Search results for: learning cycles

Authors: Juliette MacDonald, Jun Li, Wenji Xiang, Mingwei Zhao

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Shanghai International College of Fashion and Innovation (SCF) was created as a result of a collaborative partnership agreement between the University of Edinburgh and Donghua University. The College provides two programmes: Fashion Innovation and Fashion Interior Design and the overarching curriculum has the intention of developing innovation and creativity within an international learning, teaching, knowledge exchange and research context. The research problem presented here focuses on the multi-national/cultural faculty in the team, the challenges arising from difficulties in communication and the associated limitations of management frameworks. The teaching faculty at SCF are drawn from China, Finland, Korea, Singapore and the UK with input from Flying Faculty from Fashion and Interior Design, Edinburgh College of Art (ECA), for 5 weeks each semester. Rather than fully replicating the administrative and pedagogical style of one or other of the institutions within this joint partnership the aim from the outset was to create a third way which acknowledges the quality assurance requirements of both Donghua and Edinburgh, the academic and technical needs of the students and provides relevant development and support for all the SCF-based staff and Flying Academics. It has been well acknowledged by those who are involved in teaching across cultures that there is often a culture shock associated with transnational education but that the experience of being involved in the delivery of a curriculum at a Joint Institution can also be very rewarding for staff and students. It became clear at SCF that if a third way might be achieved which encourages innovative approaches to fashion education whilst balancing the expectations of Chinese and western concepts of education and the aims of two institutions, then it was going to be necessary to construct a framework which developed close working relationships for the entire teaching team, so not only between academics and students but also between technicians and administrators at ECA and SCF. The attempts at co-construction and integration are built on the sharing of cultural and educational experiences and knowledge as well as provision of opportunities for reflection on the pedagogical purpose of the curriculum and its delivery. Methods on evaluating the effectiveness of these aims include a series of surveys and interviews and analysis of data drawn from teaching projects delivered to the students along with graduate successes from the last five years, since SCF first opened its doors. This paper will provide examples of best practice developed by SCF which have helped guide the faculty and embed common core values and aims of co-construction regulations and management, whilst building a pro-active TNE (Trans-National Education) team which enhances the learning experience for staff and students alike.

Keywords: cultural co-construction, educational team management, multi-cultural challenges, TNE integration for teaching teams

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Authors: Carla M. Machado, André A. Silva, Armando Bastos, Telmo G. Santos, J. Pamies Teixeira

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Advanced high-strength steels (AHSS) are increasingly being used in automotive components. The use of AHSS sheets plays an important role in reducing weight, as well as increasing the resistance to impact in vehicle components. However, the large-scale use of these sheets becomes more difficult due to the limitations during the forming process. Such limitations are due to the elastically driven change of shape of a metal sheet during unloading and following forming, known as the springback effect. As the magnitude of the springback tends to increase with the strength of the material, it is among the most worrisome problems in the use of AHSS steels. The prediction of strain hardening, especially under non-proportional loading conditions, is very limited due to the lack of constitutive models and mainly due to very limited experimental tests. It is very clear from the literature that in experimental terms there is not much work to evaluate deformation behavior under real conditions, which implies a very limited and scarce development of mathematical models for these conditions. The Bauschinger effect is also fundamental to the difference between kinematic and isotropic hardening models used to predict springback in sheet metal forming. It is of major importance to deepen the phenomenological knowledge of the mechanical and microstructural behavior of the materials, in order to be able to reproduce with high fidelity the behavior of extension of the materials by means of computational simulation. For this, a multi phenomenological analysis and characterization are necessary to understand the various aspects involved in plastic deformation, namely the stress-strain relations and also the variations of electrical conductivity and magnetic permeability associated with the metallurgical changes due to plastic deformation. Aiming a complete mechanical-microstructural characterization, uniaxial tensile tests involving successive cycles of loading and unloading were performed, as well as biaxial tests such as the Erichsen test. Also, nondestructive evaluation comprising eddy currents to verify microstructural changes due to plastic deformation and ultrasonic tests to evaluate the local variations of thickness were made. The material parameters for the stable yield function and the monotonic strain hardening were obtained using uniaxial tension tests in different material directions and balanced biaxial tests. Both the decrease of the modulus of elasticity and Bauschinger effect were determined through the load-unload tensile tests. By means of the eddy currents tests, it was possible to verify changes in the magnetic permeability of the material according to the different plastically deformed areas. The ultrasonic tests were an important aid to quantify the local plastic extension. With these data, it is possible to parameterize the different models of kinematic hardening to better approximate the results obtained by simulation with the experimental results, which are fundamental for the springback prediction of the stamped parts.

Keywords: advanced high strength steel, Bauschinger effect, sheet metal forming, springback

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Authors: Keyi Wang

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Similar to the touchscreen, hand gesture based human-computer interaction (HCI) is a technology that could allow people to perform a variety of tasks faster and more conveniently. This paper proposes a training method of an image-based hand gesture image and video clip recognition system using a CNN (Convolutional Neural Network) with a dataset. A dataset containing 6 hand gesture images is used to train a 2D CNN model. ~98% accuracy is achieved. Furthermore, a 3D CNN model is trained on a dataset containing 4 hand gesture video clips resulting in ~83% accuracy. It is demonstrated that a Cozmo robot loaded with pre-trained models is able to recognize static and dynamic hand gestures.

Keywords: deep learning, hand gesture recognition, computer vision, image processing

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Authors: Katherine O'Grady-Bray

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For some deaf children, reading books can be a challenge. Frank Barnes School (FBS) provides guided reading time with Teachers of the Deaf, in which they read books with deaf children using a bilingual approach. The vocabulary and context of the story is explained to deaf children in BSL so they develop skills bridging English and BSL languages. However, the success of this practice is only achieved if the person is fluent in both languages. FBS piloted a scheme to convert an Oxford Reading Tree (ORT) book into an e-book that can be read using tablets. Deaf readers at FBS have access to both languages (BSL and English) during lessons and outside the classroom. The pupils receive guided reading sessions with a Teacher of the Deaf every morning, these one to one sessions give pupils the opportunity to learn how to bridge both languages e.g. how to translate English to BSL and vice versa. Generally, due to our pupils’ lack of access to incidental learning, gaining new information about the world around them is limited. This highlights the importance of quality time to scaffold their language development. In some cases, there is a shortfall of parental support at home due to poor communication skills or an unawareness of how to interact with deaf children. Some families have a limited knowledge of sign language or simply don’t have the required learning environment and strategies needed for language development with deaf children. As the majority of our pupils’ preferred language is BSL we use that to teach reading and writing English. If this is not mirrored at home, there is limited opportunity for joint reading sessions. Development of the e-Book required planning and technical development. The overall production took time as video footage needed to be shot and then edited individually for each page. There were various technical considerations such as having an appropriate background colour so not to draw attention away from the signer. Appointing a signer with the required high level of BSL was essential. The language and pace of the sign language was an important consideration as it was required to match the age and reading level of the book. When translating English text to BSL, careful consideration was given to the nonlinear nature of BSL and the differences in language structure and syntax. The e-book was produced using Apple’s ‘iBook Author’ software which allowed video footage of the signer to be embedded on pages opposite the text and illustration. This enabled BSL translation of the content of the text and inferences of the story. An interpreter was used to directly ‘voice over’ the signer rather than the actual text. The aim behind the structure and layout of the e-book is to allow parents to ‘read’ with their deaf child which helps to develop both languages. From observations, the use of e-books has given pupils confidence and motivation with their reading, developing skills bridging both BSL and English languages and more effective reading time with parents.

Keywords: bilingual book, e-book, BSL and English, bilingual e-book

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Authors: El Asnaoui Khalid, Aksasse Brahim, Ouanan Mohammed

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In this paper, we are interested in the problem of finding similar images in a large database. For this purpose we propose a new algorithm based on a combination of the 2-D histogram intersection in the HSV space and statistical moments. The proposed histogram is based on a 3x3 window and not only on the intensity of the pixel. This approach can overcome the drawback of the conventional 1-D histogram which is ignoring the spatial distribution of pixels in the image, while the statistical moments are used to escape the effects of the discretisation of the color space which is intrinsic to the use of histograms. We compare the performance of our new algorithm to various methods of the state of the art and we show that it has several advantages. It is fast, consumes little memory and requires no learning. To validate our results, we apply this algorithm to search for similar images in different image databases.

Keywords: 2-D histogram, statistical moments, indexing, similarity distance, histograms intersection

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Authors: Jitka Rychtarikova

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Regional differences in mortality in the Czech Republic (CR) may be moderate from a broader European perspective, but important discrepancies in life expectancy can be found between smaller territorial units. In this study territorial units are based on Administrative Districts of Municipalities with Extended Powers (MEP). This definition came into force January 1, 2003. There are 205 units and the city of Prague. MEP represents the smallest unit for which mortality patterns based on life tables can be investigated and the Czech Statistical Office has been calculating such life tables (every five-years) since 2004. MEP life tables from 2009-2013 for males and females allowed the investigation of three main life cycles with the use of temporary life expectancies between the exact ages of 0 and 35; 35 and 65; and the life expectancy at exact age 65. The results showed regional survival inequalities primarily in adult and older ages. Consequently, only mortality indicators for adult and elderly population were related to census 2011 unlinked data for the same age groups. The most relevant socio-economic factors taken from the census are: having a partner, educational level and unemployment rate. The unemployment rate was measured for adults aged 35-64 completed years. Exploratory spatial data analysis methods were used to detect regional patterns in spatially contiguous units of MEP. The presence of spatial non-stationarity (spatial autocorrelation) of mortality levels for male and female adults (35-64), and elderly males and females (65+) was tested using global Moran’s I. Spatial autocorrelation of mortality patterns was mapped using local Moran’s I with the intention to depict clusters of low or high mortality and spatial outliers for two age groups (35-64 and 65+). The highest Moran’s I was observed for male temporary life expectancy between exact ages 35 and 65 (0.52) and the lowest was among women with life expectancy of 65 (0.26). Generally, men showed stronger spatial autocorrelation compared to women. The relationship between mortality indicators such as life expectancies and socio-economic factors like the percentage of males/females having a partner; percentage of males/females with at least higher secondary education; and percentage of unemployed males/females from economically active population aged 35-64 years, was evaluated using multiple regression (OLS). The results were then compared to outputs from geographically weighted regression (GWR). In the Czech Republic, there are two broader territories North-West Bohemia (NWB) and North Moravia (NM), in which excess mortality is well established. Results of the t-test of spatial regression showed that for males aged 30-64 the association between mortality and unemployment (when adjusted for education and partnership) was stronger in NM compared to NWB, while educational level impacted the length of survival more in NWB. Geographic variation and relationships in mortality of the CR MEP will also be tested using the spatial Durbin approach. The calculations were conducted by means of ArcGIS 10.6 and SAS 9.4.

Keywords: Czech Republic, mortality, municipality, socio-economic factors, spatial analysis

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Authors: M. Maier, I. Dedigama, J. Majasan, Y. Wu, Q. Meyer, L. Castanheira, G. Hinds, P. R. Shearing, D. J. L. Brett

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Increasing the efficiency of electrolyser technology is commonly seen as one of the main challenges on the way to the Hydrogen Economy. There is a significant lack of understanding of the different states of operation of polymer electrolyte membrane water electrolysers (PEMWE) and how these influence the overall efficiency. This in particular means the two-phase flow through the membrane, gas diffusion layers (GDL) and flow channels. In order to increase the efficiency of PEMWE and facilitate their spread as commercial hydrogen production technology, new analytic approaches have to be found. Acoustic emission (AE) offers the possibility to analyse the processes within a PEMWE in a non-destructive, fast and cheap in-situ way. This work describes the generation and analysis of AE data coming from a PEM water electrolyser, for, to the best of our knowledge, the first time in literature. Different experiments are carried out. Each experiment is designed so that only specific physical processes occur and AE solely related to one process can be measured. Therefore, a range of experimental conditions is used to induce different flow regimes within flow channels and GDL. The resulting AE data is first separated into different events, which are defined by exceeding the noise threshold. Each acoustic event consists of a number of consequent peaks and ends when the wave diminishes under the noise threshold. For all these acoustic events the following key attributes are extracted: maximum peak amplitude, duration, number of peaks, peaks before the maximum, average intensity of a peak and time till the maximum is reached. Each event is then expressed as a vector containing the normalized values for all criteria. Principal Component Analysis is performed on the resulting data, which orders the criteria by the eigenvalues of their covariance matrix. This can be used as an easy way of determining which criteria convey the most information on the acoustic data. In the following, the data is ordered in the two- or three-dimensional space formed by the most relevant criteria axes. By finding spaces in the two- or three-dimensional space only occupied by acoustic events originating from one of the three experiments it is possible to relate physical processes to certain acoustic patterns. Due to the complex nature of the AE data modern machine learning techniques are needed to recognize these patterns in-situ. Using the AE data produced before allows to train a self-learning algorithm and develop an analytical tool to diagnose different operational states in a PEMWE. Combining this technique with the measurement of polarization curves and electrochemical impedance spectroscopy allows for in-situ optimization and recognition of suboptimal states of operation.

Keywords: acoustic emission, gas diffusion layers, in-situ diagnosis, PEM water electrolyser

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Authors: Abdullah Khuwaileh

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While teaching and translating vocabulary is no longer a neglected area in ELT in general and in translation in particular, the psychology of its acquisition has been a neglected area. Our paper aims at exploring some of the learning and translating conditions under which vocabulary is acquired and translated properly. To achieve this objective, two teaching methods (experiments) were applied on 4 translators to measure their acquisition of a number of transparent vocabulary items. Some of these items were knowingly chosen from 'deceptively transparent words'. All the data, sample, etc., were taken from Jordan University of Science and Technology (JUST) and Yarmouk University, where the researcher is employed. The study showed that translators might translate transparent words inaccurately, particularly if these words are uncontextualised. It was also shown that the morphological structures of words may lead translators or even EFL learners to misinterpretations of meaning.

Keywords: english, transparent, word, processing, translation

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Authors: Mustafa M. Donma, Orkide Donma

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The impact of metabolic syndrome (MetS) on cognition and functions of the brain is being investigated. Iron deficiency and deficiencies of B9 (folate) as well as B12 (cobalamin) vitamins are best-known nutritional anemias. They are associated with cognitive disorders and learning difficulties. The antidepressant effects of vitamin D are known and the deficiency state affects mental functions negatively. The aim of this study is to investigate possible correlations of MetS with serum brain-derived neurotrophic factor (BDNF), iron, folate, cobalamin and vitamin D in pediatric patients. 30 children, whose age- and sex-dependent body mass index (BMI) percentiles vary between 85 and 15, 60 morbid obese children with above 99^th percentiles constituted the study population. Anthropometric measurements were taken. BMI values were calculated. Age- and sex-dependent BMI percentile values were obtained using the appropriate tables prepared by the World Health Organization (WHO). Obesity classification was performed according to WHO criteria. Those with MetS were evaluated according to MetS criteria. Serum BDNF was determined by enzyme-linked immunosorbent assay. Serum folate was analyzed by an immunoassay analyzer. Serum cobalamin concentrations were measured using electrochemiluminescence immunoassay. Vitamin D status was determined by the measurement of 25-hydroxycholecalciferol [25-hydroxy vitamin D3, 25(OH)D] using high performance liquid chromatography. Statistical evaluations were performed using SPSS for Windows, version 16. The p values less than 0.05 were accepted as statistically significant. Although statistically insignificant, lower folate and cobalamin values were found in MO children compared to those observed for children with normal BMI. For iron and BDNF values, no alterations were detected among the groups. Significantly decreased vitamin D concentrations were noted in MO children with MetS in comparison with those in children with normal BMI (p ≤ 0.05). The positive correlation observed between iron and BDNF in normal-BMI group was not found in two MO groups. In THE MetS group, the partial correlation among iron, BDNF, folate, cobalamin, vitamin D controlling for waist circumference and BMI was r = -0.501; p ≤ 0.05. None was calculated in MO and normal BMI groups. In conclusion, vitamin D should also be considered during the assessment of pediatric MetS. Waist circumference and BMI should collectively be evaluated during the evaluation of MetS in children. Within this context, BDNF appears to be a key biochemical parameter during the examination of obesity degree in terms of mental functions, cognition and learning capacity. The association observed between iron and BDNF in children with normal BMI was not detected in MO groups possibly due to development of inflammation and other obesity-related pathologies. It was suggested that this finding may contribute to mental function impairments commonly observed among obese children.

Keywords: brain-derived neurotrophic factor, iron, vitamin B9, vitamin B12, vitamin D

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Authors: B. M. Vishal, Monamie Basu, Gopinath M., Rose Havilah Pulla

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Though there are several methods of synthesizing silver nano particles, Green synthesis always has its own dignity. Ranging from the cost-effectiveness to the ease of synthesis, the process is simplified in the best possible way and is one of the most explored topics. This study of extracting secondary metabolites from Perilla frutescens and using them for therapeutic additives has its own significance. Unlike the other researches that have been done so far, this study aims to synthesize Silver nano particles from Perilla frutescens using three available forms of the plant: leaves, seed, and commercial leaf extract powder. Perilla frutescens, commonly known as 'Beefsteak Plant', is a perennial plant and belongs to the mint family. The plant has two varieties classed within itself. They are frutescens crispa and frutescens frutescens. The species, frutescens crispa (commonly known as 'Shisho' in Japanese), is generally used for edible purposes. Its leaves occur in two forms, varying on the colors. It is found in two different colors of red with purple streaks and green with crinkly pattern on it. This species is aromatic due to the presence of two major compounds: polyphenols and perillaldehyde. The red (purple streak) variety of this plant is due to the presence of a pigment, Perilla anthocyanin. The species, frutescens frutescens (commonly known as 'Egoma' in Japanese), is the main source for perilla oil. This species is also aromatic, but in this case, the major compound which gives the aroma is Perilla ketone or egoma ketone. Shisho grows short as compared with Wild Sesame and both produce seeds. The seeds of Wild Sesame are large and soft whereas that of Shisho is small and hard. The seeds have a large proportion of lipids, ranging about 38-45 percent. Excluding those, the seeds have a large quantity of Omega-3 fatty acids, linoleic acid, and an Omega-6 fatty acid. Other than these, Perilla leaf extract has gold and silver nano particles in it. The yield comparison in all the cases have been done, and the process’ optimal conditions were modified, keeping in mind the efficiencies. The characterization of secondary metabolites includes GC-MS and FTIR which can be used to identify the components of purpose that actually helps in synthesizing silver nano particles. The analysis of silver was done through a series of characterization tests that include XRD, UV-Vis, EDAX, and SEM. After the synthesis, for being used as therapeutic additives, the toxin analysis was done, and the results were tabulated. The synthesis of silver nano particles was done in a series of multiple cycles of extraction from leaves, seeds and commercially purchased leaf extract. The yield and efficiency comparison were done to bring out the best and the cheapest possible way of synthesizing silver nano particles using Perilla frutescens. The synthesized nano particles can be used in therapeutic drugs, which has a wide range of application from burn treatment to cancer treatment. This will, in turn, replace the traditional processes of synthesizing nano particles, as this method will prove effective in terms of cost and the environmental implications.

Keywords: nanoparticles, green synthesis, Perilla frutescens, characterisation, toxin analysis

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Authors: S. Sabatino, V. Calderaro, V. Galdi, G. Graber, L. Ippolito

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Climate change is a rapidly growing global threat caused mainly by increased emissions of carbon dioxide (CO₂) into the atmosphere. These emissions come from multiple sources, including industry, power generation, and the transport sector. The need to tackle climate change and reduce CO₂ emissions is indisputable. A crucial solution to achieving decarbonization in the transport sector is the adoption of electric vehicles (EVs). These vehicles use lithium (Li-Ion) batteries as an energy source, making them extremely efficient and with low direct emissions. However, Li-Ion batteries are not without problems, including the risk of overheating and performance degradation. To ensure its safety and longevity, it is essential to use a battery management system (BMS). The BMS constantly monitors battery status, adjusts temperature and cell balance, ensuring optimal performance and preventing dangerous situations. From the monitoring carried out, it is also able to optimally manage the battery to increase its life. Among the parameters monitored by the BMS, the main ones are State of Charge (SoC), State of Health (SoH), and State of Power (SoP). The evaluation of these parameters can be carried out in two ways: offline, using benchtop batteries tested in the laboratory, or online, using batteries installed in moving vehicles. Online estimation is the preferred approach, as it relies on capturing real-time data from batteries while operating in real-life situations, such as in everyday EV use. Actual battery usage conditions are highly variable. Moving vehicles are exposed to a wide range of factors, including temperature variations, different driving styles, and complex charge/discharge cycles. This variability is difficult to replicate in a controlled laboratory environment and can greatly affect performance and battery life. Online estimation captures this variety of conditions, providing a more accurate assessment of battery behavior in real-world situations. In this article, a hybrid approach based on a neural network and a statistical method for real-time estimation of SoC, SoH, and SoP parameters of interest is proposed. These parameters are estimated from the analysis of a one-day driving profile of an electric vehicle, assumed to be divided into the following four phases: (i) Partial discharge (SoC 100% - SoC 50%), (ii) Partial discharge (SoC 50% - SoC 80%), (iii) Deep Discharge (SoC 80% - SoC 30%) (iv) Full charge (SoC 30% - SoC 100%). The neural network predicts the values of ohmic resistance and incremental capacity, while the statistical method is used to estimate the parameters of interest. This reduces the complexity of the model and improves its prediction accuracy. The effectiveness of the proposed model is evaluated by analyzing its performance in terms of square mean error (RMSE) and percentage error (MAPE) and comparing it with the reference method found in the literature.

Keywords: electric vehicle, Li-Ion battery, BMS, state-of-charge, state-of-health, state-of-power, artificial neural networks

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Authors: Mohammed Arif, Abdessalam Kifouche

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Speech is a very convenient way of communication between people and machines. It conveys information about the identity of the talker. Since speaker recognition technology is increasingly securing our everyday lives, the objective of this paper is to develop two automatic text-independent speaker verification systems (TI SV) using low-level spectral features and machine learning methods. (i) The first system is based on a support vector machine (SVM), which was widely used in voice signal processing with the aim of speaker recognition involving verifying the identity of the speaker based on its voice characteristics, and (ii) the second is based on Gaussian Mixture Model (GMM) and Universal Background Model (UBM) to combine different functions from different resources to implement the SVM based.

Keywords: speaker verification, text-independent, support vector machine, Gaussian mixture model, cepstral analysis

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Authors: Brittany E. Coff, Tommy K. K. Ngai, Laura A. S. MacDonald

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Many organizations in the Water, Sanitation and Hygiene (WASH) sector provide education and training in order to increase the effectiveness of their WASH interventions. A key challenge for these organizations is measuring how well their education and training activities contribute to WASH improvements. It is crucial for implementers to understand the returns of their education and training activities so that they can improve and make better progress toward the desired outcomes. This paper presents information on CAWST’s development and piloting of the evaluation methodology. The Centre for Affordable Water and Sanitation Technology (CAWST) has developed a methodology for evaluating education and training activities, so that organizations can understand the effectiveness of their WASH activities and improve accordingly. CAWST developed this methodology through a series of research partnerships, followed by staged field pilots in Nepal, Peru, Ethiopia and Haiti. During the research partnerships, CAWST collaborated with universities in the UK and Canada to: review a range of available evaluation frameworks, investigate existing practices for evaluating education activities, and develop a draft methodology for evaluating education programs. The draft methodology was then piloted in three separate studies to evaluate CAWST’s, and CAWST’s partner’s, WASH education programs. Each of the pilot studies evaluated education programs in different locations, with different objectives, and at different times within the project cycles. The evaluations in Nepal and Peru were conducted in 2013 and investigated the outcomes and impacts of CAWST’s WASH education services in those countries over the past 5-10 years. In 2014, the methodology was applied to complete a rigorous evaluation of a 3-day WASH Awareness training program in Ethiopia, one year after the training had occurred. In 2015, the methodology was applied in Haiti to complete a rapid assessment of a Community Health Promotion program, which informed the development of an improved training program. After each pilot evaluation, the methodology was reviewed and improvements were made. A key concept within the methodology is that in order for training activities to lead to improved WASH practices at the community level, it is not enough for participants to acquire new knowledge and skills; they must also apply the new skills and influence the behavior of others following the training. The steps of the methodology include: development of a Theory of Change for the education program, application of the Kirkpatrick model to develop indicators, development of data collection tools, data collection, data analysis and interpretation, and use of the findings for improvement. The methodology was applied in different ways for each pilot and was found to be practical to apply and adapt to meet the needs of each case. It was useful in gathering specific information on the outcomes of the education and training activities, and in developing recommendations for program improvement. Based on the results of the pilot studies, CAWST is developing a set of support materials to enable other WASH implementers to apply the methodology. By using this methodology, more WASH organizations will be able to understand the outcomes and impacts of their training activities, leading to higher quality education programs and improved WASH outcomes.

Keywords: education and training, capacity building, evaluation, water and sanitation

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Authors: Amdy Moustapha Drame, Ilya V. Germashev, E. A. Markushevskaya

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Among the main problems of medicine is breast cancer, from which a significant number of women around the world are constantly dying. Therefore, the detection of malignant breast tumors is an urgent task. For many years, various technologies for detecting these tumors have been used, in particular, in thermal imaging in order to determine different levels of breast cancer development. These periodic screening methods are a diagnostic tool for women and may have become an alternative to older methods such as mammography. This article proposes a model for the identification of malignant neoplasms of the mammary glands by the asymmetry of internal and external thermal imaging fields.

Keywords: asymmetry, breast cancer, tumors, deep learning, thermogram, convolutional transformation, classification

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Authors: Si Chen, Quanhong Jiang

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In the increasingly mature posture recognition technology, human movement information is widely used in sports rehabilitation, human-computer interaction, medical health, human posture assessment, and other fields today; this project uses the most original ideas; it is proposed to use the collection equipment for the collection of myoelectric data, reflect the muscle posture change on a degree of freedom through data processing, carry out data-muscle three-dimensional model joint adjustment, and realize basic pose recognition. Based on this, bionic aids or medical rehabilitation equipment can be further developed with the help of robotic arms and cutting-edge technology, which has a bright future and unlimited development space.

Keywords: pose recognition, 3D animation, electromyography, machine learning, bionics

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Authors: Samia Elfekih, Wee Tek Tay, Karl Gordon, Paul De Barro

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Invasive species represent an increasing threat to food biosecurity, causing significant economic losses in agricultural systems. An example is the sweet potato whitefly, Bemisia tabaci, which is a complex of morphologically indistinguishable species causing average annual global damage estimated at US$2.4 billion. The Bemisia complex represents an interesting model for evolutionary studies because of their extensive distribution and potential for invasiveness and population expansion. Within this complex, two species, Middle East-Asia Minor 1 (MEAM1) and Mediterranean (MED) have invaded well beyond their home ranges whereas others, such as Indian Ocean (IO) and Australia (AUS), have not. In order to understand why some Bemisia species have become invasive, genome-wide sequence scans were used to estimate population dynamics over time and relate these to climate. The Bayesian Skyline Plot (BSP) method as implemented in BEAST was used to infer the historical effective population size. In order to overcome sampling bias, the populations were combined based on geographical origin. The datasets used for this particular analysis are genome-wide SNPs (single nucleotide polymorphisms) called separately in each of the following groups: Sub-Saharan Africa (Burkina Faso), Europe (Spain, France, Greece and Croatia), USA (Arizona), Mediterranean-Middle East (Israel, Italy), Middle East-Central Asia (Turkmenistan, Iran) and Reunion Island. The non-invasive ‘AUS’ species endemic to Australia was used as an outgroup. The main findings of this study show that the BSP for the Sub-Saharan African MED population is different from that observed in MED populations from the Mediterranean Basin, suggesting evolution under a different set of environmental conditions. For MED, the effective size of the African (Burkina Faso) population showed a rapid expansion ≈250,000-310,000 years ago (YA), preceded by a period of slower growth. The European MED populations (i.e., Spain, France, Croatia, and Greece) showed a single burst of expansion at ≈160,000-200,000 YA. The MEAM1 populations from Israel and Italy and the ones from Iran and Turkmenistan are similar as they both show the earlier expansion at ≈250,000-300,000 YA. The single IO population lacked the latter expansion but had the earlier one. This pattern is shared with the Sub-Saharan African (Burkina Faso) MED, suggesting IO also faced a similar history of environmental change, which seems plausible given their relatively close geographical distributions. In conclusion, populations within the invasive species MED and MEAM1 exhibited signatures of population expansion lacking in non-invasive species (IO and AUS) during the Pleistocene, a geological epoch marked by repeated climatic oscillations with cycles of glacial and interglacial periods. These expansions strongly suggested the potential of some Bemisia species’ genomes to affect their adaptability and invasiveness.

Keywords: whitefly, RADseq, invasive species, SNP, climate change

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Authors: Tim Farrelly

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In recent years, AI-powered object detection systems have opened the doors for innovative new applications and products, especially those operating in the real world or ‘on edge’ – namely, in sport. This paper investigates the viability of an ultra-low parameter convolutional neural network specially designed for the detection of footballs on ‘on the edge’ devices. The main contribution of this paper is the exploration of integrating new design features (depth-wise separable convolutional blocks and squeezed and excitation modules) into an ultra-low parameter network and demonstrating subsequent improvements in performance. The results show that tracking the ball from Full HD images with negligibly high accu-racy is possible in real-time.

Keywords: deep learning, object detection, machine vision applications, sport, network design

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Authors: Shradha Parsekar, Suma Nair, Ajay Bailey, Binu V. S.

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Background: Concealing of cancer-related information is seen in many low-and-middle-income countries and may be associated with multiple factors. Comparatively, there is lack of information about, how breast cancers diagnosed women disclose cancer-related information to their social contacts and vice versa. To get more insights on the participant’s experience, opinions, expectations, and attitudes, a qualitative study is a suitable approach. Therefore, this study involving in-depth interviews was planned to lessen this gap. Methods: Interviews were conducted separately among breast cancer patients and their caregivers with semi-structured qualitative interview guide. Purposive and convenient sampling was being used to recruit patients and caregivers, respectively. Ethical clearance and permission from the tertiary hospital were obtained and participants were selected from the Udupi district, Karnataka, India. After obtaining a list of breast cancer diagnosed cases, participants were contacted in person and their willingness to take part in the study was taken. About 39 caregivers and 35 patients belonging to different breast cancer stages were recruited. Interviews were recorded with prior permission. Data was managed by Atlas.ti 8 software. The recordings were transcribed, translated and coded in two cycles. Most of the patients belonged to stage II and III cancer. Codes were grouped together into to whom breast cancer status was concealed to and underneath reason for the same. Main findings: followings are the codes and code families which emerged from the data. 1) Concealing the breast cancer status from social contacts other than close family members (such as extended family, neighbor and friends). Participants perceived the reasons as, a) to avoid questions which people probe (which doesn’t have answers), b) to avoid people paying courtesy visit (to inquire about the health as it is Indian culture to visit the sick person) making it inconvenient for patient and caregivers have to offer something and talk to them, c) to avoid people getting shocked (react as if cancer is different from other diseases) or getting emotional/sad, or getting fear of death d) to avoid getting negative suggestion or talking anything in front of patient as it may affect patient negatively, e) to avoid getting stigmatized, f) to avoid getting obstacle in child’s marriage. 2) Participant concealed the breast cancer status of young children as they perceived that it may a) affect studies, b) affect emotionally, c) children may get scared. 3) Concealing the breast cancer status from patients as the caregivers perceived that they have fear of a) worsening patient’s health, b) patient getting tensed, c) patient getting shocked, and d) patient getting scared. However, some participants stressed important in disclosing the cancer status to social contact/patient to make the people aware of the disease. Conclusion: The news of breast cancer spreads like electricity in the wire, therefore, patient or family avoid it for many reasons. Although, globally, due to physicians’ ethical obligations, there is an inclination towards more disclosure of cancer diagnosis and status of prognosis to the patient. However, it is an ongoing argument whether patient/social contacts should know the status especially in a country like India.

Keywords: breast cancer, concealing cancer status, India, qualitative study

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Authors: Divvela Vishnu Sai Kumar, Deepak Arora, Sheenu Rizvi

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Forecasting a cyclone through satellite images consists of the estimation of the intensity of the cyclone and predicting it before a cyclone comes. This research work can help people to take safety measures before the cyclone comes. The prediction of the intensity of a cyclone is very important to save lives and minimize the damage caused by cyclones. These cyclones are very costliest natural disasters that cause a lot of damage globally due to a lot of hazards. Authors have proposed five different CNN (Convolutional Neural Network) models that estimate the intensity of cyclones through INSAT-3D IR images. There are a lot of techniques that are used to estimate the intensity; the best model proposed by authors estimates intensity with a root mean squared error (RMSE) of 10.02 kts.

Keywords: estimating cyclone intensity, deep learning, convolution neural network, prediction models

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Authors: Amer Momani, Tarek Al-Hawari, Abdallah Alakayleh

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This study explains how to construct an actionable activity-based costing and management system to accurately track and account the total costs of architectural aluminum projects. Two ABC models were proposed to accomplish this purpose. First, the learning and development model was introduced to examine how to apply an ABC model in an architectural aluminum firm for the first time and to be familiar with ABC concepts. Second, an actual ABC model was built on the basis of the results of the previous model to accurately trace the actual costs incurred on each project in a year, and to be able to provide a quote with the best trade-off between competitiveness and profitability. The validity of the proposed model was verified on a local architectural aluminum company.

Keywords: activity-based costing, activity-based management, construction, architectural aluminum

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Authors: Eleanor Nel

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Research output is an indicator of institutional performance (and quality), resulting in increased pressure on academic institutions to perform in the research arena. Research output is further utilised to obtain research funding. Resultantly, academic institutions face significant pressure from governing bodies to provide evidence on the return for research investments. Research output has thus become a substantial discourse within institutions, mainly due to the processes linked to evaluating research output and the associated allocation of research funding. This focus on research outputs often surpasses the development of robust, widely accepted tools to additionally measure research impact at institutions. A publication writing programme, for enhancing research output, was launched at a South African university in 2011. Significant amounts of time, money, and energy have since been invested in the programme. Although participants provided feedback after each session, no formal review was conducted to evaluate the research output directly associated with the programme. Concerns in higher education about training costs, learning results, and the effect on society have increased the focus on value for money and the need to improve training, research performance, and productivity. Furthermore, universities rely on efficient and reliable monitoring and evaluation systems, in addition to the need to demonstrate accountability. While publishing does not occur immediately, achieving a return on investment from the intervention is critical. A multi-method study, guided by the New World Kirkpatrick Model (NWKM), was conducted to determine the impact of the publication writing programme for the period of 2011 to 2018. Quantitative results indicated a total of 314 academics participating in 72 workshops over the study period. To better understand the quantitative results, an open-ended questionnaire and semi-structured interviews were conducted with nine participants from a particular faculty as a convenience sample. The purpose of the research was to collect information to develop a comprehensive framework for impact evaluation that could be used to enhance the current design and delivery of the programme. The qualitative findings highlighted the critical role of a multi-stakeholder strategy in strengthening support before, during, and after a publication writing programme to improve the impact and research outputs. Furthermore, monitoring on-the-job learning is critical to ingrain the new skills academics have learned during the writing workshops and to encourage them to be accountable and empowered. The NWKM additionally provided essential pointers on how to link the results more effectively from publication writing programmes to institutional strategic objectives to improve research performance and quality, as well as what should be included in a comprehensive evaluation framework.

Keywords: evaluation, framework, impact, research output

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Authors: Lakshmi N. Reddi, Akanksha Varma Sagi

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Studies on biomimetics are largely developed, deriving inspiration from natural processes in our objective world to develop novel technologies. Recent studies are diverse in nature, making their categorization quite challenging. Based on an exhaustive survey, we developed categorizations based on either the essential elements of nature - air, water, land, fire, and space, or on form/shape, functionality, and process. Such diverse studies as aircraft wings inspired by bird wings, a self-cleaning coating inspired by a lotus petal, wetsuits inspired by beaver fur, and search algorithms inspired by arboreal ant path networks lend themselves to these categorizations. Our categorizations of biomimetic studies allowed us to define a different dimension of biomimetics. This new dimension is not restricted to inspiration from the objective world. It is based on the premise that the biological processes observed in the objective world find their reflections in our human bodies in a variety of ways. For example, the lungs provide the most efficient example for liquid-gas phase exchange, the heart exemplifies a very efficient pumping and circulatory system, and the kidneys epitomize the most effective cleaning system. The main focus of this paper is to bring out the magnificence of the cerebro-spinal system (CSS) insofar as it relates to our current computer architecture. In particular, the paper uses four key measures to analyze the differences between CSS and human- engineered computational systems. These are adaptability, sustainability, energy efficiency, and resilience. We found that the cerebrospinal system reveals some important challenges in the development and evolution of our current computer architectures. In particular, the myriad ways in which the CSS is integrated with other systems/processes (circulatory, respiration, etc) offer useful insights on how the human-engineered computational systems could be made more sustainable, energy-efficient, resilient, and adaptable. In our paper, we highlight the energy consumption differences between CSS and our current computational designs. Apart from the obvious differences in materials used between the two, the systemic nature of how CSS functions provides clues to enhance life-cycles of our current computational systems. The rapid formation and changes in the physiology of dendritic spines and their synaptic plasticity causing memory changes (ex., long-term potentiation and long-term depression) allowed us to formulate differences in the adaptability and resilience of CSS. In addition, the CSS is sustained by integrative functions of various organs, and its robustness comes from its interdependence with the circulatory system. The paper documents and analyzes quantifiable differences between the two in terms of the four measures. Our analyses point out the possibilities in the development of computational systems that are more adaptable, sustainable, energy efficient, and resilient. It concludes with the potential approaches for technological advancement through creation of more interconnected and interdependent systems to replicate the effective operation of cerebro-spinal system.

Keywords: cerebrospinal system, computer architecture, adaptability, sustainability, resilience, energy efficiency

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Authors: Marc Sader, Michiel Stock, Bernard De Baets

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Considering a large amount of adsorption data of adsorbate gases on adsorbent materials in literature, it is interesting to predict such adsorption data without experimentation. A quantitative structure-activity relationship (QSAR) is developed to correlate molecular characteristics of gases and existing knowledge of materials with their respective adsorption properties. The application of Random Forest, a machine learning method, on a set of adsorption isotherms at a wide range of partial pressures and concentrations is studied. The predicted adsorption isotherms are fitted to several adsorption equations to estimate the adsorption properties. To impute the adsorption properties of desired gases on desired materials, leave-one-out cross-validation is employed. Extensive experimental results for a range of settings are reported.

Keywords: adsorption, predictive modeling, QSAR, random forest

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Authors: Judit Vilarmau

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Generative AI is emerging rapidly and transforming higher education in many ways, occasioning new challenges and disrupting traditional models and methods. The studies and authors explored remark on the impact on the ethics, curriculum, and pedagogical methods. Students are increasingly using generative AI for study, as a virtual tutor, and as a resource for generating works and doing assignments. This point is crucial for educators to make sure that students are using generative AI with ethical considerations. Generative AI also has relevant benefits for educators and can help them personalize learning experiences and promote self-regulation. Educators must seek and explore tools like ChatGPT to innovate without forgetting an ethical and pedagogical perspective. Eighteen studies were systematically reviewed, and the findings provide implementation guidelines with pedagogical and ethical considerations.

Keywords: ethics, generative artificial intelligence, guidelines, higher education, pedagogy

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Authors: Hee Soo Kim, Ha Young Kyung

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This paper examines the role of positive emotions in human psychology. By understanding Fredrickson and Lyubomirsky et al.’s on positive emotions, one can better understand people’s intuitive understanding, mental health and well-being. Fredrickson asserts that positive emotions create positive affects and personal resources, and Lyubomirsky et al. relate such positive resources to the creation of happiness and personal development. This paper finds that positive emotions play a significant role in the learning process, and they are instrumental in creating a long-lasting repertoire of personal resources and play an essential role in the development of the intuitive understanding of life variables, resilience in coping with life challenges, and ability to build more successful lives.

Keywords: Positive emotions, positive affects, personal resources, negative emotions, development

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Authors: Wen Huei Chou, Te Lung Pan, Tsu Wen Yeh

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New media have recently received increasing attention as a new communication form. The COVID-19 outbreak has pushed people’s lifestyles into the digital age, and the drug market has infiltrated formal e-commerce platforms. The self-media boom has fostered growth in online drug myths. To set the record straight, it is imperative to develop new media-based interventions. However, the usefulness of new media on this issue has not yet been fully examined. This study selected 13 articles on the development of new media-based interventions to prevent drug abuse from Airiti Library and Pub-Med as of October 3, 2021. The key conclusions are that (1) new media have a significantly positive influence on skills, self-efficacy, and behavior; (2) most interventions package traditional course learning into new media formats; and (3) new media can create a covert, interactive environment that cannot be replicated offline, which may merit attention in future research.

Keywords: drug abuse, interventions, new media, systematic review

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Authors: Slimane Ouhmad, Abdellah Halimi

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In this work, we have applied neural networks method MLP type to a database from an array of six sensors for the detection of three toxic gases. As the choice of the number of hidden layers and the weight values has a great influence on the convergence of the learning algorithm, we proposed, in this article, a mathematical formulation to determine the optimal number of hidden layers and good weight values based on the method of back propagation of errors. The results of this modeling have improved discrimination of these gases on the one hand, and optimize the computation time on the other hand, the comparison to other results achieved in this case.

Keywords: MLP Neural Network, back-propagation, number of neurons in the hidden layer, identification, computing time

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Authors: Abraham Motlhabane

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In most practical-related science lessons, the focus is on completing the experimental procedure as directed by the teacher. However, the scientific discourse among learners themselves and teacher–learner discourse about scientific processes, scientific inquiry and the nature of science should play an important role in the teaching and learning of science. This means the incorporation of inquiry-based activities aimed at sparking debates about scientific concepts. This article analyses a science lesson presented by a teacher to his colleagues acting as learners. Six lessons were presented and transcribed. One of the lessons has been used for this study as the basis for the events as they unfolded during the lesson. Data was obtained through direct observations and the use of a predetermined observation schedule. Field notes were compiled during teacher preparations and the presentation of the lessons.

Keywords: discourse, inquiry, practical work, science, scientific

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Authors: Debjit Ray

Abstract:

Horizontal gene transfer (HGT) and recombination leads to the emergence of bacterial antibiotic resistance and pathogenic traits. HGT events can be identified by comparing a large number of fully sequenced genomes across a species or genus, define the phylogenetic range of HGT, and find potential sources of new resistance genes. In-depth comparative phylogenomics can also identify subtle genome or plasmid structural changes or mutations associated with phenotypic changes. Comparative phylogenomics requires that accurately sequenced, complete and properly annotated genomes of the organism. Assembling closed genomes requires additional mate-pair reads or “long read” sequencing data to accompany short-read paired-end data. To bring down the cost and time required of producing assembled genomes and annotating genome features that inform drug resistance and pathogenicity, we are analyzing the performance for genome assembly of data from the Illumina NextSeq, which has faster throughput than the Illumina HiSeq (~1-2 days versus ~1 week), and shorter reads (150bp paired-end versus 300bp paired end) but higher capacity (150-400M reads per run versus ~5-15M) compared to the Illumina MiSeq. Bioinformatics improvements are also needed to make rapid, routine production of complete genomes a reality. Modern assemblers such as SPAdes 3.6.0 running on a standard Linux blade are capable in a few hours of converting mixes of reads from different library preps into high-quality assemblies with only a few gaps. Remaining breaks in scaffolds are generally due to repeats (e.g., rRNA genes) are addressed by our software for gap closure techniques, that avoid custom PCR or targeted sequencing. Our goal is to improve the understanding of emergence of pathogenesis using sequencing, comparative genomics, and machine learning analysis of ~1000 pathogen genomes. Machine learning algorithms will be used to digest the diverse features (change in virulence genes, recombination, horizontal gene transfer, patient diagnostics). Temporal data and evolutionary models can thus determine whether the origin of a particular isolate is likely to have been from the environment (could it have evolved from previous isolates). It can be useful for comparing differences in virulence along or across the tree. More intriguing, it can test whether there is a direction to virulence strength. This would open new avenues in the prediction of uncharacterized clinical bugs and multidrug resistance evolution and pathogen emergence.

Keywords: genomics, pathogens, genome assembly, superbugs

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Authors: Gabriel Chavira, Jorge Orozco, Salvador Nava, Eduardo Álvarez, Julio Rolón, Roberto Pichardo

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Ambient Intelligence promotes a shift in computing which involves fitting-out the environments with devices to support context-aware applications. One of main objectives is the reduction to a minimum of the user’s interactive effort, the diversity and quantity of devices with which people are surrounded with, in existing environments; increase the level of difficulty to achieve this goal. The mobile phones and their amazing global penetration, makes it an excellent device for delivering new services to the user, without requiring a learning effort. The environment will have to be able to perceive all of the interaction techniques. In this paper, we present the PICTAC model (Perceiving touch Interaction through TAgging Context), which similarly delivers service to members of a research group.

Keywords: ambient intelligence, tagging context, touch interaction, touching services

Procedia PDF Downloads 376