Search results for: expert supporting system

Authors: Abeer K. Jameel, Harry Evdorides

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The Assessment of the road safety performance is a challengeable issue. This is not only because of the ineffective and unreliability of road and traffic crash data system but also because of its systematic character. Recent strategic plans and interventions implemented in some of the developed countries where a significant decline in the rate of traffic and road crashes considers that the road safety is a system. This system consists of four main elements which are: road user, road infrastructure, vehicles and speed in addition to other supporting elements such as the institutional framework and post-crash care system. To assess the performance of a system, it is required to assess all its elements. To present an understandable results of the assessment, it is required to present a unique term representing the performance of the overall system. This paper aims to develop an overall performance indicator which may be used to assess the road safety system. The variables of this indicators are the main elements of the road safety system. The data regarding these variables will be collected from the World Health Organization report. Multi-criteria analysis method is used to aggregate the four sub-indicators for the four variables. Two weighting methods will be assumed, equal weights and different weights. For the different weights method, the factor analysis method is used. The weights then will be converting to scores. The total score will be the overall indicator for the road safety performance in a national scale. This indicator will be used to compare and rank countries according to their road safety performance indicator. The country with the higher score is the country which provides most sustainable and effective interventions for successful road safety system. These indicator will be tested by comparing them with the aggregate real crash rate for each country.

Keywords: factor analysis, Multi-criteria analysis, road safety assessment, safe system indicator

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Authors: Fru Vitalis Akuma, Jenna Koenen

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The science education community is increasingly calling for learning experiences that mirror the work of scientists. Although inquiry-based science education is aligned with these calls, the implementation of this strategy is a complex and daunting task for many teachers. Thus, policymakers and researchers have noted the need for continued teacher Professional Development (PD) in the enactment of inquiry-based science education, coupled with effective ways of reaching the goals of teacher PD. This is a complex problem for which educational design research is suitable. The purpose at this stage of our design research is to develop a generic PD framework that is valid as the blueprint of a PD program for supporting science teachers in relation to inquiry-based curriculum units. The seven components of the framework are the goal, learning theory, strategy, phases, support, motivation, and an instructional model. Based on a systematic review of the literature on effective (science) teacher PD, coupled with developer screening, we have generated a design principle per component of the PD framework. For example, as per the associated design principle, the goal of the framework is to provide science teachers with experiences in authentic inquiry, coupled with enhancing their competencies linked to the adoption, customization and design; then the classroom implementation and the revision of inquiry-based curriculum units. The seven design principles have allowed us to synthesize the PD framework, which, coupled with the design principles, are the preliminary outcomes of the current research. We are in the process of evaluating the content and construct validity of the framework, based on nine one-on-one interviews with experts in inquiry-based classroom and teacher learning. To this end, we have developed an interview protocol with the input of eight such experts in South Africa and Germany. Using the protocol, the expert appraisal of the PD framework will involve three experts from Germany, South Africa, and Cameroon, respectively. These countries, where we originate and/or work, provide a variety of inquiry-based science education contexts, making the countries suitable in the evaluation of the generic PD framework. Based on the evaluation, we will revise the framework and its seven design principles to arrive at the final outcomes of the current research. While the final content and construct a valid version of the framework will serve as an example of the needed ways through which effective inquiry-based science teacher PD may be achieved, the final design principles will be useful to researchers when transforming the framework for use in any specific educational context. For example, in our further research, we will transform the framework to one that is practical and effective in supporting inquiry-based practical work in resource-constrained physical sciences classrooms in South Africa. Researchers in other educational contexts may similarly consider the final framework and design principles in their work. Thus, our final outcomes will inform practice and research around the support of teachers to increase the incorporation of learning experiences that mirror the work of scientists in a worldwide manner.

Keywords: design principles, educational design research, evaluation, inquiry-based science education, professional development framework

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Authors: Nabil A. Ahmed, Nasser A. N. Mhaisen

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The paper presents a solution to enhance the power quality and to reduce the peak load demand in Kuwait electric grid as a solution to the shortage of electricity production. Technical, environmental and economic feasibility study of utilizing integrated grid-connected photovoltaic (PV) system in residential buildings for supplying 7.1% of electrical power consumption in Kuwait is carried out using RETScreen software. A 10 KWp on-grid PV power generation system spread on the rooftop of the residential buildings is adopted and investigated and the complete system performance is simulated using PSIM software. Taking into account the international prices of electricity and natural gas, the proposed solution is investigated and tested for four different types of installation systems in terms of power generation and costs which includes horizontal installation, 25º tilted angle, single axis tracking and dual axis tracking. Results shows that the 25º tilted angle fixed mounted system is the most efficient type. The payback period as a tool of benefit analysis of the proposed system is calculated and it found to be 2.55 years.

Keywords: photovoltaics, residential buildings, electrical grid, production capacity, on-grid, power generation

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Authors: Walid Moudani, Ahmad Shahin

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This research presents a study to handle the recruitment services system. It aims to enhance a business intelligence system by embedding data mining in its core engine and to facilitate the link between job searchers and recruiters companies. The purpose of this study is to present an intelligent management system for supporting recruitment services based on data mining methods. It consists to apply segmentation on the extracted job postings offered by the different recruiters. The details of the job postings are associated to a set of relevant features that are extracted from the web and which are based on critical criterion in order to define consistent clusters. Thereafter, we assign the job searchers to the best cluster while providing a ranking according to the job postings of the selected cluster. The performance of the proposed model used is analyzed, based on a real case study, with the clustered job postings dataset and classified job searchers dataset by using some metrics.

Keywords: job postings, job searchers, clustering, genetic algorithms, business intelligence

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Authors: Hamed Saremi

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One of the challenges in manufacturing and service companies to provide a product or service is recognized Brand to consumers in target markets. They provide most of their processes under the same capacity. But the constant threat of devastating internal and external resources to prevent a rise Brands and more companies are recognizing the stages are bankrupt. This paper has tried to identify and analyze effective indicators of brand equity and focuses on indicators and presents a model of intelligent create a model to prevent possible damage. In this study identified indicators of brand equity based on literature study and according to expert opinions, set of indicators By techniques DEMATEL Then to used Multi-Step Adaptive Neural-Fuzzy Inference system (ANFIS) to design a multi-stage intelligent system for assessment of brand equity.

Keywords: anfis, dematel, brand, cosmetic product, brand value

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Authors: Osama Elsarrar, Marjorie Darrah, Richard Devin

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This paper discusses the idea of capturing an expert’s knowledge in the form of human understandable rules and then inserting these rules into a dynamic cell structure (DCS) neural network. The DCS is a form of self-organizing map that can be used for many purposes, including classification and prediction. This particular neural network is considered to be a topology preserving network that starts with no pre-structure, but assumes a structure once trained. The DCS has been used in mission and safety-critical applications, including adaptive flight control and health-monitoring in aerial vehicles. The approach is to insert expert knowledge into the DCS before training. Rules are translated into a pre-structure and then training data are presented. This idea has been demonstrated using the well-known Iris data set and it has been shown that inserting the pre-structure results in better accuracy with the same training.

Keywords: neural network, self-organizing map, rule extraction, rule insertion

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Authors: Ho-Hsin Lee, Yue-Min Jiang, Shu-Hui Tsai, Jian-Ren Chen, Mei-Yu XU, Wen-Tien Wu

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This project presents an AI-based method and system for wound status analysis. The system uses a three-in-one sensor device to analyze wound status, including color, temperature, and a 3D sensor to provide wound information up to 2mm below the surface, such as redness, heat, and blood circulation information. The system has a 90% accuracy rate, requiring only one manual correction in 70% of cases, with a one-second delay. The system also provides an offline application that allows for manual correction of the wound bed range using color-based guidance to estimate wound bed size with 96% accuracy and a maximum of one manual correction in 96% of cases, with a one-second delay. Additionally, AI-assisted wound bed range selection achieves 100% of cases without manual intervention, with an accuracy rate of 76%, while AI-based wound tissue type classification achieves an 85.3% accuracy rate for five categories. The AI system also includes similar case search and expert recommendation capabilities. For AI-assisted wound range selection, the system uses WIFI6 technology, increasing data transmission speeds by 22 times. The project aims to save up to 64% of the time required for human wound record keeping and reduce the estimated time to assess wound status by 96%, with an 80% accuracy rate. Overall, the proposed AI method and system integrate multiple sensors to provide accurate wound information and offer offline and online AI-assisted wound bed size estimation and wound tissue type classification. The system decreases delay time to one second, reduces the number of manual corrections required, saves time on wound record keeping, and increases data transmission speed, all of which have the potential to significantly improve wound care and management efficiency and accuracy.

Keywords: wound status analysis, AI-based system, multi-sensor integration, color-based guidance

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Authors: Chin-Yu Lin, Kun-Chi Wang, Shih-Hsu Wang, Wei-Chih Wang

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A construction superintendent needs to know not only the amount of quantities of cost items or materials completed to develop a daily report or calculate the daily progress (earned value) in each day, but also the amount of quantities of materials (e.g., reinforced steel and concrete) to be ordered (or moved into the jobsite) for performing the in-progress or ready-to-start construction activities (e.g., erection of reinforced steel and concrete pouring). These daily construction management tasks require great effort in extracting accurate quantities in a short time (usually must be completed right before getting off work every day). As a result, most superintendents can only provide these quantity data based on either what they see on the site (high inaccuracy) or the extraction of quantities from two-dimension (2D) construction drawings (high time consumption). Hence, the current practice of providing the amount of quantity data completed in each day needs improvement in terms of more accuracy and efficiency. Recently, a three-dimension (3D)-based building information model (BIM) technique has been widely applied to support construction quantity takeoffs (QTO) process. The capability of virtual reality (VR) allows to view a building from the first person's viewpoint. Thus, this study proposes an innovative system by integrating VR (using 'Unity') and BIM (using 'Revit') to extract quantities to support the above daily construction management tasks. The use of VR allows a system user to be present in a virtual building to more objectively assess the construction progress in the office. This VR- and BIM-based system is also facilitated by an integrated database (consisting of the information and data associated with the BIM model, QTO, and costs). In each day, a superintendent can work through a BIM-based virtual building to quickly identify (via a developed VR shooting function) the building components (or objects) that are in-progress or finished in the jobsite. And he then specifies a percentage (e.g., 20%, 50% or 100%) of completion of each identified building object based on his observation on the jobsite. Next, the system will generate the completed quantities that day by multiplying the specified percentage by the full quantities of the cost items (or materials) associated with the identified object. A building construction project located in northern Taiwan is used as a case study to test the benefits (i.e., accuracy and efficiency) of the proposed system in quantity extraction for supporting the development of daily reports and the orders of construction materials.

Keywords: building information model, construction management, quantity takeoffs, virtual reality

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Authors: N. D'Amico, E. Grossi, B. Colombo, F. Rigiroli, M. Buscema, D. Fazzini, G. Cornalba, S. Papa

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Purpose: To characterize, through a radiomic approach, the nature of nodules considered non-specific by expert radiologists, recognized in magnetic resonance mammography (MRm) with T1-weighted (T1w) sequences with paramagnetic contrast. Material and Methods: 47 cases out of 1200 undergoing MRm, in which the MRm assessment gave uncertain classification (non-specific nodules), were admitted to the study. The clinical outcome of the non-specific nodules was later found through follow-up or further exams (biopsy), finding 35 benign and 12 malignant. All MR Images were acquired at 1.5T, a first basal T1w sequence and then four T1w acquisitions after the paramagnetic contrast injection. After a manual segmentation of the lesions, done by a radiologist, and the extraction of 150 radiomic features (30 features per 5 subsequent times) a machine learning (ML) approach was used. An evolutionary algorithm (TWIST system based on KNN algorithm) was used to subdivide the dataset into training and validation test and to select features yielding the maximal amount of information. After this pre-processing, different machine learning systems were applied to develop a predictive model based on a training-testing crossover procedure. 10 cases with a benign nodule (follow-up older than 5 years) and 18 with an evident malignant tumor (clear malignant histological exam) were added to the dataset in order to allow the ML system to better learn from data. Results: NaiveBayes algorithm working on 79 features selected by a TWIST system, resulted to be the best performing ML system with a sensitivity of 96% and a specificity of 78% and a global accuracy of 87% (average values of two training-testing procedures ab-ba). The results showed that in the subset of 47 non-specific nodules, the algorithm predicted the outcome of 45 nodules which an expert radiologist could not identify. Conclusion: In this pilot study we identified a radiomic approach allowing ML systems to perform well in the diagnosis of a non-specific nodule at MR mammography. This algorithm could be a great support for the early diagnosis of malignant breast tumor, in the event the radiologist is not able to identify the kind of lesion and reduces the necessity for long follow-up. Clinical Relevance: This machine learning algorithm could be essential to support the radiologist in early diagnosis of non-specific nodules, in order to avoid strenuous follow-up and painful biopsy for the patient.

Keywords: breast, machine learning, MRI, radiomics

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Authors: Chandragiri Nagadeep, M. V. V. S. Durga, Sadu Mahikshith

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Future generation is depended on new ideas and innovations that develops the country economical growth and technology standards so, Startups plays an important role in satisfying above goals. Startups includes support which is given by investing into it by investors but, single digit investors can’t keep supporting one startup and lot of security problems occurs while transferring large funds to startup’s bank account. Targeting security and most supportive funding, TogEther solves these issues by providing a platform where “Crowd Funding” is available in a decentralized way such that funding is done with digital currency called cryptocurrency where transactions are done in a secured way using “Block Chain Technology”. Not only Funding but also Ideas along with their documents can be presented and hosted with help of IPFS (Inter Planetary File System).

Keywords: blockchain, ethereum, web3, reactjs, interplanetary file system, funding

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Authors: Kumari Sweta, Ajanta Goswami, Abhilasha Dixit

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Landslide is a geomorphic process that plays an essential role in the evolution of the hill-slope and long-term landscape evolution. But its abrupt nature and the associated catastrophic forces of the process can have undesirable socio-economic impacts, like substantial economic losses, fatalities, ecosystem, geomorphologic and infrastructure disturbances. The estimated fatality rate is approximately 1person /100 sq. Km and the average economic loss is more than 550 crores/year in the Himalayan belt due to landslides. This study presents a comparative performance of a statistical bivariate method and a machine learning technique for landslide susceptibility mapping in and around Dharamshala, Himachal Pradesh. The final produced landslide susceptibility maps (LSMs) with better accuracy could be used for land-use planning to prevent future losses. Dharamshala, a part of North-western Himalaya, is one of the fastest-growing tourism hubs with a total population of 30,764 according to the 2011 census and is amongst one of the hundred Indian cities to be developed as a smart city under PM’s Smart Cities Mission. A total of 209 landslide locations were identified in using high-resolution linear imaging self-scanning (LISS IV) data. The thematic maps of parameters influencing landslide occurrence were generated using remote sensing and other ancillary data in the GIS environment. The landslide causative parameters used in the study are slope angle, slope aspect, elevation, curvature, topographic wetness index, relative relief, distance from lineaments, land use land cover, and geology. LSMs were prepared using information value (Info Val), and Fuzzy Expert System (FES) models. Info Val is a statistical bivariate method, in which information values were calculated as the ratio of the landslide pixels per factor class (Si/Ni) to the total landslide pixel per parameter (S/N). Using this information values all parameters were reclassified and then summed in GIS to obtain the landslide susceptibility index (LSI) map. The FES method is a machine learning technique based on ‘mean and neighbour’ strategy for the construction of fuzzifier (input) and defuzzifier (output) membership function (MF) structure, and the FR method is used for formulating if-then rules. Two types of membership structures were utilized for membership function Bell-Gaussian (BG) and Trapezoidal-Triangular (TT). LSI for BG and TT were obtained applying membership function and if-then rules in MATLAB. The final LSMs were spatially and statistically validated. The validation results showed that in terms of accuracy, Info Val (83.4%) is better than BG (83.0%) and TT (82.6%), whereas, in terms of spatial distribution, BG is best. Hence, considering both statistical and spatial accuracy, BG is the most accurate one.

Keywords: bivariate statistical techniques, BG and TT membership structure, fuzzy expert system, information value method, machine learning technique

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Authors: Dodi Ikhsanshaleh

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When subjected to dynamic load, foundation oscillates in the way that depends on the soil behaviour, the geometry and inertia of the foundation and the dynamic exctation. The practical guideline to analysis block-type foundation excitated by dynamic load from vibrating machine is presented. The analysis use Lumped Mass Parameter Method to express dynamic properties such as stiffness and damping of soil. The numerical examples are performed on design block-type foundation supporting gas turbine compressor which is important equipment package in gas processing plant

Keywords: block foundation, dynamic load, lumped mass parameter

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Authors: Susanna Vanhamäki, Gabor Schneider, Kati Manskinen

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‘Bioeconomy’ is a complex concept that cuts across many sectors and covers several policy areas. To achieve an overall understanding and support a successful bioeconomy, a cross-sectorial approach is necessary. In practice, due to the concept’s wide scope and varying international approaches, fully understanding bioeconomy is challenging on policy level. This paper provides a background of the topic through an analysis of bioeconomy strategies in the Baltic Sea region. Expert interviews and a small survey were conducted to discover the current and intended focuses of these countries’ bioeconomy sectors. The research shows that supporting sustainability is one of the keys in developing the future bioeconomy. The results highlighted that the bioeconomy has to be sustainable and based on circular economy principles. Currently, traditional bioeconomy sectors like food, wood, fish & waters as well as fuel & energy, which are in the core of national bioeconomy strategies, are best known and are considered more relevant than other bioeconomy industries. However, there is increasing potential for novel sectors, such as textiles and pharmaceuticals. The present research indicates that the opportunities presented by these bioeconomy sectors should be recognised and promoted. Education, research and innovation can play key roles in developing transformative and sustainable improvements in primary production and renewable resources. Furthermore, cooperation between businesses and educators is important.

Keywords: bioeconomy, circular economy, policy, strategy

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Authors: Roy B. Clariana, Ryan L. Solnosky

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Structural feedback is any form of feedback that aims to improve the quality of students’ domain-normative conceptual interrelationships. Research with structural feedback points to the potential mediating role of network graphs as feedback for tuning students’ conceptual understanding; for example, improved content knowledge and motivation were observed for undergraduate students who accessed the instructor’s networks of course content. This exploratory study uses a one-group pretest-posttest design to examine the effects of instructor-provided network feedback during lectures on students’ knowledge structure measured using a concept sorting task at the pretest and posttest. Undergraduate students in an architectural engineering course (n = 32) completed a lesson module and then an end-of-unit quiz on building with wood and wood framing. Three weeks later, as a review, students completed a sorting task that used 26 terms from that lesson, then a week later, the sorting task data were used to create a group-average network, this network along with the instructor’s expert network were added to that week’s lecture slides and were compared and discussed during class time. A week later, students completed the sorting task again. The pre and post-sorting data were rendered into pathfinder networks, and then these students’ networks were compared to five referent networks, specifically the textbook chapter network, the lecture slides network, a network of the end-of-unit quiz, the actual expert network that served as the feedback intervention, and the group-average network. Inspection of means shows that knowledge structure measures improved for all five measures from pre-to-post, becoming more like the lesson content and like the expert. Repeated measures analysis with follow-up paired samples t-tests showed pre-to-post significant increases for both the end-of-unit quiz and the expert network referents. The findings show that instructor presentation of structural feedback as networks improved or ‘tuned’ students’ knowledge structure of the lesson content. This approach only takes a few extra minutes of class time and is fairly simple to implement in ordinary classrooms, and so it has wide potential to support classroom instruction and student learning. Further research is needed to determine how critical it is to present both the group-average network along with the expert network for comparison in order to highlight group-level misconceptions, or is presenting only the expert network sufficient? If a group-level network is necessary, then a simple clicker-like classroom tool could be developed to collect sorting task data during lectures that could then immediately provide the group-average network for class discussion and reflection.

Keywords: classroom instruction, engineering education, knowledge structure, pathfinder networks, structural feedback

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Authors: Bakr Zade, Paolo Cervera

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With the aim of maximising return on innovation investments, organisations create central units to support successful implementation of innovation management initiatives. The support units–referred to in this research as innovation management offices (IMOs)–range from small teams of innovation management champions to fully resourced centres of excellence for innovation management. However, roles and responsibilities of IMOs vary in different organisations. This research investigates the different types of IMO in organisations, based on their different roles and responsibilities in supporting innovation management processes. The research uses grounded theory methodology to uncover an IMO taxonomy from emergent concepts during innovation management maturity assessment exercises in twelve organisations from the United Kingdom and the United Arab Emirates. The taxonomy distinguishes five types of IMO, based on their roles and responsibilities in supporting innovation management processes, from organisational strategic foresight to managing innovation management project portfolios. The IMO taxonomy addresses a gap in research into innovation management support in organisations and offers a practical framework that diverse organisations can appreciate and use in designing IMOs that are aligned with their innovation management visions and strategies.

Keywords: future foresight, future shaping, innovation management, innovation management office, portfolio management

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Authors: J. M. Counsell, Y. Khalid, M. J. Stewart

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Achieving nearly zero carbon heating continues to be identified by UK government analysis as an important feature of any lowest cost pathway to reducing greenhouse gas emissions. Heat currently accounts for 48% of UK energy consumption and approximately one third of UK’s greenhouse gas emissions. Heat Networks are being promoted by UK investment policies as one means of supporting hybrid heat pump based solutions. To this effect the RISE (Renewable Integrated and Sustainable Electric) heating system project is investigating how an all-electric heating sourceshybrid configuration could play a key role in long-term decarbonisation of heat.  For the purposes of this study, hybrid systems are defined as systems combining the technologies of an electric driven air source heat pump, electric powered thermal storage, a thermal vessel and micro-heat network as an integrated system.  This hybrid strategy allows for the system to store up energy during periods of low electricity demand from the national grid, turning it into a dynamic supply of low cost heat which is utilized only when required. Currently a prototype of such a system is being tested in a modern house integrated with advanced controls and sensors. This paper presents the virtual performance analysis of the system and its design for a micro heat network with multiple dwelling units. The results show that the RISE system is controllable and can reduce carbon emissions whilst being competitive in running costs with a conventional gas boiler heating system.

Keywords: gas boilers, heat pumps, hybrid heating and thermal storage, renewable integrated and sustainable electric

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Authors: Ezgi Tozak, H. Pelin Karasu, Umit Girgin

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In this study, difficulties encountered in the process of supporting the reading skills of a student with hearing loss whose inclusion was ongoing and the solutions improved during the practice process were examined. The study design was action research. Participants of this study, which was conducted between the dates of 29 September 2016 and 22 February 2017, consisted of a student with hearing loss, a classroom teacher, a teacher in the rehabilitation center, researcher/teacher and validity committee members. The data were obtained through observations, validity committee meeting, interviews, documents, and the researcher diary. Research findings show that in the process of supporting reading skills of the student with hearing loss, the student's knowledge of concepts was limited, and the student had difficulties in feeling and identification of sounds, reading and understanding words-sentences and retelling what he/she listened to. With the purpose of overcoming these difficulties in the implementation process, activities were prepared towards concepts, sound education, reading and understanding words and sentences, and retelling what you listen to; these activities were supported with visual materials and real objects and repeated with diversities.

Keywords: inclusion, reading process, supportive education, student with hearing loss

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Authors: Suraj Nair, Aravindkumar Vijayalingam, Alexander Perzylo, Alois Knoll

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In the last decade robotics research and development activities have grown rapidly, especially in the domain of service robotics. Integrating service robots into human occupied spaces such as homes, offices, hospitals, etc. has become increasingly worked upon. The primary motive is to ease daily lives of humans by taking over some of the household/office chores. However, several challenges remain in systematically integrating such systems in human shared work-spaces. In addition to sensing and indoor-navigation challenges, programmability of such systems is a major hurdle due to the fact that the potential user cannot be expected to have knowledge in robotics or similar mechatronic systems. In this paper, we propose a cognitive system for service robotics which allows non-expert users to easily model system behaviour in an underspecified manner through abstract tasks and objects associated with them. The system uses domain knowledge expressed in the form of an ontology along with logical reasoning mechanisms to infer all the missing pieces of information required for executing the tasks. Furthermore, the system is also capable of recovering from failed tasks arising due to on-line disturbances by using the knowledge base and inferring alternate methods to execute the same tasks. The system is demonstrated through a coffee fetching scenario in an office environment using a mobile robot equipped with sensors and software capabilities for autonomous navigation and human-interaction through natural language.

Keywords: cognitive robotics, reasoning, service robotics, task based systems

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Authors: Efleda Preclaro Tolentino

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Research indicates that an educator’s belief system is reflected in the way they structure the learning environment. Their values and belief system have the potential to positively impact school readiness through an understanding of children’s development and the creation of a stable, motivating environment. Based on the premise that the social environment influences the development of social skills, knowledge construct, and shared values of young children, this study examined verbal and nonverbal exchanges between early childhood teachers and their preschool students within the context of remote learning. Using the qualitative method of data collection, the study determined the nature of interactions between preschoolers and their teachers within a remote learning environment at a preschool in Southeast Asia that utilized the Mother Tongue-based Multilingual Education (MTBMLE) Approach. From the lens of sociocultural theory, the study investigated preschoolers’ use of literacies to convey meaning and to interact within a remote learning environment. Using a Strengths Perspective, the study revealed the creativity and resourcefulness of preschoolers in expressing themselves through trans-literacies that were made possible by the use of online mode of learning within cultural and subcultural norms. The study likewise examined how social skills acquired by young children were transmitted (verbally or nonverbally) in their interactions with peers during Zoom meetings. By examining the dynamics of social exchanges between teachers and children, the findings of the study underscore the importance of providing support for preschool students as they apply acquired values and shared practices within a remote learning environment. The potential of distance learning in the early years will be explored, specifically in supporting young children’s language and literacy development. At the same time, the study examines the role of teachers as cultivators of trans-literacies. The teachers’ skillful use of technology in facilitating young children’s learning, as well as in supporting interactions with families, will be examined. The findings of this study will explore the potential of distance learning in early childhood education to establish continuity in learning, supporting young children’s social and emotional transitions, and nurturing trans-literacies that transcend prevailing definitions of learning contexts. The implications of teachers and parents working collaboratively to support student learning will be examined. The importance of preparing teachers to be resourceful, adaptable, and innovative to ensure that learning takes place across a variety of modes and settings will be discussed.

Keywords: transliteracy, preschoolers, remote learning, strengths perspective

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Authors: Usiobaifo Agharese Rosemary, Osaseri Roseline Oghogho

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Diabetes is a complex group of disease with a variety of causes; it is a disorder of the body metabolism in the digestion of carbohydrates food. The application of machine learning in the field of medical diagnosis has been the focus of many researchers and the use of recognition and classification model as a decision support tools has help the medical expert in diagnosis of diseases. Considering the large volume of medical data which require special techniques, experience, and high diagnostic skill in the diagnosis of diseases, the application of an artificial intelligent system to assist medical personnel in order to enhance their efficiency and accuracy in diagnosis will be an invaluable tool. In this study will propose a diabetes diagnosis model using rough set and K-nearest Neighbor classifier algorithm. The system consists of two modules: the feature extraction module and predictor module, rough data set is used to preprocess the attributes while K-nearest neighbor classifier is used to classify the given data. The dataset used for this model was taken for University of Benin Teaching Hospital (UBTH) database. Half of the data was used in the training while the other half was used in testing the system. The proposed model was able to achieve over 80% accuracy.

Keywords: classifier algorithm, diabetes, diagnostic model, machine learning

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Authors: T. Penkova, A. Korobko, V. Nicheporchuk, L. Nozhenkova, A. Metus

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This paper presents an approach of on-line control of the state of technosphere and environment objects based on the integration of Data Warehouse, OLAP and Expert systems technologies. It looks at the structure and content of data warehouse that provides consolidation and storage of monitoring data. There is a description of OLAP-models that provide a multidimensional analysis of monitoring data and dynamic analysis of principal parameters of controlled objects. The authors suggest some criteria of emergency risk assessment using expert knowledge about danger levels. It is demonstrated now some of the proposed solutions could be adopted in territorial decision making support systems. Operational control allows authorities to detect threat, prevent natural and anthropogenic emergencies and ensure a comprehensive safety of territory.

Keywords: decision making support systems, emergency risk assessment, natural and anthropogenic safety, on-line control, territory

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Authors: Dalwinder Singh, Amandeep Verma, Manpreet Kaur, Birmohan Singh

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The detection of pre-cancerous changes using a Pap smear test of cervical cell is the important step for the early diagnosis of cervical cancer. The Pap smear test consists of a sample of human cells taken from the cervix which are analysed to detect cancerous and pre-cancerous stage of the given subject. The manual analysis of these cells is labor intensive and time consuming process which relies on expert cytotechnologist. In this paper, a computer assisted system for the automated analysis of the cervical cells has been proposed. We propose a morphology based approach to the nucleus detection and segmentation of the cytoplasmic region of the given single or multiple overlapped cell. Further, various texture and region based features are calculated from these cells to classify these into normal and abnormal cell. Experimental results on public available dataset show that our system has achieved satisfactory success rate.

Keywords: cervical cancer, cervical tissue, mathematical morphology, texture features

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Authors: Rashida Suleiman, Asamoah Jnr. Boakye, Suleiman Ahmed Ibn Ahmed

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In recent years, there has been an enormous success in discoveries of scientific knowledge in medicine coupled with the advancement of technology. Despite all these successes, diagnoses and treatment of diseases have become complex. MYCIN is a groundbreaking illustration of a clinical decision support system (CDSS), which was developed to assist physicians in the diagnosis and treatment of bacterial infections by providing suggestions for antibiotic regimens. MYCIN was one of the earliest expert systems to demonstrate how CDSSs may assist human decision-making in complicated areas. Relevant databases were searched using google scholar, PubMed and general Google search, which were peculiar to clinical decision support systems. The articles were then screened for a comprehensive overview of the functionality, consultative style and statistical usage of MYCIN, a clinical decision support system. Inferences drawn from the articles showed some usage of MYCIN for problem-based learning among clinicians and students in some countries. Furthermore, the data demonstrated that MYCIN had completed clinical testing at Stanford University Hospital following years of research. The system (MYCIN) was shown to be extremely accurate and effective in diagnosing and treating bacterial infections, and it demonstrated how CDSSs might enhance clinical decision-making in difficult circumstances. Despite the challenges MYCIN presents, the benefits of its usage to clinicians, students and software developers are enormous.

Keywords: clinical decision support system, MYCIN, diagnosis, bacterial infections, support systems

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Authors: Mohita Gangwar Sharma

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Different factors are compelling manufacturers to move towards the phenomenon of servitization i.e. when firms go beyond giving support to the customers in operating the equipment. The challenges that are being faced in this transition by the manufacturing firms from being a product provider to a product- service provider are multipronged. Product-Service Systems (PSS) lies in between the pure-product and pure-service continuum. Through this study, we wish to understand the dimensions of ‘PSS-quality’. We draw upon the quality literature for both the product and services and through an expert survey for a specific transportation sector using analytical hierarchical process (AHP) derive a conceptual model that can be used as a comprehensive measurement tool for PSS offerings.

Keywords: servitisation, quality, product-service system, AHP

Procedia PDF Downloads 277

Authors: Veerakumar Arumugam, Rajesh Mishra, Jiri Militky, Jana Salacova

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The thermo-physiological comfort and compression properties of knitted spacer fabrics have been evaluated by varying the different spacer fabric parameters. Air permeability and water vapor transmission of the fabrics were measured using the Textest FX-3300 air permeability tester and PERMETEST. Then thermal behavior of fabrics was obtained by Thermal conductivity analyzer and overall moisture management capacity was evaluated by moisture management tester. Spacer Fabrics compression properties were also tested using Kawabata Evaluation System (KES-FB3). In the KES testing, the compression resilience, work of compression, linearity of compression and other parameters were calculated from the pressure-thickness curves. Analysis of Variance (ANOVA) was performed using new statistical software named QC expert trilobite and Darwin in order to compare the influence of different fabric parameters on thermo-physiological and compression behavior of samples. This study established that the raw materials, type of spacer yarn, density, thickness and tightness of surface layer have significant influence on both thermal conductivity and work of compression in spacer fabrics. The parameter which mainly influence on the water vapor permeability of these fabrics is the properties of raw material i.e. the wetting and wicking properties of fibers. The Pearson correlation between moisture capacity of the fabrics and water vapour permeability was found using statistical software named QC expert trilobite and Darwin. These findings are important requirements for the further designing of clothing for extreme environmental conditions.

Keywords: 3D spacer fabrics, thermal conductivity, moisture management, work of compression (WC), resilience of compression (RC)

Procedia PDF Downloads 517

Authors: Sudhir K. Gupta

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Introduction: When a forensic doctor determines that a suspicious death is a suicide, homicide, or accident, the decision virtually becomes incontestable by the investigating police officer, and it becomes an issue whether the medical opinion was created with necessary checks and balances on the other probabilities of the case. It is suggested that the opinion of Forensic Medical experts is conventional, mutable, and shifting from one expert to another. The determination of suicide, accident, or homicide is mandatorily required, which is the Gold Standard for conducting death investigations. Forensic investigations serve many audiences, but the court is by far the most critical. The likely questions on direct and cross-examination determine how forensic doctors gather and handle evidence and what conclusions they reach. Methodology: The author interacted with the investigative authority, and a crime scene visit was also done along with the perusal of the Postmortem report, subsequent opinion, and crime scene photographs and statements of the witness and accused. Further analysis of all relevant scientific documents and opinions of other forensic doctors, forensic scientists, and ballistic experts involved in these cases was done to arrive at an opinion with scientific justification. Findings: The opinions arrived at by the author and how they helped the judiciary in delivering justice in these cases have been discussed in this article. This can help the readers to understand the process involved in formulating a credible forensic medical expert opinion for investigators and the judiciary. Conclusion: A criminal case might be won or lost over doubt cast on the chain of custody. Medically trained forensic doctors, therefore, learn to practice their profession in legally appropriate ways, and opinions must be based on medical justifications with credible references.

Keywords: forensic doctor, professional credibility, investigation, expert opinion

Procedia PDF Downloads 46

Authors: Roman Graf, Sergiu Gordea, Heather M. Ryan

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This paper presents an approach for the easy creation of an institutional risk profile for endangerment analysis of file formats. The main contribution of this work is the employment of data mining techniques to support risk factors set up with just the most important values that are important for a particular organisation. Subsequently, the risk profile employs fuzzy models and associated configurations for the file format metadata aggregator to support digital preservation experts with a semi-automatic estimation of endangerment level for file formats. Our goal is to make use of a domain expert knowledge base aggregated from a digital preservation survey in order to detect preservation risks for a particular institution. Another contribution is support for visualisation and analysis of risk factors for a requried dimension. The proposed methods improve the visibility of risk factor information and the quality of a digital preservation process. The presented approach is meant to facilitate decision making for the preservation of digital content in libraries and archives using domain expert knowledge and automatically aggregated file format metadata from linked open data sources. To facilitate decision-making, the aggregated information about the risk factors is presented as a multidimensional vector. The goal is to visualise particular dimensions of this vector for analysis by an expert. The sample risk profile calculation and the visualisation of some risk factor dimensions is presented in the evaluation section.

Keywords: digital information management, file format, endangerment analysis, fuzzy models

Procedia PDF Downloads 377

Authors: Nigina Toktasynova, Sholpan Sagyndykova, Zhanat Kenzhebayeva, Maksat Kalimoldayev, Mariya Ishimova, Irbulat Utepbergenov

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Any business needs a stable operation and continuous improvement, therefore it is necessary to constantly interact with the environment, to analyze the work of the enterprise in terms of employees, executives and consumers, as well as to correct any inconsistencies of certain types of processes and their aggregate. In the case of heat supply organizations, in addition to suppliers, local legislation must be considered which often is the main regulator of pricing of services. In this case, the process approach used to build a functional organizational structure in these types of businesses in Kazakhstan is a challenge not only in the implementation, but also in ways of analyzing the employee's salary. To solve these problems, we investigated the management system of heating enterprise, including strategic planning based on the balanced scorecard (BSC), quality management in accordance with the standards of the Quality Management System (QMS) ISO 9001 and analysis of the system based on expert judgment using fuzzy inference. To carry out our work we used the theory of fuzzy sets, the QMS in accordance with ISO 9001, BSC according to the method of Kaplan and Norton, method of construction of business processes according to the notation IDEF0, theory of modeling using Matlab software simulation tools and graphical programming LabVIEW. The results of the work are as follows: We determined possibilities of improving the management of heat-supply plant-based on QMS; after the justification and adaptation of software tool it has been used to automate a series of functions for the management and reduction of resources and for the maintenance of the system up to date; an application for the analysis of the QMS based on fuzzy inference has been created with novel organization of communication software with the application enabling the analysis of relevant data of enterprise management system.

Keywords: balanced scorecard, heat supply, quality management system, the theory of fuzzy sets

Procedia PDF Downloads 342

Authors: Anastassis Kozanitis

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The first year of college or university can be particularly challenging for students from minority groups, who often face unique obstacles related to their cultural background, socioeconomic status, or underrepresented identities. Recognizing the importance of fostering inclusivity and supporting the success of these students, educational institutions in Quebec, Canada, have implemented a range of initiatives tailored to address their specific needs. This presentation provides an overview of four key first-year experience measures for minority groups, focusing on mentorship programs, student-lead cultural centers, walk-in support offices, and diversity training, all aimed at promoting inclusion and enhancing the academic journey and overall well-being of these students. Semi-structured individual interviews were conducted with individuals working in connection with the measures of interest. A qualitative content analysis allowed for the characterization of facilitating factors of the support measures identified. Hence, all four measures have proven to be instrumental in supporting the transition and success of first-year students from minority groups. These initiatives provide safe spaces where students can connect with their cultural heritage, engage in dialogue, and celebrate diversity. In conclusion, first-year experience initiatives for minority groups in college and university play a pivotal role in fostering inclusivity and supporting the success of students from underrepresented backgrounds.

Keywords: diversity, first year, minority groups, inclusion, support measures, higher education

Procedia PDF Downloads 45

Authors: S. K. Kakraliya, R. D. Jat, H. S. Jat, P. C. Sharma, M. L. Jat

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The traditional rice-wheat (RW) system in the IGP of South Asia is tillage, water, energy, and capital intensive. Coupled with more pumping of groundwater over the years to meet the high irrigation water requirement of the RW system has resulted in over-exploitation of groundwater. Replacement of traditional rice with less water crops such as maize under climate-smart agriculture (CSA) based management (tillage, crop establishment and residue management) practices are required to promote sustainable intensification. Furthermore, inefficient nutrient management practices are responsible for low crop yields and nutrient use efficiencies in maize-wheat (MW) system. A 7-year field experiment was conducted in farmer’s participatory strategic research mode at Taraori, Karnal, India to evaluate the effects of tillage and crop establishment (TCE) methods, residue management, mungbean integration, and nutrient management practices on crop yields, water productivity and profitability of MW system. The main plot treatments included four combinations of TCE, residue and mungbean integration [conventional tillage (CT), conventional tillage with mungbean (CT + MB), permanent bed (PB) and permanent bed with MB (PB + MB] with three nutrient management practices [farmer’s fertilizer practice (FFP), recommended dose of fertilizer (RDF) and site-specific nutrient management (SSNM)] using Nutrient Expert® as subplot treatments. System productivity, water use efficiency (WUE) and net returns under PB + MB were significantly increased by 25–30%, 28–31% and 35–40% compared to CT respectively, during seven years of experimentation. The integration of MB in MW system contributed ~25and ~ 28% increases in system productivity and net returns compared with no MB, respectively. SSNM based nutrient management increased the mean (averaged across 7 yrs) system productivity by 12- 15% compared with FFP. The study revealed that CSA based sustainable intensification (PB + MB) and SSNM approach provided opportunities for enhancing crop productivity, WUE and profitability of the MW system in India.

Keywords: Conservation Agriculture, Precision water and nutrient management, Permanent beds, Crop yields

Procedia PDF Downloads 108