Search results for: collaborative database

Authors: Vicario Marina, Bustos Freddy, Olivares Jesús, Gómez Pilar

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This paper presents a didactic model and a tool as educational resources to support the learning of geometry; they focus on topics difficult to understand. The target population is elementary school students. The tool is based on a collaborative educational approach using multi-touch devices. The proposal is based on the challenges found in the instructional design and prototype implementation. Traditionally, elementary students have had many problems assimilating mathematical topics; this new Educatronic prototype facilitates the learning experience using exercises and they were tested with different children demonstrating the benefits of the prototype by improving their mathematical skills.

Keywords: educatronic prototype, geometry, multitouch surface, educational computing, primary school, mathematics, educational informatics

Procedia PDF Downloads 300

Authors: Abdorrasoul Malekpour, Mohammad Ghorbani Mojtaba Mortazavi, Mohammadreza Fattahi, Mohammad Hassan Meshkibaf, Ali Fakhrzad, Saeid Salehi, Saeideh Zahedi, Amir Ahmadimoghaddam, Parviz Farzadnia Dr., Mohammadreza Hajyani Asl Bs

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Hepatitis B as an infectious disease has eight main genotypes (A–H). The aim of this study is to Bioinformatically identify Rare Codon Clusters (RCC) in proteins structure of HBV. For detection of protein family accession numbers (Pfam) of HBV proteins; used of uni-prot database and Pfam search tool were used. Obtained Pfam IDs were analyzed in Sherlocc program and RCCs in HBV proteins were detected. In further, the structures of TrEMBL entries proteins studied in PDB database and 3D structures of the HBV proteins and locations of RCCs were visualized and studied using Swiss PDB Viewer software. Pfam search tool have found nine significant hits and 0 insignificant hits in 3 frames. Results of Pfams studied in the Sherlocc program show this program not identified RCCs in the external core antigen (PF08290) and truncated HBeAg protein (PF08290). By contrast the RCCs become identified in Hepatitis core antigen (PF00906) Large envelope protein S (PF00695), X protein (PF00739), DNA polymerase (viral) N-terminal domain (PF00242) and Protein P (Pf00336). In HBV genome, seven RCC identified that found in hepatitis core antigen, large envelope protein S and DNA polymerase proteins and proteins structures of TrEMBL entries sequences that reported in Sherlocc program outputs are not complete. Based on situation of RCC in structure of HBV proteins, it suggested those RCCs are important in HBV life cycle. We hoped that this study provide a new and deep perspective in protein research and drug design for treatment of HBV.

Keywords: rare codon clusters, hepatitis B virus, bioinformatic study, infectious disease

Procedia PDF Downloads 455

Authors: Rakhyun Kim, Sungho Tae

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Global environmental issues such as abnormal weathers due to global warming, resource depletion, and ecosystem distortions have been escalating due to rapid increase of population growth, and expansion of industrial and economic development. Accordingly, initiatives have been implemented by many countries to protect the environment through indirect regulation methods such as Environmental Product Declaration (EPD), in addition to direct regulations such as various emission standards. Following this trend, life cycle assessment (LCA) techniques that provide quantitative environmental information, such as Human Toxicity Potential (HTP), for buildings are being developed in the construction industry. However, at present, the studies on the environmental database of building materials are not sufficient to provide this support adequately. The purpose of this study is to analysis human toxicity potential of major building material production stage using life cycle assessment. For this purpose, the theoretical consideration of the life cycle assessment and environmental impact category was performed and the direction of the study was set up. That is, the major material in the global warming potential view was drawn against the building and life cycle inventory database was selected. The classification was performed about 17 kinds of substance and impact index, such as human toxicity potential, that it specifies in CML2001. The environmental impact of analysis human toxicity potential for the building material production stage was calculated through the characterization. Meanwhile, the environmental impact of building material in the same category was analyze based on the characterization impact which was calculated in this study. In this study, establishment of environmental impact coefficients of major building material by complying with ISO 14040. Through this, it is believed to effectively support the decisions of stakeholders to improve the environmental performance of buildings and provide a basis for voluntary participation of architects in environment consideration activities.

Keywords: human toxicity potential, major building material, life cycle assessment, production stage

Procedia PDF Downloads 110

Authors: Michael Moeti, Khuliso Sigama, Thapelo Samuel Matlala

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One of the principal challenges that the world is confronted with is insecurity. The crime rate is increasing exponentially, and protecting our physical assets especially in the motorist industry, is becoming impossible when applying our own strength. The need to develop technological solutions that detect and report theft without any human interference is inevitable. This is critical, especially for vehicle owners, to ensure theft detection and speedy identification towards recovery efforts in cases where a vehicle is missing or attempted theft is taking place. The vehicle theft detection system uses Convolutional Neural Network (CNN) to recognize the driver's face captured using an installed mobile phone device. The location identification function uses a Global Positioning System (GPS) to determine the real-time location of the vehicle. Upon identification of the location, Global System for Mobile Communications (GSM) technology is used to report or notify the vehicle owner about the whereabouts of the vehicle. The installed mobile app was implemented by making use of python as it is undoubtedly the best choice in machine learning. It allows easy access to machine learning algorithms through its widely developed library ecosystem. The graphical user interface was developed by making use of JAVA as it is better suited for mobile development. Google's online database (Firebase) was used as a means of storage for the application. The system integration test was performed using a simple percentage analysis. Sixty (60) vehicle owners participated in this study as a sample, and questionnaires were used in order to establish the acceptability of the system developed. The result indicates the efficiency of the proposed system, and consequently, the paper proposes the use of the system can effectively monitor the vehicle at any given place, even if it is driven outside its normal jurisdiction. More so, the system can be used as a database to detect, locate and report missing vehicles to different security agencies.

Keywords: CNN, location identification, tracking, GPS, GSM

Procedia PDF Downloads 136

Authors: Arin Ghazarian, Cyril Rakovski

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Differential privacy has become the leading technique to protect the privacy of individuals in a database while allowing useful analysis to be done and the results to be shared. It puts a guarantee on the amount of privacy loss in the worst-case scenario. Differential privacy is not a toggle between full privacy and zero privacy. It controls the tradeoff between the accuracy of the results and the privacy loss using a single key parameter called

Keywords: arrhythmia, cardiology, differential privacy, ECG, epsilon, medi-cal data, privacy preserving analytics, statistical databases

Procedia PDF Downloads 130

Authors: Rajlakshmi Guha, Sajjad Ansari, Shazia Nasreen, Hirak Banerjee, Jiaul Paik

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Dyslexia is a neurocognitive disorder, affecting around fifteen percent of the Indian population. The symptoms include difficulty in reading alphabet, words, and sentences. This can be difficult at the phonemic or recognition level and may further affect lexical structures. Therapeutic intervention of dyslexic children post assessment is generally done by special educators and psychologists through one on one interaction. Considering the large number of children affected and the scarcity of experts, access to care is limited in India. Moreover, unavailability of resources and timely communication with caregivers add on to the problem of proper intervention. With the development of Educational Technology and its use in India, access to information and care has been improved in such a large and diverse country. In this context, this paper proposes an ICT enabled home-based intervention program for dyslexic children which would support the child, and provide an interactive interface between expert, parents, and students. The paper discusses the details of the database design and system layout of the program. Along with, it also highlights the development of different technical aids required to build out personalized android applications for the Indian dyslexic population. These technical aids include speech database creation for children, automatic speech recognition system, serious game development, and color coded fonts. The paper also emphasizes the games developed to assist the dyslexic child on cognitive training primarily for attention, working memory, and spatial reasoning. In addition, it talks about the specific elements of the interactive intervention tool that makes it effective for home based intervention of dyslexia.

Keywords: Android applications, cognitive training, dyslexia, intervention

Procedia PDF Downloads 276

Authors: Raminder Kaur

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This paper considers the emerging area of integrating Virtual Reality (VR) technologies into the teaching of Visual Anthropology, Research Methods, and the Anthropology of Contemporary India in the University of Sussex. If deployed in a critical and self-reflexive manner, there are several advantages to VR-based immersive learning: (i) Based on data available for British schools, it has been noted that ‘Learning through experience can boost knowledge retention by up to 75%’. (ii) It can tutor students to learn with and from virtual worlds, devising new collaborative methods where suited. (iii) It can foster inclusive learning by aiding students with SEN and disabilities who may not be able to explore such areas in the physical world. (iv) It can inspire and instill confidence in students with anxieties about approaching new subjects, realms, or regions. (v) It augments our provision of ‘smart classrooms’ synchronised to the kinds of emerging immersive learning environments that students come from in schools.

Keywords: virtual reality, anthropology, immersive learning, university

Procedia PDF Downloads 49

Authors: Modesta E. Ezema, Christopher C. Ezema, Christian C. Ugwu, Udoka F. Eze, Florence M. Babalola

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Some employees knowingly or unknowingly contribute to loss of data and also expose data to threat in the process of getting their jobs done. Many organizations today are faced with the challenges of how to secure their data as cyber criminals constantly devise new ways of attacking the organization’s secret data. However, this paper enlists the latest strategies that must be put in place in order to protect these important data from being attacked in a collaborative work place. It also introduces us to Advanced Persistent Threats (APTs) and how it works. The empirical study was conducted to collect data from the employee in data centers on how data could be protected from malicious codes and cyber criminals and their responses are highly considered to help checkmate the activities of malicious code and cyber criminals in our work places.

Keywords: data, employee, malware, work place

Procedia PDF Downloads 361

Authors: Yusuf Hussaini Atulukwu, Daramola Japheth, Tabitit S. Tabiti, Daramola Elizabeth Lara

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In view of the recent limitations faced by the township concerning poorly constructed and in some cases non - existence of drainage facilities that resulted into incessant flooding in some parts of the community poses threat to life,property and the environment. The research seeks to address this issue by showing the spatial distribution of drainage network in Bida Urban using Geographic information System techniques. Relevant features were extracted from existing Bida based Map using un-screen digitization and x, y, z, data of existing drainages were acquired using handheld Global Positioning System (GPS). These data were uploaded into ArcGIS 9.2, software, and stored in the relational database structure that was used to produce the spatial data drainage network of the township. The result revealed that about 40 % of the drainages are blocked with sand and refuse, 35 % water-logged as a result of building across erosion channels and dilapidated bridges as a result of lack of drainage along major roads. The study thus concluded that drainage network systems in Bida community are not in good working condition and urgent measures must be initiated in order to avoid future disasters especially with the raining season setting in. Based on the above findings, the study therefore recommends that people within the locality should avoid dumping municipal waste within the drainage path while sand blocked or weed blocked drains should be clear by the authority concerned. In the same vein the authority should ensured that contract of drainage construction be awarded to professionals and all the natural drainages caused by erosion should be addressed to avoid future disasters.

Keywords: drainage network, spatial, digitization, relational database, waste

Procedia PDF Downloads 315

Authors: Lucia Billeci, Gennaro Tartarisco, Maurizio Varanini

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Fetal cardiac monitoring by fetal electrocardiogram (fECG) can provide significant clinical information about the healthy condition of the fetus. Despite this potentiality till now the use of fECG in clinical practice has been quite limited due to the difficulties in its measuring. The recovery of fECG from the signals acquired non-invasively by using electrodes placed on the maternal abdomen is a challenging task because abdominal signals are a mixture of several components and the fetal one is very weak. This paper presents an approach for fECG extraction from abdominal maternal recordings, which exploits the characteristics of pseudo-periodicity of fetal ECG. It consists of devising a quality index (fQI) for fECG and of finding the linear combinations of preprocessed abdominal signals, which maximize these fQI (quality index optimization - QIO). It aims at improving the performances of the most commonly adopted methods for fECG extraction, usually based on maternal ECG (mECG) estimating and canceling. The procedure for the fECG extraction and fetal QRS (fQRS) detection is completely unsupervised and based on the following steps: signal pre-processing; maternal ECG (mECG) extraction and maternal QRS detection; mECG component approximation and canceling by weighted principal component analysis; fECG extraction by fQI maximization and fetal QRS detection. The proposed method was compared with our previously developed procedure, which obtained the highest at the Physionet/Computing in Cardiology Challenge 2013. That procedure was based on removing the mECG from abdominal signals estimated by a principal component analysis (PCA) and applying the Independent component Analysis (ICA) on the residual signals. Both methods were developed and tuned using 69, 1 min long, abdominal measurements with fetal QRS annotation of the dataset A provided by PhysioNet/Computing in Cardiology Challenge 2013. The QIO-based and the ICA-based methods were compared in analyzing two databases of abdominal maternal ECG available on the Physionet site. The first is the Abdominal and Direct Fetal Electrocardiogram Database (ADdb) which contains the fetal QRS annotations thus allowing a quantitative performance comparison, the second is the Non-Invasive Fetal Electrocardiogram Database (NIdb), which does not contain the fetal QRS annotations so that the comparison between the two methods can be only qualitative. In particular, the comparison on NIdb was performed defining an index of quality for the fetal RR series. On the annotated database ADdb the QIO method, provided the performance indexes Sens=0.9988, PPA=0.9991, F1=0.9989 overcoming the ICA-based one, which provided Sens=0.9966, PPA=0.9972, F1=0.9969. The comparison on NIdb was performed defining an index of quality for the fetal RR series. The index of quality resulted higher for the QIO-based method compared to the ICA-based one in 35 records out 55 cases of the NIdb. The QIO-based method gave very high performances with both the databases. The results of this study foresees the application of the algorithm in a fully unsupervised way for the implementation in wearable devices for self-monitoring of fetal health.

Keywords: fetal electrocardiography, fetal QRS detection, independent component analysis (ICA), optimization, wearable

Procedia PDF Downloads 262

Authors: Vilma Zydziunaite, Vaida Jurgile, Roman Balandiuk

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Good, great, and leading teachers are experienced and respected role models, who are innovative, organized, collaborative, trustworthy, and confident facilitators of learning. They model integrity, have strong interpersonal and communication skills, display the highest level of professionalism, a commitment to students, and expertise, and demonstrate a passion for student learning while taking the initiative as influential change agents. Usually, we call them teacher(s) leaders by integrating three notions such as good, great, and leading in a one-teacher leader. Here are described essences of three concepts: ‘good teacher,’ ‘great teacher,’ and teacher leader’ as they are inseparable in teaching practices, teacher’s professional life, and educational interactions with students, fellow teachers, school administration, students’ families and school communities.

Keywords: great teacher, good teacher, leading teacher, school, student

Procedia PDF Downloads 113

Authors: Yildiz Stella Dak, Jale Tezcan

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Ground motion models that relate a strong motion parameter of interest to a set of predictive seismological variables describing the earthquake source, the propagation path of the seismic wave, and the local site conditions constitute a critical component of seismic hazard analyses. When a sufficient number of strong motion records are available, ground motion relations are developed using statistical analysis of the recorded ground motion data. In regions lacking a sufficient number of recordings, a synthetic database is developed using stochastic, theoretical or hybrid approaches. Regardless of the manner the database was developed, ground motion relations are developed using regression analysis. Development of a ground motion relation is a challenging process which inevitably requires the modeler to make subjective decisions regarding the inclusion criteria of the recordings, the functional form of the model and the set of seismological variables to be included in the model. Because these decisions are critically important to the validity and the applicability of the model, there is a continuous interest on procedures that will facilitate the development of ground motion models. This paper proposes the use of the Least Absolute Shrinkage and Selection Operator (LASSO) in selecting the set predictive seismological variables to be used in developing a ground motion relation. The LASSO can be described as a penalized regression technique with a built-in capability of variable selection. Similar to the ridge regression, the LASSO is based on the idea of shrinking the regression coefficients to reduce the variance of the model. Unlike ridge regression, where the coefficients are shrunk but never set equal to zero, the LASSO sets some of the coefficients exactly to zero, effectively performing variable selection. Given a set of candidate input variables and the output variable of interest, LASSO allows ranking the input variables in terms of their relative importance, thereby facilitating the selection of the set of variables to be included in the model. Because the risk of overfitting increases as the ratio of the number of predictors to the number of recordings increases, selection of a compact set of variables is important in cases where a small number of recordings are available. In addition, identification of a small set of variables can improve the interpretability of the resulting model, especially when there is a large number of candidate predictors. A practical application of the proposed approach is presented, using more than 600 recordings from the National Geospatial-Intelligence Agency (NGA) database, where the effect of a set of seismological predictors on the 5% damped maximum direction spectral acceleration is investigated. The set of candidate predictors considered are Magnitude, Rrup, Vs30. Using LASSO, the relative importance of the candidate predictors has been ranked. Regression models with increasing levels of complexity were constructed using one, two, three, and four best predictors, and the models’ ability to explain the observed variance in the target variable have been compared. The bias-variance trade-off in the context of model selection is discussed.

Keywords: ground motion modeling, least absolute shrinkage and selection operator, penalized regression, variable selection

Procedia PDF Downloads 308

Authors: Rose A. Yemson, Ping Jiang, Oyedeji L. Inumoh

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The deployment of wireless sensor network has rapidly increased, however with the increased capacity and diversity of sensors, and applications ranging from biological, environmental, military etc. generates tremendous volume of data’s where more attention is placed on the distributed sensing and little on how to manage, analyze, retrieve and understand the data generated. This makes it more quite difficult to process live sensor data, run concurrent control and update because sensor data are either heavyweight, complex, and slow. This work will focus on developing a web service platform for automatic detection of sensors, acquisition of sensor data, storage of sensor data into a database, processing of sensor data using reconfigurable software components. This work will also create a web service based sensor data management system to monitor physical movement of an individual wearing wireless network sensor technology (SunSPOT). The sensor will detect movement of that individual by sensing the acceleration in the direction of X, Y and Z axes accordingly and then send the sensed reading to a database that will be interfaced with an internet platform. The collected sensed data will determine the posture of the person such as standing, sitting and lying down. The system is designed using the Unified Modeling Language (UML) and implemented using Java, JavaScript, html and MySQL. This system allows real time monitoring an individual closely and obtain their physical activity details without been physically presence for in-situ measurement which enables you to work remotely instead of the time consuming check of an individual. These details can help in evaluating an individual’s physical activity and generate feedback on medication. It can also help in keeping track of any mandatory physical activities required to be done by the individuals. These evaluations and feedback can help in maintaining a better health status of the individual and providing improved health care.

Keywords: HTML, java, javascript, MySQL, sunspot, UML, web-based, wireless network sensor

Procedia PDF Downloads 196

Authors: Thiago Spilborghs Bueno Meyer, Plinio Thomaz Aquino Junior

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Through speech, which privileges the functional and interactive nature of the text, it is possible to ascertain the spatiotemporal circumstances, the conditions of production and reception of the discourse, the explicit purposes such as informing, explaining, convincing, etc. These conditions allow bringing the interaction between humans closer to the human-robot interaction, making it natural and sensitive to information. However, it is not enough to understand what is said; it is necessary to recognize emotions for the desired interaction. The validity of the use of neural networks for feature selection and emotion recognition was verified. For this purpose, it is proposed the use of neural networks and comparison of models, such as recurrent neural networks and deep neural networks, in order to carry out the classification of emotions through speech signals to verify the quality of recognition. It is expected to enable the implementation of robots in a domestic environment, such as the HERA robot from the RoboFEI@Home team, which focuses on autonomous service robots for the domestic environment. Tests were performed using only the Mel-Frequency Cepstral Coefficients, as well as tests with several characteristics of Delta-MFCC, spectral contrast, and the Mel spectrogram. To carry out the training, validation and testing of the neural networks, the eNTERFACE’05 database was used, which has 42 speakers from 14 different nationalities speaking the English language. The data from the chosen database are videos that, for use in neural networks, were converted into audios. It was found as a result, a classification of 51,969% of correct answers when using the deep neural network, when the use of the recurrent neural network was verified, with the classification with accuracy equal to 44.09%. The results are more accurate when only the Mel-Frequency Cepstral Coefficients are used for the classification, using the classifier with the deep neural network, and in only one case, it is possible to observe a greater accuracy by the recurrent neural network, which occurs in the use of various features and setting 73 for batch size and 100 training epochs.

Keywords: emotion recognition, speech, deep learning, human-robot interaction, neural networks

Procedia PDF Downloads 137

Authors: Raquel Pérez Estébanez

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Context: The study focuses on the importance of informed and engaged university students in relation to sustainable development goals (SDGs). It explores existing literature on students' perceptions, knowledge, and actions regarding these goals. Research Aim: The aim of this research is to assess the level of commitment and knowledge about the SDGs among university students, specifically within their university environment. The study was conducted during the 2022-2023 academic year. Methodology: The methodology used in this study is empirical. A questionnaire was prepared and administered to university students from a public university in Spain. The response rate was 80%. The questionnaire was then validated using a Cronbach test, which resulted in a reliability coefficient of 88%. The data collected was analyzed using SPSS software. Confirmatory factor analysis (CPA) was initially conducted to strengthen the factors, followed by multivariate analysis to delve deeper into the topic and identify the factors that explain the SDG model. Findings: The primary results of the study revealed that factors such as cooperative learning, action statements, perceived functions for universities, sources of information about sustainable development that students use, actions taken by students for sustainable development reasons in the past month, and attitudes towards education for sustainable development (ESD) contribute to an understanding of the awareness of university students regarding the SDGs. Theoretical Importance: The findings highlight the importance of further research and collaborative efforts to enhance SDG education. It emphasizes the role of higher education institutions (HEIs) in fostering the learning of skills and values, preparing students for decision-making, and promoting pluralistic development and sustainable societies. The study also emphasizes the need to link sustainability not only to environmental aspects but also to social and economic considerations. Data Collection and Analysis Procedures: The questionnaire was administered to university students, resulting in an 80% response rate. The collected data was validated using a Cronbach test to ensure reliability. SPSS software was used for data analysis, starting with confirmatory factor analysis (CPA) and followed by multivariate analysis. Questions Addressed: The research aimed to address the level of commitment and knowledge about the SDGs among university students, specifically within their university environment. It also sought to identify factors that contribute to the understanding of awareness among university students regarding the SDGs. Conclusion: The study highlights the importance of informed and engaged university students in relation to the SDGs. It emphasizes the role of higher education institutions in fostering sustainable development education and preparing students for decision-making. The findings suggest the need for further research and collaborative efforts to enhance SDG education and foster a sustainable future.

Keywords: SDG, awareness, higher education, ESD

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Authors: Saleh Alshehri

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Human skin detection is a vital step in many applications. Some of the applications are critical especially those related to security. This leverages the importance of a high-performance detection algorithm. To validate the accuracy of the algorithm, image databases are usually used. However, the suitability of these image databases is still questionable. It is suggested that the suitability can be measured mainly by the span the database covers of the color space. This research investigates the validity of three famous image databases.

Keywords: image databases, image processing, pattern recognition, neural networks

Procedia PDF Downloads 240

Authors: Mark Omu

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Education has remained the greatest fulcrum on which the developmental aspirations of societies and the world over is Anchored. This has been the case from the antiquity. As a result of recognition of this fact, education occupies a crucial and centripetal position at different epochs of societal formation and transformation. This paper recognized the all-embracing role of education to society and it utilized the literary research and review of literature to espouse on the role of alternative sources of financing education. This position was borne out of the dwindling resources available to education. Especially to finance teaching, learning, research and retraining of staffers. This paper found among other things that alternative funding of education is possible and it can be achieved through selling of its research products like entrepreneurial skills, collaborative ventures in public private partnership, philanthropic of endowments, etc. These are capable of bridging the financial gap currently bedevilling the educational sectors.

Keywords: alternative sources, funding, tertiary, education, society, partnership, Nigeria

Procedia PDF Downloads 392

Authors: Anthony Vandarakis

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Today’s International Service Learning practices require an update: modern technologies, fresh educational frameworks, and a new operating system to accountably prosper. This paper describes a model of International Service Learning (ISL), which combines current technological hardware, electronic platforms, and asynchronous communications that are grounded in inclusive pedagogy. This model builds on the work around collaborative field trip learning, extending the reach to international partnerships across continents. Mobile technology, 21^st century skills and summit-basecamp modeling intersect to support novel forms of learning that tread lightly on fragile natural ecosystems, affirm local reciprocal partnership in projects, and protect traveling participants from common yet avoidable cultural pitfalls.

Keywords: International Service Learning, ISL, field experiences, mobile technology, out there in here, summit basecamp pedagogy

Procedia PDF Downloads 157

Authors: Thapanee Seechaliao

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This research paper presents guiding on how to design social media into higher education courses. The research methodology used a survey approach. The research instrument was a questionnaire about guiding on how to design social media into higher education courses. Thirty-one lecturers completed the questionnaire. The data were scored by frequency and percentage. The research results were the lecturers’ opinions concerning the designing social media into higher education courses as follows: 1) Lecturers deem that the most suitable learning theory is Collaborative Learning. 2) Lecturers consider that the most important learning and innovation Skill in the 21st century is communication and collaboration skills. 3) Lecturers think that the most suitable evaluation technique is authentic assessment. 4) Lecturers consider that the most appropriate portion used as blended learning should be 70% in the classroom setting and 30% online.

Keywords: instructional design, social media, courses, higher education

Procedia PDF Downloads 484

Authors: Nopparet Thammasaranyakun

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This research objects are: 1: To study the biodiversity of medicinal plants used for food and medicinal tourism economies along the Phu Sing district Sisaket province. 2: To study the use of medicinal plants used for food and medicinal tourism economies along the Phu Sing district Sisaket province. 3: To provide a database of information on biodiversity for food and medicinal plants and medicinal tourism economies along the Phu Sing district Sisaket province. 4: Learn to create a biodiversity of medicinal plants used as food and treatment by Journeys economic Phu Sing district Sisaket province Boundaries used in this study was the Phu Sing district. Population and Agricultural Development Center, rayong Mun due to the initiative for youth Local, Government Health officials, community leaders, teachers, students, schools, the local people and tourists. Sage wisdom to know the herbs and women's groups, OTOP Phu Sing district in SiisaKet province. By selecting the specific data that way. The process of participatory action research (PAR) is a community-based research. The method of collecting qualitative data. (Qualitative) tool is used from context, Community areas, interview and Taped recordings. Observation and focus group data was statistically analyzed using descriptive statistics (Descriptive Statistics). The results findings: 1- A study of the biodiversity of plants used for food and medicinal tourism economies along the Phu Sing district Sisaket province. Were used in the dry season and the rainy season find the medicinal plants of 251 species 41 types of drugs. 2- The study utilized medicinal plants used as food and the treatment of indigenous Phu Sing Sisaket province. Found 251 species have medicinal properties that are used for food and medicinal purposes 41 types of drugs. 3- Of the database technology of biodiversity for food and medicinal plants used by local treatment Phu Sing district Sisaket province. A data base of 251 medicinal species 41 types of drugs is used for food and medicinal properties Sisaket province. 4- learning the biodiversity of medicinal plants used for food and medicinal tourism economies along the Phu Sing district Sisaket province.

Keywords: utilization of biodiversity, peaces herbals, used as Food, Sing district, sisaket

Procedia PDF Downloads 335

Authors: Emiel Caron

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Patent databases contain patent related data, organized in a relational data model, and are used to produce various patent statistics. These databases store raw data about scientific references cited by patents. For example, Patstat holds references to tens of millions of scientific journal publications and conference proceedings. These references might be used to connect patent databases with bibliographic databases, e.g. to study to the relation between science, technology, and innovation in various domains. Problematic in such studies is the low data quality of the references, i.e. they are often ambiguous, unstructured, and incomplete. Moreover, a complete bibliographic reference is stored in only one attribute. Therefore, a computerized cleaning and disambiguation method for large patent databases is developed in this work. The method uses rule-based scoring and clustering. The rules are based on bibliographic metadata, retrieved from the raw data by regular expressions, and are transparent and adaptable. The rules in combination with string similarity measures are used to detect pairs of records that are potential duplicates. Due to the scoring, different rules can be combined, to join scientific references, i.e. the rules reinforce each other. The scores are based on expert knowledge and initial method evaluation. After the scoring, pairs of scientific references that are above a certain threshold, are clustered by means of single-linkage clustering algorithm to form connected components. The method is designed to disambiguate all the scientific references in the Patstat database. The performance evaluation of the clustering method, on a large golden set with highly cited papers, shows on average a 99% precision and a 95% recall. The method is therefore accurate but careful, i.e. it weighs precision over recall. Consequently, separate clusters of high precision are sometimes formed, when there is not enough evidence for connecting scientific references, e.g. in the case of missing year and journal information for a reference. The clusters produced by the method can be used to directly link the Patstat database with bibliographic databases as the Web of Science or Scopus.

Keywords: clustering, data cleaning, data disambiguation, data mining, patent analysis, scientometrics

Procedia PDF Downloads 172

Authors: Luís Farinha, João J. Ferreira

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Nowadays innovation represents a challenge crucial to remaining globally competitive. This study seeks to develop a conceptual model aimed at measuring the dynamic interactions of the triple/quadruple helix, balancing innovation and entrepreneurship initiatives as pillars of regional competitiveness – the Regional Helix Scoreboard (RHS). To this aim, different strands of literature are identified according to their focus on specific regional competitiveness governance mechanisms. We put forward an overview of the state-of-the-art of research and is duly assessed in order to develop and propose a framework of analysis that enables an integrated approach in the context of collaborative dynamics. We conclude by presenting the RHS for the study of regional competitiveness dynamics, which integrates and associates different backgrounds and identifies a number of key performance indicators for research challenges.

Keywords: entrepreneurship, KPIs, innovation, performance measurement, regional competitiveness, regional helix scoreboard

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Authors: Vilma Zydziunaite, Monika Kelpsiene

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In early childhood and preschool education, play has an important role in learning and cognitive processes. In the context of a changing world, personal autonomy and the use of technology are becoming increasingly important for the development of a wide range of learner competencies. By integrating technology into learning environments, the educational reality is changed, promoting unusual learning experiences for children through play-based activities. Alongside this, teachers are challenged to develop encouragement and motivation strategies that empower children to act independently. The aim of the study was to reveal the changes in the roles and experiences of teachers in the application of AR technology for the enrichment of the learning process. A quantitative research approach was used to conduct the study. The data was collected through an electronic questionnaire. Participants: 319 teachers of 5-6-year-old children using AR technology tools in their educational process. Methods of data analysis: Cronbach alpha, descriptive statistical analysis, normal distribution analysis, correlation analysis, regression analysis (SPSS software). Results. The results of the study show a significant relationship between children's learning and the educational process modeled by the teacher. The strongest predictor of child learning was found to be related to the role of the educator. Other predictors, such as pedagogical strategies, the concept of AR technology, and areas of children's education, have no significant relationship with child learning. The role of the educator was found to be a strong determinant of the child's learning process. Conclusions. The greatest potential for integrating AR technology into the teaching-learning process is revealed in collaborative learning. Teachers identified that when integrating AR technology into the educational process, they encourage children to learn from each other, develop problem-solving skills, and create inclusive learning contexts. A significant relationship has emerged - how the changing role of the teacher relates to the child's learning style and the aspiration for personal leadership and responsibility for their learning. Teachers identified the following key roles: observer of the learning process, proactive moderator, and creator of the educational context. All these roles enable the learner to become an autonomous and active participant in the learning process. This provides a better understanding and explanation of why it becomes crucial to empower the learner to experiment, explore, discover, actively create, and foster collaborative learning in the design and implementation of the educational content, also for teachers to integrate AR technologies and the application of the principles of shared leadership. No statistically significant relationship was found between the understanding of the definition of AR technology and the teacher’s choice of role in the learning process. However, teachers reported that their understanding of the definition of AR technology influences their choice of role, which has an impact on children's learning.

Keywords: teacher, learner, augmented reality, collaboration, shared leadership, preschool education

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Authors: Daniela Prado, Lexi Frankel, Amalia Ardeljan, Lokesh Manjani, Matthew Cardeiro, Omar Rashid

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Background: Clostridium difficile (C. diff) is a gram-positive bacterium that is known to cause life-threatening diarrhea and severe inflammation of the colon. It originates as an alteration of the gut microbiome and can be transmitted through spores. Recent studies have shown a high association between the development of C. diff in cancer patients due to extensive hospitalization. However, research is lacking regarding C. diff’s association in the causation or prevention of cancer. The objective of this study was to therefore assess the correlation between Clostridium difficile infection (CDI) and the incidence of bone cancer. Methods: This retrospective analysis used data provided by a Health Insurance Portability and Accountability Act (HIPAA) compliant national database to evaluate the patients infected versus patients not infected with C. diff using ICD-10 and ICD-9 codes. Access to the database was granted by the Holy Cross Health, Fort Lauderdale, for the purpose of academic research. Standard statistical methods were used. Results: Between January 2010 and December 2019, the query was analyzed and resulted in 78863 patients in both the infected and control group, respectively. The two groups were matched by age range and CCI score. The incidence of bone cancer was 659 patients (0.835%) in the C. diff group compared to 1941 patients (2.461%) in the control group. The difference was statistically significant by a P-value < 2.2x10^-16 with an odds ratio (OR)= 0.33 (0.31-0.37) with a 95% confidence interval (CI). Treatment for CDI was analyzed for both C. diff infected and noninfected populations. 91 out of 16,676 (0.55%) patients with a prior C. diff infection and treated with antibiotics were compared to the control group were 275 out of 16,676 (1.65%) patients with no history of CDI and received antibiotic treatment. Results remained statistically significant by P-value <2.2x10-16 with an OR= 0.42 (0.37, 0.48). and a 95% CI. Conclusion: The study shows a statistically significant correlation between C. diff and a reduced incidence of bone cancer. Further evaluation is recommended to assess the potential of C. difficile in reducing bone cancer incidence.

Keywords: bone cancer, colitis, clostridium difficile, microbiome

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Authors: Archana Soni, Arvind Mittal, Manmohan Kapshe

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Energy has been recognized as one of the key inputs for the economic growth and social development of a country. High economic growth naturally means a high level of energy consumption. However, in the present energy scenario where there is a wide gap between the energy generation and energy consumption, it is extremely difficult to match the demand with the supply. India being one of the largest and rapidly growing developing countries, there is an impending energy crisis which requires immediate measures to be adopted. In this situation, the concept of Energy Intensity comes under special focus to ensure energy security in an environmentally sustainable way. Energy Intensity is defined as the energy consumed per unit output in the context of industrial energy practices. It is a key determinant of the projections of future energy demands which assists in policy making. Energy Intensity is inversely related to energy efficiency; lesser the energy required to produce a unit of output or service, the greater is the energy efficiency. Energy Intensity of Indian manufacturing industries is among the highest in the world and stands for enormous energy consumption. Hence, reducing the Energy Intensity of Indian manufacturing industries is one of the best strategies to achieve a low level of energy consumption and conserve energy. This study attempts to analyse the factors which influence the Energy Intensity of Indian manufacturing firms and how they can be used to reduce the Energy Intensity. The paper considers six of the largest energy consuming manufacturing industries in India viz. Aluminium, Cement, Iron & Steel Industries, Textile Industries, Fertilizer and Paper industries and conducts a detailed Energy Intensity analysis using the data from PROWESS database of the Centre for Monitoring Indian Economy (CMIE). A total of twelve independent explanatory variables based on various factors such as raw material, labour, machinery, repair and maintenance, production technology, outsourcing, research and development, number of employees, wages paid, profit margin and capital invested have been taken into consideration for the analysis.

Keywords: energy intensity, explanatory variables, manufacturing industries, PROWESS database

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Authors: Edward Hage, Pieter Lietaert, Gabriel Abedrabbo

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Musculoskeletal disorders are an important category of work-related diseases. They are often caused by working in non-ergonomic postures and are preventable with proper workplace design, possibly including human-machine collaboration. This paper presents a methodology and a supporting software prototype to design a simple assembly cell with minimal ergonomic risk. The methodology helps to determine the optimal position and orientation of workpieces and workplace resources for specific operator assembly actions. The methodology is tested on an industrial use case: a collaborative robot (cobot) assisted assembly of a clamping device. It is shown that the automated methodology results in a workplace design with significantly reduced ergonomic risk to the operator compared to a manual design of the cell.

Keywords: ergonomics optimization, design for ergonomics, workplace design, pose generation

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Authors: A. Capodieci, G. Del Fiore, L. Mainetti

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Recently, the use of web 2.0 tools has increased in companies and public administration organizations. This phenomenon, known as "Enterprise 2.0", has, de facto, modified common organizational and operative practices. This has led “knowledge workers” to change their working practices through the use of Web 2.0 communication tools. Unfortunately, these tools have not been integrated with existing enterprise information systems, a situation that could potentially lead to a loss of information. This is an important problem in an organizational context, because knowledge of information exchanged within the organization is needed to increase the efficiency and competitiveness of the organization. In this article we demonstrate that it is possible to capture this knowledge using collaboration processes, which are processes of abstraction created in accordance with design patterns and applied to new organizational operative practices.

Keywords: business practices, business process patterns, collaboration tools, enterprise 2.0, knowledge workers

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Authors: Andrew R. Willis, Kevin Brink, Kathleen Dipple

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This article describes a software package called ROS-georegistration intended for use with the robot operating system (ROS) and the Gazebo 3D simulation environment. ROSgeoregistration provides tools for the simulation, test, and deployment of aerial georegistration algorithms and is available at github.com/uncc-visionlab/rosgeoregistration. A model creation package is provided which downloads multi-spectral images from the Google Earth Engine database and, if necessary, incorporates these images into a single, possibly very large, reference image. Additionally a Gazebo plugin which uses the real-time sensor pose and image formation model to generate simulated imagery using the specified reference image is provided along with related plugins for UAV relevant data. The novelty of this work is threefold: (1) this is the first system to link the massive multi-spectral imaging database of Google’s Earth Engine to the Gazebo simulator, (2) this is the first example of a system that can simulate geospatially and radiometrically accurate imagery from multiple sensor views of the same terrain region, and (3) integration with other UAS tools creates a new holistic UAS simulation environment to support UAS system and subsystem development where real-world testing would generally be prohibitive. Sensed imagery and ground truth registration information is published to client applications which can receive imagery synchronously with telemetry from other payload sensors, e.g., IMU, GPS/GNSS, barometer, and windspeed sensor data. To highlight functionality, we demonstrate ROSgeoregistration for simulating Electro-Optical (EO) and Synthetic Aperture Radar (SAR) image sensors and an example use case for developing and evaluating image-based UAS position feedback, i.e., pose for image-based Guidance Navigation and Control (GNC) applications.

Keywords: EO-to-EO, EO-to-SAR, flight simulation, georegistration, image generation, robot operating system, vision-based navigation

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Authors: Keerthana Gonella, Kamesh Apparaju

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Teams are all pervasive and team leadership is a much discussed topic in managing projects that characterize the modern work environment. Biotechnology industry in India is an area of research interest for scholars on leadership, especially, team leadership. The present paper examines the perception of team members on the effectiveness of their team leaders in the biotechnology industry in India. This is an empirical study in which the data was collected by administering the closed-ended questionnaire to the respondents from across India. The effectiveness of the team leader is dependent upon his goal orientation that creates a collaborative climate. Leaders with technical know-how inspire teamwork with trust. They build confidence, mitigate the differences and expand team capabilities through teamwork. Effective leaders also create team identity making the most of the differences with a vision.

Keywords: collaboration, perception, team, team capabilities, team leadership

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Authors: Sepali Guruge

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Background: There is an increase in interest among health care professionals and social workers in understanding how best to identify, mitigate, and prevent elder abuse. Purpose & method: Based on a recently completed scoping review of related literature, this paper will focus on the current state of knowledge on elder abuse interventions. Results: The results will be presented in light of the fact that limited literature exists on primary prevention of elder abuse. The existing literature on interventions to reduce or stop abuse will be critically examined in terms of their effectiveness. Particular attention will be paid to interventions such as relocation of older adults experiencing abuse, in-home assessments, empowerment and psycho-educational support for older adults. Conclusions: Overall, multi-stakeholder collaborative, community-based interventions should be designed to identify, mitigate, and prevent elder abuse.

Keywords: elder abuse, interventions, scoping review, prevention

Procedia PDF Downloads 327