Search results for: educational data mining

Authors: Mahnaz Jafari, Parisa Izadpanahi, Francesco Mancini, Muhammad Qureshi

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The advancement in Information Technology (IT) has been an intrinsic element in the developments of the 21st century bringing benefits such as increased economic productivity. However, its widespread application has also been associated with inadvertent negative impacts on society and the environment necessitating selective interventions to mitigate these impacts. This study responded to this need by developing a Green IT Rating Tool (GIRT) for higher education institutions (HEI) in Australia to evaluate the sustainability of IT-related practices from an environmental, social, and economic perspective. Each dimension must be considered equally to achieve sustainability. The development of the GIRT was informed by the views of interviewed IT professionals whose opinions formed the basis of a framework listing Green IT initiatives in order of their importance as perceived by the interviewed professionals. This framework formed the base of the GIRT, which identified Green IT initiatives (such as videoconferencing as a substitute for long-distance travel) and the associated weighting of each practice. The proposed sustainable Green IT model could be integrated into existing IT systems, leading to significant reductions in carbon emissions and e-waste and improvements in energy efficiency. The development of the GIRT and the findings of this study have the potential to inspire other organizations to adopt sustainable IT practices, positively impact the environment, and be used as a reference by IT professionals and decision-makers to evaluate IT-related sustainability practices. The GIRT could also serve as a benchmark for HEIs to compare their performance with other institutions and to track their progress over time. Additionally, the study's results suggest that virtual and cloud-based technologies could reduce e-waste and energy consumption in the higher education sector. Overall, this study highlights the importance of incorporating Green IT practices into the IT systems of HEI to contribute to a more sustainable future.

Keywords: green information technology, international higher-educational institution, sustainable solutions, environmentally friendly IT systems

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Authors: Xudong He, Jian Wang, Jiqiang Liu, Lei Han, Yang Yu, Shaohua Lv

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Nowadays, the threats of the internet are enormous and increasing; however, the classification of huge alert messages generated in this environment is relatively monotonous. It affects the accuracy of the network situation assessment, and also brings inconvenience to the security managers to deal with the emergency. In order to deal with potential network threats effectively and provide more effective data to improve the network situation awareness. It is essential to build a hierarchical filtering method to prevent the threats. In this paper, it establishes a model for data monitoring, which can filter systematically from the original data to get the grade of threats and be stored for using again. Firstly, it filters the vulnerable resources, open ports of host devices and services. Then use the entropy theory to calculate the performance changes of the host devices at the time of the threat occurring and filter again. At last, sort the changes of the performance value at the time of threat occurring. Use the alerts and performance data collected in the real network environment to evaluate and analyze. The comparative experimental analysis shows that the threat filtering method can effectively filter the threat alerts effectively.

Keywords: correlation analysis, hierarchical filtering, multisource data, network security

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Authors: Lefteris Tsipis, Demosthenes Vouyioukas, George Loumos, Antonis Kargas, Dimitris Varoutas

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The employment of technology and digitization is crucial for cultural organizations to establish and sustain digital repositories for their cultural heritage artefacts. This utilization is also essential in facilitating the presentation of cultural works and exhibits to a broader audience. Consequently, in this work, we propose a digital repository that functions as Software as a Service (SaaS), primarily promoting the safe storage, display, and sharing of cultural materials, enhancing accessibility, and fostering a deeper understanding and appreciation of cultural heritage. Moreover, the proposed digital repository service is designed as a multitenant architecture, which enables organizations to expand their reach, enhance accessibility, foster collaboration, and ensure the preservation of their content. Specifically, this project aims to assist each cultural institution in organizing its digital cultural assets into collections and feeding other digital platforms, including educational, museum, pedagogical, and games, through appropriate interfaces. Moreover, the creation of this digital repository offers a cutting-edge and effective open-access laboratory solution. It allows organizations to have a significant influence on their audiences by fostering cultural understanding and appreciation. Additionally, it facilitates the connection between different digital repositories and national/European aggregators, promoting collaboration and information sharing. By embracing this solution, cultural institutions can benefit from shared resources and features, such as system updates, backup and recovery services, and data analytics tools, that are provided by the platform.

Keywords: cultural technologies, gaming technologies, web sharing, digital repository

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Authors: A. Satty, H. Mwambi

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Much clinical trials data-based research are characterized by the unavoidable problem of dropout as a result of missing or erroneous values. This paper aims to review some of the various techniques to address the dropout problems in longitudinal clinical trials. The fundamental concepts of the patterns and mechanisms of dropout are discussed. This study presents five general techniques for handling dropout: (1) Deletion methods; (2) Imputation-based methods; (3) Data augmentation methods; (4) Likelihood-based methods; and (5) MNAR-based methods. Under each technique, several methods that are commonly used to deal with dropout are presented, including a review of the existing literature in which we examine the effectiveness of these methods in the analysis of incomplete data. Two application examples are presented to study the potential strengths or weaknesses of some of the methods under certain dropout mechanisms as well as to assess the sensitivity of the modelling assumptions.

Keywords: incomplete longitudinal clinical trials, missing at random (MAR), imputation, weighting methods, sensitivity analysis

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Authors: Claerchille Jhulia Robin

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This paper discusses the perspective of ESL learners towards pronunciation instruction. It sought to determine how these learners view the type of feedback their speech teacher gives and its impact on their own classroom practice of providing feedback. This study utilized a quantitative-qualitative approach to the problem. The respondents were Education students majoring in English. A survey questionnaire and interview guide were used for data gathering. The data from the survey was tabulated using frequency count and the data from the interview were then transcribed and analyzed. Results showed that ESL learners favor immediate corrective feedback and they do not find any issue in being corrected in front of their peers. They also practice the same corrective technique in their own classroom.

Keywords: ESL, feedback, learner perspective, pronunciation instruction

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Authors: Chorom Baek, Sungwon Choi

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The purpose of this study is to analyze the supervision system, and the training and continuing education of mental health professionals in USA, UK, Australia (New Zealand), Japan, and so on, and to deduce the implications of Korean mental health service system. In order to accomplish the purpose of this study, following methodologies were adopted: review on the related literatures, statistical data, the related manuals, online materials, and previous studies concerning issues in those countries for the past five years. The training program in Korea was compared with the others’ through this literature analysis. The induced matters were divided with some parts such as training program, continuing education, educational procedure, and curriculum. Based on the analysis, discussion and implications, the conclusion and further suggestion of this study are as follows: First, Korean Clinical Psychology of Association (KCPA) should become more powerful health main training agency for quality control. Second, actual authority of health main training agency should be a grant to training centers. Third, quality control of mental health professionals should be through standardization and systemization of promotion and qualification management. Fourth, education and training about work of supervisors and unification of criteria for supervision should be held. Fifth, the training program for mental health license should be offered by graduate schools. Sixth, legitimated system to protect the right of mental health trainees is needed. Seventh, regularly continuing education after licensed should be compulsory to keep the certification. Eighth, the training program in training centers should meet KCPA requirement. If not, KCPA can cancel the certification of the centers.

Keywords: clinical psychology, Korea, mental health system, training program

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Authors: Chayanika Hazarika Bordoloi

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This paper is an attempt to work on a highly inflectional language called Assamese. This is also one of the national languages of India and very little has been achieved in terms of computational research. Building a language processing tool for a natural language is not very smooth as the standard and language representation change at various levels. This paper presents inflectional suffixes of Assamese verbs and how the statistical tools, along with linguistic features, can improve the tagging accuracy. Conditional random fields (CRF tool) was used to automatically tag and train the text data; however, accuracy was improved after linguistic featured were fed into the training data. Assamese is a highly inflectional language; hence, it is challenging to standardizing its morphology. Inflectional suffixes are used as a feature of the text data. In order to analyze the inflections of Assamese word forms, a list of suffixes is prepared. This list comprises suffixes, comprising of all possible suffixes that various categories can take is prepared. Assamese words can be classified into inflected classes (noun, pronoun, adjective and verb) and un-inflected classes (adverb and particle). The corpus used for this morphological analysis has huge tokens. The corpus is a mixed corpus and it has given satisfactory accuracy. The accuracy rate of the tagger has gradually improved with the modified training data.

Keywords: CRF, morphology, tagging, tagset

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Authors: Yogesh Kumar Tiwari

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Chhattisgarh has realized the fundamental role of information and communication technology in the globalized world where knowledge is at the top for the growth and intellectual development. They are spreading so widely that one feels lagging behind if not using them. The influence of these radiating and technological tools has encompassed all aspects of the educational, business, and economic sectors of our world. Undeniably the computer has not only established itself globally in all walks of life but has acquired a fundamental role of paramount importance in the educational process also. This role is getting all pervading and more powerful as computers are being manufactured to be cheaper, smaller in size, adaptable and easy to handle. Computers are becoming indispensable to teachers because of their enormous capabilities and extensive competence. This study aims at observing the effect of using computer based software program of English language on the achievement of undergraduate level students studying in tribal area like Sarguja Division, Chhattisgarh, India. To testify the effect of an innovative teaching in the graduate classroom in tribal area 50 students were randomly selected and separated into two groups. The first group of 25 students were taught English grammar i.e., passive voice/narration, through traditional method using chalk and blackboard asking some formal questions. The second group, the experimental one, was taught English grammar i.e., passive voice/narration, using computer, projector with power point presentation of grammatical items. The statistical analysis was done on the students’ learning capacities and achievement. The result was extremely mesmerizing not only for the teacher but for taught also. The process of the recapitulation demonstrated that the students of experimental group responded the answers of the questions enthusiastically with innovative sense of learning. In light of the findings of the study, it was recommended that teachers and professors of English ought to use self-made instructional program in their teaching process particularly in tribal areas.

Keywords: achievement computer assisted language learning, use of instructional program

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Authors: Rodrigo T. Lourenço, Margarida Mano

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Higher Education Institutions (HEI), and other levels of Education, face important challenges. One of the most relevant one is the ability to adapt to a society that is changing over time, whilst guarantying levels of training that do not merely react to such changes. Thus, interacting with society, particularly with surrounding communities and key stakeholders, has become an essential requirement for the sustainability of these institutions. One of the formal mechanisms implemented in European educational institutions has been the design of organizational structures that include a top governance body sharing its constitution with both internal members, students and external members. Such frame holds the core mission of involving communities in the governance of educational institutions, assuming, both strategic decision-making functions, with the approval of the institutions’ strategic plans, and a supervision function, approved by activity reports. It also plays an essential role in the life of institutions by holding the responsibility of electing its top executives. In Portugal, it has been almost a decade since the publication of RJIES, the legal framework of Higher Education, such bodies being designated by General Councils. Thus, one may highlight that there has been a better understanding of the operative process of these bodies, as well as their added value to the education system. It has also been possible to analyse the extent to which their core mission has been fulfilled and to understand its growing relevance, particularly regarding the autonomy of institutions. This article aims to contribute to this theme by presenting the results of a study on the role of these bodies in the governance of Public Portuguese HEI, with a special focus on the supervisory competence of organizational performance. Through questionnaires made to board members and interviews with chairpersons of the bodies and top managers of the institutions, it was possible to conclude that there is a high concern with the connections to the external environment. However, regarding organizational performance and the role of the Council as a supervisor of that performance, the activity of the bodies has fallen short of what would be expected. Several reasons may be identified. It is important to emphasize the importance of the profile of the external members and the relationship between the organ’s standard functioning and the election of the head of the institution.

Keywords: governance, stakeholders, supervision, performance

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Authors: M. Abdullah, Al-Wadud

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Sensor-based activity recognition systems usually accounts which sensors have been activated to perform an activity. The system then combines the conditional probabilities of those sensors to represent different activities and takes the decision based on that. However, the information about the sensors which are not activated may also be of great help in deciding which activity has been performed. This paper proposes an approach where the sensory data related to both usage and non-usage of objects are utilized to make the classification of activities. Experimental results also show the promising performance of the proposed method.

Keywords: Naïve Bayesian, based classification, activity recognition, sensor data, object-usage model

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Authors: Nastaran Moosavi, Mohammad Mokhtari

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Seismic inversion is a technique which has been in use for years and its main goal is to estimate and to model physical characteristics of rocks and fluids. Generally, it is a combination of seismic and well-log data. Seismic inversion can be carried out through different methods; we have conducted and compared post-stack and pre- stack seismic inversion methods on real data in one of the fields in the Persian Gulf. Pre-stack seismic inversion can transform seismic data to rock physics such as P-impedance, S-impedance and density. While post- stack seismic inversion can just estimate P-impedance. Then these parameters can be used in reservoir identification. Based on the results of inverting seismic data, a gas reservoir was detected in one of Hydrocarbon oil fields in south of Iran (Persian Gulf). By comparing post stack and pre-stack seismic inversion it can be concluded that the pre-stack seismic inversion provides a more reliable and detailed information for identification and prediction of hydrocarbon reservoirs.

Keywords: density, p-impedance, s-impedance, post-stack seismic inversion, pre-stack seismic inversion

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Authors: Fouzi Harrou, Ying Sun, Sofiane Khadraoui

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Anomaly detection based on Principal Component Analysis (PCA) was studied intensively and largely applied to multivariate processes with highly cross-correlated process variables. Monitoring metrics such as the Hotelling's T2 and the Q statistics are usually used in PCA-based monitoring to elucidate the pattern variations in the principal and residual subspaces, respectively. However, these metrics are ill suited to detect small faults. In this paper, the Exponentially Weighted Moving Average (EWMA) based on the Q and T statistics, T2-EWMA and Q-EWMA, were developed for detecting faults in the process mean. The performance of the proposed methods was compared with that of the conventional PCA-based fault detection method using synthetic data. The results clearly show the benefit and the effectiveness of the proposed methods over the conventional PCA method, especially for detecting small faults in highly correlated multivariate data.

Keywords: data-driven method, process control, anomaly detection, dimensionality reduction

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Authors: Ahmed M. Jamel

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Electronic government initiatives and public participation to them are among the indicators of today's development criteria of the countries. After consequent two wars, Iraq's current position in, for example, UN's e-government ranking is quite concerning and did not improve in recent years, either. In the preparation of this work, we are motivated with the fact that handling geographic data of the public facilities and resources are needed in most of the e-government projects. Geographical information systems (GIS) provide most common tools not only to manage spatial data but also to integrate such type of data with nonspatial attributes of the features. With this background, this paper proposes that establishing a working GIS in the health sector of Iraq would improve e-government applications. As the case study, investigating hospital locations in Erbil is chosen.

Keywords: e-government, GIS, Iraq, Erbil

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Authors: J. Burlakovs, Y. Jani, L. Grinberga, M. Kriipsalu, O. Anne, I. Grinfelde, W. Hogland

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The worldwide future sustainable economies are oriented towards the sea: the maritime economy is becoming one of the strongest driving forces in many regions as population growth is the highest in coastal areas. For hundreds of years sea resources were depleted unsustainably by fishing, mining, transportation, tourism, and waste. European Sustainable Development Strategy is identifying and developing actions to enable the EU to achieve a continuous, long-term improvement of the quality of life through the creation of sustainable communities. The aim of this paper is to provide insight in Baltic Sea Region case studies on implemented actions on tourism industry waste and beach wrack management in coastal areas, hazardous contaminants and plastic flow treatment from waste, wastewaters and stormwaters. These projects mentioned in study promote successful prevention of contaminant flows to the sea environments and provide perspectives for creation of valuable new products from residuals for future circular economy are the step forward to green innovation winning streak.

Keywords: resilience, hazardous waste, phytoremediation, water management, circular economy

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Authors: Mohosina Jabin Toma, Gerald Tembrevilla, Marina Milner-Bolotin

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Science education in Bangladesh is losing its appeal at an alarming rate due to the lack of science laboratory equipment, excessive teacher-student ratio, and outdated teaching strategies. Research-based educational technologies aim to address some of the problems faced by teachers who have limited access to laboratory resources, like many Bangladeshi teachers. Physics Education Technology (PhET) research team has been developing science and mathematics interactive simulations to help students develop deeper conceptual understanding. Still, PhET simulations are rarely used in Bangladesh. The purpose of this study is to explore Bangladeshi teachers’ challenges in learning to implement PhET-enhanced pedagogies and examine teachers’ views on PhET’s pedagogical opportunities in secondary science education. Since it is a new technology for Bangladesh, seven workshops on PhET were conducted in Dhaka city for 129 in-service and pre-service teachers in the winter of 2023 prior to data collection. This study followed an explanatory mixed method approach that included a pre-and post-workshop survey and five semi-structured interviews. Teachers participated in the workshops voluntarily and shared their experiences at the end. Teachers’ challenges were also identified from workshop discussions and observations. The interviews took place three to four weeks after the workshop and shed light on teachers’ experiences of using PhET in actual classroom settings. The results suggest that teachers had difficulty handling new technology; hence, they recommended preparing a booklet and Bengali YouTube videos on PhET to assist them in overcoming their struggles. Teachers also faced challenges in using any inquiry-based learning approach due to the content-loaded curriculum and exam-oriented education system, as well as limited experience with inquiry-based education. The short duration of classes makes it difficult for them to design PhET activities. Furthermore, considering limited access to computers and the internet in school, teachers think PhET simulations can bring positive changes if used in homework activities. Teachers also think they lack pedagogical skills and sound content knowledge to take full advantage of PhET. They highly appreciated the workshops and proposed that the government designs some teacher training modules on how to incorporate PhET simulations. Despite all the challenges, teachers believe PhET can enhance student learning, ensure student engagement and increase student interest in STEM Education. Considering the lack of science laboratory equipment, teachers recognized the potential of PhET as a supplement to hands-on activities for secondary science education in Bangladesh. They believed that if PhET develops more curriculum-relevant sims, it will bring revolutionary changes to how Bangladeshi students learn science. All the participating teachers in this study came from two organizations, and all the workshops took place in urban areas; therefore, the findings cannot be generalized to all secondary science teachers. A nationwide study is required to include teachers from diverse backgrounds. A further study can shed light on how building a professional learning community can lessen teachers’ challenges in incorporating PhET-enhanced pedagogy in their teaching.

Keywords: educational technology, inquiry-based learning, PhET interactive simulations, PhET-enhanced pedagogies, science education, science laboratory equipment, teacher professional development

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Authors: V. Ayishwarya Bharathi, S. M. Hasker, J. Indhu, M. Mohamed Azarudeen, G. Gowthami, R. Vinoth Rajan, N. Vijayarangan

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Identification of water quality conditions in a river system based on limited observations is an essential task for meeting the goals of environmental management. The traditional method of water quality testing is to collect samples manually and then send to laboratory for analysis. However, it has been unable to meet the demands of water quality monitoring today. So a set of automatic measurement and reporting system of water quality has been developed. In this project specifies Water quality parameters collected by multi-parameter water quality probe are transmitted to data processing and monitoring center through GPRS wireless communication network of mobile. The multi parameter sensor is directly placed above the water level. The monitoring center consists of GPRS and micro-controller which monitor the data. The collected data can be monitor at any instant of time. In the pollution control board they will monitor the water quality sensor data in computer using Visual Basic Software. The system collects, transmits and processes water quality parameters automatically, so production efficiency and economy benefit are improved greatly. GPRS technology can achieve well within the complex environment of poor water quality non-monitored, and more specifically applicable to the collection point, data transmission automatically generate the field of water analysis equipment data transmission and monitoring.

Keywords: multiparameter sensor, GPRS, visual basic software, RS232

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Authors: Anuradha Chug, Sunali Gandhi

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Regression Testing is a very expensive and time-consuming process carried out to ensure the validity of modified software. Due to the availability of insufficient resources to re-execute all the test cases in time constrained environment, efforts are going on to generate test data automatically without human efforts. Many search based techniques have been proposed to generate efficient, effective as well as optimized test data, so that the overall cost of the software testing can be minimized. The generated test data should be able to uncover all potential lapses that exist in the software or product. Inspired from the natural behavior of bat for searching her food sources, current study employed a meta-heuristic, search-based bat algorithm for optimizing the test data on the basis certain parameters without compromising their effectiveness. Mathematical functions are also applied that can effectively filter out the redundant test data. As many as 50 Java programs are used to check the effectiveness of proposed test data generation and it has been found that 86% saving in testing efforts can be achieved using bat algorithm while covering 100% of the software code for testing. Bat algorithm was found to be more efficient in terms of simplicity and flexibility when the results were compared with another nature inspired algorithms such as Firefly Algorithm (FA), Hill Climbing Algorithm (HC) and Ant Colony Optimization (ACO). The output of this study would be useful to testers as they can achieve 100% path coverage for testing with minimum number of test cases.

Keywords: regression testing, test case selection, test case prioritization, genetic algorithm, bat algorithm

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Authors: Agria Rhamdhan

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WhatsApp as the most popular mobile messaging app has been used as evidence in many criminal cases. As the use of mobile messages generates large amounts of data, forensic investigation faces the challenge of large data problems. The hardest part of finding this important evidence is because current practice utilizes tools and technique that require manual analysis to check all messages. That way, analyze large sets of mobile messaging data will take a lot of time and effort. Our work offers methodologies based on forensic triage to reduce large data to manageable sets resulting easier to do detailed reviews, then show the results through interactive visualization to show important term, entities and relationship through intelligent ranking using Term Frequency-Inverse Document Frequency (TF-IDF) and Latent Dirichlet Allocation (LDA) Model. By implementing this methodology, investigators can improve investigation processing time and result's accuracy.

Keywords: forensics, triage, visualization, WhatsApp

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Authors: Mohkammad Nur Cahyadi, Hepi Hapsari Handayani, Agus Budi Raharjo, Ronny Mardianto, Daud Wahyu Imani, Arizal Bawazir, Luki Adi Triawan

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PDAM (local water company) determines customer charges by considering the customer's building or house. Charges determination significantly affects PDAM income and customer costs because the PDAM applies a subsidy policy for customers classified as small households. Periodic updates are needed so that pricing is in line with the target. A thorough customer survey in Surabaya is needed to update customer building data. However, the survey that has been carried out so far has been by deploying officers to conduct one-by-one surveys for each PDAM customer. Surveys with this method require a lot of effort and cost. For this reason, this research offers a technology called moblie mapping, a mapping method that is more efficient in terms of time and cost. The use of this tool is also quite simple, where the device will be installed in the car so that it can record the surrounding buildings while the car is running. Mobile mapping technology generally uses lidar sensors equipped with GNSS, but this technology requires high costs. In overcoming this problem, this research develops low-cost mobile mapping technology using a webcam camera sensor added to the GNSS and IMU sensors. The camera used has specifications of 3MP with a resolution of 720 and a diagonal field of view of 78⁰. The principle of this invention is to integrate four camera sensors, a GNSS webcam, and GPS to acquire photo data, which is equipped with location data (latitude, longitude) and IMU (roll, pitch, yaw). This device is also equipped with a tripod and a vacuum cleaner to attach to the car's roof so it doesn't fall off while running. The output data from this technology will be analyzed with artificial intelligence to reduce similar data (Cosine Similarity) and then classify building types. Data reduction is used to eliminate similar data and maintain the image that displays the complete house so that it can be processed for later classification of buildings. The AI method used is transfer learning by utilizing a trained model named VGG-16. From the analysis of similarity data, it was found that the data reduction reached 50%. Then georeferencing is done using the Google Maps API to get address information according to the coordinates in the data. After that, geographic join is done to link survey data with customer data already owned by PDAM Surya Sembada Surabaya.

Keywords: mobile mapping, GNSS, IMU, similarity, classification

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Authors: Abraham Motlhabane

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This research analysed the written views of science education students regarding the teaching of laboratory work using the online mode. The research adopted the qualitative methodology. The qualitative research was aimed at investigating small and distinct groups normally regarded as a single-site study. Qualitative research was used to describe and analyze the phenomena from the student’s perspective. This means the research began with assumptions of the world view that use theoretical lenses of research problems inquiring into the meaning of individual students. The research was conducted with three groups of students studying for Postgraduate Certificate in Education, Bachelor of Education and honors Bachelor of Education respectively. In each of the study programmes, the science education module is compulsory. Five science education students from each study programme were purposively selected to participate in this research. Therefore, 15 students participated in the research. In order to analysis the data, the data were first printed and hard copies were used in the analysis. The data was read several times and key concepts and ideas were highlighted. Themes and patterns were identified to describe the data. Coding as a process of organising and sorting data was used. The findings of the study are very diverse; some students are in favour of online laboratory whereas other students argue that science can only be learnt through hands-on experimentation.

Keywords: online learning, laboratory work, views, perceptions

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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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Modern experiments in high energy physics impose great demands on the reliability, the efficiency, and the data rate of Data Acquisition Systems (DAQ). This contribution focuses on the development and deployment of the new communication library DIALOG for the intelligent, FPGA-based Data Acquisition System (iFDAQ) of the COMPASS experiment at CERN. The iFDAQ utilizing a hardware event builder is designed to be able to readout data at the maximum rate of the experiment. The DIALOG library is a communication system both for distributed and mixed environments, it provides a network transparent inter-process communication layer. Using the high-performance and modern C++ framework Qt and its Qt Network API, the DIALOG library presents an alternative to the previously used DIM library. The DIALOG library was fully incorporated to all processes in the iFDAQ during the run 2016. From the software point of view, it might be considered as a significant improvement of iFDAQ in comparison with the previous run. To extend the possibilities of debugging, the online monitoring of communication among processes via DIALOG GUI is a desirable feature. In the paper, we present the DIALOG library from several insights and discuss it in a detailed way. Moreover, the efficiency measurement and comparison with the DIM library with respect to the iFDAQ requirements is provided.

Keywords: data acquisition system, DIALOG library, DIM library, FPGA, Qt framework, TCP/IP

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Authors: Bharatendra Rai

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Predictive data analysis and modeling involving machine learning techniques become challenging in presence of too many explanatory variables or features. Presence of too many features in machine learning is known to not only cause algorithms to slow down, but they can also lead to decrease in model prediction accuracy. This study involves housing dataset with 79 quantitative and qualitative features that describe various aspects people consider while buying a new house. Boruta algorithm that supports feature selection using a wrapper approach build around random forest is used in this study. This feature selection process leads to 49 confirmed features which are then used for developing predictive random forest models. The study also explores five different data partitioning ratios and their impact on model accuracy are captured using coefficient of determination (r-square) and root mean square error (rsme).

Keywords: housing data, feature selection, random forest, Boruta algorithm, root mean square error

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Authors: L. D. Upegui, Isabel Alvarez-Solorza, Karina Garduno-Ulloa, Maren Boecker

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Introduction: The increasing prevalence rate of resistant and multiresistant bacterial strains to antibiotics is a threat to public health and requires a rapid multifunctional answer. Individuals that are affected by resistant strains present a higher morbidity and mortality than individuals that are infected with the same species of bacteria but with sensitive strains. There have been identified risk factors that are related to the misuse and overuse of antibiotics, like socio-demographic characteristics and psychological aspects of the individuals that have not been explored objectively due to a lack of valid and reliable instruments for their measurement. Objective: To validate a questionnaire for the evaluation of the levels of knowledge related to the use of antibiotics in a Mexican population. Materials and Methods: Analytical cross-sectional observational study. The questionnaire consists of 12 items to evaluated knowledge (1=no, 2=not sure, 3=yes) regarding the use of antibiotics, with higher scores corresponding to a higher level of knowledge. Data are collected in a sample of students. Data collection is still ongoing. In this abstract preliminary results of 30 respondents are reported which were collected during pilot-testing. The validation of the instrument was done using the Rasch model. Fit to the Rasch model was tested checking overall fit to the model, unidimensionality, local independence and evaluating the presence of Differential Item Functioning (DIF) by age and gender. The software Rumm2030 and the SPSS were used for the analyses. Results: The participants of the pilot-testing presented an average age of 32 years ± 12.6 and 53% were women. The preliminary results indicated that the items showed good fit to the Rasch model (chi-squared=12.8 p=0.3795). Unidimensionality (number of significant t-tests of 3%) could be proven, the items were locally independent, and no DIF was observed. Knowledge was the smallest regarding statements on the role of antibiotics in treating infections, e.g., most of the respondents did not know that antibiotics would not work against viral infections (70%) and that they could also cause side effects (87%). The knowledge score ranged from 0 to 100 points with a transformed measurement (mean of knowledge 27.1 ± 4.8). Conclusions: The instrument showed good psychometric proprieties. The low scores of knowledge about antibiotics suggest that misinterpretations on the use of these medicaments were prevalent, which could influence the production of antibiotic resistance. The application of this questionnaire will allow the objective identification of 'Hight risk groups', which will be the target population for future educational campaigns, to reduce the knowledge gaps on the general population as an effort against antibiotic resistance.

Keywords: antibiotics, knowledge, misuse, overuse, questionnaire, Rasch model, validation

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Authors: M. M. Ali, Ahmed Al- Ani, Derek Eamus, Daniel K. Y. Tan

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In this glasshouse study, we developed the new image-based non-destructive technique for detecting leaf P status of different crops such as cotton, tomato and lettuce. Plants were allowed to grow on nutrient media containing different P concentrations, i.e. 0%, 50% and 100% of recommended P concentration (P0 = no P, L; P1 = 2.5 mL 10 L-1 of P and P2 = 5 mL 10 L-1 of P as NaH2PO4). After 10 weeks of growth, plants were harvested and data on leaf P contents were collected using the standard destructive laboratory method and at the same time leaf images were collected by a handheld crop image sensor. We calculated leaf area, leaf perimeter and RGB (red, green and blue) values of these images. This data was further used in the linear discriminant analysis (LDA) to estimate leaf P contents, which successfully classified these plants on the basis of leaf P contents. The data indicated that P deficiency in crop plants can be predicted using the image and morphological data. Our proposed non-destructive imaging method is precise in estimating P requirements of different crop species.

Keywords: image-based techniques, leaf area, leaf P contents, linear discriminant analysis

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Authors: June Keeling, Christina Athanasiades, Vaiva Hendrixson, Delyth Wyndham

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Recognition and education in violence, abuse, and neglect for medical and healthcare practitioners (REVAMP) is a trans-European project aiming to introduce a training programme that has been specifically developed by partners across seven European countries to meet the needs of medical and healthcare practitioners. Amalgamating the knowledge and experience of clinicians, researchers, and educators from interdisciplinary and multi-professional backgrounds, REVAMP has tackled the under-resourced and underdeveloped area of domestic violence and abuse. The team designed an online training programme to support medical and healthcare practitioners to recognise and respond appropriately to survivors of domestic violence and abuse at their point of contact with a health provider. The REVAMP partner countries include Europe: France, Lithuania, Germany, Greece, Iceland, Norway, and the UK. The training is delivered through a series of interactive online modules, adapting evidence-based pedagogical approaches to learning. Capturing and addressing the complexities of the project impacted the methodological decisions and approaches to evaluation. The challenge was to find an evaluation methodology that captured valid data across all partner languages to demonstrate the extent of the change in knowledge and understanding. Co-development by all team members was a lengthy iterative process, challenged by a lack of consistency in terminology. A mixed methods approach enabled both qualitative and quantitative data to be collected, at the start, during, and at the conclusion of the training for the purposes of evaluation. The module content and evaluation instrument were accessible in each partner country's language. Collecting both types of data provided a high-level snapshot of attainment via the quantitative dataset and an in-depth understanding of the impact of the training from the qualitative dataset. The analysis was mixed methods, with integration at multiple interfaces. The primary focus of the analysis was to support the overall project evaluation for the funding agency. A key project outcome was identifying that the trans-European approach posed several challenges. Firstly, the project partners did not share a first language or a legal or professional approach to domestic abuse and neglect. This was negotiated through complex, systematic, and iterative interaction between team members so that consensus could be achieved. Secondly, the context of the data collection in several different cultural, educational, and healthcare systems across Europe challenged the development of a robust evaluation. The participants in the pilot evaluation shared that the training was contemporary, well-designed, and of great relevance to inform practice. Initial results from the evaluation indicated that the participants were drawn from more than eight partner countries due to the online nature of the training. The primary results indicated a high level of engagement with the content and achievement through the online assessment. The main finding was that the participants perceived the impact of domestic abuse and neglect in very different ways in their individual professional contexts. Most significantly, the participants recognised the need for the training and the gap that existed previously. It is notable that a mixed-methods evaluation of a trans-European project is unusual at this scale.

Keywords: domestic violence, e-learning, health professionals, trans-European

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Authors: Kinda AlSamara

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The nineteenth century was characterized by major educational reforms in the Arab World. One of the unintended outcomes of colonization in Arab countries was the initiation of women liberation as well as the introduction of modern education and its application in sensitizing people on the rights of women and their liberation. The reforms were often attributed to various undercurrents that took place at different levels within the Ottoman Empire, and particularly the arrival and influence of the Christian missionaries were supported by the American and European governments. These trends were also significantly attributed to the increase in the presence of Europeans in the region, as well as the introduction of secular ideas and approaches related to the meaning of modernity. Using literary analysis as a method, this paper examines the role of an important male figure like the political activist and writer Qāsim Amīn and the religious reformer Muḥammad ʻAbduh in starting this discourse and shows their impact on the emancipation of women movement (Taḥrīr), and how later women led the movement with their published work. This paper explores Arab Salons and the initiation of women’s literary circles. Women from wealthy families in Egypt and Syria who had studied in Europe or interacted with European counterparts began these circles. These salons acted as central locations where people could meet and hold discussions on political, social, and literary trends as they happened each day. The paper concludes with a discussion of current debates between the Islamist and the secularist branches of the movement today. While the Islamists believe that adhering to the core of Islam with some of its contested position on women is a modern ideology of liberation that fits the current culture of modern time Egypt; the secularists argue that the influence that Islam has on the women’s liberation movement in Egypt has been a threat to the natural success and progress of the movement, which was initiated in the early nineteenth century independent of the more recent trends towards religiosity in the country.

Keywords: educational model, crisis of terminologies, Arab awakening, nineteenth century

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Authors: Rushiraj Heshi, Smriti Bhandari

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Master Data Management requires creation of Central repository, applying constraints on Repository and designing processes to manage data. Designing of Repository, constraints on repository and business processes is very tedious and time consuming task for large Enterprise. Hence Visual Repository, constraints and Process (Workflow) modeling is the most critical step in Master Data Management.In this paper, we realize a Visual Modeling tool for implementing Repositories, Constraints and Processes based on Eclipse Plugin using GMF/EMF which follows principles of Model Driven Engineering (MDE).

Keywords: EMF, GMF, GEF, repository, constraint, process

Procedia PDF Downloads 488

Authors: Martina Dickson, Hanadi Kadbey, Melissa Mcminn

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Research has shown that anxiety and trepidation towards learning about science is prevalent among elementary school teachers in Western countries. It has also been shown repeatedly that pre-service and in-service teachers who show signs of anxiety towards science are; a) less likely to teach it at all, where they have some autonomy over this, b) less likely to teach it effectively c) ultimately that their students have lower attainment scores in science. It is therefore critically important to gauge pre-service teachers’ science anxiety levels early on whilst there are still possibilities to overturn some of the reasons behind these fears and avert these serious issues occurring later on. This study takes place in the capital of the United Arab Emirates (U.A.E.) in the context of training local elementary school teachers. In the U.A.E., where Emirati teachers are already in the vast minority and attrition rates are high, it is important to offer as much support to pre-service teachers as possible. If pre-service teachers are graduating with high levels of science anxiety unabated, according to the research there is a very real concern that as generalist primary school teachers, their science teaching will be far from optimal. The aims of this research study were to ascertain the science anxiety levels of pre-service elementary teachers and to identify particular areas of their science anxiety, if appropriate. We surveyed 200 Emirati pre-service teachers and found that levels of science anxiety were directly related to their perceptions of performance in science exams, laboratory experiments and inquiry approaches to science learning. Whilst some studies have shown that science anxiety can decrease as students gain confidence in science knowledge by studying courses, we did not see this effect in our study. This is based upon a theoretical framework which holds that in some cases, science anxiety is related to lack of exposure to, or insecurity with science content itself which in some cases is alleviated by the students’ covering of material and greater confidence in the subject. Exploring this variable allowed us to explore whether students educated in schools influenced by the educational reform in Abu Dhabi have differing science anxiety levels from those who were educated prior to the reforms. We discuss the possible implications of these findings to the future teaching of science in Abu Dhabi public schools.

Keywords: pre-service teachers, science anxiety, United Arab Emirates, educational reform

Procedia PDF Downloads 326

Authors: Lily Ingsrisawang, Tasanee Nacharoen

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Introduction: The problems of unbalanced data sets generally appear in real world applications. Due to unequal class distribution, many research papers found that the performance of existing classifier tends to be biased towards the majority class. The k -nearest neighbors’ nonparametric discriminant analysis is one method that was proposed for classifying unbalanced classes with good performance. Hence, the methods of discriminant analysis are of interest to us in investigating misclassification error rates for class-imbalanced data of three diabetes risk groups. Objective: The purpose of this study was to compare the classification performance between parametric discriminant analysis and nonparametric discriminant analysis in a three-class classification application of class-imbalanced data of diabetes risk groups. Methods: Data from a healthy project for 599 staffs in a government hospital in Bangkok were obtained for the classification problem. The staffs were diagnosed into one of three diabetes risk groups: non-risk (90%), risk (5%), and diabetic (5%). The original data along with the variables; diabetes risk group, age, gender, cholesterol, and BMI was analyzed and bootstrapped up to 50 and 100 samples, 599 observations per sample, for additional estimation of misclassification error rate. Each data set was explored for the departure of multivariate normality and the equality of covariance matrices of the three risk groups. Both the original data and the bootstrap samples show non-normality and unequal covariance matrices. The parametric linear discriminant function, quadratic discriminant function, and the nonparametric k-nearest neighbors’ discriminant function were performed over 50 and 100 bootstrap samples and applied to the original data. In finding the optimal classification rule, the choices of prior probabilities were set up for both equal proportions (0.33: 0.33: 0.33) and unequal proportions with three choices of (0.90:0.05:0.05), (0.80: 0.10: 0.10) or (0.70, 0.15, 0.15). Results: The results from 50 and 100 bootstrap samples indicated that the k-nearest neighbors approach when k = 3 or k = 4 and the prior probabilities of {non-risk:risk:diabetic} as {0.90:0.05:0.05} or {0.80:0.10:0.10} gave the smallest error rate of misclassification. Conclusion: The k-nearest neighbors approach would be suggested for classifying a three-class-imbalanced data of diabetes risk groups.

Keywords: error rate, bootstrap, diabetes risk groups, k-nearest neighbors

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Authors: Amirreza Fazely Hamedani, Muzzamil Aziz, Philipp Wieder, Ramin Yahyapour

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Software-defined networking in recent years came into the sight of so many network designers as a successor to the traditional networking. Unlike traditional networks where control and data planes engage together within a single device in the network infrastructure such as switches and routers, the two planes are kept separated in software-defined networks (SDNs). All critical decisions about packet routing are made on the network controller, and the data level devices forward the packets based on these decisions. This type of network is vulnerable to DDoS attacks, degrading the overall functioning and performance of the network by continuously injecting the fake flows into it. This increases substantial burden on the controller side, and the result ultimately leads to the inaccessibility of the controller and the lack of network service to the legitimate users. Thus, the protection of this novel network architecture against denial of service attacks is essential. In the world of cybersecurity, attacks and new threats emerge every day. It is essential to have tools capable of managing and analyzing all this new information to detect possible attacks in real-time. These tools should provide a comprehensive solution to automatically detect, predict and prevent abnormalities in the network. Big data encompasses a wide range of studies, but it mainly refers to the massive amounts of structured and unstructured data that organizations deal with on a regular basis. On the other hand, it regards not only the volume of the data; but also that how data-driven information can be used to enhance decision-making processes, security, and the overall efficiency of a business. This paper presents an intelligent big data framework as a solution to handle illegitimate traffic burden on the SDN network created by the numerous DDoS attacks. The framework entails an efficient defence and monitoring mechanism against DDoS attacks by employing the state of the art machine learning techniques.

Keywords: apache spark, apache kafka, big data, DDoS attack, machine learning, SDN network

Procedia PDF Downloads 165