Search results for: cognitive behavioral training

Authors: Nishant Singh, Christian Huyck, Vaibhav Gandhi, Alexander Jones

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A robotic arm and hand controlled by simulated neurons is presented. The robot makes use of a biological neuron simulator using a point neural model. The neurons and synapses are organised to create a finite state automaton including neural inputs from sensors, and outputs to effectors. The robot performs a simple pick-and-place task. This work is a proof of concept study for a longer term approach. It is hoped that further work will lead to more effective and flexible robots. As another benefit, it is hoped that further work will also lead to a better understanding of human and other animal neural processing, particularly for physical motion. This is a multidisciplinary approach combining cognitive neuroscience, robotics, and psychology.

Keywords: cell assembly, force sensitive resistor, robot, spiking neuron

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Authors: Daniia Nigmatullina, Vlada Kugurakova, Maxim Talanov

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We present a methodology and our plans of anthropomorphic social agent visualization. That includes creation of three-dimensional model of the virtual companion's head and its facial expressions. Talking Head is a cross-disciplinary project of developing of the human-machine interface with cognitive functions. During the creation of a realistic humanoid robot or a character, there might be the ‘uncanny valley’ problem. We think about this phenomenon and its possible causes. We are going to overcome the ‘uncanny valley’ by increasing of realism. This article discusses issues that should be considered when creating highly realistic characters (particularly the head), their facial expressions and speech visualization.

Keywords: anthropomorphic social agent, facial animation, uncanny valley, visualization, 3D modeling

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Authors: Corey Clay

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A fraction of mechanical trainees (graduate students) from underrepresented groups (URM) has steadily increased through targeted recruitment and interventions to support their success during training. However, this trend has yet to translate to a connected increase in the number of faculty from these underrepresented groups. The purpose here is to look at proven strategies that departments and research institutions can develop to increase faculty hiring and promotion equity to address the lack of racial and gender diversity among their faculty. We will look at this process through an Adlerian lens, i.e., Adler theorized social interest as “a feeling of community, an orientation to living cooperatively with others, and a lifestyle that values the common good above one’s own interests and desires.” This abstract will look at implementing a cogent DEI strategy through an Adlerian perspective.

Keywords: diversity, equity, inclusion, adlerian

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Authors: Germans Natuhwera, Peter Ellis, Acuda Wilson, Anne Merriman, Martha Rabwoni

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Objective: The aim of the study was to diagnose the socio-economic burden and impact of a diagnosis of cervical cancer (CC) in rural women in the context of low-resourced country Uganda, using a phenomenological enquiry. Methods: This was a multi-site phenomenological inquiry, conducted at three hospice settings; Mobile Hospice Mbarara in southwestern, Little Hospice Hoima in Western, and Hospice Africa Uganda Kampala in central Uganda. A purposive sample of women with a histologically confirmed diagnosis of CC was recruited. Data was collected using open-ended audio-recorded interviews conducted in the native languages of participants. Interviews were transcribed verbatim in English, and Braun and Clarke’s (2019) framework of thematic analysis was used. Results: 13 women with a mean age of 49.2 and age range 29-71 participated in the study. All participants were of low socioeconomic status. The majority (84.6%) had advanced disease at diagnosis. A fuller reading of transcripts produced four major themes clustered under; (1) socioeconomic characteristics of women, (2) impact of CC on women’s relationships, (3) disrupted and impaired activities of daily living (ADLs), and (4) economic disruptions. Conclusions: A diagnosis of CC introduces significant socio-economic disruptions in a woman’s and her family’s life. CC causes disability, impairs the woman and her family’s productivity hence exacerbating levels of poverty in the home. High and expensive out-of-pocket expenditure on treatment, investigations, and transport costs further compound the socio-economic burden. Decentralizing cancer care services to regional centers, scaling up screening services, subsidizing costs of cancer care services, or making cervical cancer care treatment free of charge, strengthening monitoring mechanisms in public facilities to curb the vice of healthcare workers soliciting bribes from patients, increased mass awareness campaigns about cancer, training more healthcare professionals in cancer investigation and management, and palliative care, and introducing an introductory course on gynecologic cancers into all health training institutions are recommended.

Keywords: activities of daily living, cervical cancer, out-of-pocket, expenditure, phenomenology, socioeconomic

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Authors: Theopoula Karanikolaou

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During recent decades an increasing number of studies indicate the negative impact of gender stereotypes in various aspects of society as well as in everyday life. At the same time, children’s literature is considered an important factor of gender-role socialization as it provides young readers with socially accepted gender behavioral models. Using a content analysis approach, this research examines the female representations in Greek children’s literature published from 2009 to 2019. Results indicate that female characters are depicted as sensitive and tender both in texts and illustrations, traits that are almost absent in the male characters of the sample. Highlighting the emotional aspect of female characters in contrast with the restrained male attitude reproduces gender biases. Stereotypical gender representation in children’s literature cultivates further discrimination among men and women.

Keywords: children's literature, female representation, gender socialization, gender studies

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Authors: Riya Mishra, Trayambak Tiwari, Anju Lata Singh, I. L. Singh, Tara Singh

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Decrement in vigilance task performance echoes impediment in effortful attention; here attention fluctuated in the realm of external and internal milieu of a person. To examine this fluctuation across time period, we employed two experiments of vigilance task with variation in thought probing rate, which was embedded in the task. The thought probe varies in terms of <2 minute per thought probe and <4 minute per thought probe during vigilance task. A 2x4 repeated measure factorial design was used. 15 individuals participated in this study with an age range of 20-26 years. It was found that thought probing rate has a negative trend with vigilance task performance whereas the subjective measures of mind-wandering have a positive relation with thought probe rate.

Keywords: criterion response, mental status, mind-wandering, thought probe, vigilance

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Authors: Zoja Raud, Valery Vodovozov

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Modelling and simulation provide effective way to acquire engineering experience. An active approach to modelling and simulation proposed in the paper involves, beside the compulsory part directed by the traditional step-by-step instructions, the new optional part basing on the human’s habits to design thus stimulating the efforts towards success in active learning. Computer exercises as a part of engineering curriculum incorporate a set of effective activities. In addition to the knowledge acquired in theoretical training, the described educational arrangement helps to develop problem solutions, computation skills, and experimentation performance along with enhancement of practical experience and qualification.

Keywords: modelling, simulation, engineering education, electronics, active learning

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Authors: Ivana Scidà, Francesco Alotto, Anna Osello

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Due to the importance given today to innovation, the education sector is evolving thanks digital technologies. Virtual Reality (VR) can be a potential teaching tool offering many advantages in the field of training and education, as it allows to acquire theoretical knowledge and practical skills using an immersive experience in less time than the traditional educational process. These assumptions allow to lay the foundations for a new educational environment, involving and stimulating for students. Starting from the objective of strengthening the innovative teaching offer and the learning processes, the case study of the research concerns the digitalization of MastrLAB, High Quality Laboratory (HQL) belonging to the Department of Structural, Building and Geotechnical Engineering (DISEG) of the Polytechnic of Turin, a center specialized in experimental mechanical tests on traditional and innovative building materials and on the structures made with them. The MastrLAB-VR has been developed, a revolutionary innovative training tool designed with the aim of educating the class in total safety on the techniques of use of machinery, thus reducing the dangers arising from the performance of potentially dangerous activities. The virtual laboratory, dedicated to the students of the Building and Civil Engineering Courses of the Polytechnic of Turin, has been projected to simulate in an absolutely realistic way the experimental approach to the structural tests foreseen in their courses of study: from the tensile tests to the relaxation tests, from the steel qualification tests to the resilience tests on elements at environmental conditions or at characterizing temperatures. The research work proposes a methodology for the virtualization of technical laboratories through the application of Building Information Modelling (BIM), starting from the creation of a digital model. The process includes the creation of an independent application, which with Oculus Rift technology will allow the user to explore the environment and interact with objects through the use of joypads. The application has been tested in prototype way on volunteers, obtaining results related to the acquisition of the educational notions exposed in the experience through a virtual quiz with multiple answers, achieving an overall evaluation report. The results have shown that MastrLAB-VR is suitable for both beginners and experts and will be adopted experimentally for other laboratories of the University departments.

Keywords: building information modelling, digital learning, education, virtual laboratory, virtual reality

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Authors: Mohamed Abd Esselem Dems, Souhila Laib, Nadjia Latelli, Nadia Ouddai

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In this work, we have developed QSAR model for Relative Binding Affinity (RBA) of a large diverse set of estradiol among these derivatives, the organometallic derivatives. By dividing the dataset into a training set of 24 compounds and a test set of 6 compounds. The DFT method was used to calculate quantum chemical descriptors and physicochemical descriptors (MR and MLOGP) were performed using E-Dragon. All the validations indicated that the QSAR model built was robust and satisfactory (R2 = 90.12, Q2LOO = 86.61, RMSE = 0.272, F = 60.6473, Q2ext =86.07). We have therefore apply this model to predict the RBA, for two isomers β and α wherein Mn(CO)3 complex with the aromatic ring of estradiol, and the two isomers show little appreciation for the estrogenic receptor (RBAβ = 1.812 and RBAα = 1.741).

Keywords: DFT, estradiol, haptotropic rearrangement, QSAR, relative binding affinity

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Authors: Malizgani Paul Chavula

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Background: Comprehensive sexuality education (CSE) plays a critical role in promoting youth and adolescents’ sexual and reproductive health and well-being. However, little is known about the enablers and barriers affecting the integration of CSE into educational programmes. The aim of this review is to explore positive and negative factors influencing the integration of CSE into national curricula and educational systems in low- and middle-income countries. Methods: We conducted a systematic literature review (January 2010 to August 2022). The results accord with the Preferred Reporting Items for Systematic Reviews and Meta-analysis standards for systematic reviews. Data were retrieved from the PubMed, Cochrane, Google Scholar, and Web of Hinari databases. The search yielded 431 publications, of which 23 met the inclusion criteria for full-text screening. The review is guided by an established conceptual framework that incorporates the integration of health innovations into health systems. Data were analyzed using a thematic synthesis approach. Results: The magnitude of the problem is evidenced by sexual and reproductive health challenges such as high teenage pregnancies, early marriages, and sexually transmitted infections. Awareness of these challenges can facilitate the development of interventions and the implementation and integration of CSE. Reported aspects of the interventions include core CSE content, delivery methods, training materials and resources, and various teacher-training factors. Reasons for adoption include perceived benefits of CSE, experiences and characteristics of both teachers and learners, and religious, social, and cultural factors. Broad system characteristics include strengthening links between schools and health facilities, school and community-based collaboration, coordination of CSE implementation, and the monitoring and evaluation of CSE. Ultimately, the availability of resources, national policies and laws, international agendas, and political commitment will impact upon the extent and level of integration. Conclusion: Social, economic, cultural, political, legal, and financial contextual factors influence the implementation and integration of CSE into national curricula and educational systems. Stakeholder collaboration and involvement in the design and appropriateness of interventions is critical.

Keywords: comprehensive sexuality education, factors, integration, sexual reproductive health rights

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Authors: Ulrich Wake, Eniman Syamsuddin

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The model for camera model identificaiton is trained using pretrained model ResNet43 and ResNet50. The dataset consists of 500 photos of each phone. Dataset is divided into 1280 photos for training, 320 photos for validation and 400 photos for testing. The model is trained using One Cycle Policy Method and tested using Test-Time Augmentation. Furthermore, the model is trained for 50 epoch using regularization such as drop out and early stopping. The result is 90% accuracy for validation set and above 85% for Test-Time Augmentation using ResNet50. Every model is also trained by slightly updating the pretrained model’s weights

Keywords: ​ One Cycle Policy, ResNet34, ResNet50, Test-Time Agumentation

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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: Bingquan Shen

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Convolutional Neural Networks (CNN) have demonstrated their effectiveness in synthesizing 3D views of object instances at various viewpoints. Given the problem where one have limited viewpoints of a particular object for classification, we present a pose normalization architecture to transform the object to existing viewpoints in the training dataset before classification to yield better classification performance. We have demonstrated that this Pose Normalization Network (PNN) can capture the style of the target object and is able to re-render it to a desired viewpoint. Moreover, we have shown that the PNN improves the classification result for the 3D chairs dataset and ShapeNet airplanes dataset when given only images at limited viewpoint, as compared to a CNN baseline.

Keywords: convolutional neural networks, object classification, pose normalization, viewpoint invariant

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Authors: Saheb Yousefi, Kim T. Zebehazy, Parviz Sharifi Daramadi, Tahereh Najafi Fard, Kevin Murfitt

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Context: Children with visual impairments often face challenges in their cognitive, motor, and social development. Sensory-motor and spatial perception therapies can be beneficial for these children, but many existing programs only focus on a limited set of therapies. This study aims to investigate the effectiveness of a rehabilitation program for sensory- motor and spatial perception in reducing the fear of mobility in visually impaired children. Research Aim: The aim of this study is to determine if a rehabilitation program based on parent-child interaction can reduce the fear of mobility in visually impaired children. Methodology: This study uses a semi-experimental approach with an uneven control group design. Visually impaired children aged 10 to 14 and their parents from the Board of the Blind and Visually Impaired in Tehran Province were included in the study. The sample was divided into experimental and control groups, with a total of 30 participants. The experimental group participated in a rehabilitation program for sensory-motor and spatial perception based on parent-child interaction, while the control group did not receive this intervention. Data was collected using questionnaires on transportation issues and analyzed using multivariate and univariate mixed analysis of variance tests. Findings: The analysis of the data showed that the fear of movement was significantly improved in the experimental group compared to the control group after the intervention. Theoretical Importance: This study highlights the effectiveness of a rehabilitation program for sensory- motor and spatial perception based on parent-child interaction in reducing the fear of mobility in visually impaired children. It contributes to the existing knowledge by demonstrating the positive impact of this type of intervention on the cognitive, motor, and social development of these children. Data Collection and Analysis Procedures: Data was collected through the use of questionnaires administered to the children before and after the intervention. The data was analyzed using multivariate and univariate mixed analysis of variance tests to examine the effects of the rehabilitation program. Questions Addressed: This study addresses the question of whether a rehabilitation program based on parent-child interaction can reduce the fear of mobility in visually impaired children. Conclusion: The findings of this study support the effectiveness of the sensory-motor and spatial perception rehabilitation program based on parent-child interaction in reducing the fear of movement in visually impaired children. This intervention can be considered as a suitable method to enhance the fear of mobility in these children.

Keywords: vision impairment, sensory-motor rehabilitation, space perception, parent-child interaction, fear of movement.

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Authors: Chana Pavneet

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Background: In more recent years in dentistry, a greater emphasis has been placed on competency-based education (CBE) programmes. Undergraduate and postgraduate curriculums have been reformed to reflect these changes, and adopting a CBE approach has shown to be beneficial to trainees and places an emphasis on continuous lifelong learning. The literature is vast; however, very little work has been done specifically to the assessment of competence in dentistry and even less so in oral surgery. The majority of the literature tends to opinion pieces. Some small-scale studies have been undertaken in this area researching assessment tools which can be used to assess competence in oral surgery. However, there is a lack of general consensus on the preferable assessment methods. The aim of this review is to identify the assessment methods available and their usefulness. Methods: Electronic databases (Medline, Embase, and the Cochrane Database of systematic reviews) were searched. PRISMA guidelines were followed to identify relevant papers. Abstracts of studies were reviewed, and if they met the inclusion criteria, they were included in the review. Papers were reviewed against the critical appraisal skills programme (CASP) checklist and medical education research quality instrument (MERQSI) to assess their quality and identify any bias in a systematic manner. The validity and reliability of each assessment method or tool were assessed. Results: A number of assessment methods were identified, including self-assessment, peer assessment, and direct observation of skills by someone senior. Senior assessment tended to be the preferred method, followed by self-assessment and, finally, peer assessment. The level of training was shown to affect the preferred assessment method, with one study finding peer assessment more useful in postgraduate trainees as opposed to undergraduate trainees. Numerous tools for assessment were identified, including a checklist scale and a global rating scale. Both had their strengths and weaknesses, but the evidence was more favourable for global rating scales in terms of reliability, applicability to more clinical situations, and easier to use for examiners. Studies also looked into trainees’ opinions on assessment tools. Logbooks were not found to be significant in measuring the competence of trainees. Conclusion: There is limited literature exploring the methods and tools which assess the competence of oral surgery trainees. Current evidence shows that the most favourable assessment method and tool may differ depending on the stage of training. More research is required in this area to streamline assessment methods and tools.

Keywords: competence, oral surgery, assessment, trainees, education

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Authors: Ya-Hui Wang

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Lower speech therapy rate of tracheostomized patient was noted in comparison with previous researches. This study is aim to shed light on the referral status of speech therapy in those patients in Taiwan. This study developed an analysis for the size and key characteristics of the population of tracheostomized in-patient in the Taiwan. Method: We analyzed National Healthcare Insurance data (The Collaboration Center of Health Information Application, CCHIA) from Jan 1 2010 to Dec 31 2010. Result: over ages 3, number of tracheostomized in-patient is directly proportional to age. A high service loading was observed in North region in comparison with other regions. Only 4.87% of the tracheostomized in-patients were referred for speech therapy, and 1.9% for swallow examination, 2.5% for communication evaluation.

Keywords: refer, speech therapy, training, rehabilitation

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Authors: Svetlana L. Mishlanova, Evgeniia V. Ermakova, Mariia E. Timirkina

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The paper is concerned with the study of metaphor production in essays written by Russian and English native speakers in the framework of cognitive metaphor theory. It considers metaphorical competence as individual’s ability to recognize, understand and use metaphors in speech. The work analyzes the influence of visual metaphor on production and density of conventional and novel verbal metaphors. The main methods of research include experiment connected with image interpretation, metaphor identification procedure (MIPVU) and visual conventional metaphors identification procedure proposed by VisMet group. The research findings will be used in the project aimed at comparing metaphorical competence of native and non-native English speakers.

Keywords: metaphor, metaphorical competence, conventional, novel

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Authors: J-C. Leneveu, A. Chereau, L. Mansart, T. Mesbah, M. Wyka

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Extracting and interpreting information from Big Data represent a stake for years to come in several sectors such as finance. Currently, numerous methods are used (such as Technical Analysis) to try to understand and to anticipate market behavior, with mixed results because it still seems impossible to exactly predict a financial trend. The increase of available data on Internet and their diversity represent a great opportunity for the financial world. Indeed, it is possible, along with these standard financial data, to focus on exogenous data to take into account more macroeconomic factors. Coupling the interpretation of these data with standard methods could allow obtaining more precise trend predictions. In this paper, in order to observe the influence of exogenous data price independent of other usual effects occurring in classical markets, behaviors of Bitcoin users are introduced in a model reconstituting Bitcoin value, which is elaborated and tested for prediction purposes.

Keywords: big data, bitcoin, data mining, social network, financial trends, exogenous data, global economy, behavioral finance

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Authors: Natalia Uribe Corrales, María Fernanda Benavides Erazo, Santiago Henao Villegas

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Introduction: Transport is a crucial link in the porcine chain because it is considered a stressful event in the animal, due to it is a new environment, which generates new interactions, together with factors such as speed, noise, temperature changes, vibrations, deprivation of food and water. Therefore, inadequate handling at this stage can lead to bruises, musculoskeletal injuries, fatigue, and mortality, resulting in canal seizures and economic losses. Objective: To characterize the transport and driving practices for the mobilization of standing pigs directed to slaughter plants in the Valle de Aburrá, Antioquia, Colombia in 2017. Methods: A descriptive cross-sectional study was carried out with the transporters arriving at the slaughterhouses approved by National Institute for Food and Medicine Surveillance (INVIMA) during 2017 in the Valle de Aburrá. The process of obtaining the samples was made from probabilistic sampling. Variables such as journey time, mechanical technical certificate, training in animal welfare, driving speed, material, and condition of floors and separators, supervision of animals during the trip, load density and mortality were analyzed. It was approved by the ethics committee for the use and care of animals CICUA of CES University, Act number 14 of 2015. Results: 190 trucks were analyzed, finding that 12.4% did not have updated mechanical technical certificate; the transporters experience in pig’s transportation was an average of 9.4 years (d.e.7.5). The 85.8% reported not having received training in animal welfare. Other results were that the average speed was 63.04km/hr (d.e 13.46) and the 62% had floors in good condition; nevertheless, the 48% had bad conditions on separators. On the other hand, the 88% did not supervise their animals during the journey, although the 62.2% had an adequate loading density, in relation to the average mortality was 0.2 deaths/travel (d.e. 0.5). Conclusions: Trainers should be encouraged on issues such as proper maintenance of vehicles, animal welfare, obligatory review of animals during mobilization and speed of driving, as these poorly managed indicators generate stress in animals, increasing generation of injuries as well as possible accidents; also, it is necessary to continue to improve aspects such as aluminum floors and separators that favor easy cleaning and maintenance, as well as the appropriate handling in the density of load that generates animal welfare.

Keywords: animal welfare, driving practices, pigs, truck infrastructure

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Authors: Tolulope Aremu

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This paper is based on the idea of using deep learning methodology for optimizing production yield by tuning a few key process parameters in a manufacturing environment. The study was explicitly on how to maximize production yield and minimize operational costs by utilizing advanced neural network models, specifically Long Short-Term Memory and Convolutional Neural Networks. These models were implemented using Python-based frameworks—TensorFlow and Keras. The targets of the research are the precision molding processes in which temperature ranges between 150°C and 220°C, the pressure ranges between 5 and 15 bar, and the material flow rate ranges between 10 and 50 kg/h, which are critical parameters that have a great effect on yield. A dataset of 1 million production cycles has been considered for five continuous years, where detailed logs are present showing the exact setting of parameters and yield output. The LSTM model would model time-dependent trends in production data, while CNN analyzed the spatial correlations between parameters. Models are designed in a supervised learning manner. For the model's loss, an MSE loss function is used, optimized through the Adam optimizer. After running a total of 100 training epochs, 95% accuracy was achieved by the models recommending optimal parameter configurations. Results indicated that with the use of RSM and DOE traditional methods, there was an increase in production yield of 12%. Besides, the error margin was reduced by 8%, hence consistent quality products from the deep learning models. The monetary value was annually around $2.5 million, the cost saved from material waste, energy consumption, and equipment wear resulting from the implementation of optimized process parameters. This system was deployed in an industrial production environment with the help of a hybrid cloud system: Microsoft Azure, for data storage, and the training and deployment of their models were performed on Google Cloud AI. The functionality of real-time monitoring of the process and automatic tuning of parameters depends on cloud infrastructure. To put it into perspective, deep learning models, especially those employing LSTM and CNN, optimize the production yield by fine-tuning process parameters. Future research will consider reinforcement learning with a view to achieving further enhancement of system autonomy and scalability across various manufacturing sectors.

Keywords: production yield optimization, deep learning, tuning of process parameters, LSTM, CNN, precision manufacturing, TensorFlow, Keras, cloud infrastructure, cost saving

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Authors: Loghman Ansarian, Teoh Mei Lin

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In an attempt to increase oral proficiency of Iranian EFL learners, the researchers compared the effect of problem-based mobile-assisted language learning with the conventional language learning approach (Communicative Language Teaching) in Iran. The experimental group (n=37) went through PBL instruction and the control group (n=33) went through conventional instruction. The results of quantitative data analysis after 26 sessions of treatment revealed that PBL could positively affect participants' knowledge of grammar, vocabulary, spoken fluency, and pronunciation; however, in terms of task achievement, no significant effect was found. This study can have pedagogical implications for language teachers, and material developers.

Keywords: problem-based learning, spoken intelligibility, Iranian EFL context, cognitive learning

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Authors: Bruna Azzari Puga, Richard Roe, Andre Pagani de Souza

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abstract outlines a proposed study to examine how and to what extent interactive, experiential, learner centered methodology develops learning of basic civic and democratic competencies among young children. It stems from the Literacy and Law course taught at Georgetown University Law Center in Washington, DC, since 1998. Law students, trained in best literacy practices and legal cases affecting literacy development, read “law related” children’s books and engage in interactive and extension activities with emerging readers. The law students write a monthly journal describing their experiences and a final paper: a conventional paper or a children’s book illuminating some aspect of literacy and law. This proposal is based on the recent adaptation of Literacy and Law to Brazil at Mackenzie Presbyterian University in São Paulo in three forms: first, a course similar to the US model, often conducted jointly online with Brazilian and US law students; second, a similar course that combines readings of children’s literature with activity based learning, with law students from a satellite Mackenzie campus, for young children from a vulnerable community near the city; and third, a course taught by law students at the main Mackenzie campus for 4th grade students at the Mackenzie elementary school, that is wholly activity and discourse based. The workings and outcomes of these courses are well documented by photographs, reports, lesson plans, and law student journals. The authors, faculty who teach the above courses at Mackenzie and Georgetown, observe that literacy, broadly defined as cognitive and expressive development through reading and discourse-based activities, can be influential in developing democratic civic skills, identifiable by explicit civic competencies. For example, children experience justice in the classroom through cooperation, creativity, diversity, fairness, systemic thinking, and appreciation for rules and their purposes. Moreover, the learning of civic skills as well as the literacy skills is enhanced through interactive, learner centered practices in which the learners experience literacy and civic development. This study will develop rubrics for individual and classroom teaching and supervision by examining 1) the children’s books and students diaries of participating law students and 2) the collection of photos and videos of classroom activities, and 3) faculty and supervisor observations and reports. These rubrics, and the lesson plans and activities which are employed to advance the higher levels of performance outcomes, will be useful in training and supervision and in further replication and promotion of this form of teaching and learning. Examples of outcomes include helping, cooperating and participating; appreciation of viewpoint diversity; knowledge and utilization of democratic processes, including due process, advocacy, individual and shared decision making, consensus building, and voting; establishing and valuing appropriate rules and a reasoned approach to conflict resolution. In conclusion, further development and replication of the learner centered literacy and law practices outlined here can lead to improved qualities of democratic teaching and learning supporting mutual respect, positivity, deep learning, and the common good – foundation qualities of a sustainable world.

Keywords: democracy, law, learner-centered, literacy

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Authors: K. Sindhu, V. Shubha Rao

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The goal of every faculty is to guide students to learn fundamental concepts and also improve thinking skills. Curriculum questionnaires must be framed, which would facilitate students to improve their thinking skills. Improving thinking skill is a difficult task and one of the ways to achieve this is to frame questionnaires using Bloom’s Taxonomy. Bloom’s Taxonomy helps the faculty to assess the students in a systematic approach which involves students performing successfully at each level in a systematic manner. In this paper, we have discussed on Revised Bloom’s Taxonomy and how to frame our questions based on the taxonomy for assessment. We have also presented mapping the questions with the taxonomy table which shows the mapping of the questions in knowledge and cognitive domain.

Keywords: bloom’s taxonomy, assessment, questions, engineering education

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Authors: Lucie Mrackova, Helena Kisvetrova

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Spirituality is an integral part of human life. In a secular environment, spiritual needs are often overlooked, especially in acute nursing care. Spiritual needs assessment for patients (SNAP), which also exists in the Czech version (SNAP-CZ), can be used for objective evaluation. The aim of this study was to measure the psychometric properties of SNAP-CZ and to find correlations between SNAP-CZ and sociodemographic and clinical variables. A cross-sectional study with tools assessing spiritual needs (SNAP-CZ), anxiety (Beck Anxiety Inventory; BAI), depression (Beck Depression Inventory; BDI), pain (Visual Analogue Scale; VAS), self-sufficiency (Barthel Index; BI); cognitive function (Montreal Cognitive Test; MoCa) and selected socio-demographic data was performed. The psychometric properties of SNAP-CZ were tested using factor analysis, reliability and validity tests, and correlations between the questionnaire and sociodemographic data and clinical variables. Internal consistency was established with Cronbach’s alfa for the overall score, respective domains, and individual items. Reliability was assessed by test-retest by Interclass correlation coefficient (ICC). Data for correlation analysis were processed according to Pearson's correlation coefficient. The study included 172 trauma patients (the mean age = 40.6 ± 12.1 years) who experienced polytrauma or severe monotrauma. There were a total of 106 (61.6%) male subjects, 140 (81.4%) respondents identified themselves as non-believers. The full-scale Cronbach's alpha was 0.907. The test-retest showed the reliability of the individual domains in the range of 0.924 to 0.960 ICC. Factor analysis resulted in a three-factor solution (psychosocial needs (alfa = 0.788), spiritual needs (alfa = 0.886) and religious needs (alfa = 0.841)). Correlation analysis using Pearson's correlation coefficient showed that the domain of psychosocial needs significantly correlated only with gender (r = 0.178, p = 0.020). Males had a statistically significant lower average value in this domain (mean = 12.5) compared to females (mean = 13.8). The domain of spiritual needs significantly correlated with gender (r = 0.199, p = 0.009), social status (r = 0.156, p = 0.043), faith (r = -0.250, p = 0.001), anxiety (r = 0.194, p = 0.011) and depression (r = 0.155, p = 0.044). The domain of religious needs significantly correlated with age (r = 0,208, p = 0,007), education (r = -0,161, p = 0,035), faith (r = -0,575, p < 0,0001) and depression (r = 0,179, p = 0,019). Overall, the whole SNAP scale significantly correlated with gender (r = 0.219, p = 0.004), social status (r = 0.175, p = 0.023), faith (r = -0.334, p <0.0001), anxiety (r = 0.177, p = 0.022) and depression (r = 0.173, p = 0.025). The results of this study corroborate the reliability of the SNAP-CZ and support its future use in the nursing care of trauma patients in a secular society. Acknowledgment: The study was supported by grant nr. IGA_FZV_2020_003.

Keywords: acute nursing care, assessment of spiritual needs, patient, psychometric validation, spirituality

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Authors: Nasrin Akter, Prem Chhetri, Shams Rahman

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The present study tested Ajzen’s Theory of Planned Behavior (TPB) model to explain the formation of business customers’ intention to use 3PL services in Bangladesh. The findings show that the TPB model has a good fit to the data. Based on theoretical support and suggested modification indices, a refined TPB model was developed afterwards which provides a better predictive power for intention. Consistent with the theory, the results of a structural equation analysis revealed that the intention to use 3PL services is predicted by attitude and subjective norms but not by perceived behavioral control. Further investigation indicated that the paths between (attitude and intention) and (subjective norms and intention) did not statistically differ between 3PL user and non-user. Findings of this research provide an evidence base to formulate business strategies to increase the use of 3PL services in Bangladesh to enhance productivity and to gain economic efficiency.

Keywords: Bangladesh, intention, third-party logistics, Theory of Planned Behavior

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Authors: Mahdi Akhbardeh

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Synchronization of neuronal firing is a hallmark of several neurological diseases. Recently, stimulation techniques have been developed which make it possible to desynchronize oscillatory neuronal activity in a mild and effective way, without suppressing the neurons' firing. As yet, these techniques are being used to establish demand-controlled deep brain stimulation (DBS) techniques for the therapy of movement disorders like severe Parkinson's disease or essential tremor. We here present a first conceptualization suggesting that the nucleus accumbens is a promising target for the standard, that is, permanent high-frequency, DBS in patients with severe and chronic obsessive-compulsive disorder (OCD). In addition, we explain how demand-controlled DBS techniques may be applied to the therapy of OCD in those cases that are refractory to behavioral therapies and pharmacological treatment.

Keywords: stereotactic neurosurgery, deep brain stimulation, obsessive-compulsive disorder, phase resetting

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Authors: Nasreddin Ahmed

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Despite the ostensible extant differences amongst world languages’ structures that have culminated in the divergence in orthographic, phonological, morphological, and syntactic systems that each language has, research in cognitive linguistic strives to establish the claim that such differences are merely prima facie of a totalized universal system of signification.Linguists , since Chomsky, have never given up on the attempt to establish linguistic descriptive model that espouses a perspective in which every human language has a slot . Concurring with claim that the so-called rhetorical devices are pervasive phenomena and not literary-specific , the present paper aspires to voice the claim that rhetorical devices not only ubiquitous in all levels of a particular language but also a universal linguistic phenomena. Using illustrations from Arabic and Englishthe paper intend to provide data-supported evidence that human beings are universally using similar rhetorical, albeit given different appellations.

Keywords: language, rhetoric, syntax, stylistics

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Authors: Katarzyna Oberda

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The aim of this paper is to conceptual emotions in the process of mediation. Although human emotions have been approached from various disciplines and perspectives, e.g. philosophy, linguistics, psychology and neurology, this complex phenomenon still needs further investigation into its discursive character with the an open mind and heart. To attain this aim, the theoretical and practical considerations are taken into account both to contextualize the discursive psychology of emotions in mediation and show how cognitive and linguistic activity expressed in language may lead to the emotional turn in the process of mediation. The double directions of this research into the discursive psychology of emotions have been partially inspired by the evaluative components of mediation forms. In the conducted research, we apply the methodology of discursive psychology with the discourse analysis as a tool. The practical data come from the recorded mediations online. The major findings of the conducted research result in the reconstruction of the emotional transformation model in mediation.

Keywords: discourse analysis, discursive psychology, emotions, mediation

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Authors: Javier López

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This Paper presents the evaluation model designed for the virtual education branch of The “Universidad Manuela Beltrán, Bogotá-Colombia”. This was the result of a research, developed as a case study, which had three stages: Document review, observation, and a perception survey for teachers. In the present model, the evaluation is a cross-cutting issue to the educational process. Therefore, it consists in a group of actions and guidelines which lead to analyze the student’s learning process from the admission, during the academic training, and to the graduation. This model contributes to the evaluation components which might interest other educational institutions or might offer methodological guidance to consolidate an own model

Keywords: model, evaluation, virtual education, learning process

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Authors: Jennifer Leach, Umashanger Thayasivam

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The use of technology has benefited society in more ways than one ever thought possible. Unfortunately, though, as society’s knowledge of technology has advanced, so has its knowledge of ways to use technology to manipulate people. This has led to a simultaneous advancement in the world of fraud. Machine learning techniques can offer a possible solution to help decrease this advancement. This research explores how the use of various machine learning techniques can aid in detecting fraudulent activity across two different types of fraudulent data, and the accuracy, precision, recall, and F1 were recorded for each method. Each machine learning model was also tested across five different training and testing splits in order to discover which testing split and technique would lead to the most optimal results.

Keywords: data science, fraud detection, machine learning, supervised learning

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