Search results for: educational data mining

Authors: Rym Ghariani, Ghada Soltane, Younes Boujelbene

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Industry 4.0, a set of emerging smart and digital technologies, has been the main focus of operations management researchers and practitioners in recent years. The objective of this research paper is to study the impact of Industry 4.0 on the integration of the supply chain (SCI) in Tunisian industrial companies. A conceptual model to study the relationship between Industry 4.0 technologies and supply chain integration was designed. This model contains three explained variables (Big data, Internet of Things, and Robotics) and one variable to be explained (supply chain integration). In order to answer our research questions and investigate the research hypotheses, principal component analysis and discriminant analysis were used using SPSS26 software. The results reveal that there is a statistically positive impact significant impact of Industry 4.0 (Big data, Internet of Things and Robotics) on the integration of the supply chain. Interestingly, big data has a greater positive impact on supply chain integration than the Internet of Things and robotics.

Keywords: industry 4.0 (I4.0), big data, internet of things, robotics, supply chain integration

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Authors: Petra Hofmann, Dana Koniel, Jussi Luukkanen, Walter Nieminen, Lea Hannola, Ilkka Donoghue

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The Covid-19 pandemic forced people to isolate and become physically less connected. The pandemic has not only reshaped people’s behaviours and needs but also accelerated digital transformation (DT). DT of cities has become an imperative with the outlook of converting them into smart cities in the future. Embedding digital infrastructure and smart city initiatives as part of normal design, construction, and operation of cities provides a unique opportunity to improve the connection between people. The Internet of Things (IoT) is an emerging technology and one of the drivers in DT. It has disrupted many industries by introducing different services and business models, and IoT solutions are being applied in multiple fields, including smart cities. As IoT and data are fundamentally linked together, IoT solutions can only create value if the data generated by the IoT devices is analysed properly. Extracting relevant conclusions and actionable insights by using established techniques, data analytics contributes significantly to the growth and success of IoT applications and investments. Companies must grasp DT and be prepared to redesign their offerings and business models to remain competitive in today’s marketplace. As there are many IoT solutions available today, the amount of data is tremendous. The challenge for companies is to understand what solutions to focus on and how to prioritise and which data to differentiate from the competition. This paper explains how IoT and data analytics can impact competitive advantage and how companies should approach IoT and data analytics to translate them into concrete offerings and solutions in the smart city context. The study was carried out as a qualitative, literature-based research. A case study is provided to validate the preservation of company’s competitive advantage through smart city solutions. The results of the research contribution provide insights into the different factors and considerations related to creating competitive advantage through IoT and data analytics deployment in the smart city context. Furthermore, this paper proposes a framework that merges the factors and considerations with examples of offerings and solutions in smart cities. The data collected through IoT devices, and the intelligent use of it, can create competitive advantage to companies operating in smart city business. Companies should take into consideration the five forces of competition that shape industries and pay attention to the technological, organisational, and external contexts which define factors for consideration of competitive advantages in the field of IoT and data analytics. Companies that can utilise these key assets in their businesses will most likely conquer the markets and have a strong foothold in the smart city business.

Keywords: data analytics, smart cities, competitive advantage, internet of things

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Authors: Ibe O. Stephen, Egwuonwu N. Gabriel

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Variations in seismic P-wave velocity and depth resolution resulting from variations in subsurface water saturation were investigated in this study in order to determine the season of the year that gives the most reliable P-wave velocity and depth resolution of the subsurface in Zaria Area, Nigeria. A 2D seismic refraction tomography technique involving an ABEM Terraloc MK6 Seismograph was used to collect data across a borehole of standard log with the centre of the spread situated at the borehole site. Using the same parameters this procedure was repeated along the same spread for at least once in a month for at least eight months in a year for four years. The choice for each survey time depended on when there was significant variation in rainfall data. The seismic data collected were tomographically inverted. The results suggested that the average P-wave velocity ranges of the subsurface in the area are generally higher when the ground was wet than when it was dry. The results also suggested that the overburden of about 9.0 m in thickness, the weathered basement of about 14.0 m in thickness and the fractured basement at a depth of about 23.0 m best fitted the borehole log. This best fit was consistently obtained in the months between March and May when the average total rainfall was about 44.8 mm in the area. The results had also shown that the velocity ranges in both dry and wet formations fall within the standard ranges as provided in literature. In terms of velocity, this study has not in any way clearly distinguished the quality of the results of the seismic data obtained when the subsurface was dry from the results of the data collected when the subsurface was wet. It was concluded that for more detailed and reliable seismic studies in Zaria Area and its environs with similar climatic condition, the surveys are best conducted between March and May. The most reliable seismic data for depth resolution are most likely obtainable in the area between March and May.

Keywords: best season, variations in depth resolution, variations in P-wave velocity, variations in subsurface water saturation, Zaria area

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Authors: Mohammed M. Siddeq, Mohammed H. Rasheed, Omar M. Salih, Marcos A. Rodrigues

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This research proposes a data encoding and decoding method based on the Matrix Minimization algorithm. This algorithm is applied to high-frequency coefficients for compression/encoding. The algorithm starts by converting every three coefficients to a single value; this is accomplished based on three different keys. The decoding/decompression uses a search method called QSS (Quick Sequential Search) Decoding Algorithm presented in this research based on the sequential search to recover the exact coefficients. In the next step, the decoded data are saved in an auxiliary array. The basic idea behind the auxiliary array is to save all possible decoded coefficients; this is because another algorithm, such as conventional sequential search, could retrieve encoded/compressed data independently from the proposed algorithm. The experimental results showed that our proposed decoding algorithm retrieves original data faster than conventional sequential search algorithms.

Keywords: matrix minimization algorithm, decoding sequential search algorithm, image compression, DCT, DWT

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Authors: Shaik Asha Begum, S. Joshna Rani, Shaik Abdul Rahaman

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INTRODUCTION: Breast cancer is a disease that creates in breast cells. "KAP" study estimates the Knowledge, Attitude, and Practices of a local area. More than 1.5 million ladies (25% of all ladies with malignancy) are determined to have bosom disease consistently all through the world. Understanding the degrees of Knowledge, Attitude and Practice will empower a more effective cycle of mindfulness creation as it will permit the program to be custom-made all the more properly to the necessities of the local area. OBJECTIVES: The objective of this study is to assess the knowledge on signs and symptoms, risk factors, provide awareness on the practicing of the early detection techniques of breast cancer and provide knowledge on the overall breast cancer including preventive techniques. METHODOLOGY: This is an expressive cross-sectional investigation. This investigation of KAP was done in the Nirmala Educational Institutions from January to April 2021. A total of 300 participants are included from women students in pharmacy graduates & lecturers, and also from graduates other than the pharmacy. The examiners are taken from the BCAM (Breast Cancer Awareness Measure), tool compartment (Version 2). RESULT: According to the findings of the study, the majority of the participants were not well informed about breast cancer. A lump in the breast was the most commonly mentioned sign of breast cancer, followed by pain in the breast or nipple. The percentage of knowledge related to the breast cancer risk factors was also very less. The correct answers for breast cancer risk factors were radiation exposure (58.20 percent), a positive family history (47.6 percent), obesity (46.9 percent), a lack of physical activity (43.6 percent), and smoking (43.2 percent). Breast cancer screening, on the other hand, was uncommon (only 30 and 11.3 percent practiced clinical breast examination and mammography respectively). CONCLUSION: In this study, the knowledge on the signs and symptoms, risk factors of breast cancer - pharmacy graduates have more knowledge than the non-pharmacy graduates but in the preventive techniques and early detective tools of breast cancer -had poor knowledge in the pharmacy and non-pharmacy graduate. After the awareness program, pharmacy and non-pharmacy graduates got supportive knowledge on the preventive techniques and also practiced the early detective techniques of breast cancer.

Keywords: breast cancer, mammography, KAP study, early detection

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Authors: S. K. Appiah, E. N. Aidoo, D. Asamoah Owusu, M. W. Nuonabuor

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Urbanization remains one of the unique predominant factors which is linked to the destruction of urban environment and its associated cases of soil contamination by heavy metals through the natural and anthropogenic activities. These activities are important sources of toxic heavy metals such as arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), iron (Fe), manganese (Mn), and lead (Pb), nickel (Ni) and zinc (Zn). Often, these heavy metals lead to increased levels in some areas due to the impact of atmospheric deposition caused by their proximity to industrial plants or the indiscriminately burning of substances. Information gathered on potentially hazardous levels of these heavy metals in soils leads to establish serious health and urban agriculture implications. However, characterization of spatial variations of soil contamination by heavy metals in Ghana is limited. Kumasi is a Metropolitan city in Ghana, West Africa and is challenged with the recent spate of deteriorating soil quality due to rapid economic development and other human activities such as “Galamsey”, illegal mining operations within the metropolis. The paper seeks to use both univariate and multivariate geostatistical techniques to assess the spatial distribution of heavy metals in soils and the potential risk associated with ingestion of sources of soil contamination in the Metropolis. Geostatistical tools have the ability to detect changes in correlation structure and how a good knowledge of the study area can help to explain the different scales of variation detected. To achieve this task, point referenced data on heavy metals measured from topsoil samples in a previous study, were collected at various locations. Linear models of regionalisation and coregionalisation were fitted to all experimental semivariograms to describe the spatial dependence between the topsoil heavy metals at different spatial scales, which led to ordinary kriging and cokriging at unsampled locations and production of risk maps of soil contamination by these heavy metals. Results obtained from both the univariate and multivariate semivariogram models showed strong spatial dependence with range of autocorrelations ranging from 100 to 300 meters. The risk maps produced show strong spatial heterogeneity for almost all the soil heavy metals with extremely risk of contamination found close to areas with commercial and industrial activities. Hence, ongoing pollution interventions should be geared towards these highly risk areas for efficient management of soil contamination to avert further pollution in the metropolis.

Keywords: coregionalization, heavy metals, multivariate geostatistical analysis, soil contamination, spatial distribution

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Authors: Inas S. Khayal, Weiping Zhou, Jonathan Skinner

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Healthcare delivery systems around the world are in crisis. The need to improve health outcomes while decreasing healthcare costs have led to an imminent call to action to transform the healthcare delivery system. While Bioinformatics and Biomedical Engineering have primarily focused on biological level data and biomedical technology, there is clear evidence of the importance of the delivery of care on patient outcomes. Classic singular decomposition approaches from reductionist science are not capable of explaining complex systems. Approaches and methods from systems science and systems engineering are utilized to structure healthcare delivery system data. Specifically, systems architecture is used to develop a multi-scale and multi-dimensional characterization of the healthcare delivery system, defined here as the Healthcare Delivery System Knowledge Base. This paper is the first to contribute a new method of structuring and visualizing a multi-dimensional and multi-scale healthcare delivery system using systems architecture in order to better understand healthcare delivery.

Keywords: health informatics, systems thinking, systems architecture, healthcare delivery system, data analytics

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Authors: M. Saeed, A. Shahidzadeh

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Interaction between teachers and learners requires applying a set of samples (examples) which helps to create coordination between the goals and methods. The main result and achievement and application of samples (examples) are that they can bring the teacher and learner to a shared understanding of the concept. mathematical concepts, and also one of the challenging issues in the discussion of the function is to find the collision points of functions of and, regarding that the example space of teachers is different in this issue, this paper aims to present an example space including several problems of the secondary school with the help of intuition and drawing various graphs of functions of and for more familiarity of teachers.

Keywords: inverse function, educational example, Mathematic example, example space

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Authors: Rosy Chaudhary, Pushpa Parajuli

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Background and Objectives: Informational support to family members has a significant potential for reducing this distress related to hospitalization of their patient into the critical care unit, enabling them to cope better and support the patient. The objective of the study is to assess family members’ perception of informational support, anxiety, satisfaction with care and to reveal the association with selected socio-demographic variables and to investigate the correlation between informational support, anxiety and satisfaction with care. Materials and Methods: A descriptive cross-sectional study was conducted in 39 family caregivers of patients admitted in critical care unit of BPKIHS(B.P. Koirala Institute of Health Sciences). Consecutive sampling technique was used wherein data was collected over duration of one month using interview schedule. Descriptive and inferential statistics were used. Results: The mean age of the respondents was 34.97 ± 10.64 and two third (66.70%) were male. Mean score for informational support was 25.72(SD = 5.66; theoretical range of 10 - 40). Mean anxiety was 10.41 (SD = 5.02; theoretical range of 7 - 21). Mean score for satisfaction with care was 40.77 (SD = 6.77; theoretical range of 14 - 64). A moderate positive correlation was found between informational support and satisfaction with care (r = 0.551, p < .001) and a moderate negative correlation was found between anxiety and satisfaction with care (r = -0.590; p = 0.000). No relationship was noted between informational support and anxiety. Conclusion: The informational support and satisfaction of the family caregivers with the care provided to their patients was satisfactory. More than three fourth of the family caregivers had anxiety; the factors associated being educational status of the caregivers, the family income and duration of visiting hours. There was positive correlation between informational support and satisfaction with care provided justifying the need for comprehensive information to the family caregivers by the health personnel. There was negative correlation between anxiety and satisfaction with care.

Keywords: anxiety, caregivers, critical care unit, informational support, family

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Authors: Sebastian Kölbl, Thomas Reitmaier, Mathias Hartmann

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Trial and error approaches to adapt wearable support structures to human physiology are time consuming and elaborate. However, during preliminary design, the focus lies on understanding the interaction between exoskeleton and the human body in terms of forces and moments, namely body mechanics. For the study at hand, a multi-body simulation approach has been enhanced to evaluate actual forces and moments in a human dummy model with and without a digital mock-up of an active exoskeleton. Therefore, different motion data have been gathered and processed to perform a musculosceletal analysis. The motion data are ground reaction forces, electromyography data (EMG) and human motion data recorded with a marker-based motion capture system. Based on the experimental data, the response of the human dummy model has been calibrated. Subsequently, the scalable human dummy model, in conjunction with the motion data, is connected with the exoskeleton structure. The results of the human-machine interaction (HMI) simulation platform are in particular resulting contact forces and human joint forces to compare with admissible values with regard to the human physiology. Furthermore, it provides feedback for the sizing of the exoskeleton structure in terms of resulting interface forces (stress justification) and the effect of its compliance. A stepwise approach for the setup and validation of the modeling strategy is presented and the potential for a more time and cost-effective development of wearable support structures is outlined.

Keywords: assistive devices, ergonomic design, inverse dynamics, inverse kinematics, multibody simulation

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Authors: Oznur Ispir, Oya Celebi Cakiroglu, Esengul Elibol, Emine Ceribas, Gizem Acikgoz, Hande Yesilbas, Merve Tarhan

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This study was conducted to evaluate the academic staff teaching the 'Nursing Management' course in the undergraduate nursing programs of the state universities in Turkey and to assess the current content of the course. Design of the study is descriptive. Population of the study consists of seventy-eight undergraduate nursing programs in the state universities in Turkey. The questionnaire/survey prepared by the researchers was used as a data collection tool. The data were obtained by screening the content of the websites of nursing education programs between March and May 2016. Descriptive statistics were used to analyze the data. The research performed within the study indicated that 58% of the undergraduate nursing programs from which the data were derived were included in the school of health, 81% of the academic staff graduated from the undergraduate nursing programs, 40% worked as a lecturer and 37% specialized in a field other than the nursing. The research also implied that the above-mentioned course was included in 98% of the programs from which it was possible to obtain data. The full name of the course was 'Nursing Management' in 95% of the programs and 98% stated that the course was compulsory. Theory and application hours were 3.13 and 2.91, respectively. Moreover, the content of the course was not shared in 65% of the programs reviewed. This study demonstrated that the experience and expertise of the academic staff teaching the 'Nursing Management' course was not sufficient in the management area, and the schedule and content of the course were not sufficient although many nursing education programs provided the course. Comparison between the curricula of the course revealed significant differences.

Keywords: nursing, nursing management, nursing management course, undergraduate program

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Authors: Y. Bai, M. Bodlak, V. Frolov, S. Huber, V. Jary, I. Konorov, D. Levit, J. Novy, D. Steffen, O. Subrt, M. Virius

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In general, state-of-the-art Data Acquisition Systems (DAQ) in high energy physics experiments must satisfy high requirements in terms of reliability, efficiency and data rate capability. This paper presents the development and deployment of a debugging tool named DAQ Debugger for the intelligent, FPGA-based Data Acquisition System (iFDAQ) of the COMPASS experiment at CERN. Utilizing a hardware event builder, the iFDAQ is designed to be able to readout data at the average maximum rate of 1.5 GB/s of the experiment. In complex softwares, such as the iFDAQ, having thousands of lines of code, the debugging process is absolutely essential to reveal all software issues. Unfortunately, conventional debugging of the iFDAQ is not possible during the real data taking. The DAQ Debugger is a tool for identifying a problem, isolating the source of the problem, and then either correcting the problem or determining a way to work around it. It provides the layer for an easy integration to any process and has no impact on the process performance. Based on handling of system signals, the DAQ Debugger represents an alternative to conventional debuggers provided by most integrated development environments. Whenever problem occurs, it generates reports containing all necessary information important for a deeper investigation and analysis. The DAQ Debugger was fully incorporated to all processes in the iFDAQ during the run 2016. It helped to reveal remaining software issues and improved significantly the stability of the system in comparison with the previous run. In the paper, we present the DAQ Debugger from several insights and discuss it in a detailed way.

Keywords: DAQ Debugger, data acquisition system, FPGA, system signals, Qt framework

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Authors: Gizem İntepe, Eti Mizrahi

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Investment and financing decisions are influenced by various economic features. Detailed analysis should be conducted in order to make decisions not only by companies but also by governments. Such analysis can be conducted either at the company level or on a sectoral basis to reduce risks and to maximize profits. Sectoral disaggregation caused by seasonality effects, subventions, data advantages or disadvantages may appear in sectors behaving parallel to BIST (Borsa Istanbul stock exchange) Index. Proposed logistic indices could serve market needs as a decision parameter in sectoral basis and also helps forecasting activities in import export volume changes. Also it is an indicator of logistic activity, which is also a sign of economic mobility at the national level. Publicly available data from “Ministry of Transport, Maritime Affairs and Communications” and “Turkish Statistical Institute” is utilized to obtain five logistics indices namely as; exLogistic, imLogistic, fLogistic, dLogistic and cLogistic index. Then, efficiency and reliability of these indices are tested.

Keywords: economic activity, export trade data, import trade data, logistics indices

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Authors: Benyelles Zakaria, Yousfi Djaafar, Karoui Moussa Sofiane

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Agriculture is fundamental and remains an important objective in the Algerian economy, based on traditional techniques and structures, it generally has a purpose of consumption. Collection of agricultural statistics in Algeria is done using traditional methods, which consists of investigating the use of land through survey and field survey. These statistics suffer from problems such as poor data quality, the long delay between collection of their last final availability and high cost compared to their limited use. The objective of this work is to develop a processing chain for a reliable inventory of agricultural land by trying to develop and implement a new method of extracting information. Indeed, this methodology allowed us to combine data from remote sensing and field data to collect statistics on areas of different land. The contribution of remote sensing in the improvement of agricultural statistics, in terms of area, has been studied in the wilaya of Sidi Bel Abbes. It is in this context that we applied a method for extracting information from satellite images. This method is called the non-negative matrix factorization, which does not consider the pixel as a single entity, but will look for components the pixel itself. The results obtained by the application of the MNF were compared with field data and the results obtained by the method of maximum likelihood. We have seen a rapprochement between the most important results of the FMN and those of field data. We believe that this method of extracting information from satellite data leads to interesting results of different types of land uses.

Keywords: blind source separation, hyper-spectral image, non-negative matrix factorization, remote sensing

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Authors: M. A. Ansari, A. Hussain, A. Uddin

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A side weir is a flow diversion structure provided in the side wall of a channel to divert water from the main channel to a branch channel. The trapezoidal labyrinth weir is a special type of weir in which crest length of the weir is increased to pass higher discharge. Experimental and numerical studies related to the coefficient of discharge of trapezoidal labyrinth weir in an open channel have been presented in the present study. Group Method of Data Handling (GMDH) with the transfer function of quadratic polynomial has been used to predict the coefficient of discharge for the side trapezoidal labyrinth weir. A new model is developed for coefficient of discharge of labyrinth weir by regression method. Generalized models for predicting the coefficient of discharge for labyrinth weir using Group Method of Data Handling (GMDH) network have also been developed. The prediction based on GMDH model is more satisfactory than those given by traditional regression equations.

Keywords: discharge coefficient, group method of data handling, open channel, side labyrinth weir

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Authors: Rais Yusoh, Rosli Saad, Mokhtar Saidin, Fauzi Andika, Sabiu Bala Muhammad

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Resistivity and seismic refraction profiling have become a common method in pre-investigations for visualizing subsurface structure. The integration of the methods could reduce an interpretation ambiguity. Both methods have their individual software packages for data inversion, but potential to combine certain geophysical methods are restricted; however, the research algorithms that have this functionality was existed and are evaluated personally. The interpretation of subsurface were improve by combining inversion data from both methods by influence each other models using closure coupling; thus, by implementing both methods to support each other which could improve the subsurface interpretation. These methods were applied on a field dataset from a pre-investigation for archeology in finding the ancient river. There were no major changes in the inverted model by combining data inversion for this archetype which probably due to complex geology. The combine data analysis provides an additional technique for interpretation such as an alluvium, which can have strong influence on the ancient river findings.

Keywords: ancient river, combine inversion, resistivity, seismic refraction

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Authors: Mirain Rhys, Kevin Smith

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In 2017, the Welsh Government introduced an ambitious, new strategy to increase the number of Welsh speakers in Wales to 1 million by 2050. The Welsh education system is a vitally important feature of this strategy. All children attending state schools in Wales learn Welsh as a second language until the age of 16 and are assessed at General Certificate of Secondary Education (GCSE) level. In 2013, a review of Welsh second language instruction in Key Stages 3 and 4 was completed. The report identified considerable gaps in teachers’ preparation and training for teaching Welsh; poor Welsh language ethos at many schools; and a general lack of resources to support the instruction of Welsh. Recommendations were made across a number of dimensions including curriculum content, pedagogical practice, and teacher assessment, training, and resources. With a new national curriculum currently in development, this study builds on this review and provides unprecedented detail into pupils’ and teachers’ perceptions of Welsh language instruction. The current research built on data taken from an existing capacity building research project on Welsh education, the Wales multi-cohort study (WMS). Quantitative data taken from WMS surveys with over 1200 pupils in schools in Wales indicated that Welsh language lessons were the least enjoyable subject among pupils. The current research aimed to unpick pupil experiences in order to add to the policy development context. To achieve this, forty-four pupils and four teachers in three schools from the larger WMS sample participated in focus groups. Participants from years 9, 11 and 13 who had indicated positive, negative and neutral attitudes towards the Welsh language in a previous WMS survey were selected. Questions were based on previous research exploring issues including, but not limited to pedagogy, policy, assessment, engagement and (teacher) training. A thematic analysis of the focus group recordings revealed that the majority of participants held positive views around keeping the language alive but did not want to take on responsibility for its maintenance. These views were almost entirely based on their experiences of learning Welsh at school, especially in relation to their perceived lack of choice and opinions around particular lesson strategies and assessment. Analysis of teacher interviews highlighted a distinct lack of resources (materials and staff alike) compared to modern foreign languages, which had a negative impact on student motivation and attitudes. Both staff and students indicated a need for more practical, oral language instruction which could lead to Welsh being used outside the classroom. The data corroborate many of the review’s previous findings, but what makes this research distinctive is the way in which pupils poignantly address generally misguided aims for Welsh language instruction, poor pedagogical practice and a general disconnect between Welsh instruction and its daily use in their lives. These findings emphasize the complexity of incorporating the educational sector in strategies for Welsh language maintenance and the complications arising from pedagogical training, support, and resources, as well as teacher and pupil perceptions of, and attitudes towards, teaching and learning Welsh.

Keywords: bilingual education, language maintenance, language revitalisation, minority languages, Wales

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Authors: Arun Sanjel, Greg Speegle

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Every second, massive amounts of data are generated, and Data Intensive Scalable Computing (DISC) frameworks have evolved into effective tools for analyzing such massive amounts of data. Since the underlying architecture of these distributed computing platforms is often new to users, building a DISC application can often be time-consuming and prone to errors. The automated conversion of a sequential program to a DISC program will consequently significantly improve productivity. However, synthesizing a user’s intended program from an input specification is complex, with several important applications, such as distributed program synthesizing and code refactoring. Existing works such as Tyro and Casper rely entirely on deductive synthesis techniques or similar program synthesis approaches. Our approach is to develop a data-driven synthesis technique to identify sequential components and translate them to equivalent distributed operations. We emphasize using reinforcement learning and unit testing as feedback mechanisms to achieve our objectives.

Keywords: program synthesis, distributed computing, reinforcement learning, unit testing, DISC

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Authors: Emily Cherono Sawe, Elisha Ondieki Makori

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Knowledge and digital economies have brought challenges and potential opportunities for universities to innovate and improve the quality of learning. Disruption technologies and information dynamics continue to transform and change the landscape in teaching, scholarship, and research activities across universities. Digital literacy is a fundamental and imperative element in higher education and training, as witnessed during the new norm. COVID-19 caused unprecedented disruption in universities, where teaching and learning depended on digital innovations and applications. Academic services and activities were provided online, including library information services. Information professionals were forced to adopt various digital platforms in order to provide information services to patrons. University libraries’ roles in fulfilling educational responsibilities continue to evolve in response to changes in pedagogy, technology, economy, society, policies, and strategies of parent institutions. Libraries are currently undergoing considerable transformational change as a result of the inclusion of a digital environment. Academic libraries have been at the forefront of providing online learning resources and online information services, as well as supporting students and staff to develop digital literacy skills via online courses, tutorials, and workshops. Digital literacy transformation and information staff are crucial elements reminiscent of the prioritization of skills and knowledge for lifelong learning. The purpose of this baseline research is to assess the implications of digital literacy transformation in institutions of higher learning in Kenya and share appropriate strategies to leverage and sustain teaching and research. Objectives include examining the leverage and preparedness of the digital literacy environment in streamlining learning in the universities, exploring and benchmarking imperative digital competence for information professionals, establishing the perception of information professionals towards digital literacy skills, and determining lessons, best practices, and strategies to accelerate digital literacy transformation for effective research and learning in the universities. The study will adopt a descriptive research design using questionnaires and document analysis as the instruments for data collection. The targeted population is librarians and information professionals, as well as academics in public and private universities teaching information literacy programmes. Data and information are to be collected through an online structured questionnaire and digital face-to-face interviews. Findings and results will provide promising lessons together with best practices and strategies to transform and change digital literacies in university libraries in Kenya.

Keywords: digital literacy, digital innovations, information professionals, librarians, higher education, university libraries, digital information literacy

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Authors: Philip J. Purnell

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Innovators propose to use the Internet of Things to solve the problem of maintaining the cold chain during the transport of biopharmaceutical products. Sending a data logger with refrigerated goods is only useful to inform the recipient of the goods that they have either breached the cold chain and are therefore potentially spoiled or that they have not breached it and are therefore assumed to be in good condition. Connecting the data logger to the Internet of Things means that the supply chain manager will be informed in real-time of the exact location and the precise temperature of the material at any point on earth. Readable using a simple online interface, the supply chain manager will watch the progress of their material on a Google map together with accurate and crucially real-time temperature readings. The data logger will also send alarms to the supply chain manager if a cold chain breach becomes imminent allowing them time to contact the transporter and restore the cold chain before the material is affected. This development is expected to save billions of dollars in wasted biologics that currently arrive either spoiled or in an unreliable condition.

Keywords: internet of things, cold chain, data logger, transportation

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Authors: Lidon Lashley

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This paper presents how the social model of disability can be used to reshape inclusive education practices in Guyana. Inclusive education in Guyana is metamorphosizing but still firmly held in the tenets of the Medical Model of Disability which influences the experiences of children with Special Education Needs and/or Disabilities (SEN/D). An ethnographic approach to data gathering was employed in this study. Qualitative data was gathered from the voices of children with and without SEN/D as well as their mainstream teachers to present the interplay of discourses and subjectivities in the situation. The data was analyzed using Adele Clarke's postmodern approach to grounded theory analysis called situational analysis. The data suggest that it is possible but will be challenging to fully contextualize and adopt Loreman's synthesis and Booths and Ainscow's Index in the two mainstream schools studied. In addition, the data paved the way for the presentation of the social model framework specific to Guyana called 'Southern Inclusive Education Framework for Guyana' and its support tool called 'The Inclusive Checker created for Southern mainstream primary classrooms.

Keywords: social model of disability, medical model of disability, subjectivities, metamorphosis, special education needs, postcolonial Guyana, inclusion, culture, mainstream primary schools, Loreman's synthesis, Booths and Ainscow's index

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Authors: Md Rabiul Islam, Ben Wadham

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This paper describes how indigenous students face challenges with various school activities due to inadequate equity and diversity principles in mainstream primary schools in Bangladesh. This study focuses on indigenous students’ interactions with mainstream class teachers and students through teaching-learning activities at public primary schools. Ethnographic research methods guided data collection under a case study methodology in Chittagong Hill Tracts (CHTs) region where maximum indigenous peoples’ inhabitants. The participants (class teachers) shared information through in-depth interviews about their experiences in the four selecting schools. The authors also observed the effects of school activities by use of equity and diversity lens for indigenous students’ situations in those schools. The authors argue that the socio-economic situations of indigenous families are not supportive of the educational development of their children. Similarly, the Bangladesh government does not have enough initiative programs based on equity and diversity principles for fundamental education of indigenous children at rural schools level. Besides this, the conventional teaching system cannot improve the diversification among the students in classrooms. The principles of equity and diversity are not well embedded in professional development of teachers, and using teaching materials in classrooms. The findings suggest that implementing equitable education; there are needed to arrange teachers’ education with equitable knowledge and introducing diversified teaching materials, and implementing teaching through students centered activities that promote the diversification among the multicultural students.

Keywords: case study research, chittagong hill tracts, equity and diversity, Indigenous children

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Authors: Ritwik Dutta, Marylin Wolf

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This paper describes the trade-offs and the design from scratch of a self-contained, easy-to-use health dashboard software system that provides customizable data tracking for patients in smart homes. The system is made up of different software modules and comprises a front-end and a back-end component. Built with HTML, CSS, and JavaScript, the front-end allows adding users, logging into the system, selecting metrics, and specifying health goals. The back-end consists of a NoSQL Mongo database, a Python script, and a SimpleHTTPServer written in Python. The database stores user profiles and health data in JSON format. The Python script makes use of the PyMongo driver library to query the database and displays formatted data as a daily snapshot of user health metrics against target goals. Any number of standard and custom metrics can be added to the system, and corresponding health data can be fed automatically, via sensor APIs or manually, as text or picture data files. A real-time METAR request API permits correlating weather data with patient health, and an advanced query system is implemented to allow trend analysis of selected health metrics over custom time intervals. Available on the GitHub repository system, the project is free to use for academic purposes of learning and experimenting, or practical purposes by building on it.

Keywords: flask, Java, JavaScript, health monitoring, long-term care, Mongo, Python, smart home, software engineering, webserver

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Authors: Nathakhun Wiroonsri

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There are various cluster validity measures used for evaluating clustering results. One of the main objectives of using these measures is to seek the optimal unknown number of clusters. Some measures work well for clusters with different densities, sizes and shapes. Yet, one of the weaknesses that those validity measures share is that they sometimes provide only one clear optimal number of clusters. That number is actually unknown and there might be more than one potential sub-optimal option that a user may wish to choose based on different applications. We develop two new cluster validity indices based on a correlation between an actual distance between a pair of data points and a centroid distance of clusters that the two points are located in. Our proposed indices constantly yield several peaks at different numbers of clusters which overcome the weakness previously stated. Furthermore, the introduced correlation can also be used for evaluating the quality of a selected clustering result. Several experiments in different scenarios, including the well-known iris data set and a real-world marketing application, have been conducted to compare the proposed validity indices with several well-known ones.

Keywords: clustering algorithm, cluster validity measure, correlation, data partitions, iris data set, marketing, pattern recognition

Procedia PDF Downloads 102

Authors: Petra Hofmann, Dana Koniel, Jussi Luukkanen, Walter Nieminen, Lea Hannola, Ilkka Donoghue

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The Covid-19 pandemic forced people to isolate and become physically less connected. The pandemic hasnot only reshaped people’s behaviours and needs but also accelerated digital transformation (DT). DT of cities has become an imperative with the outlook of converting them into smart cities in the future. Embedding digital infrastructure and smart city initiatives as part of the normal design, construction, and operation of cities provides a unique opportunity to improve connection between people. Internet of Things (IoT) is an emerging technology and one of the drivers in DT. It has disrupted many industries by introducing different services and business models, and IoT solutions are being applied in multiple fields, including smart cities. As IoT and data are fundamentally linked together, IoT solutions can only create value if the data generated by the IoT devices is analysed properly. Extracting relevant conclusions and actionable insights by using established techniques, data analytics contributes significantly to the growth and success of IoT applications and investments. Companies must grasp DT and be prepared to redesign their offerings and business models to remain competitive in today’s marketplace. As there are many IoT solutions available today, the amount of data is tremendous. The challenge for companies is to understand what solutions to focus on and how to prioritise and which data to differentiate from the competition. This paper explains how IoT and data analytics can impact competitive advantage and how companies should approach IoT and data analytics to translate them into concrete offerings and solutions in the smart city context. The study was carried out as a qualitative, literature-based research. A case study is provided to validate the preservation of company’s competitive advantage through smart city solutions. The results of the researchcontribution provide insights into the different factors and considerations related to creating competitive advantage through IoT and data analytics deployment in the smart city context. Furthermore, this paper proposes a framework that merges the factors and considerations with examples of offerings and solutions in smart cities. The data collected through IoT devices, and the intelligent use of it, can create a competitive advantage to companies operating in smart city business. Companies should take into consideration the five forces of competition that shape industries and pay attention to the technological, organisational, and external contexts which define factors for consideration of competitive advantages in the field of IoT and data analytics. Companies that can utilise these key assets in their businesses will most likely conquer the markets and have a strong foothold in the smart city business.

Keywords: internet of things, data analytics, smart cities, competitive advantage

Procedia PDF Downloads 90

Authors: Amel Hannech, Mehdi Adda, Hamid Mcheick

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In this paper, we propose a generic model of user profile integrating several elements that may positively impact the research process. We exploit the classical behavior of users and integrate a delimitation process of their research activities into several research sessions enriched with contextual and temporal information, which allows reflecting the current interests of these users in every period of time and infer data freshness. We argue that the annotation of resources gives more transparency on users' needs. It also strengthens social links among resources and users, and can so increase the scope of the user profile. Based on this idea, we integrate the social tagging practice in order to exploit the social users' behavior to enrich their profiles. These profiles are then integrated into a recommendation system in order to predict the interesting personalized items of users allowing to assist them in their researches and further enrich their profiles. In this recommendation, we provide users new research experiences.

Keywords: user profiles, topical ontology, contextual information, folksonomies, tags' clusters, data freshness, association rules, data recommendation

Procedia PDF Downloads 256

Authors: John Narh

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There is high rate of deforestation in Ghana due to agricultural expansion, illegal mining and illegal logging. While it is attempting to address the illegalities, Ghana has also initiated a reforestation program known as the Modified Taungya System (MTS). Within the MTS framework, farmers are allocated degraded forestland and provided with tree seedlings to practice agroforestry until the trees form canopy. Yet, the political, ecological and economic models that inform the selection of tree species, the motivations of participating farmers as well as the factors that accounts for differential access to the land and performance of farmers engaged in the program lie underexplored. Using a sequential explanatory mixed methods approach in five forest-fringe communities in the Eastern Region of Ghana, the study reveals that economic factors and Ghana’s commitment to international conventions on the environment underpin the selection of tree species for the MTS program. Social network and access to remittances play critical roles in having access to, and enhances poor farmers’ chances in the program respectively. Farmers are more motivated by the access to degraded forestland to cultivate food crops than having a share in the trees that they plant. As such, in communities where participating farmers are not informed about their benefit in the tree that they plant, the program is largely unsuccessful.

Keywords: translocality, deforestation, forest management, social network

Procedia PDF Downloads 92

Authors: Frantisek Odvarka

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Based on the data from the Moravian Karst, the influence of the calcite speleothem growth by selected meteorological factors was evaluated. External temperature was determined as one of the main factors influencing speleothem growth in Moravian Karst. This factor significantly influences the CO₂ concentration in soil/epikarst, and cave atmosphere in the Moravian Karst and significantly contributes to the changes in the CO₂ partial pressure differences between soil/epikarst and cave atmosphere in Moravian Karst, which determines the drip water supersaturation with respect to the calcite and quantity of precipitated calcite in the Moravian Karst cave environment. External air temperatures and cave air temperatures were measured using a COMET S3120 data logger, which can measure temperatures in the range from -30 to +80 °C with an accuracy of ± 0.4 °C. CO₂ concentrations in the cave and soils were measured with a FT A600 CO₂H Ahlborn probe (value range 0 ppmv to 10,000 ppmv, accuracy 1 ppmv), which was connected to the data logger ALMEMO 2290-4, V5 Ahlborn. The soil temperature was measured with a FHA646E1 Ahlborn probe (temperature range -20 to 70 °C, accuracy ± 0.4 °C) connected to an ALMEMO 2290-4 V5 Ahlborn data logger. The airflow velocities into and out of the cave were monitored by a FVA395 TH4 Thermo anemometer (speed range from 0.05 to 2 m s⁻¹, accuracy ± 0.04 m s⁻¹), which was connected to the ALMEMO 2590-4 V5 Ahlborn data logger for recording. The flow was measured in the lower and upper entrance of the Imperial Cave. The data were analyzed in MS Office Excel 2019 and PHREEQC.

Keywords: speleothem growth, carbon dioxide partial pressure, Moravian Karst, external temperature

Procedia PDF Downloads 141

Authors: Brian Fleischli, Shani Robins

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In recent years, the implementation of wisdom skills, including emotional intelligence, mindfulness, empathy, compassion, gratitude, realism (Cognitive-Behavioral Therapy), and humility, within K-12 educational settings has demonstrated significant benefits in reducing stress, anxiety, anger, and conflict among students. This study summarizes the findings of research conducted over several years, showcasing the positive outcomes associated with teaching these skills to elementary and high school students. Additionally, this overview includes an updated synthesis of current literature concerning the application and effectiveness of training these skill sets in K-12 schools. The research outcomes highlight substantial improvements in student well-being and behavior. Demonstrated with treatment group students exhibiting notable reductions in anger, anxiety, depression, and disruptive behaviors compared to control groups. For instance, fourth-grade students showed enhanced empathy, responsibility, and attention, particularly benefiting those with lower initial scores on these measures. Specific interaction effects suggest that older students and males particularly benefit from these interventions, showcasing the nuanced impact of wisdom skill training across different demographics. Furthermore, this presentation emphasizes the critical role of Social and Emotional Learning (SEL) programs in addressing the multifaceted challenges faced by children and adolescents, including mental health issues, academic performance, and social behaviors. The integration of wisdom skills into school curricula not only fosters individual growth and emotional regulation but also enhances overall school climate and academic achievement. In conclusion, the findings contribute to the growing body of empirical evidence supporting the efficacy of teaching wisdom skills in educational settings. The success of these interventions underscores the potential for widespread implementation of evidence-based programs to promote emotional well-being and academic success among students nationwide.

Keywords: wisdom skills, CBT, cognitive behavioral training, mindfulness, empathy, anxiety

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Authors: Ali Taher Othman Ali

Abstract:

The aim of this research is to provide a draft proposal for the professional development of mathematics teachers in accordance with the orientation of science, technology, engineering and mathematics which is known by the abbreviation STEM, as a modern and contemporary orientation in the teaching and learning of mathematics and in order to achieve the objective of the research, the researcher used the theoretical descriptive method through the induction of the literature of education and the previous studies and experiments related to the topic. The researcher concluded by providing the proposal according to five basic axes, the first axe: professional development as a system, and its requirements include: development of educational systems, and allocate sufficient budgets to support the requirements of teaching STEM, identifying mechanisms for incentives and rewards for teachers attending professional development programs based on STEM; the second: development of in-depth knowledge content and its requirements include: basic sciences content development for STEM, linking the scientific understanding of teachers with real-world issues and problems, to provide the necessary resources to expand teachers' knowledge in this area; the third: the necessary pedagogical skills of teachers in the field of STEM, and its requirements include: identification of the required training and development needs and the mechanism of determining these needs, the types of professional development programs and the mechanism of designing it, the mechanisms and places of execution, evaluation and follow-up; the fourth: professional development strategies and mechanisms in the field of STEM, and its requirements include: using a variety of strategies to enable teachers to design and transfer effective educational experiences which reflect their scientific mastery in the fields of STEM, provide learning opportunities, and developing the skills of procedural research to generate new knowledge about the STEM; the fifth: to support professional development in the area of STEM, and its requirements include: support leadership within the school, provide a clear and appropriate opportunities for professional development for teachers within the school through professional learning communities, building partnerships between the Ministry of education and the local and international community institutions. The proposal includes other factors that should be considered when implementing professional development programs for mathematics teachers in the field of STEM.

Keywords: professional development, mathematics teachers, the orientation of science, technology, engineering and mathematics (STEM)

Procedia PDF Downloads 395