Search results for: learning loss

Authors: Nagaraju Pendam, C. P. Vardhani

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A simple technology–compatible design of silicon-on-insulator based 1×2 optical power splitter is proposed. For developing large area Opto-electronic Silicon-on-Insulator (SOI) devices, the power splitter is a key passive device. The SOI rib- waveguide dimensions (height, width, and etching depth, refractive indices, length of waveguide) leading simultaneously to single mode propagation. In this paper a low loss optical power splitter is designed by using R Soft cad tool and simulated by Beam propagation method, here s-bend waveguides proposed. We concentrate changing the refractive index difference, branching angle, width of the waveguide, free space wavelength of the waveguide and observing transmitted power, effective refractive index in the designed waveguide, and choosing the best simulated results to be fabricated on silicon-on insulator platform. In this design 1550 nm free spacing are used.

Keywords: beam propagation method, insertion loss, optical power splitter, rib waveguide, transmitted power

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Authors: Adel Edwar Waheeb Louka

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Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deeplearning, image processing, machine learningSarapin, intraarticular, chronic knee pain, osteoarthritisFNS, trauma, hip, neck femur fracture, minimally invasive surgery

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Authors: S. Djebali, S. Larbi, A. Bilek

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The present work aims at contributing to the study of the complex phenomenon of wear of pin on disc contact in dry sliding friction between two material couples (bronze/steel and unsaturated polyester virgin and charged with graphite powder/steel). The work consists of the determination of the coefficient of friction, the study of the influence of the tribological parameters on this coefficient and the determination of the mass loss and the wear rate of the pin. This study is also widened to the highlighting of the influence of the addition of graphite powder on the tribological properties of the polymer constituting the pin. The experiments are carried out on a pin-disc type tribometer that we have designed and manufactured. Tests are conducted according to the standards DIN 50321 and DIN EN 50324. The discs are made of annealed XC48 steel and quenched and tempered XC48 steel. The main results are described here after. The increase of the normal load and the sliding speed causes the increase of the friction coefficient, whereas the increase of the percentage of graphite and the hardness of the disc surface contributes to its reduction. The mass loss also increases with the normal load. The influence of the normal load on the friction coefficient is more significant than that of the sliding speed. The effect of the sliding speed decreases for large speed values. The increase of the amount of graphite powder leads to a decrease of the coefficient of friction, the mass loss and the wear rate. The addition of graphite to the UP resin is beneficial; it plays the role of solid lubricant.

Keywords: bronze, friction coefficient, graphite, mass loss, polyester, steel, wear rate

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Authors: Senol Dogan, Gunay Karli

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Identification of relevant publications based on a Medline query is time-consuming and error-prone. An all based process has the potential to solve this problem without any manual work. To the best of our knowledge, our study is the first to investigate the ability of machine learning to identify relevant articles accurately. 5 different machine learning algorithms were tested using 23 predictors based on several metadata fields attached to publications. We find that the Boosted model is the best-performing algorithm and its overall accuracy is 96%. In addition, specificity and sensitivity of the algorithm is 97 and 93%, respectively. As a result of the work, we understood that we can apply the same procedure to understand cancer gene expression big data.

Keywords: prediction of publications, machine learning, algorithms, bariatric surgery, comparison of algorithms, boosted, tree, logistic regression, ANN model

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Authors: Yifan Fan, Xudong Luo, Pingping Lin

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Nowadays, dialogue systems increasingly become the way for humans to access many computer systems. So, humans can interact with computers in natural language. A dialogue system consists of three parts: understanding what humans say in natural language, managing dialogue, and generating responses in natural language. In this paper, we survey deep learning based methods for dialogue management, response generation and dialogue evaluation. Specifically, these methods are based on neural network, long short-term memory network, deep reinforcement learning, pre-training and generative adversarial network. We compare these methods and point out the further research directions.

Keywords: dialogue management, response generation, deep learning, evaluation

Procedia PDF Downloads 151

Authors: Titap Yazicioglu

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Purpose: Losing an eye due to trauma is a challenging situation that reduces the quality of life by causing physical, cosmetic, and serious psychological problems. This study aimed to evaluate the effect of aesthetic rehabilitation on the change in psychological status and quality of life of patients with eye loss resulting in phthisis bulbi. Materials and Methods: The files of 25 males and 15 females with an average age of 27.5 years who had trauma-related phthisic eye and had applied to the Department of Ophthalmology at the Dr. Lütfi Kırdar Kartal Education and Research Hospital, Istanbul, Turkey, for aesthetic rehabilitation during the years 2015-19 were retrospectively analyzed. The Beck Depression Inventory (BDI), Beck Anxiety Scale(BAS), and Short Form 36 quality-of-life survey (SF-36) were used to collect data on admission and one-year follow-up. Results: Of the patients reviewed, 65% stated that eye loss had caused their avoidance of family and social environments; 30% had moderate anxiety and depression. The post-operative sub-dimension scores of general health, emotional role function, and physical and social functions were statistically significant (p = 0.001; p<0.01), but the variations in the sub-dimension scores of vitality, mental health, and total physical health were not (p>0.05). Conclusion: Lossing an eye is a traumatic event that can affect all aspects of a person’s social and professional life. A patient who has suffered from the psychological damage of physical loss of eye needs a prosthesis that can give the desired function and appearance in different aspects of life.

Keywords: eye loss, phthisis bulbi, quality of life, psychological trauma

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Authors: Bello Ali

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The use of Information and Communication Technology (ICT) in tertiary institutions by lecturers and students has become a necessity for the enhancement of quality teaching and learning. This study examined availability, accessibility and utilization of ICT in Teaching-Learning Islamic Studies in Colleges of Education, North-East, Nigeria. The study adopted multi-stage sampling technique, in which, five out of the eleven Colleges of Education (both Federal and State owned) were purposively selected for the study. Primary data was drawn from the respondents by the use of questionnaire, interviews and observations. The results of the study, generally, indicate that the availability and accessibility to ICT facilities in Colleges of Education in North-East, Nigeria, especially in teaching/learning delivery of Islamic studies were relatively inadequate and rare to lecturers and students. The study further reveals that the respondents’ level of utilization of ICT is low and only few computer packages and internet services were involved in the ICT utilization, which is yet to reach the real expected situation of the globalization and advancement in the application of ICT if compared to other parts of the world, as far as the teaching and learning of Islamic studies is concerned. Observations and conclusion were drawn from the findings and finally, recommendations on how to improve on ICT availability, accessibility and utilization in teaching/ learning were suggested.

Keywords: accessibility, availability, college of education, ICT, Islamic studies, learning, North-East, teaching, utilization

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Authors: Ratna Elizabeth

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Motivation is a very important factor since it contributes a lot to the students’ success in learning a language. Using authentic materials is believed as a mean of increasing the motivation. The materials define as authentic if they are not specifically written for the purpose of language teaching. They are genuine spoken or written language data which are drawn from many different sources. The intention of this study is to investigate the impact of using of authentic materials on students’ motivation. A single case study is conducted to the grade 9 students who learn Indonesian Language as a Foreign Language (ILFL) at an international school in Jakarta, Indonesia. Questionnaires are also distributed to the students to know their perceptions on the using of authentic materials. The results show that the using of authentic materials has increased the students’ motivation in learning the language.

Keywords: authentic materials, ILFL, language learning, motivation

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Authors: Jiraporn Adchariyaprasit

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The aesthetics of language in Thai poetry are emerged from the combination of sounds and meanings. The appreciation of such beauty can be achieved by means of education, acquisition of knowledge, and training. This research aims to study the learning process of aesthetics of language in Thai poetry for high school teachers in Bangkok and nearby provinces. There are 10 samples selected by purposive sampling for in-depth interviews. According to the research, there are four patterns in the learning process of aesthetics of language in Thai poetry which are 1) the study of characteristics and patterns of poetry, 2) the training of poetic reading, 3) the study of social and cultural contexts of poetry’s creation, and 4) the study of other sciences related to poetry such as linguistics, traditional dance, and so on.

Keywords: aesthetics, poetry, Thai poetry, poetry learning

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Authors: Ajay Krishan Tiwari

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Studies on educational psychology have demonstrated the interest of the child's psychological and cognitive environment in the quality of their school commitment. The educational psychologist works with children and adolescents to remedy these factors. The task of the educational psychologist is to liberate the child and adolescent intellectually. Its purpose is to harmonize the child with the system of learning. Psychoanalytic support requires practice in creativity, reading, math, and meditation methods. The goal of educational psychology is to restore the desire and enjoyment of learning. The educational psychologist takes into account the concerns and personality traits that hinder student learning and restores self-esteem. Educational psychologists specialize in supporting children or adolescents who have a different approach to learning. Its role is to consider the child as a whole (cognitive, affective, physical, school, family factors, etc.). It welcomes the child's way of thinking and participates in its development. It is an essential point of contact between the child and his school environment.

Keywords: educational psychology, educational theories, psychologist, cognitive environment, psychoanalytic support, enjoyment of learning

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Authors: Fink Nir

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Soldiers within armored vehicles are exposed to continuous noise reaching levels as high as 120 dB. The use of hearing protection devices (HPD) may attenuate noise by as 25 dB, but attenuated noise reaching the ear is still harmful and may result in hearing loss. Hearing conservation programs in the military suggest methods to manage the harmful effects of noise. These include noise absorption within vehicles, evaluating HPD's performance, limiting time exposure, and providing guidance.

Keywords: armored vehicle noise, hearing loss, hearing protection devices, military noise, noise attenuation

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Authors: Jiangxia Han, Liang Xue, Keda Chen

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Despite the significant progress over the last decades in reservoir simulation using numerical discretization, meshing is complex. Moreover, the high degree of freedom of the space-time flow field makes the solution process very time-consuming. Therefore, we present Physics-Informed Convolutional Neural Networks(PICNN) as a hybrid scientific theory and data method for reservoir modeling. Besides labeled data, the model is driven by the scientific theories of the underlying problem, such as governing equations, boundary conditions, and initial conditions. PICNN integrates governing equations and boundary conditions into the network architecture in the form of a customized convolution kernel. The loss function is composed of data matching, initial conditions, and other measurable prior knowledge. By customizing the convolution kernel and minimizing the loss function, the neural network parameters not only fit the data but also honor the governing equation. The PICNN provides a methodology to model and history-match flow and transport problems in porous media. Numerical results demonstrate that the proposed PICNN can provide an accurate physical solution from a limited dataset. We show how this method can be applied in the context of a forward simulation for continuous problems. Furthermore, several complex scenarios are tested, including the existence of data noise, different work schedules, and different good patterns.

Keywords: convolutional neural networks, deep learning, flow and transport in porous media, physics-informed neural networks, reservoir simulation

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Authors: Sabahat Nadeem, Farman Ali Khan

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Emotions are considered as a vital factor affecting the process of information handling, level of attention, memory capacity and decision making. Latest e-Learning systems are therefore taking into consideration the effective state of learners to make the learning process more effective and enjoyable. One such use of user’s affective information is in the systems that tend to regulate users’ emotions to a state optimally desirable for learning. So for, this objective has been tried to be achieved with the help of teaching strategies, background music, guided imagery, video clips and odors. Nevertheless, we know that colors can affect human emotions. Relationship between color and emotions has a strong influence on how we perceive our environment. Similarly, the colors of the interface can also affect the user positively as well as negatively. This affective behavior of color and its use as emotion regulation agent is not yet exploited. Therefore, this research proposes a Color-based Emotion Regulation Model (CERM), a new framework that can automatically adapt its colors according to user’s emotional state and her personality type and can help in producing a desirable emotional effect, aiming at providing an unobtrusive emotional support to the users of e-learning environment. The evaluation of CERM is carried out by comparing it with classical non-adaptive, static colored learning management system. Results indicate that colors of the interface, when carefully selected has significant positive impact on learner’s emotions.

Keywords: effective learning, e-learning, emotion regulation, emotional design

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Authors: Yan Ma

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Parents in China now are of great enthusiasm to outsource extracurricular lessons and activities to ensure their children’s English learning. This study draws on one year of ethnographic observations and interviews with parents and children in 6 families in Shaoxing, a small city in East China, to explore how parents in different social classes differ in their ideology and investment practice towards their children’s English education. Through comparative analysis, the study reveals though all the families acknowledge the importance of English and there are great similarities among families in the same social class, differences are distinct among those in different social classes with regard to how they perceived the importance and what measures they take. The results also reflect China’s sociocultural and socioeconomic factors that underlined the heated wave of English learning as well as the social, cultural and economic conditions of different families that exert a decisive influence on their children’s learning experience.

Keywords: family background, extracurricular English learning, language ideologies, language management

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Authors: Deependra Prasad Sarraf, Gajendra Prasad Rauniar, Robin Maskey, Rajiv Maharjan, Ashish Shrestha, Ramayan Prasad Kushwaha

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Objectives: To assess the perception of faculties towards online teaching-learning activities conducted during the COVID-19 pandemic and to identify barriers and facilitators to conducting online teaching-learning activities in our context. Methods: A cross-sectional study was conducted among faculties at B. P. Koirala Institute of Health Sciences using a 26-item semi-structured questionnaire. A Google Form was prepared, and its link was sent to the faculties via email. Descriptive statistics were calculated, and findings were presented as tables and graphs. Results: Out of 158 faculties, the majority were male (66.46%), medical faculties (85.44%), and assistant professors (46.84%). Only 16 (10.13%) faculties had received formal training regarding preparing and/or delivering online teaching learning activities. Out of 158, 133 (84.18%) faculties faced technical and internet issues. The most common advantage and disadvantage of online teaching learning activities perceived by the faculties were ‘not limited to time or place’ (94.30%) and ‘lack of interaction with the students’ (82.28%), respectively. Majority (94.3%) of them had a positive perception towards online teaching-learning activities conducted during COVID-19 pandemic. Slow internet connection (91.77%) and frequent electricity interruption (82.91%) were the most common perceived barriers to online teaching-learning. Conclusions: Most of the faculties had a positive perception towards online teaching-learning activities. Academic leaders and stakeholders should provide uninterrupted internet and electricity connectivity, training on online teaching-learning platform, and timely technical support.

Keywords: COVID-19 pandemic, faculties, medical education, perception

Procedia PDF Downloads 157

Authors: Khumbuzile M. Ngcobo, Seraphin D. Eyono Obono

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Science and technology has a major impact on many societal domains such as communication, medicine, food, transportation, etc. However, this dominance of modern technology can have a negative unintended impact on indigenous systems, and in particular on indigenous foods. This problem serves as a motivation to this study whose aim is to examine the perceptions of learners on the usefulness of Information and Communication Technologies (ICT's) for learning about indigenous foods. This aim will be subdivided into two types of research objectives. The design and identification of theories and models will be achieved using literature content analysis. The objective on the empirical testing of such theories and models will be achieved through the survey of Hospitality studies learners from different schools in the iLembe and Umgungundlovu Districts of the South African Kwazulu-Natal province. SPSS is used to quantitatively analyse the data collected by the questionnaire of this survey using descriptive statistics and Pearson correlations after the assessment of the validity and the reliability of the data. The main hypothesis behind this study is that there is a connection between the demographics of learners, their perceptions on the usefulness of ICTs for learning about indigenous foods and the following personality an e-learning related theories constructs: computer self-efficacy, trust in ICT systems, and conscientiousness; as suggested by existing studies on learning theories. This hypothesis was fully confirmed by the survey conducted by this study except for the demographic factors where gender and age were not found to be determinant factors of learners’ perceptions on the usefulness of ICT's for learning about indigenous foods.

Keywords: e-learning, indigenous foods, information and communication technologies, learning theories, personality

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Authors: Polina Pekker

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This work analyzes the role of lecturers in e-learning in Russia. It is based on qualitative research of lecturers who conduct courses on Russian national platforms of open education. The platform is based on edx software (provider of massive open online courses). The interviews with e-learning lecturers were conducted: from December 2015 till January 2016 and from April 2016 till May 2016. The results of interviews (face-to-face, telephone, skype) show, firstly, the difference between the role of lecturers in e-learning and in traditional education and, secondly, that the competition between lecturers is high in Russia. The results of interviews in Russia show that e-learning lecturer should have several special professional competences: the ability to keep attention of audiences without real contact, the ability to work on camera and competences related with e-learning course support (test, forum, communication on forum and etc.) It is concluded that lecturers need special course on acting and speech skills and on conducting and organizing of e-learning course in Russia. It is planned to conduct French study. When results from French research will be totally ready, they will be compared to Russian. As well French platform, France Universite Numerique, was launched earlier, in January 2014, so Russian lecturers should get best practice from the French colleagues.

Keywords: e-courses lecturer, e-learning, professional competences of lecturers, national Russian and French platforms of open education

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Authors: Paul Lam, Chi Him Chan, Alan Tse

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Language laboratories have been widely used in language learning, starting in the middle of the last century as one of the earliest forms of educational technology. They are designed to assist students’ language learning with technological innovations. Traditional language laboratories provide individual workstations that allow students to access multimedia language resources. In this type of facility, students can train their listening and speaking abilities, and teachers can also assess the performance of an individual student. Although such a setting promotes a student-centered pedagogy by encouraging students to work at their own pace and according to their own needs, it still favours a traditional, behaviourist language learning pedagogy which focuses on repetitive drilling. The change of pedagogies poses challenges to both the teachers and the facilities. The peer-learning pedagogy advocates that language learning should focus on the social aspect, which emphasizes the importance of everyday communication in language learning. The self-access, individual workstation language laboratories may not be able to provide the flexibility for interaction in the new pedagogies. Modern advancement in technology is another factor that drove our language laboratory renovation. In particular, mobile and wireless technology enabled the use of smaller and more flexible devices, making possible much clever use of space. The Chinese University of Hong Kong (CUHK) renovated nine existing language laboratories to provide lighter and more advanced equipment, movable tables, and round desks. These facilities allow more flexibility and encourage students’ interaction. It is believed that the renovated language laboratories can serve different peer learning activities and thus support peer-learning pedagogies in language teaching and learning. A survey has been conducted to collect comments from the teachers who have used the renovated language laboratories and received forty-four response. The teachers’ comments reveal that they experienced different challenges in using the renovated language laboratories, and there is a need to provide guidance to teachers during the technological and pedagogical transition. For example, teachers need instruction on using the newly installed devices such as touch-monitor and visualizer. They also need advice on planning new teaching and learning activities. Nevertheless, teachers appreciated that the renovated language laboratories are flexible and provide more spaces for different learning activities.

Keywords: language laboratories, language learning, peer-learning, student interaction

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Authors: Yolina A. Petrova, Georgi I. Petkov

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The paper presents a symbolic model for category learning and categorization (called RoleMap). Unlike the other models which implement learning in a separate working mode, role-governed category learning and categorization emerge in RoleMap while it does its usual reasoning. The model is based on several basic mechanisms known as reflecting the sub-processes of analogy-making. It steps on the assumption that in their everyday life people constantly compare what they experience and what they know. Various commonalities between the incoming information (current experience) and the stored one (long-term memory) emerge from those comparisons. Some of those commonalities are considered to be highly important, and they are transformed into concepts for further use. This process denotes the category learning. When there is missing knowledge in the incoming information (i.e. the perceived object is still not recognized), the model makes anticipations about what is missing, based on the similar episodes from its long-term memory. Various such anticipations may emerge for different reasons. However, with time only one of them wins and is transformed into a category member. This process denotes the act of categorization.

Keywords: analogy-making, categorization, category learning, cognitive modeling, role-governed categories

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Authors: Petcharat Kerdonfag, Surasak Taneepanichskul, Winai Wadwongtham

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Background: Although there have not been effective treatments for Noise Induced Hearing Loss (NIHL), it can be definitely preventable with promoting the use of Hearing Protection devices (HPDs) among workers who have been exposed to excessive noise for a long period. Objectives: The objectives of this study were to explore the use of HPDs among steel industrial workers in the high noise level zone in Samut Prakan province, Thailand and to examine the relationships of the HPDs use and hearing loss. Materials and Methods: In this cross-sectional study, eligible ninety-three participants were recruited in the designated zone of higher noise (> 85dBA) of two factories, using simple random sampling. The use of HPDs was gathered by the self-record form, examined and confirmed by the researcher team. Hearing loss was assessed by the audiometric screening at the regional Samut Prakan hospital. If an average threshold level exceeds 25 dBA at high frequency (4 and 6 Hz) in each ear, participants would be lost of hearing. Data were collected from October to December, 2016. All participants were examined by the same examiners for the validity. An Audiometric testing was performed with the participants who have been exposed to high noise levels at least 14 hours from workplace. Results: Sixty participants (64.5%) had secondary level of education. The average mean score of percent time of using HPDs was 60.5% (SD = 25.34). Sixty-seven participants (72.0%) had abnormal hearing which they have still needed to increase lower percent time of using HPDs (Mean = 37.01, SD = 23.81) than those having normal hearing (Mean = 45.77, SD = 28.44). However, there was no difference in the mean average of percent time of using HPDs between these two groups.Conclusion: The findings of this study have confirmed that the steel industrial workers still need to be motivated to use HPDs regularly. Future research should pay more attentions for creating a meaningful innovation to steel industrial workers.

Keywords: hearing protection devices, noise induced hearing loss, audiometric testing, steel industry

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Authors: Susan Diamond

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Machine Learning workloads have traditionally been run in high-performance computing (HPC) environments, where users log in to dedicated machines and utilize the attached GPUs to run training jobs on huge datasets. Training of large neural network models is very resource intensive, and even after exploiting parallelism and accelerators such as GPUs, a single training job can still take days. Consequently, the cost of hardware is a barrier to entry. Even when upfront cost is not a concern, the lead time to set up such an HPC environment takes months from acquiring hardware to set up the hardware with the right set of firmware, software installed and configured. Furthermore, scalability is hard to achieve in a rigid traditional lab environment. Therefore, it is slow to react to the dynamic change in the artificial intelligent industry. Watson Deep Learning as a service, a cloud-based deep learning platform that mitigates the long lead time and high upfront investment in hardware. It enables robust and scalable sharing of resources among the teams in an organization. It is designed for on-demand cloud environments. Providing a similar user experience in a multi-tenant cloud environment comes with its own unique challenges regarding fault tolerance, performance, and security. Watson Deep Learning as a service tackles these challenges and present a deep learning stack for the cloud environments in a secure, scalable and fault-tolerant manner. It supports a wide range of deep-learning frameworks such as Tensorflow, PyTorch, Caffe, Torch, Theano, and MXNet etc. These frameworks reduce the effort and skillset required to design, train, and use deep learning models. Deep Learning as a service is used at IBM by AI researchers in areas including machine translation, computer vision, and healthcare. 

Keywords: deep learning, machine learning, cognitive computing, model training

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Authors: Frederick Otite Ighovojah

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Corrosion in the oil and gas industries is one of the most common causes of failure. Such failure includes leaks in above-ground storage tanks (AGST). The involvement of microorganisms in the corrosion process in AGST systems is often ignored, and this outlines the need to investigate the effect of microbial corrosion in oil and gas facilities. This study's methodology comprised gathering generated water samples from a nearby AGST oil facility that was operating, which were then equally divided into two batch reactors, 1 and 2. Each batch reactor was filled with five prepared X60 coupons using sterilized forceps. To provide nutrients for the microorganisms in batch reactor 1 during the test period, 2g of NPK 15- 15-15 fertilizer was added on a weekly basis. To kill the microorganisms and significantly lower their concentration in the generated water, 5ml of dissolved ozone (a biocide) with a 0.5ppm concentration was added to batch reactor 2. The weight loss measurement (WLM) was used to evaluate for corrosion. Coupons were removed from each batch reactor, and weight loss was measured at every interval of 336 hrs for 2016 hrs. The overall results obtained indicated that coupons from the batch 1 reactor showed a higher corrosion rate and higher mass loss, and this was due to the metabolic production of an aggressive compound in the medium.

Keywords: AGST, microbial corrosion, reactor, X60 steel

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Authors: Xun Li, Haojie Wang

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Federated learning is a kind of distributed training and centralized training mode, which is of great value in the protection of user privacy. In order to solve the problem that the model is vulnerable to backdoor attacks in federated learning, a backdoor attack detection method based on a weighted k-medoids algorithm is proposed. First of all, this paper collates the update parameters of the client to construct a vector group, then uses the principal components analysis (PCA) algorithm to extract the corresponding feature information from the vector group, and finally uses the improved k-medoids clustering algorithm to identify the normal and backdoor update parameters. In this paper, the backdoor is implanted in the federation learning model through the model replacement attack method in the simulation experiment, and the update parameters from the attacker are effectively detected and removed by the defense method proposed in this paper.

Keywords: federated learning, backdoor attack, PCA, k-medoids, backdoor defense

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Authors: Anum Ali, Kashaf ad Dooja, Asif Saleem

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The future smart cities trend will be towards Internet of Things (IoT); IoT creates dynamic connections in a ubiquitous manner. Smart cities offer ease and flexibility for daily life matters. By using small devices that are connected to cloud servers based on IoT, network traffic between these devices is growing exponentially, whose security is a concerned issue, since ratio of cyber attack may make the network traffic vulnerable. This paper discusses the latest machine learning approaches in related work further to tackle the increasing rate of cyber attacks, machine learning algorithm is applied to IoT-based network traffic data. The proposed algorithm train itself on data and identify different sections of devices interaction by using supervised learning which is considered as a classifier related to a specific IoT device class. The simulation results clearly identify the attacks and produce fewer false detections.

Keywords: IoT, traffic security, deep learning, classification

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Authors: Anastassis Kozanitis, Diane Leduc, Alain Stockless

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This paper presents preliminary results from a two-year funded research program looking to analyze and understand the relationship between high cognitive engagement, higher order cognitive processes employed in situations of complex learning tasks, and the use of active learning pedagogies in engineering undergraduate programs. A mixed method approach was used to gauge student engagement and their cognitive processes when accomplishing complex tasks. Quantitative data collected from the self-report cognitive engagement scale shows that deep learning approach is positively correlated with high levels of complex learning tasks and the level of student engagement, in the context of classroom active learning pedagogies. Qualitative analyses of in depth face-to-face interviews reveal insights into the mechanisms influencing students’ cognitive processes when confronted with open-ended problem resolution. Findings also support evidence that students will adjust their level of cognitive engagement according to the specific didactic environment.

Keywords: cognitive engagement, deep and shallow strategies, engineering programs, higher order cognitive processes

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Authors: Cihan Cilbircioğlu

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Allium sativum L.(garlic) and Allium. cepa L. (onion) are the most common species of the Allium spp. and are produced at the very high rate all over the world. The yield loss caused by pests is the most important problem in the production of these crops. In the absence of control measures, yield loss would be around 35% on average. The yield loss sometimes depending on the pest species and population density can reach about 100%. Mites and nematodes are the most important pests of them. These pests that cause damage to A. sativum and A. cepa shows a wide range of taxonomic categories. The number of common pest mite and nematode species that cause damage to either A. sativum and A. cepa are over 20 species. In this study, detailed information on morphology, life cycle, management, and symptoms of the economically most important harmful important mite (acari) and nematode species of onion and garlic has been provided through careful survey of corresponding researches in Turkey and given information about new practices and approaches on their controls.

Keywords: onion, garlic, pest, acari, nematoda control methods, Turkey

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Authors: Luis H. Gonzalez-Guerra, Armandina J. Leal-Flores

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Students attending classrooms nowadays are habituated to use digital devices all the time and for multiple things. They have been familiar with digital technology throughout their lives so they have developed skills that should be naturally adopted as part of their study strategies. New learning styles require taking in consideration the use of models that support and promote student motivation for learning and development of their creative thinking skills. To achieve student learning in programming courses, different strategies are used. One of them is a collaboration between students, which is a tool which faculty can take advantage of when teaching these kinds of courses. Moreover, cooperation is an essential skill that society should reinforce in order to promote a healthy social environment and cohabitation. Nevertheless, students will still require support and advice to get a complete and correct programming solution to successfully address and solve the problems given throughout the course. This paper present a model where collaboration between students is associated with an automatic tutoring platform providing an excellent approach for the individual learning in collaborative activities in programming courses, and also motivates students to increase their knowledge regarding the topics covered in the classroom.

Keywords: automatic tutoring, collaboration learning, creative thinking, motivation

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Authors: Daniel Ecler

Abstract:

The aim of this paper was to find out how Chinese university students perceive distance learning compared to full-time teaching, to reveal its advantages and disadvantages, and to try to find what elements could be implemented in regular full-time teaching in order to make it more effective. Recent events have shown that online teaching has a significant role to play in the field of education and needs to be given increased attention and scrutiny. For this purpose, a research survey was conducted using semi-structured questionnaires, which aimed to determine the attitudes of Chinese university students to the phenomenon of distance learning. The results of this survey revealed that most students prefer distance learning to full-time teaching, mainly because it gives them more freedom to participate in teaching, regardless of the environment in which they are currently located. In conclusion, it is necessary to mention that the possibility to participate virtually in teaching from anywhere is a huge advantage that could become part of regular teaching in the future. However, further research into this issue will be necessary.

Keywords: distance learning, full-time teaching, Chinese college students, cultural background

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Authors: Matthias Grunke

Abstract:

In this qualitative study, we interviewed a young man with learning disabilities who played professional baseball for two years. Individuals with severe academic challenges constitute one of the most vulnerable groups of our society. Science has to find ways on how to arm them against life’s challenges and help them to cope with the many risk factors that they are usually confronted with. Team sports like baseball seem to be a suitable means for that purpose. In the interview, our participant talked about his life as a student with severe learning difficulties and related how his career in baseball made his academic challenges appear much less significant. He gave some meaningful insights into what helped him to build a happy and fulfilling life for himself, not only in spite of his challenges but also because of what he's learning disabilities taught him. Support from significant others, a sense of purpose, his fighting spirit ignited by sports, and the success that he experienced on the baseball field were among the most relevant factors. Overall, this study highlights the importance of finding an outlet for young people with learning disabilities where their academic difficulties retreat into the background and their talents are validated.

Keywords: baseball, inclusion, learning disabilities, resilience

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Authors: Shoba Bandi-Rao

Abstract:

The lack of college readiness is one of the major contributors to low graduation rates at community colleges, especially among educationally and financially disadvantaged students. About 45% of underprepared high school graduates are required to complete ‘remedial’ reading/writing courses before they can begin taking college-level courses. Mobile apps present ‘bite-size’ learning materials that can be useful for practicing certain literacy skills, such as vocabulary learning. The convenience of mobile phones is ideal for a majority of students at community colleges who hold full or part-time jobs. Mobile apps allow students to learn during small ‘chunks’ of time available to them outside of the class—during subway commute, between classes, etc. Learning with mobile apps is a relatively new area in research, and their effectiveness for learning new words has been inconclusive. Using Mishra & Koehler’s TPCK theoretical framework, this study explored the effectiveness of the mobile app (Quizlet) for learning one hundred common college-level words in ‘remedial’ writing class over one semester. Each week, before coming to class, students studied a list of 10-15 words presented in context within sentences. Students came across these words in the article they read in class making their learning more meaningful. A pre and post-test measured the number of words students knew, learned and remembered. Statistical analysis shows that students performed better by 41% on the post-test indicating that the mobile app was helpful for learning words. Students also completed a short survey each week that sought to determine the amount of time students spent on the vocabulary app. A positive correlation was found between the amount of time spent on the mobile app and the number of words learned. The goal of this research is to capitalize on the convenience of smartphones to (1) better prepare them for college-level course work, and (2) contribute to current literature on mobile learning.

Keywords: mobile learning, vocabulary learning, literacy skills, Quizlet

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