Search results for: learning algorithms

Authors: M. Michael Gromiha, A. Mary Thangakani, Sandeep Kumar, D. Velmurugan

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The main cause of several neurodegenerative diseases such as Alzhemier, Parkinson, and spongiform encephalopathies is formation of amyloid fibrils and plaques in proteins. We have analyzed different sets of proteins and peptides to understand the influence of sequence-based features on protein aggregation process. The comparison of 373 pairs of homologous mesophilic and thermophilic proteins showed that aggregation-prone regions (APRs) are present in both. But, the thermophilic protein monomers show greater ability to ‘stow away’ the APRs in their hydrophobic cores and protect them from solvent exposure. The comparison of amyloid forming and amorphous b-aggregating hexapeptides suggested distinct preferences for specific residues at the six positions as well as all possible combinations of nine residue pairs. The compositions of residues at different positions and residue pairs have been converted into energy potentials and utilized for distinguishing between amyloid forming and amorphous b-aggregating peptides. Our method could correctly identify the amyloid forming peptides at an accuracy of 95-100% in different datasets of peptides.

Keywords: aggregation, amyloids, thermophilic proteins, amino acid residues, machine learning techniques

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Authors: Gautier Viaud, Paul-Henry Cournède

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Plant growth models have been used extensively for the prediction of the phenotypic performance of plants. However, they remain most often calibrated for a given genotype and therefore do not take into account genotype by environment interactions. One way of achieving such an objective is to consider Bayesian hierarchical models. Three levels can be identified in such models: The first level describes how a given growth model describes the phenotype of the plant as a function of individual parameters, the second level describes how these individual parameters are distributed within a plant population, the third level corresponds to the attribution of priors on population parameters. Thanks to the Bayesian framework, choosing appropriate priors for the population parameters permits to derive analytical expressions for the full conditional distributions of these population parameters. As plant growth models are of a nonlinear nature, individual parameters cannot be sampled explicitly, and a Metropolis step must be performed. This allows for the use of a hybrid Gibbs--Metropolis sampler. A generic approach was devised for the implementation of both general state space models and estimation algorithms within a programming platform. It was designed using the Julia language, which combines an elegant syntax, metaprogramming capabilities and exhibits high efficiency. Results were obtained for Arabidopsis thaliana on both simulated and real data. An organ-scale Greenlab model for the latter is thus presented, where the surface areas of each individual leaf can be simulated. It is assumed that the error made on the measurement of leaf areas is proportional to the leaf area itself; multiplicative normal noises for the observations are therefore used. Real data were obtained via image analysis of zenithal images of Arabidopsis thaliana over a period of 21 days using a two-step segmentation and tracking algorithm which notably takes advantage of the Arabidopsis thaliana phyllotaxy. Since the model formulation is rather flexible, there is no need that the data for a single individual be available at all times, nor that the times at which data is available be the same for all the different individuals. This allows to discard data from image analysis when it is not considered reliable enough, thereby providing low-biased data in large quantity for leaf areas. The proposed model precisely reproduces the dynamics of Arabidopsis thaliana’s growth while accounting for the variability between genotypes. In addition to the estimation of the population parameters, the level of variability is an interesting indicator of the genotypic stability of model parameters. A promising perspective is to test whether some of the latter should be considered as fixed effects.

Keywords: bayesian, genotypic differentiation, hierarchical models, plant growth models

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Authors: Samuel Munaf, Kevin Swingler, Franz Brülisauer, Anthony O’Hare, George Gunn, Aaron Reeves

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Background: Avian influenza, more commonly known as Bird flu, is a viral zoonotic respiratory disease stemming from various species of poultry, including pets and migratory birds. Researchers have purported that the accessibility of health information online, in addition to the low-cost data collection methods the internet provides, has revolutionized the methods in which epidemiological and disease surveillance data is utilized. This paper examines the feasibility of using internet data sources, such as Twitter and livestock forums, for the early detection of the avian flu outbreak, through the use of text mining algorithms and social network analysis. Methods: Social media mining was conducted on Twitter between the period of 01/01/2021 to 31/12/2021 via the Twitter API in Python. The results were filtered firstly by hashtags (#avianflu, #birdflu), word occurrences (avian flu, bird flu, H5N1), and then refined further by location to include only those results from within the UK. Analysis was conducted on this text in a time-series manner to determine keyword frequencies and topic modeling to uncover insights in the text prior to a confirmed outbreak. Further analysis was performed by examining clinical signs (e.g., swollen head, blue comb, dullness) within the time series prior to the confirmed avian flu outbreak by the Animal and Plant Health Agency (APHA). Results: The increased search results in Google and avian flu-related tweets showed a correlation in time with the confirmed cases. Topic modeling uncovered clusters of word occurrences relating to livestock biosecurity, disposal of dead birds, and prevention measures. Conclusions: Text mining social media data can prove to be useful in relation to analysing discussed topics for epidemiological surveillance purposes, especially given the lack of applied research in the veterinary domain. The small sample size of tweets for certain weekly time periods makes it difficult to provide statistically plausible results, in addition to a great amount of textual noise in the data.

Keywords: veterinary epidemiology, disease surveillance, infodemiology, infoveillance, avian influenza, social media

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Authors: Josef Wolfartsberger, Michael Heiml, Georg Schwarz, Sabrina Egger

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Growing individualization and higher numbers of variants in industrial assembly products raise the complexity of manufacturing processes. Technical assistance systems considering both procedural and human factors allow for an increase in product quality and a decrease in required learning times by supporting workers with precise working instructions. Due to varying needs of workers, the presentation of working instructions leads to several challenges. This paper presents an approach for a multi-modal visualization application to support assembly work of complex parts. Our approach is integrated within an interconnected assistance system network and supports the presentation of cloud-streamed textual instructions, images, videos, 3D animations and audio files along with multi-modal user interaction, customizable UI, multi-platform support (e.g. tablet-PC, TV screen, smartphone or Augmented Reality devices), automated text translation and speech synthesis. The worker benefits from more accessible and up-to-date instructions presented in an easy-to-read way.

Keywords: assembly, assistive technologies, augmented reality, manufacturing, visualization

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Authors: Hu Yinyao

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Learning and using a second language have become more and more common in daily life. Understanding the complexity of second language proficiency can help students develop their interpersonal relationships with their friends and professors, even enhancing intimacy. This paper examines Wenzhou-Kean University students' second language proficiency and interpersonal relationships. The purpose of the research was to explore the relationship between second language proficiency, extent of intimacy, and interpersonal relationships of the 100 Wenzhou-Kean University students. A mixed methodology was utilized in the research study. Student respondents from Wenzhou-Kean University were chosen randomly by using random sampling. The data analysis used descriptive data in terms of figures and thematical data in the table. The researcher found that Wenzhou-Kean University’s students have shown lower intermediate level of second language proficiency and that their intimacy is middle when using a second language. Especially when talking about some sensitive topics, students tend not to use a second language due to low proficiency. This research project has a strong implication on interpersonal relationships and second language proficiency. The outcome of the study would be greatly helpful to enhance the interpersonal relationship and intimacy between students and students, students and professors who use.

Keywords: Interpersonal relationship, second language proficiency, intimacy, education, univeristy students

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Authors: Felicia Kikelomo Oluwalola

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This study examined lecturers’ perception of the roles of Information and Communication Technology (ICT) in Office Technology and Management (OTM) programme in polytechnics, in South-West, Nigeria. Descriptive survey design was adopted in this study. Purposive sampling technique was used to select all OTM lecturers in the nine (9) Polytechnics in the South-West, Nigeria. A 4-rating scale was adopted questionnaire titled ‘Lecturers’ Perception of the Roles of ICT in OTM Programme in Polytechnics’ with a reliability index of 0.93 was used. Two research questions were answered, and one null hypothesis was tested for the study. Data collected was analysed using descriptive statistics, independent t-test and one way Analysis of Variance (ANOVA) at 0.05 level of significance. The study revealed that lecturers have right perception of the roles of ICT in OTM programme in polytechnics. Also, the study revealed no significant difference between the mean perception of male and female lecturers in office technology and management. Based on the findings, the study recommended among others that recruitment of professionals in the field of ICT is necessary for effective teaching learning to be established and OTM curriculum should be constantly reviewed to enhance some ICT package that is acceptable globally.

Keywords: communication, information, perception, technology

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Authors: Annabelle Nelson

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This literature review documents indigenous storytelling as it functions to help humans face adversity and find emotional strength by aligning with nature. Archetypes in stories can transform the inner world from a Jungian perspective. Joseph Campbell’s hero-heroine cycle depicts the structure of stories to include a call to adventure, tests, helpers, and a return as the transformed person can help him or herself and even help their communities. By showcasing certain character traits, such as bravery or perseverance or humility, stories give maps for humans to face adversity. The main characters or archetypes in stories, as Carl Jung posited, provide a vehicle that can open consciousness if a listener identifies with the character. As documented in the review, this has many benefits. First, it can open consciousness to the collective unconscious for insight and intuitive clarity, as well as healing and release emotional trauma. The resultant spacious quality of consciousness allows the spiritual self to present insights to conscious awareness. Research in applied youth development programs demonstrates the utility of storytelling to prompt healthy choices and transform difficult life experience into success.

Keywords: archetypes, learning, storytelling, transformation

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Authors: Mona Baniahmadi, Saied Haghanifar

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Radio Frequency Identification (RFID) is regarded as a promising technology for the optimization of supply chain processes since it improves manufacturing and retail operations from forecasting demand for planning, managing inventory, and distribution. This study precisely aims at learning to know the RFID technology and at explaining how it can concretely be used for supply chain management and how it can help improving it in the case of Hejrat Company which is located in Iran and works on the distribution of medical drugs and cosmetics. This study uses some statistical analysis to calculate the expected benefits of an integrated RFID system on supply chain obtained through competitive advantages increases with decreasing cost factor. The study investigates how the cost of storage process, labor cost, the cost of missing goods, inventory management optimization, on-time delivery, order cost, lost sales and supply process optimization affect the performance of the integrated RFID supply chain regarding cost factors and provides a competitive advantage.

Keywords: cost, competitive advantage, radio frequency identification, supply chain

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Authors: Kholod J. Alotaibi, Andrew M. Gravell

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A study was conducted in which 212 software developers in higher education institutions in Saudi Arabia were surveyed to gather an indication of their understanding of the concept of usability, their acceptance of its importance, and to see how well its principles are applied. Interviews were then held with 20 of these developers, and a demonstration of Usage-Centred Design was attempted, a highly usability focused software development methodology, at one select institution for its redesign of an e-learning exam system interface during the requirements gathering phase. The study confirms the need to raise awareness of usability and its importance, and for Usage-Centred Design to be applied in its entirety, also need to encourage greater consultation with potential end-users of software and collaborative practices. The demonstration of Usage-Centred Design confirmed its ability to capture usability requirements more completely and precisely than would otherwise be the case, and hence its usefulness for developers concerned with improving software usability. The concluding discussion delves on the challenges for promoting usability and Usage-Centred Design in light of the research results and findings and recommendations are made for the same.

Keywords: usability, usage-centred, applying principles of usage-centred, Saudi Arabia

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Authors: Mina Sadat Orooje, Mohammad Mehdi Latifi, Behnam Fereydooni Eftekhari

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The integration of cutting-edge Internet of Things (IoT) technologies with advanced Artificial Intelligence (AI) systems is revolutionizing healthcare facility management. However, the current landscape of hospital building maintenance suffers from slow, repetitive, and disjointed processes, leading to significant financial, resource, and time losses. Additionally, the potential of Building Information Modeling (BIM) in facility maintenance is hindered by a lack of data within digital models of built environments, necessitating a more streamlined data collection process. This paper presents a robust framework that harmonizes AI with BIM-IoT technology to elevate healthcare Facility Maintenance Management (FMM) and address these pressing challenges. The methodology begins with a thorough literature review and requirements analysis, providing insights into existing technological landscapes and associated obstacles. Extensive data collection and analysis efforts follow to deepen understanding of hospital infrastructure and maintenance records. Critical AI algorithms are identified to address predictive maintenance, anomaly detection, and optimization needs alongside integration strategies for BIM and IoT technologies, enabling real-time data collection and analysis. The framework outlines protocols for data processing, analysis, and decision-making. A prototype implementation is executed to showcase the framework's functionality, followed by a rigorous validation process to evaluate its efficacy and gather user feedback. Refinement and optimization steps are then undertaken based on evaluation outcomes. Emphasis is placed on the scalability of the framework in real-world scenarios and its potential applications across diverse healthcare facility contexts. Finally, the findings are meticulously documented and shared within the healthcare and facility management communities. This framework aims to significantly boost maintenance efficiency, cut costs, provide decision support, enable real-time monitoring, offer data-driven insights, and ultimately enhance patient safety and satisfaction. By tackling current challenges in healthcare facility maintenance management it paves the way for the adoption of smarter and more efficient maintenance practices in healthcare facilities.

Keywords: artificial intelligence, building information modeling, healthcare facility maintenance, internet of things integration, maintenance efficiency

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Authors: Farhad Asadi, Mohammad Javad Mollakazemi

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In this paper, Bayesian online inference in models of data series are constructed by change-points algorithm, which separated the observed time series into independent series and study the change and variation of the regime of the data with related statistical characteristics. variation of statistical characteristics of time series data often represent separated phenomena in the some dynamical system, like a change in state of brain dynamical reflected in EEG signal data measurement or a change in important regime of data in many dynamical system. In this paper, prediction algorithm for studying change point location in some time series data is simulated. It is verified that pattern of proposed distribution of data has important factor on simpler and smother fluctuation of hazard rate parameter and also for better identification of change point locations. Finally, the conditions of how the time series distribution effect on factors in this approach are explained and validated with different time series databases for some dynamical system.

Keywords: time series, fluctuation in statistical characteristics, optimal learning, change-point algorithm

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Authors: Sonja Giese, Tess N. Peacock

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South African based Innovation Edge is experimenting with technology to drive positive behavior change, enable data-driven decision making, and scale quality early years services. This paper uses five case studies to illustrate how technology can be used in resource-constrained environments to first, encourage parenting practices that build early language development (using a stage-based mobile messaging pilot, ChildConnect), secondly, to improve the quality of ECD programs (using a mobile application, CareUp), thirdly, how to affordably scale services for the early detection of visual and hearing impairments (using a mobile tool, HearX), fourthly, how to build a transparent and accountable system for the registration and funding of ECD (using a blockchain enabled platform, Amply), and finally enable rapid data collection and feedback to facilitate quality enhancement of programs at scale (the Early Learning Outcomes Measure). ChildConnect and CareUp were both developed using a design based iterative research approach. The usage and uptake of ChildConnect and CareUp was evaluated with qualitative and quantitative methods. Actual child outcomes were not measured in the initial pilots. Although parents who used and engaged on either platform felt more supported and informed, parent engagement and usage remains a challenge. This is contrast to ECD practitioners whose usage and knowledge with CareUp showed both sustained engagement and knowledge improvement. HearX is an easy-to-use tool to identify hearing loss and visual impairment. The tool was tested with 10000 children in an informal settlement. The feasibility of cost-effectively decentralising screening services was demonstrated. Practical and financial barriers remain with respect to parental consent and for successful referrals. Amply uses mobile and blockchain technology to increase impact and accountability of public services. In the pilot project, Amply is being used to replace an existing paper-based system to register children for a government-funded pre-school subsidy in South Africa. Early Learning Outcomes Measure defines what it means for a child to be developmentally ‘on track’ at aged 50-69 months. ELOM administration is enabled via a tablet which allows for easy and accurate data collection, transfer, analysis, and feedback. ELOM is being used extensively to drive quality enhancement of ECD programs across multiple modalities. The nature of ECD services in South Africa is that they are in large part provided by disconnected private individuals or Non-Governmental Organizations (in contrast to basic education which is publicly provided by the government). It is a disparate sector which means that scaling successful interventions is that much harder. All five interventions show the potential of technology to support and enhance a range of ECD services, but pathways to scale are still being tested.

Keywords: assessment, behavior change, communication, data, disabilities, mobile, scale, technology, quality

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Authors: Yishu Gong, Liangliang Yang, Jianyu Zhang, Zhengyu Chen, Sihong He, Xusheng Zhang, Wei Zhang

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Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that affects millions of people worldwide and is characterized by cognitive decline and behavioral changes. People living with Alzheimer’s disease often find it hard to complete routine tasks. However, there are limited objective assessments that aim to quantify the difficulty of certain tasks for AD patients compared to non-AD people. In this study, we propose to use speech emotion recognition (SER), especially the frustration level, as a potential biomarker for quantifying the difficulty patients experience when describing a picture. We build an SER model using data from the IEMOCAP dataset and apply the model to the DementiaBank data to detect the AD/non-AD group difference and perform longitudinal analysis to track the AD disease progression. Our results show that the frustration level detected from the SER model can possibly be used as a cost-effective tool for objective tracking of AD progression in addition to the Mini-Mental State Examination (MMSE) score.

Keywords: Alzheimer’s disease, speech emotion recognition, longitudinal biomarker, machine learning

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Authors: K. C. Wong

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This paper demonstrates a number of examples in the hope to shed some light on the possibility of designing future operating systems in a more adaptation-based manner. A modern operating system, we conceive, should possess the capability of 'learning' in such a way that it can dynamically adjust its services and behavior according to the current status of the environment in which it operates. In other words, a modern operating system should play a more proactive role during the session of providing system services to users. As such, a modern operating system is expected to create a computing environment, in which its users are provided with system services more matching their dynamically changing needs. The examples demonstrated in this paper show that user's resource access patterns 'learned' and determined during a session can be utilized to improve system performance and hence to provide users with a better and more effective computing environment. The paper also discusses how to use the frequency, the continuity, and the duration of resource accesses in a session to quantitatively measure and determine user's resource access patterns for the examples shown in the paper.

Keywords: adaptation-based systems, operating systems, resource access patterns, system performance

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Authors: Francesco Lubrano, Fabrizio Bertone, Federico Stirano

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Modern societies strongly depend on Critical Infrastructures (CI). Hospitals, power supplies, water supplies, telecommunications are just few examples of CIs that provide vital functions to societies. CIs like hospitals are very complex environments, characterized by a huge number of cyber and physical systems that are becoming increasingly integrated. Ensuring a high level of security within such critical infrastructure requires a deep knowledge of vulnerabilities, threats, and potential attacks that may occur, as well as defence and prevention or mitigation strategies. The possibility to remotely monitor and control almost everything is pushing the adoption of network-connected devices. This implicitly introduces new threats and potential vulnerabilities, posing a risk, especially to those devices connected to the Internet. Modern medical devices used in hospitals are not an exception and are more and more being connected to enhance their functionalities and easing the management. Moreover, hospitals are environments with high flows of people, that are difficult to monitor and can somehow easily have access to the same places used by the staff, potentially creating damages. It is therefore clear that physical and cyber threats should be considered, analysed, and treated together as cyber-physical threats. This means that an integrated approach is required. SAFECARE, an integrated cyber-physical security solution, tries to respond to the presented issues within healthcare infrastructures. The challenge is to bring together the most advanced technologies from the physical and cyber security spheres, to achieve a global optimum for systemic security and for the management of combined cyber and physical threats and incidents and their interconnections. Moreover, potential impacts and cascading effects are evaluated through impact propagation models that rely on modular ontologies and a rule-based engine. Indeed, SAFECARE architecture foresees i) a macroblock related to cyber security field, where innovative tools are deployed to monitor network traffic, systems and medical devices; ii) a physical security macroblock, where video management systems are coupled with access control management, building management systems and innovative AI algorithms to detect behavior anomalies; iii) an integration system that collects all the incoming incidents, simulating their potential cascading effects, providing alerts and updated information regarding assets availability.

Keywords: cyber security, defence strategies, impact propagation, integrated security, physical security

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Authors: Elias Nemer, Greg Vines

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Time-frequency transformation and spectral representations of audio signals are commonly used in various machine learning applications. Training networks on frequency features such as the Mel-Spectrogram or Cochleogram have been proven more effective and convenient than training on-time samples. In practical realizations, these features are created on a different processor and/or pre-computed and stored on disk, requiring additional efforts and making it difficult to experiment with different features. In this paper, we provide a PyTorch framework for creating various spectral features as well as time-frequency transformation and time-domain filter-banks using the built-in trainable conv1d() layer. This allows computing these features on the fly as part of a larger network and enabling easier experimentation with various combinations and parameters. Our work extends the work in the literature developed for that end: First, by adding more of these features and also by allowing the possibility of either starting from initialized kernels or training them from random values. The code is written as a template of classes and scripts that users may integrate into their own PyTorch classes or simply use as is and add more layers for various applications.

Keywords: neural networks Mel-Spectrogram, chromagram, cochleogram, discrete Fourrier transform, PyTorch conv1d()

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Authors: Frederic Jumelle, Kelvin So, Didan Deng

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In this paper, we are introducing a model of artificial general intelligence (AGI), the functional neural network (FNN), for modeling human decision-making processes. The FNN is composed of multiple artificial mirror neurons (AMN) racing in the network. Each AMN has a similar structure programmed independently by the users and composed of an intention wheel, a motor core, and a sensory core racing at a specific velocity. The mathematics of the node’s formulation and the racing mechanism of multiple nodes in the network will be discussed, and the group decision process with fuzzy logic and the transformation of these conceptual methods into practical methods of simulation and in operations will be developed. Eventually, we will describe some possible future research directions in the fields of finance, education, and medicine, including the opportunity to design an intelligent learning agent with application in AGI. We believe that FNN has a promising potential to transform the way we can compute decision-making and lead to a new generation of AI chips for seamless human-machine interactions (HMI).

Keywords: neural computing, human machine interation, artificial general intelligence, decision processing

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Authors: Joann Douziech

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Individuals with intellectual and developmental disabilities (IDD) possess characteristics that present both challenges and gifts. Individuals with IDD require and are worthy of intentional, strategic, and specialized support throughout their lifespan to ensure optimum quality-of-life outcomes. The current global advocacy movement advancing the rights of individuals with IDD emphasizes a high degree of choice over life decisions. For some individuals, this degree of choice results in a variety of negative health and well-being outcomes. Improving the quality of life outcomes requires the combination of a commitment to the rights of the individual with a responsibility to provide support and choice commensurate with individual capacity. A belief that individuals with IDD are capable of learning and they are worthy of being taught provides the foundation for a holistic model of support throughout their lifespan. This model is based on three pillars of engineering the environment, promoting skill development and maintenance, and staff support. In an ever-changing world, supporting quality of life requires attention to moments, phases, and changes in stages throughout the lifespan. Balancing these complexities with strategic, responsive, and dynamic interventions enhances the quality of life of individuals with ID throughout their lifespan.

Keywords: achieving optimum quality of life, comprehensive support, lifespan approach, philosophy and pedagogy

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Authors: Nady Farag Faragalla Hanna

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In the car dealership industry in Japan, the sales specialist is a key factor in the success of the company. I hypothesize that when a company understands the characteristics of sales professionals in its industry, it is easier to recruit and train salespeople effectively. Lean human resources management ensures the economic success and performance of companies, especially small and medium-sized companies.The purpose of the article is to determine the characteristics of sales specialists for small and medium-sized car dealerships using the chi-square test and the proximate variable model. Accordingly, the results show that career change experience, learning ability and product knowledge are important, while university education, career building through internal transfer, leadership experience and people development are not important for becoming a sales professional. I also show that the characteristics of sales specialists are perseverance, humility, improvisation and passion for business.

Keywords: electronics engineering, marketing, sales, E-commerce digitalization, interactive systems, sales process ARIMA models, sales demand forecasting, time series, R codetraits of sales professionals, variable precision rough sets theory, sales professional, sales professionals

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Authors: Liu Dan

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It was considered either unnecessary or impossible for primary school students to implement online teaching until last year. A large number of E-learning or E-teaching researches have been focused on adult-learners, andragogy and technology, however, primary school education, it is facing many problems that need to be solved. Therefore, this research is aimed at exploring barriers and influential factors on online teaching for K-12 students from teachers’ perspectives and discussing the E-pedagogy that is suitable for primary school students and teachers. Eight hundred and ninety-six teachers from 10 primary schools in Shanghai were invited to participate in a questionnaire survey. Data were analysed by hierarchical regression, and the results stress the significant three barriers by teachers with online teaching: the existing system is deficient in emotional interaction, teachers’ attitude towards the technology is negative and the present teacher training is lack of systematic E-pedagogy guidance. The barriers discovered by this study will help the software designers (E-lab) develop tools that allow for flexible and evolving pedagogical approaches whilst providing an easy entry point for cautious newcomers, so that help the teachers free to engage in E-teaching at pedagogical and disciplinary levels, to enhance their repertoire of teaching practices.

Keywords: online teaching barriers (OTB), e-teaching, primary school, teachers, technology

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Authors: Mehrdad Shahrbanozadeh, Gholam Abbas Barani, Saeed Shojaee

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In this study, a finite element (Seep3D model) and an artificial neural network (ANN) model were developed to simulate flow through dam foundation. Seep3D model is capable of simulating three-dimensional flow through a heterogeneous and anisotropic, saturated and unsaturated porous media. Flow through the Shahid Abbaspour dam foundation has been used as a case study. The FEM with 24960 triangular elements and 28707 nodes applied to model flow through foundation of this dam. The FEM being made denser in the neighborhood of the curtain screen. The ANN model developed for Shahid Abbaspour dam is a feedforward four layer network employing the sigmoid function as an activator and the back-propagation algorithm for the network learning. The water level elevations of the upstream and downstream of the dam have been used as input variables and the piezometric heads as the target outputs in the ANN model. The two models are calibrated and verified using the Shahid Abbaspour’s dam piezometric data. Results of the models were compared with those measured by the piezometers which are in good agreement. The model results also revealed that the ANN model performed as good as and in some cases better than the FEM.

Keywords: seepage, dam foundation, finite element method, neural network, seep 3D model

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Authors: Tiago do Carmo Nogueira, Cássio Dener Noronha Vinhal, Gélson da Cruz Júnior, Matheus Rudolfo Diedrich Ullmann

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Generating automatic image descriptions through natural language is a challenging task. Image captioning is a task that consistently describes an image by combining computer vision and natural language processing techniques. To accomplish this task, cutting-edge models use encoder-decoder structures. Thus, Convolutional Neural Networks (CNN) are used to extract the characteristics of the images, and Recurrent Neural Networks (RNN) generate the descriptive sentences of the images. However, cutting-edge approaches still suffer from problems of generating incorrect captions and accumulating errors in the decoders. To solve this problem, we propose a model based on the encoder-decoder structure, introducing a module that generates the weights according to the importance of the word to form the sentence, using the part-of-speech (PoS). Thus, the results demonstrate that our model surpasses state-of-the-art models.

Keywords: gated recurrent units, caption generation, convolutional neural network, part-of-speech

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Authors: Lee Bih Ni, Kiu Su Na

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This paper discusses the Chinese Language Teaching as a Second Language by focusing on Immersion Teaching. Researchers used narrative literature review to describe the current states of both art and science in focused areas of inquiry. Immersion teaching comes with a standard that teachers must reliably meet. Chinese language-immersion instruction consists of language and content lessons, including functional usage of the language, academic language, authentic language, and correct Chinese sociocultural language. Researchers used narrative literature reviews to build a scientific knowledge base. Researchers collected all the important points of discussion, and put them here with reference to the specific field where this paper is originally based on. The findings show that Chinese Language in immersion teaching is not like standard foreign language classroom; immersion setting provides more opportunities to teach students colloquial language than academic. Immersion techniques also introduce a language’s cultural and social contexts in a meaningful and memorable way. It is particularly important that immersion teachers connect classwork with real-life experiences. Immersion also includes more elements of discovery and inquiry based learning than do other kinds of instructional practices. Students are always and consistently interpreted the conclusions and context clues.

Keywords: a second language, Chinese language teaching, immersion teaching, instructional strategies

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Authors: Leah Plocharczyk, Matthew Conner

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This paper analyzes the relatively new trend of PSE programs which seek to provide education, vocational training, and a college experience to individuals with an intellectual and developmental disability (IDD). Specifically, the paper examines the degree of interaction between PSE programs and the libraries of their college campuses. Using ThinkCollege, a clearinghouse and advocate for PSE programs, the researchers identified 293 programs throughout the country. These were all contacted with an email survey asking them about the nature of their involvement, if any, with the academic libraries on their campus. Where indicated by the responses, the libraries of PSE programs were contacted for additional information about their programming. Responses to the survey questions were tabulated and analyzed quantitatively. Written comments were analyzed for themes which were then tabulated. This paper presents the results of this study. They show obvious preferences for library programming, such as group formal instruction, individual liaisons, embedded reference, and various instructional designs. These are discussed in terms of special education principles of mainstreaming, level of restriction, training demands and cost effectiveness. The work serves as a foundation for best practices that can advance the field.

Keywords: disability studies, instructional design, universal design for learning, assessment methodology

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Authors: Douglas Shabe

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The world of the performing musician is one of high pressure that comes from the expected high standards they have to live up to and that they expect from themselves. The pressure that musicians put themselves under can manifest itself in physical problems such as focal dystonia. Knowledge of the contributing factors and potential rehabilitation strategies cannot only give players hope for recovery but also the information to prevent it from happening in the first place. This dissertation presents a multiple case study of two performing brass musicians who developed focal dystonia of the embouchure, also known as embouchure dystonia, combined with an autoethnography of the author’s experience of battling embouchure dystonia and our attempts at recovery. Extensive research into the current state of focal dystonia research was done to establish a base of knowledge. That knowledge was used to develop interview questions for the two participants and interpret the findings of the qualitative data collected. The research knowledge, as well as the qualitative data from the case studies, was also used to interpret the author’s experience. The author determined that behavioral, environmental, and psychological factors were of prime importance in the subjects’ development of focal dystonia and that modifications of those factors are essential for the best chance at recovery.

Keywords: focal dystonia, embouchure dystonia, music teaching and learning, music education

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Authors: Dave Kenneth Tayao Cayado, Carlo P. Magno, Venice Cristine Dangaran

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The present study determines whether there will be differences in the self-regulation dispositions that learners utilize when writing different types of composition. There were 7 self-regulation factors that were used to develop a scale in this study such as memory strategy, goal setting, self-evaluation, seeking assistance, learning responsibility, environmental structuring, and organizing. The scale was made specific for writing a composition. The researcher-made scale was administered to 150 participants who all came from a university in the Philippines. The participants were asked to write two compositions namely opinion essay and research introduction/review of related literature. The zero-order correlation revealed that all the factors of self-regulation are correlated with one another. However, only seeking assistance and self-evaluation are correlated with opinion essay and technical writing is not correlated to any of the self-regulation factors. However, when path analysis was used, it was shown that seeking assistance can predict opinion essay scores whereas memory strategy, self-evaluation, and organizing can predict technical writing scores.

Keywords: opinion essay, self-regulation, technical writing, writing skills

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Authors: N. C. van der Merwe, J. Oosthuizen, M. F. Makhetha, J. Adams, B. K. Dajee, S-R. Schneider

Abstract:

Women representing high-risk breast cancer families, who tested negative for pathogenic mutations in BRCA1 and BRCA2, are four times more likely to develop breast cancer compared to women in the general population. Sequencing of genes involved in genomic stability and DNA repair led to the identification of novel contributors to familial breast cancer risk. These include BLM and PALB2. Bloom's syndrome is a rare homozygous autosomal recessive chromosomal instability disorder with a high incidence of various types of neoplasia and is associated with breast cancer when in a heterozygous state. PALB2, on the other hand, binds to BRCA2 and together, they partake actively in DNA damage repair. Archived DNA samples of 66 BRCA1/2 negative high-risk breast cancer patients were retrospectively selected based on the presence of an extensive family history of the disease ( > 3 affecteds per family). All coding regions and splice-site boundaries of both genes were screened using High-Resolution Melting Analysis. Samples exhibiting variation were bi-directionally automated Sanger sequenced. The clinical significance of each variant was assessed using various in silico and splice site prediction algorithms. Comprehensive screening identified a total of 11 BLM and 26 PALB2 variants. The variants detected ranged from global to rare and included three novel mutations. Three BLM and two PALB2 likely pathogenic mutations were identified that could account for the disease in these extensive breast cancer families in the absence of BRCA mutations (BLM c.11T > A, p.V4D; BLM c.2603C > T, p.P868L; BLM c.3961G > A, p.V1321I; PALB2 c.421C > T, p.Gln141Ter; PALB2 c.508A > T, p.Arg170Ter). Conclusion: The study confirmed the contribution of pathogenic mutations in BLM and PALB2 to the familial breast cancer burden in South Africa. It explained the presence of the disease in 7.5% of the BRCA1/2 negative families with an extensive family history of breast cancer. Segregation analysis will be performed to confirm the clinical impact of these mutations for each of these families. These results justify the inclusion of both these genes in a comprehensive breast and ovarian next generation sequencing cancer panel and should be screened simultaneously with BRCA1 and BRCA2 as it might explain a significant percentage of familial breast and ovarian cancer in South Africa.

Keywords: Bloom Syndrome, familial breast cancer, PALB2, South Africa

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Authors: Zeytu G. Asfaw, Serkalem K. Abrha, Demisew G. Degefu

Abstract:

Background: HIV/AIDS remains a major public health problem in Ethiopia and heavily affecting people of productive and reproductive age. We aimed to compare the performance of Parametric Survival Analysis and Bayesian Survival Analysis using simulations and in a real dataset application focused on determining predictors of HIV patient survival. Methods: A Parametric Survival Models - Exponential, Weibull, Log-normal, Log-logistic, Gompertz and Generalized gamma distributions were considered. Simulation study was carried out with two different algorithms that were informative and noninformative priors. A retrospective cohort study was implemented for HIV infected patients under Highly Active Antiretroviral Therapy in Alamata General Hospital, North Ethiopia. Results: A total of 320 HIV patients were included in the study where 52.19% females and 47.81% males. According to Kaplan-Meier survival estimates for the two sex groups, females has shown better survival time in comparison with their male counterparts. The median survival time of HIV patients was 79 months. During the follow-up period 89 (27.81%) deaths and 231 (72.19%) censored individuals registered. The average baseline cluster of differentiation 4 (CD4) cells count for HIV/AIDS patients were 126.01 but after a three-year antiretroviral therapy follow-up the average cluster of differentiation 4 (CD4) cells counts were 305.74, which was quite encouraging. Age, functional status, tuberculosis screen, past opportunistic infection, baseline cluster of differentiation 4 (CD4) cells, World Health Organization clinical stage, sex, marital status, employment status, occupation type, baseline weight were found statistically significant factors for longer survival of HIV patients. The standard error of all covariate in Bayesian log-normal survival model is less than the classical one. Hence, Bayesian survival analysis showed better performance than classical parametric survival analysis, when subjective data analysis was performed by considering expert opinions and historical knowledge about the parameters. Conclusions: Thus, HIV/AIDS patient mortality rate could be reduced through timely antiretroviral therapy with special care on the potential factors. Moreover, Bayesian log-normal survival model was preferable than the classical log-normal survival model for determining predictors of HIV patients survival.

Keywords: antiretroviral therapy (ART), Bayesian analysis, HIV, log-normal, parametric survival models

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Authors: Sakapas Saengchai, Vilasinee Jintalikhitdee, Mathinee Khongsatid, Nattapol Pourprasert

Abstract:

This paper studied the participation of people of the five villages of Bang Nang Li Community in Ampawa District, Samut Songkram Province, in designing community planning. The population was 2,755 villagers from the 5 villages with 349 people sampled. The level of involvement was measured by using Likert Five Scale for: preparing readiness of local people in the community, providing information for community and self analysis and learning, designing goals and directions for community development, designing strategic plans for community projects, and operating according to the plans. All process items reported a medium level of involvement except the item of preparing readiness for local people that presented the highest mean score. A test of a correlation between personal factors and level of involvement in designing the community planning unveiled no correlation between gender, age and career. Contrarily, the findings revealed that the villagers’ educational level and community membership status had a correlation with their level of involvement in designing the community planning.

Keywords: community development, community planning, people participation, educational level

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Authors: Gulden Aykinbaeva, Assem Umirzakova, Assel Makhadiyeva

Abstract:

The problem of studying of young married couples in connection with a change of social institute of a family and marriage is represented very actual for family consultation, considering a family role in the development of modern society. Results of numerous researchs say that one of difficult in formation and stabilization of a matrimony is the period of a young family. This period is characterized by various processes of integration, adaptation and emotional compatibility of spouses. The young family in it the period endures the first standard crisis which postpones a print for the further development of the family scenario. Emergence new, earlier not existing, systems of values render a huge value on the process of formation of a young family and each of spouses separately. Possibly to solve the set family tasks at the development of the uniform system of the family relations in which socially mature persons capable to consider a family as the creativity of each other act as subjects. Due to the research objective in work the following techniques were used: a questionnaire of satisfaction with V. V. Stolin's marriage and A. N. Volkova's technique directed on detection of coherence of family values and role installations in a married couple, and also content – the analysis. Development of an internal basis of a family on mutual clearing of values is important during the work with married couples. 'The mature view' of the partner in the marriage union provides coherence between the expected and real behavior of the partner that is important for the realization of the purposes of adaptation in a family. For research of communication of the data obtained by means of A. N. Volkova's techniques, V. V. Stolina and content – the analysis, the correlation analysis, with the application of the criterion of Spirmen was used. The analysis of results of the conducted research allowed us to determine the number of consistent patterns: 1. Nature of change of satisfaction with marriage at spouses testifies that the matrimonial relations undergo high-quality changes at different stages of formation of a young family. 2. The matrimonial relations in the course of their development, formation and functioning in young marriage undergo considerable changes on psychological, social and psychological and insignificant — at the psychophysiological and sociocultural levels. The material received by us allows to plan ways of further detailed researches of the development of the matrimonial relations not only in the young marriage but also at further stages of development of a matrimony. We believe that the results received in this research can be almost applied at creation of algorithms of selection of marriage partners, at diagnostics of character and the maintenance of matrimonial disharmonies, at the forecast of stability of marriage and a family.

Keywords: married couples, formation of the young family, psychological consultation, matrimony

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