Search results for: autonomous learning system
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 23034

Search results for: autonomous learning system

18204 Teaching Business Process Management using IBM’s INNOV8 BPM Simulation Game

Authors: Hossam Ali-Hassan, Michael Bliemel

Abstract:

This poster reflects upon our experiences using INNOV8, IBM’s Business Process Management (BPM) simulation game, in online MBA and undergraduate MIS classes over a period of 2 years. The game is designed to gives both business and information technology players a better understanding of how effective BPM impacts an entire business ecosystem. The game includes three different scenarios: Smarter Traffic, which is used to evaluate existing traffic patterns and re-route traffic based on incoming metrics; Smarter Customer Service where players develop more efficient ways to respond to customers in a call centre environment; and Smarter Supply Chains where players balance supply and demand and reduce environmental impact in a traditional supply chain model. We use the game as an experiential learning tool, where students have to act as managers making real time changes to business processes to meet changing business demands and environments. The students learn how information technology (IT) and information systems (IS) can be used to intelligently solve different problems and how computer simulations can be used to test different scenarios or models based on business decisions without having to actually make the potentially costly and/or disruptive changes to business processes. Moreover, when students play the three different scenarios, they quickly see how practical process improvements can help meet profitability, customer satisfaction and environmental goals while addressing real problems faced by municipalities and businesses today. After spending approximately two hours in the game, students reflect on their experience from it to apply several BPM principles that were presented in their textbook through the use of a structured set of assignment questions. For each final scenario students submit a screenshot of their solution followed by one paragraph explaining what criteria you were trying to optimize, and why they picked their input variables. In this poster we outline the course and the module’s learning objectives where we used the game to place this into context. We illustrate key features of the INNOV8 Simulation Game, and describe how we used them to reinforce theoretical concepts. The poster will also illustrate examples from the simulation, assignment, and learning outcomes.

Keywords: experiential learning, business process management, BPM, INNOV8, simulation, game

Procedia PDF Downloads 319
18203 Visualize Global Warming and Its Consequences Using Augmented Reality

Authors: K. R. Parvathy, R. Rao Bhavani , M. L. McLain, Kamal Bijlani, R. Jayakrishnan

Abstract:

Augmented Reality (AR) technology is considered to be an important emerging technology used in education today. One potentially key use of AR in education is to teach socio-scientific issues (SSI), topics that inure students towards social conscience and critical thinking. This work uses multiple markers and virtual buttons that interact with each other, creating a life-like visual spectacle. Learning about issues such as global warming by using AR technology, students will have an increased sense of experiencing immersion, immediacy, and presence, thereby enhancing their learning as well as likely improving their ability to make better informed decisions about considerations of such issues. Another advantage of AR is that it is a low cost technology, making it advantageous for educators to adapt to their classrooms. Also in this work we compare the effectiveness of AR versus ordinary video by polling a group of students to assess the content understandability, effectiveness and interaction of both the delivery methods.

Keywords: augmented reality, global warming, multiple markers, virtual buttons

Procedia PDF Downloads 386
18202 Parental Investment in Education: A Pathway for the Children's Access to Quality Education

Authors: Tukur Husaini Nahuche

Abstract:

The parent resources play a vital role in the life of the offspring. It help give children basic necessities of life like food, clothing, and housing. In a like manner financial assets allow parents to move into neighborhood with more affluent school systems, to pay school bills, purchase expensive technologies like personal computer, save money for tutoring books, magazines, journals, Newspapers etc. Making of proper provision in the home environment conducive for learning after school hours and creation of other outdoor activities for them are what necessitate in enhancing and accelerating children’s learning opportunities. Indeed, this paper intends to discuss parental investment in education, parent income resources, parental education, occupation, and income as relatively influencing children’s access to quality education. With the hope that families would provide equal opportunities for children irrespective of their sex, intelligence, subject choice,etc.

Keywords: parental investment, children's access, quality education

Procedia PDF Downloads 538
18201 Wireless Sensor Anomaly Detection Using Soft Computing

Authors: Mouhammd Alkasassbeh, Alaa Lasasmeh

Abstract:

We live in an era of rapid development as a result of significant scientific growth. Like other technologies, wireless sensor networks (WSNs) are playing one of the main roles. Based on WSNs, ZigBee adds many features to devices, such as minimum cost and power consumption, and increasing the range and connect ability of sensor nodes. ZigBee technology has come to be used in various fields, including science, engineering, and networks, and even in medicinal aspects of intelligence building. In this work, we generated two main datasets, the first being based on tree topology and the second on star topology. The datasets were evaluated by three machine learning (ML) algorithms: J48, meta.j48 and multilayer perceptron (MLP). Each topology was classified into normal and abnormal (attack) network traffic. The dataset used in our work contained simulated data from network simulation 2 (NS2). In each database, the Bayesian network meta.j48 classifier achieved the highest accuracy level among other classifiers, of 99.7% and 99.2% respectively.

Keywords: IDS, Machine learning, WSN, ZigBee technology

Procedia PDF Downloads 528
18200 Naïve Bayes: A Classical Approach for the Epileptic Seizures Recognition

Authors: Bhaveek Maini, Sanjay Dhanka, Surita Maini

Abstract:

Electroencephalography (EEG) is used to classify several epileptic seizures worldwide. It is a very crucial task for the neurologist to identify the epileptic seizure with manual EEG analysis, as it takes lots of effort and time. Human error is always at high risk in EEG, as acquiring signals needs manual intervention. Disease diagnosis using machine learning (ML) has continuously been explored since its inception. Moreover, where a large number of datasets have to be analyzed, ML is acting as a boon for doctors. In this research paper, authors proposed two different ML models, i.e., logistic regression (LR) and Naïve Bayes (NB), to predict epileptic seizures based on general parameters. These two techniques are applied to the epileptic seizures recognition dataset, available on the UCI ML repository. The algorithms are implemented on an 80:20 train test ratio (80% for training and 20% for testing), and the performance of the model was validated by 10-fold cross-validation. The proposed study has claimed accuracy of 81.87% and 95.49% for LR and NB, respectively.

Keywords: epileptic seizure recognition, logistic regression, Naïve Bayes, machine learning

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18199 The Concept of Neurostatistics as a Neuroscience

Authors: Igwenagu Chinelo Mercy

Abstract:

This study is on the concept of Neurostatistics in relation to neuroscience. Neuroscience also known as neurobiology is the scientific study of the nervous system. In the study of neuroscience, it has been noted that brain function and its relations to the process of acquiring knowledge and behaviour can be better explained by the use of various interrelated methods. The scope of neuroscience has broadened over time to include different approaches used to study the nervous system at different scales. On the other hand, Neurostatistics based on this study is viewed as a statistical concept that uses similar techniques of neuron mechanisms to solve some problems especially in the field of life science. This study is imperative in this era of Artificial intelligence/Machine leaning in the sense that clear understanding of the technique and its proper application could assist in solving some medical disorder that are mainly associated with the nervous system. This will also help in layman’s understanding of the technique of the nervous system in order to overcome some of the health challenges associated with it. For this concept to be well understood, an illustrative example using a brain associated disorder was used for demonstration. Structural equation modelling was adopted in the analysis. The results clearly show the link between the techniques of statistical model and nervous system. Hence, based on this study, the appropriateness of Neurostatistics application in relation to neuroscience could be based on the understanding of the behavioural pattern of both concepts.

Keywords: brain, neurons, neuroscience, neurostatistics, structural equation modeling

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18198 Digital Twin of Real Electrical Distribution System with Real Time Recursive Load Flow Calculation and State Estimation

Authors: Anosh Arshad Sundhu, Francesco Giordano, Giacomo Della Croce, Maurizio Arnone

Abstract:

Digital Twin (DT) is a technology that generates a virtual representation of a physical system or process, enabling real-time monitoring, analysis, and simulation. DT of an Electrical Distribution System (EDS) can perform online analysis by integrating the static and real-time data in order to show the current grid status and predictions about the future status to the Distribution System Operator (DSO), producers and consumers. DT technology for EDS also offers the opportunity to DSO to test hypothetical scenarios. This paper discusses the development of a DT of an EDS by Smart Grid Controller (SGC) application, which is developed using open-source libraries and languages. The developed application can be integrated with Supervisory Control and Data Acquisition System (SCADA) of any EDS for creating the DT. The paper shows the performance of developed tools inside the application, tested on real EDS for grid observability, Smart Recursive Load Flow (SRLF) calculation and state estimation of loads in MV feeders.

Keywords: digital twin, distributed energy resources, remote terminal units, supervisory control and data acquisition system, smart recursive load flow

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18197 A Simulation-Based Method for Evaluation of Energy System Cooperation between Pulp and Paper Mills and a District Heating System: A Case Study

Authors: Alexander Hedlund, Anna-Karin Stengard, Olof Björkqvist

Abstract:

A step towards reducing greenhouse gases and energy consumption is to collaborate with the energy system between several industries. This work is based on a case study on integration of pulp and paper mills with a district heating system in Sundsvall, Sweden. Present research shows that it is possible to make a significant reduction in the electricity demand in the mechanical pulping process. However, the profitability of the efficiency measures could be an issue, as the excess steam recovered from the refiners decreases with the electricity consumption. A consequence will be that the fuel demand for steam production will increase. If the fuel price is similar to the electricity price it would reduce the profit of such a project. If the paper mill can be integrated with a district heating system, it is possible to upgrade excess heat from a nearby kraft pulp mill to process steam via the district heating system in order to avoid the additional fuel need. The concept is investigated by using a simulation model describing both the mass and energy balance as well as the operating margin. Three scenarios were analyzed: reference, electricity reduction and energy substitution. The simulation show that the total input to the system is lowest in the Energy substitution scenario. Additionally, in the Energy substitution scenario the steam from the incineration boiler covers not only the steam shortage but also a part of the steam produced using the biofuel boiler, the cooling tower connected to the incineration boiler is no longer needed and the excess heat can cover the whole district heating load during the whole year. The study shows a substantial economic advantage if all stakeholders act together as one system. However, costs and benefits are unequally shared between the actors. This means that there is a need for new business models in order to share the system costs and benefits.

Keywords: energy system, cooperation, simulation method, excess heat, district heating

Procedia PDF Downloads 218
18196 Early Stage Suicide Ideation Detection Using Supervised Machine Learning and Neural Network Classifier

Authors: Devendra Kr Tayal, Vrinda Gupta, Aastha Bansal, Khushi Singh, Sristi Sharma, Hunny Gaur

Abstract:

In today's world, suicide is a serious problem. In order to save lives, early suicide attempt detection and prevention should be addressed. A good number of at-risk people utilize social media platforms to talk about their issues or find knowledge on related chores. Twitter and Reddit are two of the most common platforms that are used for expressing oneself. Extensive research has already been done in this field. Through supervised classification techniques like Nave Bayes, Bernoulli Nave Bayes, and Multiple Layer Perceptron on a Reddit dataset, we demonstrate the early recognition of suicidal ideation. We also performed comparative analysis on these approaches and used accuracy, recall score, F1 score, and precision score for analysis.

Keywords: machine learning, suicide ideation detection, supervised classification, natural language processing

Procedia PDF Downloads 80
18195 Robot Technology Impact on Dyslexic Students’ English Learning

Authors: Khaled Hamdan, Abid Amorri, Fatima Hamdan

Abstract:

Involving students in English language learning process and achieving an adequate English language proficiency in the target language can be a great challenge for both teachers and students. This can prove even a far greater challenge to engage students with special needs (Dyslexia) if they have physical impairment and inadequate mastery of basic communicative language competence/proficiency in the target language. From this perspective, technology like robots can probably be used to enhance learning process for the special needs students who have extensive communication needs, who face continuous struggle to interact with their peers and teachers and meet academic requirements. Robots, precisely NAO, can probably provide them with the perfect opportunity to practice social and communication skills, and meet their English academic requirements. This research paper aims to identify to what extent robots can be used to improve students’ social interaction and communication skills and to understand the potential for robotics-based education in motivating and engaging UAEU dyslexic students to meet university requirements. To reach this end, the paper will explore several factors that come into play – Motion Level-involving cognitive activities, Interaction Level-involving language processing, Behavior Level -establishing a close relationship with the robot and Appraisal Level- focusing on dyslexia students’ achievement in the target language.

Keywords: dyslexia, robot technology, motion, interaction, behavior and appraisal levels, social and communication skills

Procedia PDF Downloads 350
18194 Closing the Assessment Loop: Case Study in Improving Outcomes for Online College Students during Pandemic

Authors: Arlene Caney, Linda Fellag

Abstract:

To counter the adverse effect of Covid-19 on college student success, two faculty members at a US community college have used web-based assessment data to improve curricula and, thus, student outcomes. This case study exemplifies how “closing the loop” by analyzing outcome assessments in real time can improve student learning for academically underprepared students struggling during the pandemic. The purpose of the study was to develop ways to mitigate the negative impact of Covid-19 on student success of underprepared college students. Using the Assessment, Evaluation, Feedback and Intervention System (AEFIS) and other assessment tools provided by the college’s Office of Institutional Research, an English professor and a Music professor collected data in skill areas related to their curricula over four semesters, gaining insight into specific course sections and learners’ performance across different Covid-driven course formats—face-to-face, hybrid, synchronous, and asynchronous. Real-time data collection allowed faculty to shorten and close the assessment loop, and prompted faculty to enhance their curricula with engaging material, student-centered activities, and a variety of tech tools. Frequent communication, individualized study, constructive criticism, and encouragement were among other measures taken to enhance teaching and learning. As a result, even while student success rates were declining college-wide, student outcomes in these faculty members’ asynchronous and synchronous online classes improved or remained comparable to student outcomes in hybrid and face-to-face sections. These practices have demonstrated that even high-risk students who enter college with remedial level language and mathematics skills, interrupted education, work and family responsibilities, and language and cultural diversity can maintain positive outcomes in college across semesters, even during the pandemic.

Keywords: AEFIS, assessment, distance education, institutional research center

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18193 Assessment of a Coupled Geothermal-Solar Thermal Based Hydrogen Production System

Authors: Maryam Hamlehdar, Guillermo A. Narsilio

Abstract:

To enhance the feasibility of utilising geothermal hot sedimentary aquifers (HSAs) for clean hydrogen production, one approach is the implementation of solar-integrated geothermal energy systems. This detailed modelling study conducts a thermo-economic assessment of an advanced Organic Rankine Cycle (ORC)-based hydrogen production system that uses low-temperature geothermal reservoirs, with a specific focus on hot sedimentary aquifers (HSAs) over a 30-year period. In the proposed hybrid system, solar-thermal energy is used to raise the water temperature extracted from the geothermal production well. This temperature increase leads to a higher steam output, powering the turbine and subsequently enhancing the electricity output for running the electrolyser. Thermodynamic modeling of a parabolic trough solar (PTS) collector is developed and integrated with modeling for a geothermal-based configuration. This configuration includes a closed regenerator cycle (CRC), proton exchange membrane (PEM) electrolyser, and thermoelectric generator (TEG). Following this, the study investigates the impact of solar energy use on the temperature enhancement of the geothermal reservoir. It assesses the resulting consequences on the lifecycle performance of the hydrogen production system in comparison with a standalone geothermal system. The results indicate that, with the appropriate solar collector area, a combined solar-geothermal hydrogen production system outperforms a standalone geothermal system in both cost and rate of production. These findings underscore a solar-assisted geothermal hybrid system holds the potential to generate lower-cost hydrogen with enhanced efficiency, thereby boosting the appeal of numerous low to medium-temperature geothermal sources for hydrogen production.

Keywords: clean hydrogen production, integrated solar-geothermal, low-temperature geothermal energy, numerical modelling

Procedia PDF Downloads 49
18192 Proposition on Improving Environmental Forensic System in China

Authors: Huilei Wang, Yuanfeng Wang

Abstract:

In the early period of China, economy developed rapidly at the cost of environment. Recently, it is generally recognized that the heavily polluted environment not only puts a brake on economic development but also paces negative impact on people’ health as well as probably next decades of generations. Accordingly, the latest Environmental Protection Law revised in 2014 makes a clear-cut division of environmental responsibility and regulates stricter penalties of breaching law. As the new environmental law is enforced gradually, environmental forensic is increasingly required in the process of ascertaining facts in judicial proceedings of environmental cases. Based on the outcomes of documentary analysis for all environmental cases judged on the basis of new environmental law, it is concluded that there still exists problems in present system of environmental forensic. Thus, this paper is aimed to make proposition on improving Chinese environmental forensic system, which involves: (i) promoting capability of environmental forensic system (EFS) to handle professional questions; (ii) develop price mechanism; (iii) multi-departments cooperate to establish unifying and complete EFS system;(iv) enhance the probative value of results of EFS. Such protocol for amending present regulation on environmental forensic is of significant importance because a quality report of environmental forensic will contributes to providing strong probative evidence of culprits’ activity of releasing contaminant into environment, degree of damages for victims and above all, causality between the behavior of public nuisance and damages.

Keywords: China, environmental cases, environmental forensic system, proposition

Procedia PDF Downloads 363
18191 Use of Simulation in Medical Education: Role and Challenges

Authors: Raneem Osama Salem, Ayesha Nuzhat, Fatimah Nasser Al Shehri, Nasser Al Hamdan

Abstract:

Background: Recently, most medical schools around the globe are using simulation for teaching and assessing students’ clinical skills and competence. There are many obstacles that could face students and faculty when simulation sessions are introduced into undergraduate curriculum. Objective: The aim of this study is to obtain the opinion of undergraduate medical students and our faculty regarding the role of simulation in undergraduate curriculum, the simulation modalities used, and perceived barriers in implementing stimulation sessions. Methods: To address the role of simulation, modalities used, and perceived challenges to implementation of simulation sessions, a self-administered pilot tested questionnaire with 18 items using a 5 point Likert scale was distributed. Participants included undergraduate male medical students (n=125) and female students (n=70) as well as the faculty members (n=14). Result: Various learning outcomes are achieved and improved through the technology enhanced simulation sessions such as communication skills, diagnostic skills, procedural skills, self-confidence, and integration of basic and clinical sciences. The use of high fidelity simulators, simulated patients and task trainers was more desirable by our students and faculty for teaching and learning as well as an evaluation tool. According to most of the students,' institutional support in terms of resources, staff and duration of sessions was adequate. However, motivation to participate in the sessions and provision of adequate feedback by the staff was a constraint. Conclusion: The use of simulation laboratory is of great benefit to the students and a great teaching tool for the staff to ensure students learning of the various skills.

Keywords: simulators, medical students, skills, simulated patients, performance, challenges, skill laboratory

Procedia PDF Downloads 392
18190 A Prediction Method for Large-Size Event Occurrences in the Sandpile Model

Authors: S. Channgam, A. Sae-Tang, T. Termsaithong

Abstract:

In this research, the occurrences of large size events in various system sizes of the Bak-Tang-Wiesenfeld sandpile model are considered. The system sizes (square lattice) of model considered here are 25×25, 50×50, 75×75 and 100×100. The cross-correlation between the ratio of sites containing 3 grain time series and the large size event time series for these 4 system sizes are also analyzed. Moreover, a prediction method of the large-size event for the 50×50 system size is also introduced. Lastly, it can be shown that this prediction method provides a slightly higher efficiency than random predictions.

Keywords: Bak-Tang-Wiesenfeld sandpile model, cross-correlation, avalanches, prediction method

Procedia PDF Downloads 364
18189 Empirical Analysis of the Effect of Cloud Movement in a Basic Off-Grid Photovoltaic System: Case Study Using Transient Response of DC-DC Converters

Authors: Asowata Osamede, Christo Pienaar, Johan Bekker

Abstract:

Mismatch in electrical energy (power) or outage from commercial providers, in general, does not promote development to the public and private sector, these basically limit the development of industries. The necessity for a well-structured photovoltaic (PV) system is of importance for an efficient and cost-effective monitoring system. The major renewable energy potential on earth is provided from solar radiation and solar photovoltaics (PV) are considered a promising technological solution to support the global transformation to a low-carbon economy and reduction on the dependence on fossil fuels. Solar arrays which consist of various PV module should be operated at the maximum power point in order to reduce the overall cost of the system. So power regulation and conditioning circuits should be incorporated in the set-up of a PV system. Power regulation circuits used in PV systems include maximum power point trackers, DC-DC converters and solar chargers. Inappropriate choice of power conditioning device in a basic off-grid PV system can attribute to power loss, hence the need for a right choice of power conditioning device to be coupled with the system of the essence. This paper presents the design and implementation of a power conditioning devices in order to improve the overall yield from the availability of solar energy and the system’s total efficiency. The power conditioning devices taken into consideration in the project includes the Buck and Boost DC-DC converters as well as solar chargers with MPPT. A logging interface circuit (LIC) is designed and employed into the system. The LIC is designed on a printed circuit board. It basically has DC current signalling sensors, specifically the LTS 6-NP. The LIC is consequently required to program the voltages in the system (these include the PV voltage and the power conditioning device voltage). The voltage is structured in such a way that it can be accommodated by the data logger. Preliminary results which include availability of power as well as power loss in the system and efficiency will be presented and this would be used to draw the final conclusion.

Keywords: tilt and orientation angles, solar chargers, PV panels, storage devices, direct solar radiation

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18188 Acausal and Causal Model Construction with FEM Approach Using Modelica

Authors: Oke Oktavianty, Tadayuki Kyoutani, Shigeyuki Haruyama, Junji Kaneko, Ken Kaminishi

Abstract:

Modelica has many advantages and it is very useful in modeling and simulation especially for the multi-domain with a complex technical system. However, the big obstacle for a beginner is to understand the basic concept and to build a new system model for a real system. In order to understand how to solve the simple circuit model by hand translation and to get a better understanding of how modelica works, we provide a detailed explanation about solver ordering system in horizontal and vertical sorting and make some proposals for improvement. In this study, some difficulties in using modelica software with the original concept and the comparison with Finite Element Method (FEM) approach is discussed. We also present our textual modeling approach using FEM concept for acausal and causal model construction. Furthermore, simulation results are provided that demonstrate the comparison between using textual modeling with original coding in modelica and FEM concept.

Keywords: FEM, a causal model, modelica, horizontal and vertical sorting

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18187 Numerical Verification of a Backfill-Rectangular Tank-Fluid System

Authors: Ramazan Livaoğlu, Tufan Çakır

Abstract:

The performance of rectangular tanks during earthquakes has been observed to depend significantly on the existence of water in the container and the presence of the backfill acting on tank wall. Therefore, in design of rectangular tanks, the topics of fluid-structure-backfill interactions and determination of modal characteristics of the interaction system have traditionally been one of the great theoretical and practical controversy. Although finite element method has been and will continue to be used to a significant extent in treating the response of the system, experimental verification of numerical models remains prerequisite for their adoption and reliable application in practice. Thus, in this study, the numerical and experimental investigations were performed on the backfill-exterior wall-fluid interaction system. Firstly, three dimensional finite element model (3D-FEM) was developed to acquire modal frequencies and mode shapes of the system by means of ANSYS. Secondly, a series of in-situ tests were fulfilled to define modal characteristics of same system to determine the applicability of the FEM to a real physical situation under field conditions. Finally, comparing the theoretical predictions from the model to results from experimental measurement, a close agreement was found between theory and experiment. Thus, it can be easily stated that experimental verification provides strong support for the use of proposed model in further investigations.

Keywords: fluid-structure interaction, modal analysis, rectangular tank, soil structure interaction

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18186 Graphical User Interface Testing by Using Deep Learning

Authors: Akshat Mathur, Sunil Kumar Khatri

Abstract:

This paper presents brief about how the use of Artificial intelligence in respect to GUI testing can reduce workload by using DL-fueled method. This paper also discusses about how graphical user interface and event driven software testing can derive benefits from the use of AI techniques. The use of AI techniques not only reduces the task and work load but also helps in getting better output than manual testing. Although results are same, but the use of Artifical intelligence techniques for GUI testing has proven to provide ideal results. DL-fueled framework helped us to find imperfections of the entire webpage and provides test failure result in a score format between 0 and 1which signifies that are test meets it quality criteria or not. This paper proposes DL-fueled method which helps us to find the genuine GUI bugs and defects and also helped us to scale the existing labour-intensive and skill-intensive methodologies.

Keywords: graphical user interface, GUI, artificial intelligence, deep learning, ML technology

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18185 Integrated Livestock and Cropping System and Sustainable Rural Development in India: A Case Study

Authors: Nizamuddin Khan

Abstract:

Integrated livestock and cropping system is very old agricultural practice since antiquity. It is an eco-friendly and sustainable farming system in which both the resources are optimally and rationally utilized through the recycling and re-utilization of their by-products. Indian farmers follow in- farm integrated farming system unlike in developed countries where both farm and off-farm system prevailed. The data on different components of the integrated farming system is very limited and that too is not widely available in published form. The primary source is the only option for understanding the mechanism, process, evaluation and performance of integrated livestock cropping system. Researcher generated data through the field survey of sampled respondents from sampled villages from Bulandshahr district of Uttar Pradesh. The present paper aims to understand the component group of system, degree, and level of integration, level of generation of employment, income, improvement in farm ecology, the economic viability of farmers and check in rural-urban migration. The study revealed that area witnessed intra farm integration in which both livestock and cultivation of crops take place on the same farm. Buffalo, goat, and poultry are common components of integration. Wheat, paddy, sugarcane and horticulture are among the crops. The farmers are getting 25% benefit more than those who do not follow the integrated system. Livestock husbandry provides employment and income through the year, especially during agriculture offseason. 80% of farmers viewed that approximately 35% of the total expenditure incurred is met from the livestock sector. Landless, marginal and small farmers are highly benefited from agricultural integration. About 70% of farmers acknowledged that using wastes of animals and crops the soil ecology is significantly maintained. Further, the integrated farming system is helpful in reducing rural to urban migration. An incentive with credit facilities, assured marketing, technological aid and government support is urgently needed for sustainable development of agriculture and farmers.

Keywords: integrated, recycle, employment, soil ecology, sustainability

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18184 Evaluation of Machine Learning Algorithms and Ensemble Methods for Prediction of Students’ Graduation

Authors: Soha A. Bahanshal, Vaibhav Verdhan, Bayong Kim

Abstract:

Graduation rates at six-year colleges are becoming a more essential indicator for incoming fresh students and for university rankings. Predicting student graduation is extremely beneficial to schools and has a huge potential for targeted intervention. It is important for educational institutions since it enables the development of strategic plans that will assist or improve students' performance in achieving their degrees on time (GOT). A first step and a helping hand in extracting useful information from these data and gaining insights into the prediction of students' progress and performance is offered by machine learning techniques. Data analysis and visualization techniques are applied to understand and interpret the data. The data used for the analysis contains students who have graduated in 6 years in the academic year 2017-2018 for science majors. This analysis can be used to predict the graduation of students in the next academic year. Different Predictive modelings such as logistic regression, decision trees, support vector machines, Random Forest, Naïve Bayes, and KNeighborsClassifier are applied to predict whether a student will graduate. These classifiers were evaluated with k folds of 5. The performance of these classifiers was compared based on accuracy measurement. The results indicated that Ensemble Classifier achieves better accuracy, about 91.12%. This GOT prediction model would hopefully be useful to university administration and academics in developing measures for assisting and boosting students' academic performance and ensuring they graduate on time.

Keywords: prediction, decision trees, machine learning, support vector machine, ensemble model, student graduation, GOT graduate on time

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18183 School Emergency Drills Evaluation through E-PreS Monitoring System

Authors: A. Kourou, A. Ioakeimidou, V. Avramea

Abstract:

Planning for natural disasters and emergencies is something every school or educational institution must consider, regardless of its size or location. Preparedness is the key to save lives if a disaster strikes. School disaster management mirrors individual and family disaster prevention, and wider community disaster prevention efforts. This paper presents the usage of E-PreS System as a helpful, managerial tool during the school earthquake drill, in order to support schools in developing effective disaster and emergency plans specific to their local needs. The project comes up with a holistic methodology using real-time evaluation involving different categories of actors, districts, steps and metrics. The main outcomes of E-PreS project are the development of E-PreS web platform that host the needed data of school emergency planning; the development of E-PreS System; the implementation of disaster drills using E-PreS System in educational premises and local schools; and the evaluation of E-PreS System. Taking into consideration that every disaster drill aims to test and valid school plan and procedures; clarify and train personnel in roles and responsibilities; improve interagency coordination; identify gaps in resources; improve individual performance; and identify opportunities for improvement, E-PreS Project was submitted and approved by the European Commission (EC).

Keywords: disaster drills, earthquake preparedness, E-PreS System, school emergency plans

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18182 Comparison Between Fuzzy and P&O Control for MPPT for Photovoltaic System Using Boost Converter

Authors: M. Doumi, A. Miloudi, A. G. Aissaoui, K. Tahir, C. Belfedal, S. Tahir

Abstract:

The studies on the photovoltaic system are extensively increasing because of a large, secure, essentially exhaustible and broadly available resource as a future energy supply. However, the output power induced in the photovoltaic modules is influenced by an intensity of solar cell radiation, temperature of the solar cells and so on. Therefore, to maximize the efficiency of the photovoltaic system, it is necessary to track the maximum power point of the PV array, for this Maximum Power Point Tracking (MPPT) technique is used. Some MPPT techniques are available in that perturbation and observation (P&O) and Fuzzy logic controller (FLC). The fuzzy control method has been compared with perturb and observe (P&O) method as one of the most widely conventional method used in this area. Both techniques have been analyzed and simulated. MPPT using fuzzy logic shows superior performance and more reliable control with respect to the P&O technique for this application.

Keywords: photovoltaic system, MPPT, perturb and observe, fuzzy logic

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18181 Radiological Hazard Assessments and Control of Radionuclides Emitted from Building Materials in Kuwait Using Expert Systems

Authors: Abdulla Almulla, Wafaa Mahdi

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Building materials can make a significant contribution to the level of natural radioactivity in closed dwelling areas. Therefore, developing an expert system for monitoring the activity concentrations (ACs) of naturally occurring radioactive materials (NORMs) existing in building materials is useful for limiting the population’s exposure to gamma radiation emitted from those materials. The present work not only is aimed at examining the indoor radon concentration emitted by the building materials that are originated from various countries but are commercially available in Kuwait, but also is aimed at developing an expert system for monitoring the radiation emitted from these materials and classifying it as normal (acceptable) or dangerous (unacceptable). This system makes it possible to always monitor any radiological risks to human health. When detecting high doses of radiation, the system gives warning messages.

Keywords: building materials, NORMs, HNBRA, radionuclides, activity concentrations, expert systems

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18180 Increasing Participation of KUD (Rural Unit Cooperative) Through 'Kemal Propuri' System to Independence Farmers

Authors: Ikrima Zaleda Zia, Devi Fitri Kumalasari, Rosita Khusna, Farah Hidayati, Ilham Fajrul Haq, Amin Yusuf Efendi

Abstract:

Fertilizer is one of the production factors that are important to agriculture. Fertilizers contribution to the agricultural sector improvement is quite high. Fertilizers scarcity on the society are giving effect to agricultural sector, that is decreasing farmers production. Through a system called Kemal Propuri, society will be taught how to be independent, especially in terms of supplying the fertilizer and how to earn extra income besides of relying on the agriculture production. This research aims to determine implementation measures of Kemal Propuri in realizing farmers independence. This research was designed to use descriptive research with a qualitative approach. In this case, writers are trying to make an illustration of the increasing role of KUD (rural unit cooperative) through Kemal Propuri system (Independence System Through Individual Fertilizer Production) towards farmer independence. It can be concluded that Kemal Propuri system can contribute in order to achieve farmers independence. Independence fertilizer production will overcome farmers dependence of the subsidized fertilizer from the government.

Keywords: Kemal Propuri, KUD (Rural Unit Cooperative), independence farmers, fertilizer production

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18179 The Coexistence of Quality Practices and Frozen Concept in R and D Projects

Authors: Ayala Kobo-Greenhut, Amos Notea, Izhar Ben-Shlomo

Abstract:

In R&D projects, there is no doubt about the need to change a current concept to an alternative one over time (i.e., concept leaping). Concept leaping is required since with most R&D projects uncertainty is present as they take place in dynamic environments. Despite the importance of concept leaping when needed, R&D teams may fail to do so (i.e., frozen concept). This research suggests a possible reason why frozen concept happens in the framework of quality engineering and control engineering. We suggest that frozen concept occurs since concept determines the derived plan and its implementation may be considered as equivalent to a closed-loop process, and is subject to the problem of not recognizing gaps as failures. We suggest that although implementing quality practices into an R&D project’s routine has many advantages, it intensifies the frozen concept problem since working according to quality practices relates to exploitation of learning behavior, while leaping to a new concept relates to exploring learning behavior.

Keywords: closed loop, control engineering, design, leaping, frozen concept, quality engineering, quality practices

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18178 Cyber-Med: Practical Detection Methodology of Cyber-Attacks Aimed at Medical Devices Eco-Systems

Authors: Nir Nissim, Erez Shalom, Tomer Lancewiki, Yuval Elovici, Yuval Shahar

Abstract:

Background: A Medical Device (MD) is an instrument, machine, implant, or similar device that includes a component intended for the purpose of the diagnosis, cure, treatment, or prevention of disease in humans or animals. Medical devices play increasingly important roles in health services eco-systems, including: (1) Patient Diagnostics and Monitoring; Medical Treatment and Surgery; and Patient Life Support Devices and Stabilizers. MDs are part of the medical device eco-system and are connected to the network, sending vital information to the internal medical information systems of medical centers that manage this data. Wireless components (e.g. Wi-Fi) are often embedded within medical devices, enabling doctors and technicians to control and configure them remotely. All these functionalities, roles, and uses of MDs make them attractive targets of cyber-attacks launched for many malicious goals; this trend is likely to significantly increase over the next several years, with increased awareness regarding MD vulnerabilities, the enhancement of potential attackers’ skills, and expanded use of medical devices. Significance: We propose to develop and implement Cyber-Med, a unique collaborative project of Ben-Gurion University of the Negev and the Clalit Health Services Health Maintenance Organization. Cyber-Med focuses on the development of a comprehensive detection framework that relies on a critical attack repository that we aim to create. Cyber-Med will allow researchers and companies to better understand the vulnerabilities and attacks associated with medical devices as well as providing a comprehensive platform for developing detection solutions. Methodology: The Cyber-Med detection framework will consist of two independent, but complementary detection approaches: one for known attacks, and the other for unknown attacks. These modules incorporate novel ideas and algorithms inspired by our team's domains of expertise, including cyber security, biomedical informatics, and advanced machine learning, and temporal data mining techniques. The establishment and maintenance of Cyber-Med’s up-to-date attack repository will strengthen the capabilities of Cyber-Med’s detection framework. Major Findings: Based on our initial survey, we have already found more than 15 types of vulnerabilities and possible attacks aimed at MDs and their eco-system. Many of these attacks target individual patients who use devices such pacemakers and insulin pumps. In addition, such attacks are also aimed at MDs that are widely used by medical centers such as MRIs, CTs, and dialysis engines; the information systems that store patient information; protocols such as DICOM; standards such as HL7; and medical information systems such as PACS. However, current detection tools, techniques, and solutions generally fail to detect both the known and unknown attacks launched against MDs. Very little research has been conducted in order to protect these devices from cyber-attacks, since most of the development and engineering efforts are aimed at the devices’ core medical functionality, the contribution to patients’ healthcare, and the business aspects associated with the medical device.

Keywords: medical device, cyber security, attack, detection, machine learning

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18177 Development of Management System of the Experience of Defensive Modeling and Simulation by Data Mining Approach

Authors: D. Nam Kim, D. Jin Kim, Jeonghwan Jeon

Abstract:

Defense Defensive Modeling and Simulation (M&S) is a system which enables impracticable training for reducing constraints of time, space and financial resources. The necessity of defensive M&S has been increasing not only for education and training but also virtual fight. Soldiers who are using defensive M&S for education and training will obtain empirical knowledge and know-how. However, the obtained knowledge of individual soldiers have not been managed and utilized yet since the nature of military organizations: confidentiality and frequent change of members. Therefore, this study aims to develop a management system for the experience of defensive M&S based on data mining approach. Since individual empirical knowledge gained through using the defensive M&S is both quantitative and qualitative data, data mining approach is appropriate for dealing with individual empirical knowledge. This research is expected to be helpful for soldiers and military policy makers.

Keywords: data mining, defensive m&s, management system, knowledge management

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18176 Iot-Based Interactive Patient Identification and Safety Management System

Authors: Jonghoon Chun, Insung Kim, Jonghyun Lim, Gun Ro

Abstract:

We believe that it is possible to provide a solution to reduce patient safety accidents by displaying correct medical records and prescription information through interactive patient identification. Our system is based on the use of smart bands worn by patients and these bands communicate with the hybrid gateways which understand both BLE and Wifi communication protocols. Through the convergence of low-power Bluetooth (BLE) and hybrid gateway technology, which is one of short-range wireless communication technologies, we implement ‘Intelligent Patient Identification and Location Tracking System’ to prevent medical malfunction frequently occurring in medical institutions. Based on big data and IOT technology using MongoDB, smart band (BLE, NFC function) and hybrid gateway, we develop a system to enable two-way communication between medical staff and hospitalized patients as well as to store locational information of the patients in minutes. Based on the precise information provided using big data systems, such as location tracking and movement of in-hospital patients wearing smart bands, our findings include the fact that a patient-specific location tracking algorithm can more efficiently operate HIS (Hospital Information System) and other related systems. Through the system, we can always correctly identify patients using identification tags. In addition, the system automatically determines whether the patient is a scheduled for medical service by the system in use at the medical institution, and displays the appropriateness of the medical treatment and the medical information (medical record and prescription information) on the screen and voice. This work was supported in part by the Korea Technology and Information Promotion Agency for SMEs (TIPA) grant funded by the Korean Small and Medium Business Administration (No. S2410390).

Keywords: BLE, hybrid gateway, patient identification, IoT, safety management, smart band

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18175 In the Spirit of Open Educational Resources: Library Resources and Fashion Merchandising

Authors: Lizhu Y. Davis, Gretchen Higginbottom, Vang Vang

Abstract:

This presentation explores the adoption of library resources to engage students in a Visual Merchandising course during the 2016 spring semester. This study was a cross-disciplinary collaboration between the Fashion Merchandising Program and the Madden Library at California State University, Fresno. The goal of the project was to explore and assess the students’ use of library resources as a part of the Affordable Learning Solutions Initiative, a California State University (CSU) Office of the Chancellor Program that enables faculty to choose and provide high-quality, free or low-cost educational materials for their students. Students were interviewed afterwards and the results were generally favorable and provided insight into how students perceive and use library resources to support their research needs. This study reveals an important step in examining how open educational resources impact student learning.

Keywords: collaboration, library resources, open educational resources, visual merchandising

Procedia PDF Downloads 300