Search results for: training material

Authors: Javeed Akhtar, R. K. Pandey, Z. R. Azaz Ahmad Azad

Abstract:

For the purpose of making different uses of food material for the development of extruded foods are produced using single and twin extruders. Extrusion cooking is a useful and economical tool for processing of novel food. This high temperature, short time processing technology causes chemical and physical changes that alter the nutritional and physical quality of the product. Extrusion processing of food ingredients characteristically depends on associating process conditions that influence the product qualities. The process parameters are optimized for extrusion of food material in order to obtain the maximum nutritive value by inactivating the anti-nutritional factors. The processing conditions such as moisture content, temperature and time are controlled to avoid over heating or under heating which otherwise would result in a product of lower nutritional quality.

Keywords: extrusion processing, single and twin extruder, operating condition of extruders and extruded novel foods, food and agricultural engineering

Procedia PDF Downloads 369

Authors: Ali Ashjaran

Abstract:

Graphene is undoubtedly emerging as one of the most promising materials because of its unique combination of superb properties, which opens a way for its exploitation in a wide spectrum of applications ranging from electronics to optics, sensors, and biodevices. In addition, Graphene-based nanomaterials have many promising applications in energy-related areas. Graphene a single layer of carbon atoms, combines several exceptional properties, which makes it uniquely suited as a coating material: transparency, excellent mechanical stability, low chemical reactivity, Optical, impermeability to most gases, flexibility, and very high thermal and electrical conductivity. Graphene is a material that can be utilized in numerous disciplines including, but not limited to: bioengineering, composite materials, energy technology and nanotechnology, biological engineering, optical electronics, ultrafiltration, photovoltaic cells. This review aims to provide an overiew of graphene structure, properties and some applications.

Keywords: graphene, carbon, anti corrosion, optical and electrical properties, sensors

Procedia PDF Downloads 266

Authors: Sipho Mbatha, Anne Mastament-Mason

Abstract:

The Multi-Fibre Arrangement (MFA) which regulated all trade in the Apparel Manufacturing Industries (AMI) for four decades was dissolved in 2005. Since 2005, the Apparel Manufacturing Industry of South Africa (AMISA) has been battling to adjust to an environment of liberalised trade, mainly due to strategic, infrastructural and skills factors. In developing competitive advantage strategy for the AMISA, the study aimed to do the following (1) to apply Porter’s diamond model’s determinant “Factor Condition” as framework to develop competitive advantage strategies. (2) Examine the effectiveness of government policy Industrial Policy Action Plan (IPAP 2007) in supporting AMISA. (3) Examine chance events that could be used as bases for competitive advantage strategies for the AMISA. This study found that the lack of advanced skills and poor infrastructure are affecting the competitive advantage of AMISA. The then Clothing, Textiles, Leather and Footwear Sector Education and Training Authority (CTLF-SETA) has also fallen short of addressing the skills gap within the apparel manufacturing industries. The only time that AMISA have shown signs of competitive advantage was when they made use of government grants and incentives available to only compliant AMISA. The findings have shown that the apparel retail groups have shown support for the AMISA by shouldering raw material costs, making it easier to manufacture the required apparel at acceptable lead times. AMISA can compete in low end apparel, provided quick response is intensified, the development of local textiles and raw materials is expedited.

Keywords: compliance rule, apparel manufacturing idustry, factor conditions, advance skills, industrial policy action plan of South Africa

Procedia PDF Downloads 587

Authors: Farid Amidi-Fazli

Abstract:

Problems and disadvantages of using conventional plastics are more apparent in recent years and have attracted researchers' attention. Polymers from natural resources or bio polymers represent a suitable replacement to overcome to the disadvantages of plastics. But due to the some flaws of bio polymers, using suitable filler almost seems necessary. Nanocrystalline cellulose with low cost and availability can be applied as appropriate filler. In this study nanocrystalline cellulose was produced from cotton Linter and was characterized. The cotton Linter was hydrolyzed in sulfuric acid then neutralized by the two different concentrations of NaOH. The resulted suspension was treated by ultrasound waves. Process efficiency was determined as 90%. The final product was studied using scanning electron microscopy and x-ray diffraction technique. The obtained diagram of XRD experiment confirmed that the produced material was nanocrystalline cellulose. Also percentage of crystallinity was calculated as 84% in the obtained material as well as the size of crystals. It can be said that the applied method is a rapid and easy method for the production of nanocrystalline cellulose.

Keywords: nanocrystalline cellulose, crystallinity, XRD, cotton linter

Procedia PDF Downloads 494

Authors: Rafenomananjara Tsinjo Nirina, Tomoo Sekito, Andrianaivoravelona Jaconnet Oliva

Abstract:

Manufacturing a composite material from post-consumer bottles is an interesting outlet since Madagascar is still facing the challenges of managing plastic waste on the one hand and appropriate waste treatment facilities are not yet developed on the other hand. New waste management options are needed to divert End-Of-Life (EOL) soft plastic wastes from landfills and incineration. Waste polyethylene terephthalate (PET) bottles might be considered as a valuable resource and recovered into polymer concrete. The methodology is easy to implement and appropriate to the local context in Madagascar. This approach will contribute to the production of ecological building materials that might be profitable for the environment and the construction sector. This work aims to study the feasibility of using the post-consumer PET bottles as an alternative binding agent instead of the conventional Portland cement and water. Then, the mechanical and physical properties of the materials were evaluated.

Keywords: PET recycling, polymer concrete, ecological building materials, pollution mitigation

Procedia PDF Downloads 77

Authors: Brian Fleischli, Shani Robins

Abstract:

In recent years, the implementation of wisdom skills, including emotional intelligence, mindfulness, empathy, compassion, gratitude, realism (Cognitive-Behavioral Therapy), and humility, within K-12 educational settings has demonstrated significant benefits in reducing stress, anxiety, anger, and conflict among students. This study summarizes the findings of research conducted over several years, showcasing the positive outcomes associated with teaching these skills to elementary and high school students. Additionally, this overview includes an updated synthesis of current literature concerning the application and effectiveness of training these skill sets in K-12 schools. The research outcomes highlight substantial improvements in student well-being and behavior. Demonstrated with treatment group students exhibiting notable reductions in anger, anxiety, depression, and disruptive behaviors compared to control groups. For instance, fourth-grade students showed enhanced empathy, responsibility, and attention, particularly benefiting those with lower initial scores on these measures. Specific interaction effects suggest that older students and males particularly benefit from these interventions, showcasing the nuanced impact of wisdom skill training across different demographics. Furthermore, this presentation emphasizes the critical role of Social and Emotional Learning (SEL) programs in addressing the multifaceted challenges faced by children and adolescents, including mental health issues, academic performance, and social behaviors. The integration of wisdom skills into school curricula not only fosters individual growth and emotional regulation but also enhances overall school climate and academic achievement. In conclusion, the findings contribute to the growing body of empirical evidence supporting the efficacy of teaching wisdom skills in educational settings. The success of these interventions underscores the potential for widespread implementation of evidence-based programs to promote emotional well-being and academic success among students nationwide.

Keywords: wisdom skills, CBT, cognitive behavioral training, mindfulness, empathy, anxiety

Procedia PDF Downloads 31

Authors: Thangavelu Muthukumar, Thotapalli Parvathaleswara Sastry

Abstract:

Collagen is the most abundantly available connective tissue protein, which is being used as a biomaterial for various biomedical applications. Presently, fish wastes are disposed improperly which is causing serious environmental pollution resulting in offensive odour. Fish scales are promising source of Type I collagen. Medicinal plants have been used since time immemorial for treatment of various ailments of skin and dermatological disorders especially cuts, wounds, and burns. Developing biomaterials from the natural sources which are having wound healing properties within the search of a common man is the need of hour, particularly in developing and third world countries. With these objectives in view we have developed a wound dressing material containing fish scale collagen (FSC) incorporated with Macrotyloma uniflorum plant extract (PE). The wound dressing composite was characterized for its physiochemical properties using conventional methods. SEM image revealed that the composite has fibrous and porous surface which helps in transportation of oxygen as well as absorbing wound fluids. The biomaterial has shown 95% biocompatibility with required mechanical strength and has exhibited antimicrobial properties. This biomaterial has been used as a wound dressing material in experimental wounds of rats. The healing pattern was evaluated by macroscopic observations, panimetric studies, biochemical, histopathological observations. The results showed faster healing pattern in the wounds treated with CSPE compared to the other composites used in this study and untreated control. These experiments clearly suggest that CSPE can be used as wound/burn dressing materials.

Keywords: collagen, wound dressing, Macrotyloma uniflorum, burn dressing

Procedia PDF Downloads 395

Authors: Tesfaye Worku

Abstract:

Human hair, chicken feathers, and hairs of other birds and animals are commonly described as waste products, and the currently available disposal methods, such as burying and burning these waste products, are contributing to environmental pollution. However, those waste products are used to develop fiber-reinforced textile composite material. In this research work, the composite was developed using human hair fiber and analysis of the mechanical and physical properties of the developed composite sample. A composite sample was made with different ratios of human hair and unsaturated polyester resin, and an analysis of the mechanical and physical properties of the developed composite sample was tested according to standards. The fabricated human hair fibers reinforced polymer matrix composite sample has given encouraging results in terms of high strength and rigidity for lightweight house ceiling board material.

Keywords: composite, human hair fiber, matrix, unsaturated polyester

Procedia PDF Downloads 43

Authors: N. Aliyu, G. Atkinson, N. Stannard

Abstract:

Compacted insulated iron powder is a key material in high volume electric motors manufacturing. It offers high production rates, dimensionally stable components, and low scrap volumes. It is the aim of this paper to develop a three-phase compact single sided concentrated winding axial flux PM motor with soft magnetic composite (SMC) core for reducing core losses and cost. To succeed the motor would need to be designed in such a way as to exploit the isotropic magnetic properties of the material and open slot constructions with surface mounted PM for higher speed up to 6000 rpm, without excessive rotor losses. Higher fill factor up to 70% was achieved by compacting the coils, which offered a significant improvement in performance. A finite-element analysis was performed for accurate parameters calculation and the simulation results are thoroughly presented and agree with the theoretical calculations very well.

Keywords: SMC core, axial gap motor, high efficiency, torque

Procedia PDF Downloads 321

Authors: Jhoanne Pedres Boñgol, Zhang Liu, Yuyin Qiu, King Lun Yeung

Abstract:

Flexible ceramic sorbent material can be a viable technology to capture and recover emulsified fats, oils, and grease (FOG) that often cause sanitary sewer overflows. This study investigates the sorption capacity and recovery rate of ceramic material in surfactant-stabilized oil-water emulsion by synthesizing silica aerogel: SiO₂–X via acid-base sol-gel method followed by ambient pressure drying. The SiO₂–X is amorphous, microstructured, lightweight, flexible, and highly oleophilic. It displays spring-back behavior apparent at 80% compression with compressive strength of 0.20 MPa and can stand a weight of 1000 times its own. The contact angles measured at 0° and 177° in oil and water, respectively, confirm its oleophilicity and hydrophobicity while its thermal stability even at 450 °C is confirmed via TGA. In pure oil phase, the qe,AV. of 1x1 mm SiO₂–X is 7.5 g g⁻¹ at tqe= 10 min, and a qe,AV. of 6.05 to 6.76 g g⁻¹ at tqe= 24 hrs in O/W emulsion. The filter ceramic can be reused 50 x with 75-80 % FOG recovery by manual compression.

Keywords: adsorption, aerogel, emulsion, FOG

Procedia PDF Downloads 144

Authors: Vesna Pungercar, Florian Musso

Abstract:

Identifying materials that can substitute rare or expensive natural resources is one of the key challenges for improving resource efficiency in the building sector. With a growing world population and rising living standards, more and more salt is produced as waste through seawater desalination and potash mining processes. Unfortunately, most of the salt is directly disposed of into nature, where it causes environmental pollution. On the other hand, salt is affordable, is used therapeutically in various respiratory treatments, and can store humidity and heat. It was, therefore, necessary to determine salt materials already in use in building construction and their hygrothermal properties. This research aims to identify salt materials from different scientific branches and historically, to investigate their properties and prioritize the most promising salt materials for indoor applications in a thermal envelope. This was realized through literature review and classification of salt materials into three groups (raw salt materials, composite salt materials, and processed salt materials). The outcome of this research shows that salt has already been used as a building material for centuries and has a potential for future applications due to its hygrothermal properties in a thermal envelope.

Keywords: salt, building material, hygrothermal properties, environment

Procedia PDF Downloads 151

Authors: Gülşah Kanbur, Veysel Ayhan

Abstract:

Feed oil samples which are used as mixed feed raw material were taken from six different feed factories in March, May and July. All factories make production in Konya, Turkey and all of the samples were which taken are crude soybean oil. Some physical and chemical analysis, free radical scavenger effect and total phenol content were determined on these oil samples. Moisture content was found between 0.10-22.23 %, saponification number was determined 143.13 to 167.93 KOH/kg, free fatty acidity was varied 0.73 to 35.00 % , peroxide value was found between 1.53 and 28.43 meq/kg , unsaponifiable matter was determined from 0.40 to 17.10 % , viscosity was found between 34.30 and 625.67 mPas, sediment amount was determined between 0.60-18.16 % , free radical scavenger effect was varied 20.7 to 43.04 % inhibition of the extract and total phenol content was found between 1.20 and 2.69 mg/L extract. Different results were found between months and factories.

Keywords: crude soybean oil, feed oils, mixed feed, Konya

Procedia PDF Downloads 299

Authors: Xu Tao, Yilun Xu, Dingwei Xiang, Yaofei Sun

Abstract:

The practice of urban planning and construction based on the concept of the “low carbon eco-city” has been universally accepted by the academic community in response to urban issues such as population, resources, environment, and social development. Based on this, the current article first analyzes the concepts of low carbon eco-city, then builds a complex adaptive system (CAS) theory based on Chinese traditional philosophical thinking, and analyzes the adaptive relationship between material and non-material elements. A three-dimensional evaluation model of natural ecology, economic low carbon, and social harmony was constructed. Finally, the construction of a low carbon eco-city index system in Hexi Newtown of Nanjing was used as an example to verify the effectiveness of the research results; this paradigm provides a new way to achieve a low carbon eco-city system.

Keywords: complex adaptive system, low carbon ecology, index system, model

Procedia PDF Downloads 140

Authors: C. D’Urso, L. Frusteri, M. Samperi, G. Leonardi

Abstract:

Solid metal halides are used as active cathode ingredients in the case of Na-NiCl2 batteries that require a fused secondary electrolyte, sodium tetrachloraluminate (NaAlCl4), to facilitate the movement of the Na+ ion into the cathode. The sodium-nickel chloride (Na - NiCl2) battery has been extensively investigated as a promising system for large-scale energy storage applications. The growth of Ni and NaCl particles in the cathodes is one of the most important factors that degrade the performance of the Na-NiCl2 battery. The larger the particles of active ingredients contained in the cathode, the smaller the active surface available for the electrochemical reaction. Therefore, the growth of Ni and NaCl particles can lead to an increase in cell polarization resulting from the reduced active area. A higher current density, a higher state of charge (SOC) at the end of the charge (EOC) and a lower Ni / NaCl ratio are the main parameters that result in the rapid growth of Ni particles. In light of these problems, cathode and chemistry Nano-materials with recognized and well-documented electrochemical functions have been studied and manufactured to simultaneously improve battery performance and develop less expensive and more performing, sustainable and environmentally friendly materials. Starting from the well-known cathodic material (Na-NiCl2), the new electrolytic materials have been prepared on the replacement of nickel with iron (10-90%substitution of Nichel with Iron), to obtain a new material with potential advantages compared to current battery technologies; for example,, (1) lower cost of cathode material compared to state of the art as well as (2) choices of cheaper materials (stainless steels could be used for cell components, including cathode current collectors and cell housings). The study on the particle size of the cathode and the physicochemical characterization of the cathode was carried out in the test cell using, where possible, the GITT method (galvanostatic technique of intermittent titration). Furthermore, the impact of temperature on the different cathode compositions of the positive electrode was studied. Especially the optimum operating temperature is an important parameter of the active material.

Keywords: critical raw materials, energy storage, sodium metal halide, battery

Procedia PDF Downloads 90

Authors: Yaseri Dahlia Apritasari

Abstract:

Visual comfort is important for the building occupants to need. Visual comfort can be fulfilled through natural lighting (daylighting) and artificial lighting. One strategy to optimize natural lighting can be achieved through the facade second skin design. This strategy can reduce glare, and fulfill visual comfort need. However, the design strategy cannot achieve light intensity for visual comfort. Because the materials, design and opening percentage of the facade of second skin blocked sunlight. This paper discusses aluminum material for the facade second skin design that can fulfill the optimal visual comfort with the case studies Multi Media Tower building. The methodology of the research is combination quantitative and qualitative through field study observed, lighting measurement and visual comfort questionnaire. Then it used too simulation modeling (DIALUX 4.13, 2016) for three facades second skin design model. Through following steps; (1) Measuring visual comfort factor: light intensity indoor and outdoor; (2) Taking visual comfort data from building occupants; (3) Making models with different facade second skin design; (3) Simulating and analyzing the light intensity value for each models that meet occupants visual comfort standard: 350 lux (Indonesia National Standard, 2010). The result shows that optimization of aluminum material for the facade second skin design can meet optimal visual comfort for building occupants. The result can give recommendation aluminum opening percentage of the facade second skin can meet optimal visual comfort for building occupants.

Keywords: aluminium material, Facade, second skin, visual comfort

Procedia PDF Downloads 342

Authors: Kien-Trinh Thi Bui, Cuong Manh Nguyen

Abstract:

In order to simulate and reproduce the operational characteristics of a dam visually, it is necessary to capture the displacement at different measurement points and analyze the observed movement data promptly to forecast the dam safety. The accuracy of forecasts is further improved by applying machine learning methods to data analysis progress. In this study, the horizontal displacement monitoring data of the Ialy hydroelectric dam was applied to machine learning algorithms: Gaussian processes, multi-layer perceptron neural networks, and the M5-rules algorithm for modelling and forecasting of horizontal displacement of the Ialy hydropower dam (Vietnam), respectively, for analysing. The database which used in this research was built by collecting time series of data from 2006 to 2021 and divided into two parts: training dataset and validating dataset. The final results show all three algorithms have high performance for both training and model validation, but the MLPs is the best model. The usability of them are further investigated by comparison with a benchmark models created by multi-linear regression. The result show the performance which obtained from all the GP model, the MLPs model and the M5-Rules model are much better, therefore these three models should be used to analyze and predict the horizontal displacement of the dam.

Keywords: Gaussian processes, horizontal displacement, hydropower dam, Ialy dam, M5-Rules, multi-layer perception neural networks

Procedia PDF Downloads 187

Authors: Atef M. Ghaleb, Mohamed Z. Ramadan, Khalid Saad Aljaloud

Abstract:

The aim of this study is to assesses the lifting capabilities of persons experiencing hypoxia. It also examines the behavior of the physiological response induced through the lifting process related to changing in the hypoxia and lifting frequency variables. For this purpose, the study performed two consecutive tests by using; (1) training and acclimatization; and (2) an actual collection of data. A total of 10 male students from King Saud University, Kingdom of Saudi Arabia, were recruited in the study. A two-way repeated measures design, with two independent variables (ambient oxygen (15%, 18% and 21%)) and lifting frequency (1 lift/min and 4 lifts/min) and four dependent variables i.e., maximum acceptable weight of lift (MAWL), Electromyography (EMG) of four muscle groups (anterior deltoid, trapezius, biceps brachii, and erector spinae), rating of perceived exertion (RPE), and rating of oxygen feeling (ROF) were used in this study. The results show that lifting frequency has significantly impacted the MAWL and muscles’ activities. The oxygen content had a significant effect on the RPE and ROE. The study has revealed that acclimatization and training sessions significantly reduce the effect of the hypoxia on the human physiological parameters during the manual materials handling tasks.

Keywords: lifting capabilities, muscle activities, oxygen content, perceived exertion

Procedia PDF Downloads 121

Authors: Arazan Jane V., Badiang, Ronesito Jr. R., Clavesillas Cristine Joy H., Belleza Saramie S.

Abstract:

This study examined the coaching style among the PE Teachers in terms of Autonomy, Supportive style, and Controlling Style. On the other hand, gives opportunities to an athlete to be independent, task-oriented, and acknowledge their feelings and perspective of each individual. A controlling coaching style is also portrayed by the rises and falls over an athlete's training development; when this variance is identified, it might harm training. The selection of the respondents of the study will use a random sample of High School PE teachers of the Division of Davao del Norte with a total of 78 High School PE teachers, which can be broken down into 70 High School PE Teachers for Quantitative data for the survey questionnaire and 8 PE Teachers for Qualitative data (IDI). In the quantitative phase, a set of survey questionnaires will be used to gather data from the participants—the extent of the Implementation Questionnaire. The tool will be a researcher-made questionnaire based on the Coaching Styles of selected High School PE teachers of Davao Del Norte. In the qualitative phase, an interview guide questionnaire will be used. Focus group discussions will be conducted to determine themes and patterns or participants' experiences and insights. The researchers conclude that the degree of coaching style among PE Teachers from the Division of Davao del Norte is high, as seen by the findings of this study, and that coaching style among these teachers is highly noticeable.

Keywords: supportive autonomy style, controlling style, live experiences, exemplified

Procedia PDF Downloads 87

Authors: Eiman Kattan

Abstract:

This study aims to evaluate the impact of classifying labelled remote sensing images conventional neural network (CNN) architecture, i.e., AlexNet on different land cover scenarios based on two remotely sensed datasets from different point of views such as the computational time and performance. Thus, a set of experiments were conducted to specify the effectiveness of the selected convolutional neural network using two implementing approaches, named fully trained and fine-tuned. For validation purposes, two remote sensing datasets, AID, and RSSCN7 which are publicly available and have different land covers features were used in the experiments. These datasets have a wide diversity of input data, number of classes, amount of labelled data, and texture patterns. A specifically designed interactive deep learning GPU training platform for image classification (Nvidia Digit) was employed in the experiments. It has shown efficiency in training, validation, and testing. As a result, the fully trained approach has achieved a trivial result for both of the two data sets, AID and RSSCN7 by 73.346% and 71.857% within 24 min, 1 sec and 8 min, 3 sec respectively. However, dramatic improvement of the classification performance using the fine-tuning approach has been recorded by 92.5% and 91% respectively within 24min, 44 secs and 8 min 41 sec respectively. The represented conclusion opens the opportunities for a better classification performance in various applications such as agriculture and crops remote sensing.

Keywords: conventional neural network, remote sensing, land cover, land use

Procedia PDF Downloads 349

Authors: B. R. Campomanes-Alvarez, P. Quiros, B. Fernandez

Abstract:

Automatic Speech Recognition (ASR) is a machine-based process of decoding and transcribing oral speech. A typical ASR system receives acoustic input from a speaker or an audio file, analyzes it using algorithms, and produces an output in the form of a text. Some speech recognition systems use Hidden Markov Models (HMMs) to deal with the temporal variability of speech and Gaussian Mixture Models (GMMs) to determine how well each state of each HMM fits a short window of frames of coefficients that represents the acoustic input. Another way to evaluate the fit is to use a feed-forward neural network that takes several frames of coefficients as input and produces posterior probabilities over HMM states as output. Deep neural networks (DNNs) that have many hidden layers and are trained using new methods have been shown to outperform GMMs on a variety of speech recognition systems. Acoustic models for state-of-the-art ASR systems are usually training on massive amounts of data. However, audio files with their corresponding transcriptions can be difficult to obtain, especially in the Spanish language. Hence, in the case of these low-resource scenarios, building an ASR model is considered as a complex task due to the lack of labeled data, resulting in an under-trained system. Semi-supervised learning approaches arise as necessary tasks given the high cost of transcribing audio data. The main goal of this proposal is to develop a procedure based on acoustic semi-supervised learning for Spanish ASR systems by using DNNs. This semi-supervised learning approach consists of: (a) Training a seed ASR model with a DNN using a set of audios and their respective transcriptions. A DNN with a one-hidden-layer network was initialized; increasing the number of hidden layers in training, to a five. A refinement, which consisted of the weight matrix plus bias term and a Stochastic Gradient Descent (SGD) training were also performed. The objective function was the cross-entropy criterion. (b) Decoding/testing a set of unlabeled data with the obtained seed model. (c) Selecting a suitable subset of the validated data to retrain the seed model, thereby improving its performance on the target test set. To choose the most precise transcriptions, three confidence scores or metrics, regarding the lattice concept (based on the graph cost, the acoustic cost and a combination of both), was performed as selection technique. The performance of the ASR system will be calculated by means of the Word Error Rate (WER). The test dataset was renewed in order to extract the new transcriptions added to the training dataset. Some experiments were carried out in order to select the best ASR results. A comparison between a GMM-based model without retraining and the DNN proposed system was also made under the same conditions. Results showed that the semi-supervised ASR-model based on DNNs outperformed the GMM-model, in terms of WER, in all tested cases. The best result obtained an improvement of 6% relative WER. Hence, these promising results suggest that the proposed technique could be suitable for building ASR models in low-resource environments.

Keywords: automatic speech recognition, deep neural networks, machine learning, semi-supervised learning

Procedia PDF Downloads 327

Authors: Kenneth O. Otasowie, Matthew Ikuabe, Clinton Aigbavboa, Ayodeji Oke

Abstract:

Subcontracting has become a fundamental feature in the construction industry, particularly as most projects in South Africa (SA) are executed by subcontractors. However, the sector in SA contributes to the high level of occupational hazards and injuries recorded, despite Health and Safety (H&S) regulations being enforced in the industry. Hence, this study aims to evaluate the barriers to health and safety practices by subcontractors in SA Construction Industry. A survey design was adopted. A total number of one hundred and forty-four (144) questionnaires were administered to quantity surveyors, construction managers, construction project managers, project managers, architects, and civil and structural engineers, who are owners or work in small and medium enterprises in Guateng Province, SA and eighty-three (83) were returned and found suitable for analysis. Collected data were analysed using percentage, mean item score, standard deviation, and one-sample t-test. The findings show that lack of skilled workers, lack of safety training, and insufficient safety awareness are the most significant barriers to health and safety practices in SA Construction Industry. Therefore, the study recommends the improvement in skills of staff and adequate training for the safe execution of work be provided to all employees and supervisors in these subcontracting firms. These will mitigate the rate of accident occurrence on construction sites.

Keywords: barriers, health and safety, subcontractors, South Africa

Procedia PDF Downloads 86

Authors: Choi Woo-Seok, Kim Eun-Sup, Ha Eun-Ryong

Abstract:

Converter slag is used as a low-value product like a construction fill material and soil stabilizer unlike electric furnace slag and blast furnace slag. This study is fundamental research for utilizing the converter slag as the cement admixture. Magnetic separation was conducted for quality improvement of the converter slag, and it was classified according to into 3 types; SA: pure slag, SB: separated slag, SC: remained slag after separating. In XRF result, SB slag was Fe₂CO₃ ratio was higher, and CaO ratio was lower than SA. SC slag was Fe₂CO₃ ratio was lower, and CaO ratio was higher than SA. In compressive strength test for soil cement using SA, SB, SC as the cement admixture, SC slag was more effective in terms of 28days compressive strength than SA, SB slag. In this result, it is considered that the remained material (SC) after magnetic separation is available as the cement admixture.

Keywords: converter slag, magnetic separation, cement admixture, compressive strength

Procedia PDF Downloads 766

Authors: George Onomah

Abstract:

Background: The integration of information communication technology (ICT) in Mathematics education faces notable challenges, which this study aimed to dissect and understand. Objectives: The primary goal was to assess the internal and external factors affecting the adoption of ICT by in-service Mathematics teachers. Internal factors examined included teachers' pedagogical beliefs, prior teaching experience, attitudes towards computers, and proficiency with technology. External factors included the availability of technological resources, the level of ICT training received, the sufficiency of allocated time for technology use, and the institutional culture within educational environments. Methods: A descriptive survey design was employed to methodically investigate these factors. Data collection was carried out using a five-point Likert scale questionnaire, administered to a carefully selected sample of 100 in-service Mathematics teachers through a combination of purposive and convenience sampling techniques. Findings: Results from multiple regression analysis revealed a significant underutilization of ICT in Mathematics teaching, highlighting a pronounced deficiency in current classroom practices. Recommendations: The findings suggest an urgent need for educational department heads to implement regular and comprehensive ICT training programs aimed at enhancing teachers' technological capabilities and promoting the integration of ICT in Mathematics teaching methodologies.

Keywords: ICT, Mathematics, integration, barriers

Procedia PDF Downloads 30

Authors: Maryam Fallahpoor, Biswajeet Pradhan

Abstract:

Background: Artificial intelligence (AI) serves as a valuable tool in mitigating the scarcity of human resources required for the evaluation and categorization of vast quantities of medical imaging data. When AI operates with optimal precision, it minimizes the demand for human interpretations and, thereby, reduces the burden on radiologists. Among various AI approaches, deep learning (DL) stands out as it obviates the need for feature extraction, a process that can impede classification, especially with intricate datasets. The advent of DL models has ushered in a new era in medical imaging, particularly in the context of COVID-19 detection. Traditional 2D imaging techniques exhibit limitations when applied to volumetric data, such as Computed Tomography (CT) scans. Medical images predominantly exist in one of two formats: neuroimaging informatics technology initiative (NIfTI) and digital imaging and communications in medicine (DICOM). Purpose: This study aims to employ DL for the classification of COVID-19-infected pulmonary patients and normal cases based on 3D CT scans while investigating the impact of image format. Material and Methods: The dataset used for model training and testing consisted of 1245 patients from IranMehr Hospital. All scans shared a matrix size of 512 × 512, although they exhibited varying slice numbers. Consequently, after loading the DICOM CT scans, image resampling and interpolation were performed to standardize the slice count. All images underwent cropping and resampling, resulting in uniform dimensions of 128 × 128 × 60. Resolution uniformity was achieved through resampling to 1 mm × 1 mm × 1 mm, and image intensities were confined to the range of (−1000, 400) Hounsfield units (HU). For classification purposes, positive pulmonary COVID-19 involvement was designated as 1, while normal images were assigned a value of 0. Subsequently, a U-net-based lung segmentation module was applied to obtain 3D segmented lung regions. The pre-processing stage included normalization, zero-centering, and shuffling. Four distinct 3D CNN models (ResNet152, ResNet50, DensNet169, and DensNet201) were employed in this study. Results: The findings revealed that the segmentation technique yielded superior results for DICOM images, which could be attributed to the potential loss of information during the conversion of original DICOM images to NIFTI format. Notably, ResNet152 and ResNet50 exhibited the highest accuracy at 90.0%, and the same models achieved the best F1 score at 87%. ResNet152 also secured the highest Area under the Curve (AUC) at 0.932. Regarding sensitivity and specificity, DensNet201 achieved the highest values at 93% and 96%, respectively. Conclusion: This study underscores the capacity of deep learning to classify COVID-19 pulmonary involvement using real 3D hospital data. The results underscore the significance of employing DICOM format 3D CT images alongside appropriate pre-processing techniques when training DL models for COVID-19 detection. This approach enhances the accuracy and reliability of diagnostic systems for COVID-19 detection.

Keywords: deep learning, COVID-19 detection, NIFTI format, DICOM format

Procedia PDF Downloads 65

Authors: Nikhil Jain, Yang Xu, Bin Yu

Abstract:

Hexagonal boron nitride (h-BN) has been used as a substrate and gate dielectric for graphene field effect transistors (GFETs). Using a graphene/h-BN/TiN (channel/dielectric/gate) stack, key material properties of h-BN were investigated i.e. dielectric strength and tunneling behavior. Work function difference between graphene and TiN results in spontaneous p-doping of graphene through a multi-layer h-BN flake. However, at high levels of current stress, n-doping of graphene is observed, possibly due to the charge transfer across the thin h-BN multi layer. Neither Direct Tunneling (DT) nor Fowler-Nordheim Tunneling (FNT) was observed in TiN/h-BN/Au hetero structures with h-BN showing two distinct volatile conduction states before breakdown. Hexagonal boron nitride emerges as a material of choice for gate dielectrics in GFETs because of robust dielectric properties and high tunneling barrier.

Keywords: graphene, transistors, conduction, hexagonal boron nitride, dielectric strength, tunneling

Procedia PDF Downloads 344

Authors: Maria Jose Mendoza Gordillo

Abstract:

Introduction: Research regarding breastfeeding is devoted to how essential breastfeeding is to guarantee wellbeing for the mother and the baby from a medical standpoint relegating the cultural, material and social barriers for breastfeeding. Consequently, worldwide breastfeeding rates are low, and Ecuador is not the exception, especially among working mothers. Worldwide, health care providers have low rates of breastfeeding due to several barriers to lactation, such as the work schedule, a lack of private places for pumping while at work, and negative emotions. Goals and Methods: This study aimed to explore how do Ecuadorian women embrace their identities as nutritionists and mothers within their breastfeeding experience. The primary data come from 20 synchronous semi-structured interviews, which follow a topic guide. The interviews were recorded and transcribed verbatim. The data analysis followed the Phronetic Iterative Approach. Results: Women shifted the preconceived idea of the ideal breastfeeding that came from the medicalized discourse of breastfeeding, and that was constructed in their training as nutritionists. Although these women believe that breast milk and breastfeeding is the best way to feed a baby, the internalized ideal of breastfeeding shifted through the experience of motherhood. When these women developed their identity as mothers, they understood that the ideal breastfeeding is different from the medicalized discourse. Although they have that clash between the ideal and the external reality, they continued breastfeeding their babies and those experiences made them improve their professional practice. Conclusions: The narratives that women shared illustrate how complex it was to manage the different roles and identities that they wanted to fulfill to keep their identity of a good mother who breastfeeds her baby and, at the same time, a good healthcare provider identity. The process of breastfeeding for this group of women who are mothers and healthcare professionals appears to be a unique relational and identity negotiation process.

Keywords: breastfeeding, identity, nutritionist, qualitative

Procedia PDF Downloads 161

Authors: Nasiru Aliyu, Glyn Atkinson, Nick Stannard

Abstract:

With increasing demand for electric motors used in nearly all sectors of our day to day activities, which range from the motor that rotates the washing machine and dishwasher to the tens of thousands of motors used in domestic appliance. The number of applications for soft magnetic composites (SMC) material is growing significantly. This paper presents the development of a compact single sided concentrated winding axial flux PM motor using soft magnetic composite as core for reducing core losses and cost. The effects of changing the flux carrying component to pressed SMC parts are investigated based on a comprehensive understanding of the properties of the material. A 3-D finite-element analysis is performed for accurate parameter calculation. To validate the simulation, a new static test measurement was fully conducted on a prototype motor and agree with the theoretical calculations and old measured static test.

Keywords: SMC, compact development, axial field motor, 3DFA

Procedia PDF Downloads 314

Authors: Luristya Nur Mahfut, Nada Mawarda Rilek, Ameiga Cautsarina Putri, Mujaroh Khotimah

Abstract:

The use of bioetanol from lignocellulosic material has begone to be developed. In Indonesia the most abundant lignocellulosic material is stem of palm which contain 32.22% of cellulose. Indonesia produces approximatelly 300.375.000 tons of stem of palm each year. To produce bioetanol from lignocellulosic material, the first process is pretreatment. But, until now the method of lignocellulosic pretretament is uneffective. This is related to the particle size and the method of pretreatment of less than optimal so that led to an overhaul of the lignin insufficient, consequently increased levels of cellulose was not significant resulting in low yield of bioetanol. To solve the problem, this research was implemented by using the process of pretreatment method ultasonifikasi in order to produce higher pulp with nano-sized particles that will obtain higher of yield ethanol from stem of palm. Research methods used in this research is the RAK that is composed of one factor which is the frequency ultrasonic waves with three varians, they are 30 kHz, 40 kHz, 50 kHz, and use constant variable is concentration of NaOH. The analysis conducted in this research is the influence of the frequency of the wave to increase levels of cellulose and change size on the scale of nanometers on pretreatment process by using the PSA methods (Particle Size Analyzer), and a Cheason. For the analysis of the results, data, and best treatment using ANOVA and test BNT with confidence interval 5%. The best treatment was obtained by combination X3 (frequency of sonication 50 kHz) and lignin (19,6%) cellulose (59,49%) and hemicellulose (11,8%) with particle size 385,2nm (18,8%).

Keywords: bioethanol, pretreatment, stem of palm, cellulosa

Procedia PDF Downloads 315

Authors: Cherief Houria, Fouka Mourad

Abstract:

In this work, the simulation of the radiation attenuation is carried out in a photon detector consisting of different common shielding material using a Monte Carlo program called PTM. The aim of the study is to investigate the effect of atomic weight and the thickness of shielding materials on the gamma radiation attenuation ability. The linear attenuation coefficients of Aluminum (Al), Iron (Fe), and lead (Pb) elements were evaluated at photons energy of 661:7KeV that are considered to be emitted from a standard radioactive point source Cs 137. The experimental measurements have been performed for three materials to obtain these linear attenuation coefficients, using a Gamma NaI(Tl) scintillation detector. Our results have been compared with the simulation results of the linear attenuation coefficient using the XCOM database and Geant4 codes and reveal that they are well agreed with both simulation data.

Keywords: gamma photon, Monte Carlo program, radiation attenuation, shielding material, the linear attenuation coefficient

Procedia PDF Downloads 188

Authors: Fereshteh Zarei, Mahdi Kohandel

Abstract:

The aim of this study was investigate and compare plyometric and vibration exercises on muscle explosive power in non-athlete female students. For this purpose, 45 female students from non-athletes selected target then divided in to the three groups, two experimental and one control groups. From all groups were getting pre-tested. Experimental A did whole-body vibration exercises involved standing on one of machine vibration with frequency 30 Hz, amplitude 10 mm and in 5 different postures. Training for each position was 40 seconds with 60 seconds rest between it, and each season 5 seconds was added to duration of each body condition, until time up to 2 minutes for each postures. Exercises were done three times a week for 2 month. Experimental group B did plyometric exercises that include jumping, such as horizontal, vertical, and skipping .They included 10 times repeat for 5 set in each season. Intensity with increasing repetitions and sets were added. At this time, asked from control group that keep a daily activity and avoided strength training, explosive power and. after do exercises by groups we measured factors again. One-way analysis of variance and paired t statistical methods were used to analyze the data. There was significant difference in the amount of explosive power between the control and vibration groups (p=0/048) there was significant difference between the control and plyometric groups (019/0 = p). But between vibration and plyometric groups didn't observe significant difference in the amount of explosive power.

Keywords: vibration, plyometric, exercises, explosive power, non-athlete

Procedia PDF Downloads 436