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Authors: Julia Wimmers-Klick

Abstract:

At the Canadian University of British Columbia's Faculty of Medicine, anatomy has traditionally been taught through a combination of lectures and dissection labs in the first two years, with radiology taught separately through lectures and online modules. However, this separation may leave students underprepared for medical practice, as medical imaging is essential for diagnosing anatomical and pathological conditions. To address this, a pilot project was initiated aimed at integrating radiological imaging into anatomy dissection labs from day one of medical school. The incorporated radiological images correlated with the current dissection areas. Additional stations were added within the lab, tailored to the specific content being covered. These stations focused on bones, and quiz questions, along with light-box exercises using radiographs, CT scans, and MRIs provided by the radiology department. The images used were free of pathologies. Examples of these will be presented in the poster. Feedback from short interviews with students and instructors has been positive, particularly among second-year students who appreciated the integration compared to their first-year experience. This low-budget approach was easy to implement but faced challenges, as lab instructors were not radiologists and occasionally struggled to answer students' questions. Instructors expressed a desire for basic training or a refresher course in radiology image reading, particularly focused on identifying healthy landmarks. Overall, all participants agreed that integrating radiology with anatomy reinforces learning during dissection, enhancing students' understanding and preparation for clinical practice.

Keywords: quality improvement, radiology education, anatomy education, integration

Procedia PDF Downloads 11

Authors: Jamunarani Appalasamy, Tha Kyi Kyi, Quek Kia Fatt, Joyce Pauline Joseph, Anuar Zaini M. Zain

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Background: The Health Belief Theory had always been associated with chronic disease management. Various health behaviour concepts and perception branching from this Health Belief Theory had involved with medication understanding, use, and self-efficacy which directly link to medication adherence. In a previous quantitative and qualitative study, stroke patients in Malaysia were found to be strongly believing information obtained by various sources such as the internet and social communication. This action leads to lower perception of their stroke preventative medication benefit which in long-term creates non-adherence. Hence, this study intends to pilot an intervention which uses audio-visual concept incorporated with mHealth service to enhance learning and self-reflection among stroke patients to manage their disease. Methods/Design: Twenty patients will be allocated to a proposed intervention whereas another twenty patients are allocated to the usual treatment. The intervention involves a series of developed audio-visual videos sent via mobile phone which later await for responses and feedback from the receiver (patient) via SMS or recorded calls. The primary outcome would be the medication understanding, use and self-efficacy measured over two months pre and post intervention. Secondary outcome is measured from changes of blood parameters and other self-reported questionnaires. Discussion: This study shall also assess uptake/attrition, feasibility, and acceptability of this intervention. Trial Registration: NMRR-15-851-24737 (IIR)

Keywords: health belief, medication understanding, medication use, self-efficacy

Procedia PDF Downloads 220

Authors: Hayder H. Kareem, Shunqi Pan

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Groundwater is a vital water resource in many areas in the world, particularly in the Middle-East region where the water resources become scarce and depleting. Sustainable management and planning of the groundwater resources become essential and urgent given the impact of the global climate change. In the recent years, numerical models have been widely used to predict the flow pattern and assess the water resources security, as well as the groundwater quality affected by the contaminants transported. In this study, MODFLOW is used to study the current status of groundwater resources and the risk of water resource security in the region centred at Al-Najaf City, which is located in the mid-west of Iraq and adjacent to the Euphrates River. In this study, a conceptual model is built using the geologic and hydrogeologic collected for the region, together with the Digital Elevation Model (DEM) data obtained from the "Global Land Cover Facility" (GLCF) and "United State Geological Survey" (USGS) for the study area. The computer model is also implemented with the distributions of 69 wells in the area with the steady pro-defined hydraulic head along its boundaries. The model is then applied with the recharge rate (from precipitation) of 7.55 mm/year, given from the analysis of the field data in the study area for the period of 1980-2014. The hydraulic conductivity from the measurements at the locations of wells is interpolated for model use. The model is calibrated with the measured hydraulic heads at the locations of 50 of 69 wells in the domain and results show a good agreement. The standard-error-of-estimate (SEE), root-mean-square errors (RMSE), Normalized RMSE and correlation coefficient are 0.297 m, 2.087 m, 6.899% and 0.971 respectively. Sensitivity analysis is also carried out, and it is found that the model is sensitive to recharge, particularly when the rate is greater than (15mm/year). Hydraulic conductivity is found to be another parameter which can affect the results significantly, therefore it requires high quality field data. The results show that there is a general flow pattern from the west to east of the study area, which agrees well with the observations and the gradient of the ground surface. It is found that with the current operational pumping rates of the wells in the area, a dry area is resulted in Al-Najaf City due to the large quantity of groundwater withdrawn. The computed water balance with the current operational pumping quantity shows that the Euphrates River supplies water into the groundwater of approximately 11759 m3/day, instead of gaining water of 11178 m3/day from the groundwater if no pumping from the wells. It is expected that the results obtained from the study can provide important information for the sustainable and effective planning and management of the regional groundwater resources for Al-Najaf City.

Keywords: Al-Najaf city, conceptual modelling, groundwater, unconfined aquifer, visual MODFLOW

Procedia PDF Downloads 213

Authors: Rosa S. Wong, Keith T. S. Tung, Frederick K. Ho, Winnie W. Y. Tso, King-wa Fu, Nirmala Rao, Patrick Ip

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As technology advances, exposures in early childhood are no longer confined to stimulations in the surrounding physical environments. Children nowadays are also subject to influences from the digital world. In particular, early access to game consoles can cause risks to child development, especially when the game is not developmentally appropriate for young children. Overstimulation is possible and could impair brain development. On the other hand, recreational parent-child activities, including outdoor activities and visits to museums, require child interaction with parents, which is beneficial for developing adaptive emotion regulation and social skills. Given the differences between these two types of exposures, this study investigated and compared the independent effects of early exposure to a game console and early play-based parent-child activities on children’s long-term psychosocial outcomes. This study used data from a subset of children (n=304, 142 male and 162 female) in the longitudinal cohort study, which studied the long-term impact of family socioeconomic status on child development. In 2012/13, we recruited a group of children at Kindergarten 3 (K3) randomly from Hong Kong local kindergartens and collected data regarding their duration of exposure to game console and recreational parent-child activities at that time. In 2018/19, we re-surveyed the parents of these children who were matriculated as Form 1 (F1) students (ages ranging from 11 to 13 years) in secondary schools and asked the parents to rate their children’s psychosocial problems in F1. Linear regressions were conducted to examine the associations between early exposures and adolescent psychosocial problems with and without adjustment for child gender and K3 family socioeconomic status. On average, K3 children spent about 42 minutes on a game console every day and had 2-3 recreational activities with their parents every week. Univariate analyses showed that more time spent on game consoles at K3 was associated with more psychosocial difficulties in F1 particularly more externalizing problems. The effect of early exposure to game console on externalizing behavior remained significant (B=0.59, 95%CI: 0.15 to 1.03, p=0.009) after adjusting for recreational parent-child activities and child gender. For recreational parent-child activities at K3, its effect on overall psychosocial difficulties became insignificant after adjusting for early exposure to game consoles and child gender. However, it was found to have significant protective effect on externalizing problems (B=-0.65, 95%CI: -1.23 to -0.07, p=0.028) even after adjusting for the confounders. Early exposure to game consoles has negative impact on children’s psychosocial health, whereas play-based parent-child activities can foster positive psychosocial outcomes. More efforts should be directed to propagate the risks and benefits of these activities and urge the parents and caregivers to replace child-alone screen time with parent-child play time in daily routine.

Keywords: early childhood, electronic device, parenting, psychosocial wellbeing

Procedia PDF Downloads 167

Authors: Zhu Weimin, Allegorico Carmine, Ruggiero Gionata

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During decades of Baker Hughes (BH) iCenter experience, it is demonstrated that in addition to conventional insights on equipment steady operation conditions, insights on transient conditions can add significant and exclusive value for anomaly detection, downtime saving, and predictive maintenance. Our work shows examples from the BH iCenter experience to introduce the advantages and features of using transient condition analytics: (i) Operation under critical engine conditions: e.g., high level or high change rate of temperature, pressure, flow, vibration, etc., that would not be reachable in normal operation, (ii) Management of dedicated sub-systems or components, many of which are often bottlenecks for reliability and maintenance, (iii) Indirect detection of anomalies in the absence of instrumentation, (iv) Repetitive sequences: if data is properly processed, the engineering features of transients provide not only anomaly detection but also problem characterization and prognostic indicators for predictive maintenance, (v) Engine variables accounting for fatigue analysis. iCenter has been developing and deploying a series of analytics based on transient conditions. They are contributing to exclusive value adding in the following areas: (i) Reliability improvement, (ii) Startup reliability improvement, (iii) Predictive maintenance, (iv) Repair/overhaul cost down. Illustrative examples for each of the above areas are presented in our study, focusing on challenges and adopted techniques ranging from purely statistical approaches to the implementation of machine learning algorithms. The obtained results demonstrate how the value is obtained using transient condition analytics in the BH iCenter experience.

Keywords: analytics, diagnostics, monitoring, turbomachinery

Procedia PDF Downloads 74

Authors: Mairaj Salim, Asma Zaheer

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Oman has accomplished as much or more than its fellow Gulf monarchies, despite starting from scratch considerably later, having less oil income to utilize, dealing with a larger and more rugged geography, and resolving a bitter civil war along the way. Of course, Oman's progress in the past 30-plus years has not been without problems and missteps, but the balance is squarely on the positive side of the ledger. Oil has been the driving force of the Omani economy since Oman began commercial production in 1967. The oil industry supports the country’s high standard of living and is primarily responsible for its modern and expansive infrastructure, including electrical utilities, telephone services, roads, public education and medical services. In addition to extensive oil reserves, Oman also has substantial natural gas reserves, which are expected to play a leading role in the Omani economy in the Twenty-first Century. To reduce the country’s dependence on oil revenues, the government is restructuring the economy by directing investment to non-oil activities. Since the 21st century IT has changed the performing tasks. To manage the affairs for the benefits of organizations and economy, the Omani government has adopted E-Business technologies for the development. E-Business is important because it allows • Transformation of old economy relationships (vertical/linear relationships) to new economy relationships characterized by end-to-end relationship management solutions (integrated or extended relationships) • Facilitation and organization of networks, small firms depend on ‘partner’ firms for supplies and product distribution to meet customer demands • SMEs to outsource back-end process or cost centers enabling the SME to focus on their core competence • ICT to connect, manage and integrate processes internally and externally • SMEs to join networks and enter new markets, through shortened supply chains to increase market share, customers and suppliers • SMEs to take up the benefits of e-business to reduce costs, increase customer satisfaction, improve client referral and attract quality partners • New business models of collaboration for SMEs to increase their skill base • SMEs to enter virtual trading arena and increase their market reach A national strategy for the advancement of information and communication technology (ICT) has been worked out, mainly to introduce e-government, e-commerce, and a digital society. An information technology complex KOM (Knowledge Oasis Muscat) had been established, consisting of section for information technology, incubator services, a shopping center of technology software and hardware, ICT colleges, E-Government services and other relevant services. So, all these efforts play a vital role in the development of Oman economy.

Keywords: ICT, ITA, CRM, SCM, ERP, KOM, SMEs, e-commerce and e-business

Procedia PDF Downloads 251

Authors: Anastasios Papathanasiou, George Liontos, Athanasios Katsouras, Vasiliki Liagkou, Euripides Glavas

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Email remains a crucial communication tool due to its efficiency, accessibility and cost-effectiveness, enabling rapid information exchange across global networks. However, the global adoption of email has also made it a prime target for cyber threats, including phishing, malware and Business Email Compromise (BEC) attacks, which exploit its integral role in personal and professional realms in order to perform fraud and data breaches. To combat these threats, this research advocates for a multi-layered defense strategy incorporating advanced technological tools such as anti-spam and anti-malware software, machine learning algorithms and authentication protocols. Moreover, we developed an artificial intelligence model specifically designed to analyze email headers and assess their security status. This AI-driven model examines various components of email headers, such as "From" addresses, ‘Received’ paths and the integrity of SPF, DKIM and DMARC records. Upon analysis, it generates comprehensive reports that indicate whether an email is likely to be malicious or benign. This capability empowers users to identify potentially dangerous emails promptly, enhancing their ability to avoid phishing attacks, malware infections and other cyber threats.

Keywords: email security, artificial intelligence, header analysis, threat detection, phishing, DMARC, DKIM, SPF, ai model

Procedia PDF Downloads 60

Authors: Kothuri Sriraman, Mattupalli Komal Teja

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In this paper, a novel algorithm is proposed for the recognition of hulls in a hand written images that might be irregular or digit or character shape. Identification of objects and internal objects is quite difficult to extract, when the structure of the image is having bulk of clusters. The estimation results are easily obtained while going through identifying the sub-regional objects by using the SASK algorithm. Focusing mainly to recognize the number of internal objects exist in a given image, so as it is shadow-free and error-free. The hard clustering and density clustering process of obtained image rough set is used to recognize the differentiated internal objects, if any. In order to find out the internal hull regions it involves three steps pre-processing, Boundary Extraction and finally, apply the Hull Detection system. By detecting the sub-regional hulls it can increase the machine learning capability in detection of characters and it can also be extend in order to get the hull recognition even in irregular shape objects like wise black holes in the space exploration with their intensities. Layered hulls are those having the structured layers inside while it is useful in the Military Services and Traffic to identify the number of vehicles or persons. This proposed SASK algorithm is helpful in making of that kind of identifying the regions and can useful in undergo for the decision process (to clear the traffic, to identify the number of persons in the opponent’s in the war).

Keywords: chain code, Hull regions, Hough transform, Hull recognition, Layered Outline Extraction, SASK algorithm

Procedia PDF Downloads 349

Authors: Jianhong Xiang, Rui Sun, Linyu Wang

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In recent years, due to the continuous improvement of deep learning theory, Convolutional Neural Network (CNN) has played a great superior performance in the research of Hyperspectral Image (HSI) classification. Since HSI has rich spatial-spectral information, only utilizing a single dimensional or single size convolutional kernel will limit the detailed feature information received by CNN, which limits the classification accuracy of HSI. In this paper, we design a multi-scale CNN with MLP based on residual and attention modules (INRAM-3DCNN) for the HSI classification task. We propose to use multiple 3D convolutional kernels to extract the packet feature information and fully learn the spatial-spectral features of HSI while designing residual 3D convolutional branches to avoid the decline of classification accuracy due to network degradation. Secondly, we also design the 2D Inception module with a joint channel attention mechanism to quickly extract key spatial feature information at different scales of HSI and reduce the complexity of the 3D model. Due to the high parallel processing capability and nonlinear global action of the Multilayer Perceptron (MLP), we use it in combination with the previous CNN structure for the final classification process. The experimental results on two HSI datasets show that the proposed INRAM-3DCNN method has superior classification performance and can perform the classification task excellently.

Keywords: INRAM-3DCNN, residual, channel attention, hyperspectral image classification

Procedia PDF Downloads 79

Authors: Lam Hong Lan

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The textile industry is said to be the second-largest polluter, responsible for 92 million tonnes of waste annually. There is an urgent need to practice the circular economy to increase the use and reuse around the world. By its nature, the pre-owned fashion business is considered part of the circular economy as it helps to eliminate waste and circulate products. Second-hand clothes and accessories used to be associated with a ‘cheap image’ that carried ‘old energy’ in Vietnam. This perception has been shifted, especially amongst the younger generation. Vietnamese consumer is spending more on products and services that increase self-esteem. The same consumer is moving away from a collectivist social identity towards a ‘me, not we’ outlook as they look for a way to express their individual identity. And pre-owned fashion is one of their solutions as it values money, can create a unique personal style for the wearer and links with sustainability. The design of this study is based on the second-hand shopping motivation theory. A semi-structured online survey with 100 consumers from one pre-owned clothing community and one pre-owned e-commerce site in Vietnam. The findings show that in contrast with Vietnamese older consumers (55+yo) who, in the previous study, generally associated pre-owned fashion with ‘low-cost’, ‘cheap image’ that carried ‘old energy’, young customers (20-30 yo) were actively promoted their pre-owned fashion items to the public via outlet’s social platforms and their social media. This cultural shift comes from the impact of global and local discourse around sustainable fashion and the growth of digital platforms in the pre-owned fashion business in the last five years, which has generally supported wider interest in pre-owned fashion in Vietnam. It can be summarised in three areas: (1) global and local celebrity influencers. A number of celebrities have been photographed wearing vintage items in music videos, photoshoots or at red carpet events. (2) E-commerce and intermediaries. International e-commerce sites – e.g., Vinted, TheRealReal – and/or local apps – e.g., Re.Loved – can influence attitudes and behaviors towards pre-owned consumption. (3) Eco-awareness. The increased online coverage of climate change and environmental pollution has encouraged customers to adopt a more eco-friendly approach to their wardrobes. While sustainable biomaterials and designs are still navigating their way into sustainability, sustainable consumerism via pre-owned fashion seems to be an immediate solution to lengthen the clothes lifecycle. This study has found that young consumers are primarily seeking value for money and/or a unique personal style from pre-owned/vintage fashion while using these purchases to promote their own “eco-awareness” via their social media networks. This is a good indication for fashion designers to keep in mind in their design process and for fashion enterprises in their business model’s choice to not overproduce fashion items.

Keywords: cultural shift, pre-owned fashion, sustainable consumption, sustainable fashion.

Procedia PDF Downloads 83

Authors: Nina Leila Mussa

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Background: The devastating effects of the war on Syria’s educational infrastructure has been widely reported, with millions of children denied access. However, among those who resettled in Lebanon, the impact of receiving educational assistance on their abilities to pass the English entrance exam is not well described. The aim of this study was to identify predictors of success among Syrian refugees receiving English language courses in a Lebanese university. Methods: The database of Syrian refugee girls matriculated in English courses at the American University of Beirut (AUB) was reviewed. The study period was 7/2018-09/2020. Variables compared included: family size and income, welfare status, parents’ education, English proficiency, access to the internet, and need for external help with homework. Results: For the study period, there were 28 girls enrolled. The average family size was 6 (range 4-9), with eight having completed primary, 14 secondary education, and 6 graduated high school. Eighteen were single-income families. After 12 weeks of English courses, 16 passed the Test of English as Foreign Language (TOEFL) from the first attempt, and 12 failed. Out of the 12, 8 received external help, and 6 passed on the second attempt, which brings the total number of successful passing to 22. Conclusion: Despite the tragedy of war, girls receiving assistance in learning English in Lebanon are able to pass the basic language test. Investment in enhancing those educational experiences will be determinantal in achieving widespread progress among those at-risk children.

Keywords: refugee girls, TOEFL, education, success

Procedia PDF Downloads 123

Authors: Magdalena Wilk-Kozubek, Magdalena Rowińska, Krzysztof Rola, Joanna Cybińska

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Leuco dye-based thermochromic systems are classified as intelligent materials because they exhibit thermally induced color changes. Thanks to this feature, they are mainly used as temperature sensors in many industrial sectors. For example, placing a thermochromic material on a chemical reactor may warn about exceeding the maximum permitted temperature for a chemical process. Usually two components, a color former and a developer are needed to produce a system with irreversible color change. The color former is an electron donating (proton accepting) compound such as fluoran leuco dye. The developer is an electron accepting (proton donating) compound such as organic carboxylic acid. When the developer melts, the color former - developer complex is created and the termochromic system becomes colored. Typically, the melting point of the applied developer determines the temperature at which the color change occurs. When the lactone ring of the color former is closed, then the dye is in its colorless state. The ring opening, induced by the addition of a proton, causes the dye to turn into its colored state. Since the color former and the developer are often solid, they can be incorporated into polymer films to facilitate their practical use in industry. The objective of this research was to fabricate a leuco dye-based termochromic system that will irreversibly change color after reaching the temperature of 100°C. For this purpose, benzofluoran leuco dye (as color former) and phenoxyacetic acid (as developer with a melting point of 100°C) were introduced into the polymer films during the drop casting process. The film preparation process was optimized in order to obtain thin films with appropriate properties such as transparency, flexibility and homogeneity. Among the optimized factors were the concentration of benzofluoran leuco dye and phenoxyacetic acid, the type, average molecular weight and concentration of the polymer, and the type and concentration of the surfactant. The selected films, containing benzofluoran leuco dye and phenoxyacetic acid, were combined by mild heat treatment. Structural characterization of single and combined films was carried out by FTIR spectroscopy, morphological analysis was performed by optical microscopy and SEM, phase transitions were examined by DSC, color changes were investigated by digital photography and UV-Vis spectroscopy, while emission changes were studied by photoluminescence spectroscopy. The resulting thermochromic system is colorless at room temperature, but after reaching 100°C the developer melts and it turns irreversibly pink. Therefore, it could be used as an additional sensor to warn against boiling of water in power plants using water cooling. Currently used electronic temperature indicators are prone to faults and unwanted third-party actions. The sensor constructed in this work is transparent, thanks to which it can be unnoticed by an outsider and constitute a reliable reference for the person responsible for the apparatus.

Keywords: color developer, leuco dye, thin film, thermochromism

Procedia PDF Downloads 100

Authors: Sujeet Kumar

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Education has greater importance particularly in terms of increasing human capital and economic competitiveness. It plays a crucial role in terms of cognitive and skill development. Its plays a vital role in process of socialization, fostering social justice, and enhancing social cohesion. Policy related to education has been always a priority for developed countries, which is later adopted by developing countries also. The government of India has also brought change in education polices in line with recognizing change at national and supranational level. However, quality education is still not become an open door for every child in India and several reports are produced year to year about level of school education in India. This paper is concerned with schooling in India. Particularly, it focuses on two government and two private schools in Bihar, but reference has made to schools in Delhi especially around slum communities. The paper presents brief historical context and an overview of current school systems in India. Later, it focuses on analysis of current development in policy in reference with field observation, which is anchored around choice, diversity, market – orientation and gap between different groups of pupils. There is greater degree of difference observed at private and government school levels in terms of quality of teachers, method of teaching and overall environment of learning. The paper concludes that the recent policy development in education particularly Sarva Siksha Abhiyaan (SAA) and Right to Education Act (2009) has required renovating new approach to bridge the gap through broader consultation at grassroots and participatory approach with different stakeholders.

Keywords: education, public policy, participatory approach

Procedia PDF Downloads 394

Authors: Rana Alaa El-Deen Ahmed, M. Elemam Shehab, Shereen Morsy, Nermeen Mekawie

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With the growing popularity and acceptance of e-commerce platforms, users face an ever increasing burden in actually choosing the right product from the large number of online offers. Thus, techniques for personalization and shopping guides are needed by users. For a pleasant and successful shopping experience, users need to know easily which products to buy with high confidence. Since selling a wide variety of products has become easier due to the popularity of online stores, online retailers are able to sell more products than a physical store. The disadvantage is that the customers might not find products they need. In this research the customer will be able to find the products he is searching for, because recommender systems are used in some ecommerce web sites. Recommender system learns from the information about customers and products and provides appropriate personalized recommendations to customers to find the needed product. In this paper eleven classification algorithms are comparatively tested to find the best classifier fit for consumer online shopping attitudes and behavior in the experimented dataset. The WEKA knowledge analysis tool, which is an open source data mining workbench software used in comparing conventional classifiers to get the best classifier was used in this research. In this research by using the data mining tool (WEKA) with the experimented classifiers the results show that decision table and filtered classifier gives the highest accuracy and the lowest accuracy classification via clustering and simple cart.

Keywords: classification, data mining, machine learning, online shopping, WEKA

Procedia PDF Downloads 352

Authors: Virender Singh, Mathew Rees, Simon Hampton, Sivaram Annadurai

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Plant identification is a challenging task that aims to identify the family, genus, and species according to plant morphological features. Automated deep learning-based computer vision algorithms are widely used for identifying plants and can help users narrow down the possibilities. However, numerous morphological similarities between and within species render correct classification difficult. In this paper, we tested custom convolution neural network (CNN) and vision transformer (ViT) based models using the PyTorch framework to classify plants. We used a large dataset of 88,000 provided by the Royal Horticultural Society (RHS) and a smaller dataset of 16,000 images from the PlantClef 2015 dataset for classifying plants at genus and species levels, respectively. Our results show that for classifying plants at the genus level, ViT models perform better compared to CNN-based models ResNet50 and ResNet-RS-420 and other state-of-the-art CNN-based models suggested in previous studies on a similar dataset. ViT model achieved top accuracy of 83.3% for classifying plants at the genus level. For classifying plants at the species level, ViT models perform better compared to CNN-based models ResNet50 and ResNet-RS-420, with a top accuracy of 92.5%. We show that the correct set of augmentation techniques plays an important role in classification success. In conclusion, these results could help end users, professionals and the general public alike in identifying plants quicker and with improved accuracy.

Keywords: plant identification, CNN, image processing, vision transformer, classification

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Authors: Muhammad Zafarullah Khan, Sumeera Abbasi

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The Farmers Field School (FFS) learning approach aims to improve knowledge of the farmers through integrated crop management and provide leadership in their decision making process. The study was conducted to assess the impact of FFS on vegetables production before and after FFS intervention in four villages of district Peshawar in cropping season 2012, by interviewing 80 FFS respondents, twenty from each selected village. It was observed from the study results that all the respondents were satisfied from the impact of FFS and they informed an increased in production in vegetables. It was further observed that after the implementation of FFS the sowing seed rate of tomato and cucumber were decreased from 0.185kg/kanal to 0.100 kg/ kanal and 0.120kg/kanal to 0.010kg/kanal where as the production of tomato and cucumber were increased from 8158.75kgs/kanal to 10302. 5kgs/kanal and 3230kgs/kanal to 5340kgs/kanal, respectively. The cost of agriculture inputs per kanal including seed cost, crop management, Farm Yard Manure, and weedicides in case of tomato were reduced by Rs.28, Rs. 3170, Rs.658and Rs 205 whereas in cucumber reduced by Rs.35, Rs.570, Rs 80 and Rs.430 respectively. Only fertilizers cost was increased by Rs. 2200 in case of tomato and Rs 465 in case of cucumber. Overall the cost was reduced to Rs 545 in tomato and Rs 490 in cucumber production.FFS provided a healthy vegetables and also reduced input cost by adopting integrated crop management. Therefore the promotion of FFS is needed to be planned for farmers to reduce cost of production, so that the more farmers should be benefited.

Keywords: impact, farmer field schools, vegetable production, Peshawar Khyber Pakhtunkhwa

Procedia PDF Downloads 256

Authors: Jameela Ali, Hamid A. Jalab, Loay E. George, Abdul Rahim Ahmad, Azizah Suliman, Karim Al-Jashamy

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Red blood cells (RBC) are the most common types of blood cells and are the most intensively studied in cell biology. The lack of RBCs is a condition in which the amount of hemoglobin level is lower than normal and is referred to as “anemia”. Abnormalities in RBCs will affect the exchange of oxygen. This paper presents a comparative study for various techniques for classifying the RBCs as normal, or abnormal (anemic) using WEKA. WEKA is an open source consists of different machine learning algorithms for data mining applications. The algorithm tested are Radial Basis Function neural network, Support vector machine, and K-Nearest Neighbors algorithm. Two sets of combined features were utilized for classification of blood cells images. The first set, exclusively consist of geometrical features, was used to identify whether the tested blood cell has a spherical shape or non-spherical cells. While the second set, consist mainly of textural features was used to recognize the types of the spherical cells. We have provided an evaluation based on applying these classification methods to our RBCs image dataset which were obtained from Serdang Hospital-alaysia, and measuring the accuracy of test results. The best achieved classification rates are 97%, 98%, and 79% for Support vector machines, Radial Basis Function neural network, and K-Nearest Neighbors algorithm respectively.

Keywords: K-nearest neighbors algorithm, radial basis function neural network, red blood cells, support vector machine

Procedia PDF Downloads 410

Authors: Derjew Ayele Ejigu, Houde Song, Xiaojing Liu

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This work presents the particle swarm optimization trained neural network (PSO-NN) supervisory proportional integral derivative (PID) control method to monitor the pressurized water reactor (PWR) core power for safe operation. The proposed control approach is implemented on the transfer function of the PWR core, which is computed from the state-space model. The PWR core state-space model is designed from the neutronics, thermal-hydraulics, and reactivity models using perturbation around the equilibrium value. The proposed control approach computes the control rod speed to maneuver the core power to track the reference in a closed-loop scheme. The particle swarm optimization (PSO) algorithm is used to train the neural network (NN) and to tune the PID simultaneously. The controller performance is examined using integral absolute error, integral time absolute error, integral square error, and integral time square error functions, and the stability of the system is analyzed by using the Bode diagram. The simulation results indicated that the controller shows satisfactory performance to control and track the load power effectively and smoothly as compared to the PSO-PID control technique. This study will give benefit to design a supervisory controller for nuclear engineering research fields for control application.

Keywords: machine learning, neural network, pressurized water reactor, supervisory controller

Procedia PDF Downloads 156

Authors: Arunima Verma, Padmabati Mondal

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Serotonin-receptor binding plays a key role in several neurological and biological processes, including mood, sleep, hunger, cognition, learning, and memory. In this article, we performed molecular dynamics simulation to examine the key residues that play an essential role in the binding of serotonin to the G-protein-coupled 5-HT₁ᴮ receptor (5-HT₁ᴮ R) via electrostatic interactions. An end-point free energy calculation method (MM-PBSA) determines the stability of the 5-HT1B R due to serotonin binding. The single-point mutation of the polar or charged amino acid residues (Asp129, Thr134) on the binding sites and the calculation of binding free energy validate the importance of these residues in the stability of the serotonin-receptor complex. Principal component analysis indicates the serotonin-bound 5-HT1BR is more stabilized than the apo-receptor in terms of dynamical changes. The difference dynamic cross-correlations map shows the correlation between the transmembrane and mini-Go, which indicates signal transduction happening between mini-Go and the receptor. Allosteric communication reveals the key nodes for signal transduction in 5-HT1BR. These results provide useful insights into the signal transduction pathways and mutagenesis study to regulate the functionality of the complex. The developed protocols can be applied to study local non-covalent interactions and long-range allosteric communications in any protein-ligand system for computer-aided drug design.

Keywords: allostery, CADD, MD simulations, MM-PBSA

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Authors: Kyu Jin Kim, Byung Kwan Oh, Hyo Seon Park

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The seismic responses-based structural health monitoring system has been performed to prevent seismic damage. Structural seismic damage of building is caused by the instantaneous stress concentration which is related with dynamic characteristic of earthquake. Meanwhile, seismic response analysis to estimate the dynamic responses of building demands significantly high computational cost. To prevent the failure of structural members from the characteristic of the earthquake and the significantly high computational cost for seismic response analysis, this paper presents an artificial neural network (ANN) based prediction model for dynamic responses of building considering specific time length. Through the measured dynamic responses, input and output node of the ANN are formed by the length of specific time, and adopted for the training. In the model, evolutionary radial basis function neural network (ERBFNN), that radial basis function network (RBFN) is integrated with evolutionary optimization algorithm to find variables in RBF, is implemented. The effectiveness of the proposed model is verified through an analytical study applying responses from dynamic analysis for multi-degree of freedom system to training data in ERBFNN.

Keywords: structural health monitoring, dynamic response, artificial neural network, radial basis function network, genetic algorithm

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Authors: Qaisara Parveen, M. Imran Yousuf

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The purpose of this study was to find the effectiveness of the use of advance organizer model for enhancing meta-cognition of students in the subject of science. It was hypothesized that the students of experimental group taught through advance organizer model would show the better cognition than the students of control group taught through traditional teaching. The population of the study consisted of all secondary school students studying in government high school located in Rawalpindi. The sample of the study consisted of 50 students of 9th class of humanities group. The sample was selected on the basis of their pretest scores through matching, and the groups were randomly assigned for the treatment. The experimental group was taught through advance organizer model while the control group was taught through traditional teaching. The self-developed achievement test was used for the purpose of pretest and posttest. After collecting the pre-test score and post-test score, the data was analyzed and interpreted by use of descriptive statistics as mean and standard deviation and inferential statistics t-test. The findings indicate that students taught using advance organizers had a higher level of meta-cognition as compared to control group. Further, meta cognition level of boys was found higher than that of girls students. This study also revealed the fact that though the students at different meta-cognition level approached learning situations in a different manner, Advance organizer model is far superior to Traditional method of teaching.

Keywords: descriptive, experimental, humanities, meta-cognition, statistics, science

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Authors: Shotiros Protong

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The incidents of sudden landslides in Thailand during the past decade have occurred frequently and more severely. It is necessary to focus on the principal parameters used for analysis such as land cover land use, rainfall values, characteristic of soil and digital elevation model (DEM). The combination of intense rainfall and severe monsoons is increasing due to global climate change. Landslide occurrences rapidly increase during intense rainfall especially in the rainy season in Thailand which usually starts around mid-May and ends in the middle of October. The rain-triggered landslide hazard analysis is the focus of this research. The combination of geotechnical and hydrological data are used to determine permeability, conductivity, bedding orientation, overburden and presence of loose blocks. The regional landslide hazard mapping is developed using the Slope Stability Index SINMAP model supported on Arc GIS software version 10.1. Geological and land use data are used to define the probability of landslide occurrences in terms of geotechnical data. The geological data can indicate the shear strength and the angle of friction values for soils above given rock types, which leads to the general applicability of the approach for landslide hazard analysis. To address the research objectives, the methods are described in this study: setup and calibration of the SINMAP model, sensitivity of the SINMAP model, geotechnical laboratory, landslide assessment at present calibration and landslide assessment under future climate simulation scenario A2 and B2. In terms of hydrological data, the millimetres/twenty-four hours of average rainfall data are used to assess the rain triggered landslide hazard analysis in slope stability mapping. During 1954-2012 period, is used for the baseline of rainfall data at the present calibration. The climate change in Thailand, the future of climate scenarios are simulated by spatial and temporal scales. The precipitation impact is need to predict for the climate future, Statistical Downscaling Model (SDSM) version 4.2, is used to assess the simulation scenario of future change between latitude 16o 26’ and 18o 37’ north and between longitude 98o 52’ and 103o 05’ east by SDSM software. The research allows the mapping of risk parameters for landslide dynamics, and indicates the spatial and time trends of landslide occurrences. Thus, regional landslide hazard mapping under present-day climatic conditions from 1954 to 2012 and simulations of climate change based on GCM scenarios A2 and B2 from 2013 to 2099 related to the threshold rainfall values for the selected the study area in Uttaradit province in the northern part of Thailand. Finally, the landslide hazard mapping will be compared and shown by areas (km2 ) in both the present and the future under climate simulation scenarios A2 and B2 in Uttaradit province.

Keywords: landslide hazard, GIS, slope stability index (SINMAP), landslides, Thailand

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Authors: Benyapa Thitimapong

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Teenage pregnancy and adolescent mothers have become a matter of increasing concern in Thailand. Since adolescent mothers have been a big problem for two main consequences; health outcomes and socio-economic impacts. Adolescent mothers often endure poor living conditions; limited financial resources while also experience high stress, family instability, and limited educational opportunities. These disadvantages are negative and have long-term effects on adolescent mothers, their families, and the community. The majority of pregnant students and adolescent mothers dropped out of school after becoming pregnant, and some of them return to study again after they gave birth. This research aimed to explain the meaning of adolescent mothers who had undergone with childrearing and studying simultaneously after childbirth. A phenomenological qualitative approach was undertaken to investigate this study. The participants were 20 adolescent mothers each of whom became a mother and a student concurrently within less than 2 years after giving birth to a healthy baby and had also undergone the experience of childrearing and studying in non-formal education. In-depth interview was carried out for data collection, and the data were analyzed using content analysis method. ‘Learning to move forward’ was the meaning of adolescent mothers who experienced with childrearing and studying simultaneously. Their expressions were classified into two categories 1) having more responsibility, and 2) conceding and going on. The result of this study can be used as evidence for health care providers, especially nurses to facilitate and support pregnant adolescents and adolescent mothers to continue their education. Also, it can be used to guide policy to promote in all educational system to enable these groups to remain in school for their life-long success in the future.

Keywords: adolescent mothers, childrearing, studying, teenage pregnancy

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Authors: Sylvanus N. Wosu

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Research shows that factors, such as low motivation, preparation, resources, emotional and social integration, and fears of risk-taking, are the most common barriers to access, matriculation, and retention into science, technology, engineering, and mathematics (STEM) disciplines for underrepresented (URM) students. These factors have been shown to impact students’ attraction and success in STEM fields. Standardized tests such as the SAT and ACT often used as predictor of success, are not always true predictors of success for African and Hispanic American students. Without an adequate academic support environment, even a high SAT score does not guarantee academic success in science and engineering. This paper proposes a model for Academic Coaching for building success and inclusive excellence in STEM education. Academic coaching is framed as a process of motivating students to be independent learners through relational mentorship, facilitating learning supports inside and outside of the classroom or school environment, and developing problem-solving skills and success attitudes that lead to higher performance in the specific subjects. The model is formulated based on best strategies and practices for enriching Academic Performance Impact skills and motivating students’ interests in STEM. A scaled model for measuring the Academic Performance Impact (API) index and STEM is discussed. The study correlates API with state standardized test and shows that the average impact of those skills can be predicted by the Academic Performance Impact (API) index or Academic Preparedness Index.

Keywords: diversity, equity, graduate education, inclusion, inclusive excellence, model

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Authors: Toktam mehrabani

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Textiles, fashion, and architecture, though seemingly disparate fields, share a deep and evolving relationship. This paper explores the intersection of these disciplines, examining how the tactile, structural, and aesthetic qualities of textiles have influenced both fashion and architecture over time. By investigating historical and contemporary examples, this paper seeks to unravel the ways in which textiles and fashion have not only shaped architectural design but have also acted as a bridge between functionality, art, and human experience in the built environment.Textiles have been integral to human culture since the dawn of civilization. Their presence transcends mere functionality, serving as a medium for artistic expression, cultural identity, and social commentary. Fashion, derived from textiles, has long been associated with personal identity and societal trends, while architecture reflects human needs, environmental context, and cultural values. This paper posits that the relationship between textiles, fashion, and architecture is more interconnected than often perceived, with each influencing and inspiring the other across time. Textiles in Architectural Design: From ancient draperies in temples to tapestries in castles, textiles have adorned structures, softening rigid spaces and adding layers of warmth and luxury. Fabric screens and curtains have also served functional purposes, such as controlling light, acoustics, and temperature. Fashion as Architectural Expression: Renaissance and Baroque fashion used exaggerated forms, corsetry, and layers to mirror the grandiosity of architectural styles of the time. Clothing acted as wearable architecture, with structured garments mirroring the strong lines and curves of buildings..Structural Textiles in Architecture: In the 21st century, textiles are no longer just decorative; they have become integral to architectural innovation. Materials like tensile fabrics and smart textiles are used in creating flexible, lightweight structures. Iconic examples include Frei Otto’s work with tensile membranes, seen in the Munich Olympic Stadium.Technological advancements have drastically transformed the relationship between textiles, fashion, and architecture. Digital tools like 3D printing and laser cutting allow designers in both fields to push the limits of form and structure. Smart textiles that react to environmental stimuli are being explored for use in both wearable technology and adaptable architecture, such as facades that change in response to weather conditions. Textiles, fashion, and architecture are inextricably linked through their shared exploration of form, structure, and expression. This interdisciplinary relationship continues to evolve, driven by technological advancements and a growing emphasis on sustainability. As fashion becomes more architectural in its construction and architecture more fluid in its forms, the lines between these disciplines blur, offering new possibilities for creativity and functionality in both wearable and built environments.

Keywords: textiles in architecture, fashion and architecture, textile architecture, structural textiles, wearable architecture, architectural fashion

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Authors: Anna Slupik, Anna Mosiolek, Sebastian Wojtowicz, Dariusz Bialoszewski

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Introduction: Whole-body vibration (WBV) uses high frequency mechanical stimuli generated by a vibration plate and transmitted through bone, muscle and connective tissues to the whole body. Research has shown that long-term vibration-plate training improves neuromuscular facilitation, especially in afferent neural pathways, responsible for the conduction of vibration and proprioceptive stimuli, muscle function, balance and proprioception. Some researchers suggest that the vibration stimulus briefly inhibits the conduction of afferent signals from proprioceptors and can interfere with the maintenance of body balance. The aim of this study was to evaluate the influence of a single set of exercises associated with whole-body vibration on the joint position sense and body balance. Material and methods: The study enrolled 55 people aged 19-24 years. These individuals were randomly divided into a test group (30 persons) and a control group (25 persons). Both groups performed the same set of exercises on a vibration plate. The following vibration parameters: frequency of 20Hz and amplitude of 3mm, were used in the test group. The control group performed exercises on the vibration plate while it was off. All participants were instructed to perform six dynamic exercises lasting 30 seconds each with a 60-second period of rest between them. The exercises involved large muscle groups of the trunk, pelvis and lower limbs. Measurements were carried out before and immediately after exercise. Joint position sense (JPS) was measured in the knee joint for the starting position at 45° in an open kinematic chain. JPS error was measured using a digital inclinometer. Balance was assessed in a standing position with both feet on the ground with the eyes open and closed (each test lasting 30 sec). Balance was assessed using Matscan with FootMat 7.0 SAM software. The surface of the ellipse of confidence and front-back as well as right-left swing were measured to assess balance. Statistical analysis was performed using Statistica 10.0 PL software. Results: There were no significant differences between the groups, both before and after the exercise (p> 0.05). JPS did not change in both the test (10.7° vs. 8.4°) and control groups (9.0° vs. 8.4°). No significant differences were shown in any of the test parameters during balance tests with the eyes open or closed in both the test and control groups (p> 0.05). Conclusions. 1. Deterioration in proprioception or balance was not observed immediately after the vibration stimulus. This suggests that vibration-induced blockage of proprioceptive stimuli conduction can have only a short-lasting effect that occurs only as long as a vibration stimulus is present. 2. Short-term use of vibration in treatment does not impair proprioception and seems to be safe for patients with proprioceptive impairment. 3. These results need to be supplemented with an assessment of proprioception during the application of vibration stimuli. Additionally, the impact of vibration parameters used in the exercises should be evaluated.

Keywords: balance, joint position sense, proprioception, whole body vibration

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Authors: Aisha Ijaz

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The paper focuses on the impact of Muslim religiosity on convenience food purchases and involvement experienced in a non-Muslim culture. There is a scarcity of research on the purchasing patterns of Muslim diaspora communities residing in risk societies, particularly in contexts where there is an increasing inclination toward industrialized food items alongside a renewed interest in the concept of natural foods. The United Kingdom serves as an appropriate setting for this study due to the increasing Muslim population in the country, paralleled by the expanding Halal Food Market. A multi-dimensional framework is proposed, testing for five forms of involvement, specifically Purchase Decision Involvement, Product Involvement, Behavioural Involvement, Intrinsic Risk and Extrinsic Risk. Quantitative cross-sectional consumer data were collected through a face-to-face survey contact method with 141 Muslims during the summer of 2020 in Liverpool located in the Northwest of England. proportion formula was utilitsed, and the population of interest was stratified by gender and age before recruitment took place through local mosques and community centers. Six input variables were used (intrinsic religiosity and involvement dimensions), dividing the sample into 4 clusters using the Two-Step Cluster Analysis procedure in SPSS. Nuanced variances were observed in the type of involvement experienced by religiosity group, which influences behaviour when purchasing convenience food. Four distinct market segments were identified: highly religious ego-involving (39.7%), less religious active (26.2%), highly religious unaware (16.3%), less religious concerned (17.7%). These segments differ significantly with respects to their involvement, behavioural variables (place of purchase and information sources used), socio-cultural (acculturation and social class), and individual characteristics. Choosing the appropriate convenience food is centrally related to the value system of highly religious ego-involving first-generation Muslims, which explains their preference for shopping at ethnic food stores. Less religious active consumers are older and highly alert in information processing to make the optimal food choice, relying heavily on product label sources. Highly religious unaware Muslims are less dietary acculturated to the UK diet and tend to rely on digital and expert advice sources. The less-religious concerned segment, who are typified by younger age and third generation, are engaged with the purchase process because they are worried about making unsuitable food choices. Research implications are outlined and potential avenues for further explorations are identified.

Keywords: consumer behaviour, consumption, convenience food, religion, muslims, UK

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Authors: Peter R. Reuter

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Health professionals play important roles in helping patients use Complementary and Alternative Medicine (CAM) practices safely and accurately. Consequently, it is important for future health professionals to learn about CAM practices during their time in undergraduate and graduate programs. To satisfy this need for education, teaching CAM in nursing and medical schools and other health professions programs is becoming more prevalent. Our study was the first to look specifically at the knowledge of, and attitude toward CAM of undergraduate health professions students at a university in the U.S. Students were invited to participate in one of two anonymous online surveys depending on whether they were pre-health professions students or graduating health professions seniors. Of the 763 responses analyzed, 71.7% were from pre-health professions students, and 28.3% came from graduating seniors. The overall attitude of participants toward and interest in learning about CAM practices was generally fairly positive with graduating seniors being more positive than pre-health professions students. Yoga, meditation, massage therapy, aromatherapy, and chiropractic care were the practices most respondents had personal experience with. Massage therapy, yoga, chiropractic care, meditation, music therapy, and diet-based therapy received the highest ratings from respondents. Three-quarters of respondents planned on including aspects of holistic medicine in their future career as a health professional. The top five practices named were yoga, meditation, massage therapy, diet-based therapy, and music therapy. The study confirms the need to educate health professions students about CAM practices to give them the background information they need to select or recommend the best practices for their patients' needs.

Keywords: CAM education, health professions, health professions students, pre-health professions students

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Authors: Wei Sun, Yan Dong

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There is an increasing interest in introducing computational thinking at an early age. Computational thinking, like mathematical thinking, engineering thinking, and scientific thinking, is a kind of analytical thinking. Learning computational thinking skills is not only to improve technological literacy, but also allows learners to equip with practicable skills such as problem-solving skills. As people realize the importance of computational thinking, the field of educational technology faces a problem: how to choose appropriate tools and activities to help students develop computational thinking skills. Robots are gradually becoming a popular teaching tool, as robots provide a tangible way for young children to access to technology, and controlling a robot through programming offers them opportunities to engage in developing computational thinking. This study explores whether the introduction of flowcharts into the robotics programming courses can help children convert natural language into a programming language more easily, and then to better cultivate their computational thinking skills. An experimental study was adopted with a sample of children ages six to seven (N = 16) participated, and a one-meter-tall humanoid robot was used as the teaching tool. Results show that children can master basic programming concepts through robotic courses. Children's computational thinking has been significantly improved. Besides, results suggest that flowcharts do have an impact on young children’s computational thinking skills development, but it only has a significant effect on the "sequencing" and "correspondence" skills. Overall, the study demonstrates that the humanoid robot and flowcharts have qualities that foster young children to learn programming and develop computational thinking skills.

Keywords: robotics, computational thinking, programming, young children, flow chart

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Authors: Yan Torres, Fernanda Simoes, Francisco Petrucci-Fonseca, Freddie-Jeanne Richard

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The non-invasive samples are an alternative of collecting genetic samples directly. Non-invasive samples are collected without the manipulation of the animal (e.g., scats, feathers and hairs). Nevertheless, the use of non-invasive samples has some limitations. The main issue is degraded DNA, leading to poorer extraction efficiency and genotyping. Those errors delayed for some years a widespread use of non-invasive genetic information. Possibilities to limit genotyping errors can be done using analysis methods that can assimilate the errors and singularities of non-invasive samples. Genotype matching and population estimation algorithms can be highlighted as important analysis tools that have been adapted to deal with those errors. Although, this recent development of analysis methods there is still a lack of empirical performance comparison of them. A comparison of methods with dataset different in size and structure can be useful for future studies since non-invasive samples are a powerful tool for getting information specially for endangered and rare populations. To compare the analysis methods, four different datasets used were obtained from the Dryad digital repository were used. Three different matching algorithms (Cervus, Colony and Error Tolerant Likelihood Matching - ETLM) are used for matching genotypes and two different ones for population estimation (Capwire and BayesN). The three matching algorithms showed different patterns of results. The ETLM produced less number of unique individuals and recaptures. A similarity in the matched genotypes between Colony and Cervus was observed. That is not a surprise since the similarity between those methods on the likelihood pairwise and clustering algorithms. The matching of ETLM showed almost no similarity with the genotypes that were matched with the other methods. The different cluster algorithm system and error model of ETLM seems to lead to a more criterious selection, although the processing time and interface friendly of ETLM were the worst between the compared methods. The population estimators performed differently regarding the datasets. There was a consensus between the different estimators only for the one dataset. The BayesN showed higher and lower estimations when compared with Capwire. The BayesN does not consider the total number of recaptures like Capwire only the recapture events. So, this makes the estimator sensitive to data heterogeneity. Heterogeneity in the sense means different capture rates between individuals. In those examples, the tolerance for homogeneity seems to be crucial for BayesN work properly. Both methods are user-friendly and have reasonable processing time. An amplified analysis with simulated genotype data can clarify the sensibility of the algorithms. The present comparison of the matching methods indicates that Colony seems to be more appropriated for general use considering a time/interface/robustness balance. The heterogeneity of the recaptures affected strongly the BayesN estimations, leading to over and underestimations population numbers. Capwire is then advisable to general use since it performs better in a wide range of situations.

Keywords: algorithms, genetics, matching, population

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