchers. By using a variety of structural and functional neuroimaging techniques, these studies have already made considerable progress in terms of our understanding of neural networks and processing related to first and second language acquisition. However, the methodological designs employed in neuroimaging studies to test language learning have been questioned by applied linguists working within the field of second language acquisition (SLA). One of the major criticisms is that tasks designed to measure language learning gains rarely have a communicative function, and seldom assess learners’ ability to use the language in authentic situations. This brings the validity of many neuroimaging tasks into question. The fundamental reason why people learn a language is to communicate, and it is well-known that both first and second language proficiency are developed through meaningful social interaction. With this in mind, the SLA field is in agreement that second language acquisition and proficiency should be measured through learners’ ability to communicate in authentic real-life situations. Whilst authenticity is not always possible to achieve in a classroom environment, the importance of task authenticity should be reflected in the design of language assessments, teaching materials, and curricula. Tasks that bear little relation to how language is used in real-life situations can be considered to lack construct validity. This paper first describes the typical tasks used in neuroimaging studies to measure language gains and proficiency, then analyses to what extent these tasks can validly assess these constructs.

Keywords: neuroimaging studies, research design, second language acquisition, task validity

Procedia PDF Downloads 141