Search results for: result-based monitoring and evaluation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8908

Search results for: result-based monitoring and evaluation

8458 Insight-Based Evaluation of a Map-Based Dashboard

Authors: Anna Fredriksson Häägg, Charlotte Weil, Niklas Rönnberg

Abstract:

Map-based dashboards are used for data exploration every day. The present study used an insight-based methodology for evaluating a map-based dashboard that presents research findings of water management and ecosystem services in the Amazon. In addition to analyzing the insights gained from using the dashboard, the evaluation method was compared to standardized questionnaires and task-based evaluations. The result suggests that the dashboard enabled the participants to gain domain-relevant, complex insights regarding the topic presented. Furthermore, the insight-based analysis highlighted unexpected insights and hypotheses regarding causes and potential adaptation strategies for remediation. Although time- and resource-consuming, the insight-based methodology was shown to have the potential of thoroughly analyzing how end users can utilize map-based dashboards for data exploration and decision making. Finally, the insight-based methodology is argued to evaluate tools in scenarios more similar to real-life usage compared to task-based evaluation methods.

Keywords: visual analytics, dashboard, insight-based evaluation, geographic visualization

Procedia PDF Downloads 93
8457 The Application of Distributed Optical Strain Sensing to Measure Rock Bolt Deformation Subject to Bedding Shear

Authors: Thomas P. Roper, Brad Forbes, Jurij Karlovšek

Abstract:

Shear displacement along bedding defects is a well-recognised behaviour when tunnelling and mining in stratified rock. This deformation can affect the durability and integrity of installed rock bolts. In-situ monitoring of rock bolt deformation under bedding shear cannot be accurately derived from traditional strain gauge bolts as sensors are too large and spaced too far apart to accurately assess concentrated displacement along discrete defects. A possible solution to this is the use of fiber optic technologies developed for precision monitoring. Distributed Optic Sensor (DOS) embedded rock bolts were installed in a tunnel project with the aim of measuring the bolt deformation profile under significant shear displacements. This technology successfully measured the 3D strain distribution along the bolts when subjected to bedding shear and resolved the axial and lateral strain constituents in order to determine the deformational geometry of the bolts. The results are compared well with the current visual method for monitoring shear displacement using borescope holes, considering this method as suitable.

Keywords: distributed optical strain sensing, rock bolt, bedding shear, sandstone tunnel

Procedia PDF Downloads 137
8456 Evaluation of External Costs of Traffic Accident in Slovak Republic

Authors: Anna Dolinayova, Jozef Danis, Juraj Camaj

Abstract:

The report deals with comparison of traffic accidents in Slovak republic in road and rail transport since year 2009 until 2014, with evaluation of external costs and consequently with the possibilities of their internalization. The results of road traffic accidents analysis are realized in line with after-effects they have caused; in line with main cause, place of origin (within or out of town) and in accordance to age of people they were killed or hard, eventually easy injured in traffic accidents. Evaluation of individual after-effects is carried in terms of probability of traffic accidents occurrence.

Keywords: external costs, traffic accident, rail transport, road transport

Procedia PDF Downloads 563
8455 Performance Evaluation of Acoustic-Spectrographic Voice Identification Method in Native and Non-Native Speech

Authors: E. Krasnova, E. Bulgakova, V. Shchemelinin

Abstract:

The paper deals with acoustic-spectrographic voice identification method in terms of its performance in non-native language speech. Performance evaluation is conducted by comparing the result of the analysis of recordings containing native language speech with recordings that contain foreign language speech. Our research is based on Tajik and Russian speech of Tajik native speakers due to the character of the criminal situation with drug trafficking. We propose a pilot experiment that represents a primary attempt enter the field.

Keywords: speaker identification, acoustic-spectrographic method, non-native speech, performance evaluation

Procedia PDF Downloads 423
8454 Imputation of Incomplete Large-Scale Monitoring Count Data via Penalized Estimation

Authors: Mohamed Dakki, Genevieve Robin, Marie Suet, Abdeljebbar Qninba, Mohamed A. El Agbani, Asmâa Ouassou, Rhimou El Hamoumi, Hichem Azafzaf, Sami Rebah, Claudia Feltrup-Azafzaf, Nafouel Hamouda, Wed a.L. Ibrahim, Hosni H. Asran, Amr A. Elhady, Haitham Ibrahim, Khaled Etayeb, Essam Bouras, Almokhtar Saied, Ashrof Glidan, Bakar M. Habib, Mohamed S. Sayoud, Nadjiba Bendjedda, Laura Dami, Clemence Deschamps, Elie Gaget, Jean-Yves Mondain-Monval, Pierre Defos Du Rau

Abstract:

In biodiversity monitoring, large datasets are becoming more and more widely available and are increasingly used globally to estimate species trends and con- servation status. These large-scale datasets challenge existing statistical analysis methods, many of which are not adapted to their size, incompleteness and heterogeneity. The development of scalable methods to impute missing data in incomplete large-scale monitoring datasets is crucial to balance sampling in time or space and thus better inform conservation policies. We developed a new method based on penalized Poisson models to impute and analyse incomplete monitoring data in a large-scale framework. The method al- lows parameterization of (a) space and time factors, (b) the main effects of predic- tor covariates, as well as (c) space–time interactions. It also benefits from robust statistical and computational capability in large-scale settings. The method was tested extensively on both simulated and real-life waterbird data, with the findings revealing that it outperforms six existing methods in terms of missing data imputation errors. Applying the method to 16 waterbird species, we estimated their long-term trends for the first time at the entire North African scale, a region where monitoring data suffer from many gaps in space and time series. This new approach opens promising perspectives to increase the accuracy of species-abundance trend estimations. We made it freely available in the r package ‘lori’ (https://CRAN.R-project.org/package=lori) and recommend its use for large- scale count data, particularly in citizen science monitoring programmes.

Keywords: biodiversity monitoring, high-dimensional statistics, incomplete count data, missing data imputation, waterbird trends in North-Africa

Procedia PDF Downloads 124
8453 Development of a Spatial Data for Renal Registry in Nigeria Health Sector

Authors: Adekunle Kolawole Ojo, Idowu Peter Adebayo, Egwuche Sylvester O.

Abstract:

Chronic Kidney Disease (CKD) is a significant cause of morbidity and mortality across developed and developing nations and is associated with increased risk. There are no existing electronic means of capturing and monitoring CKD in Nigeria. The work is aimed at developing a spatial data model that can be used to implement renal registries required for tracking and monitoring the spatial distribution of renal diseases by public health officers and patients. In this study, we have developed a spatial data model for a functional renal registry.

Keywords: renal registry, health informatics, chronic kidney disease, interface

Procedia PDF Downloads 168
8452 Usability Evaluation of a Self-Report Mobile App for COVID-19 Symptoms: Supporting Health Monitoring in the Work Context

Authors: Kevin Montanez, Patricia Garcia

Abstract:

The confinement and restrictions adopted to avoid an exponential spread of the COVID-19 have negatively impacted the Peruvian economy. In this context, Industries offering essential products could continue operating, but they have to follow safety protocols and implement strategies to ensure employee health. In view of the increasing internet access and mobile phone ownership, “Alerta Temprana”, a mobile app, was developed to self-report COVID-19 symptoms in the work context. In this study, the usability of the mobile app “Alerta Temprana” was evaluated from the perspective of health monitors and workers. In addition to reporting the metrics related to the usability of the application, the utility of the system is also evaluated from the monitors' perspective. In this descriptive study, the participants used the mobile app for two months. Afterwards, System Usability Scale (SUS) questionnaire was answered by the workers and monitors. A Usefulness questionnaire with open questions was also used for the monitors. The data related to the use of the application was collected during one month. Furthermore, descriptive statistics and bivariate analysis were used. The workers rated the application as good (70.39). In the case of the monitors, usability was excellent (83.0). The most important feature for the monitors were the emails generated by the application. The average interaction per user was 30 seconds and a total of 6172 self-reports were sent. Finally, a statistically significant association was found between the acceptability scale and the work area. The results of this study suggest that Alerta Temprana has the potential to be used for surveillance and health monitoring in any context of face-to-face modality. Participants reported a high degree of ease of use. However, from the perspective of workers, SUS cannot diagnose usability issues and we suggest we use another standard usability questionnaire to improve "Alerta Temprana" for future use.

Keywords: public health in informatics, mobile app, usability, self-report

Procedia PDF Downloads 87
8451 Developing a Web-Based Tender Evaluation System Based on Fuzzy Multi-Attributes Group Decision Making for Nigerian Public Sector Tendering

Authors: Bello Abdullahi, Yahaya M. Ibrahim, Ahmed D. Ibrahim, Kabir Bala

Abstract:

Public sector tendering has traditionally been conducted using manual paper-based processes which are known to be inefficient, less transparent and more prone to manipulations and errors. The advent of the Internet and the World Wide Web has led to the development of numerous e-Tendering systems that addressed some of the problems associated with the manual paper-based tendering system. However, most of these systems rarely support the evaluation of tenders and where they do it is mostly based on the single decision maker which is not suitable in public sector tendering, where for the sake of objectivity, transparency, and fairness, it is required that the evaluation is conducted through a tender evaluation committee. Currently, in Nigeria, the public tendering process in general and the evaluation of tenders, in particular, are largely conducted using manual paper-based processes. Automating these manual-based processes to digital-based processes can help in enhancing the proficiency of public sector tendering in Nigeria. This paper is part of a larger study to develop an electronic tendering system that supports the whole tendering lifecycle based on Nigerian procurement law. Specifically, this paper presents the design and implementation of part of the system that supports group evaluation of tenders based on a technique called fuzzy multi-attributes group decision making. The system was developed using Object-Oriented methodologies and Unified Modelling Language and hypothetically applied in the evaluation of technical and financial proposals submitted by bidders. The system was validated by professionals with extensive experiences in public sector procurement. The results of the validation showed that the system called NPS-eTender has an average rating of 74% with respect to correct and accurate modelling of the existing manual tendering domain and an average rating of 67.6% with respect to its potential to enhance the proficiency of public sector tendering in Nigeria. Thus, based on the results of the validation, the automation of the evaluation process to support tender evaluation committee is achievable and can lead to a more proficient public sector tendering system.

Keywords: e-Tendering, e-Procurement, group decision making, tender evaluation, tender evaluation committee, UML, object-oriented methodologies, system development

Procedia PDF Downloads 239
8450 Design and Implementation a Platform for Adaptive Online Learning Based on Fuzzy Logic

Authors: Budoor Al Abid

Abstract:

Educational systems are increasingly provided as open online services, providing guidance and support for individual learners. To adapt the learning systems, a proper evaluation must be made. This paper builds the evaluation model Fuzzy C Means Adaptive System (FCMAS) based on data mining techniques to assess the difficulty of the questions. The following steps are implemented; first using a dataset from an online international learning system called (slepemapy.cz) the dataset contains over 1300000 records with 9 features for students, questions and answers information with feedback evaluation. Next, a normalization process as preprocessing step was applied. Then FCM clustering algorithms are used to adaptive the difficulty of the questions. The result is three cluster labeled data depending on the higher Wight (easy, Intermediate, difficult). The FCM algorithm gives a label to all the questions one by one. Then Random Forest (RF) Classifier model is constructed on the clustered dataset uses 70% of the dataset for training and 30% for testing; the result of the model is a 99.9% accuracy rate. This approach improves the Adaptive E-learning system because it depends on the student behavior and gives accurate results in the evaluation process more than the evaluation system that depends on feedback only.

Keywords: machine learning, adaptive, fuzzy logic, data mining

Procedia PDF Downloads 168
8449 RFID Logistic Management with Cold Chain Monitoring: Cold Store Case Study

Authors: Mira Trebar

Abstract:

Logistics processes of perishable food in the supply chain include the distribution activities and the real time temperature monitoring to fulfil the cold chain requirements. The paper presents the use of RFID (Radio Frequency Identification) technology as an identification tool of receiving and shipping activities in the cold store. At the same time, the use of RFID data loggers with temperature sensors is presented to observe and store the temperatures for the purpose of analyzing the processes and having the history data available for traceability purposes and efficient recall management.

Keywords: logistics, warehouse, RFID device, cold chain

Procedia PDF Downloads 599
8448 Proposal Evaluation of Critical Success Factors (CSF) in Lean Manufacturing Projects

Authors: Guilherme Gorgulho, Carlos Roberto Camello Lima

Abstract:

Critical success factors (CSF) are used to design the practice of project management that can lead directly or indirectly to the success of the project. This management includes many elements that have to be synchronized in order to ensure the project on-time delivery, quality and the lowest possible cost. The objective of this work is to develop a proposal for evaluation of the FCS in lean manufacturing projects, and apply the evaluation in a pilot project. The results show that the use of continuous improvement programs in organizations brings benefits as the process cost reduction and improve productivity.

Keywords: continuous improvement, critical success factors (csf), lean thinking, project management

Procedia PDF Downloads 336
8447 Geoinformation Technology of Agricultural Monitoring Using Multi-Temporal Satellite Imagery

Authors: Olena Kavats, Dmitry Khramov, Kateryna Sergieieva, Vladimir Vasyliev, Iurii Kavats

Abstract:

Geoinformation technologies of space agromonitoring are a means of operative decision making support in the tasks of managing the agricultural sector of the economy. Existing technologies use satellite images in the optical range of electromagnetic spectrum. Time series of optical images often contain gaps due to the presence of clouds and haze. A geoinformation technology is created. It allows to fill gaps in time series of optical images (Sentinel-2, Landsat-8, PROBA-V, MODIS) with radar survey data (Sentinel-1) and use information about agrometeorological conditions of the growing season for individual monitoring years. The technology allows to perform crop classification and mapping for spring-summer (winter and spring crops) and autumn-winter (winter crops) periods of vegetation, monitoring the dynamics of crop state seasonal changes, crop yield forecasting. Crop classification is based on supervised classification algorithms, takes into account the peculiarities of crop growth at different vegetation stages (dates of sowing, emergence, active vegetation, and harvesting) and agriculture land state characteristics (row spacing, seedling density, etc.). A catalog of samples of the main agricultural crops (Ukraine) is created and crop spectral signatures are calculated with the preliminary removal of row spacing, cloud cover, and cloud shadows in order to construct time series of crop growth characteristics. The obtained data is used in grain crop growth tracking and in timely detection of growth trends deviations from reference samples of a given crop for a selected date. Statistical models of crop yield forecast are created in the forms of linear and nonlinear interconnections between crop yield indicators and crop state characteristics (temperature, precipitation, vegetation indices, etc.). Predicted values of grain crop yield are evaluated with an accuracy up to 95%. The developed technology was used for agricultural areas monitoring in a number of Great Britain and Ukraine regions using EOS Crop Monitoring Platform (https://crop-monitoring.eos.com). The obtained results allow to conclude that joint use of Sentinel-1 and Sentinel-2 images improve separation of winter crops (rapeseed, wheat, barley) in the early stages of vegetation (October-December). It allows to separate successfully the soybean, corn, and sunflower sowing areas that are quite similar in their spectral characteristics.

Keywords: geoinformation technology, crop classification, crop yield prediction, agricultural monitoring, EOS Crop Monitoring Platform

Procedia PDF Downloads 417
8446 Multi-Agent Approach for Monitoring and Control of Biotechnological Processes

Authors: Ivanka Valova

Abstract:

This paper is aimed at using a multi-agent approach to monitor and diagnose a biotechnological system in order to validate certain control actions depending on the process development and the operating conditions. A multi-agent system is defined as a network of interacting software modules that collectively solve complex tasks. Remote monitoring and control of biotechnological processes is a necessity when automated and reliable systems operating with no interruption of certain activities are required. The advantage of our approach is in its flexibility, modularity and the possibility of improving by acquiring functionalities through the integration of artificial intelligence.

Keywords: multi-agent approach, artificial intelligence, biotechnological processes, anaerobic biodegradation

Procedia PDF Downloads 41
8445 A Long Range Wide Area Network-Based Smart Pest Monitoring System

Authors: Yun-Chung Yu, Yan-Wen Wang, Min-Sheng Liao, Joe-Air Jiang, Yuen-Chung Lee

Abstract:

This paper proposes to use a Long Range Wide Area Network (LoRaWAN) for a smart pest monitoring system which aims at the oriental fruit fly (Bactrocera dorsalis) to improve the communication efficiency of the system. The oriental fruit fly is one of the main pests in Southeast Asia and the Pacific Rim. Different smart pest monitoring systems based on the Internet of Things (IoT) architecture have been developed to solve problems of employing manual measurement. These systems often use Octopus II, a communication module following the 2.4GHz IEEE 802.15.4 ZigBee specification, as sensor nodes. The Octopus II is commonly used in low-power and short-distance communication. However, the energy consumption increase as the logical topology becomes more complicate to have enough coverage in the large area. By comparison, LoRaWAN follows the Low Power Wide Area Network (LPWAN) specification, which targets the key requirements of the IoT technology, such as secure bi-directional communication, mobility, and localization services. The LoRaWAN network has advantages of long range communication, high stability, and low energy consumption. The 433MHz LoRaWAN model has two superiorities over the 2.4GHz ZigBee model: greater diffraction and less interference. In this paper, The Octopus II module is replaced by a LoRa model to increase the coverage of the monitoring system, improve the communication performance, and prolong the network lifetime. The performance of the LoRa-based system is compared with a ZigBee-based system using three indexes: the packet receiving rate, delay time, and energy consumption, and the experiments are done in different settings (e.g. distances and environmental conditions). In the distance experiment, a pest monitoring system using the two communication specifications is deployed in an area with various obstacles, such as buildings and living creatures, and the performance of employing the two communication specifications is examined. The experiment results show that the packet receiving the rate of the LoRa-based system is 96% , which is much higher than that of the ZigBee system when the distance between any two modules is about 500m. These results indicate the capability of a LoRaWAN-based monitoring system in long range transmission and ensure the stability of the system.

Keywords: LoRaWan, oriental fruit fly, IoT, Octopus II

Procedia PDF Downloads 327
8444 Protecting the Health of Astronauts: Enhancing Occupational Health Monitoring and Surveillance for Former NASA Astronauts to Understand Long-Term Outcomes of Spaceflight-Related Exposures

Authors: Meredith Rossi, Lesley Lee, Mary Wear, Mary Van Baalen, Bradley Rhodes

Abstract:

The astronaut community is unique, and may be disproportionately exposed to occupational hazards not commonly seen in other communities. The extent to which the demands of the astronaut occupation and exposure to spaceflight-related hazards affect the health of the astronaut population over the life course is not completely known. A better understanding of the individual, population, and mission impacts of astronaut occupational exposures is critical to providing clinical care, targeting occupational surveillance efforts, and planning for future space exploration. The ability to characterize the risk of latent health conditions is a significant component of this understanding. Provision of health screening services to active and former astronauts ensures individual, mission, and community health and safety. Currently, the NASA-Johnson Space Center (JSC) Flight Medicine Clinic (FMC) provides extensive medical monitoring to active astronauts throughout their careers. Upon retirement, astronauts may voluntarily return to the JSC FMC for an annual preventive exam. However, current retiree monitoring includes only selected screening tests, representing an opportunity for augmentation. The potential long-term health effects of spaceflight demand an expanded framework of testing for former astronauts. The need is two-fold: screening tests widely recommended for other aging populations are necessary to rule out conditions resulting from the natural aging process (e.g., colonoscopy, mammography); and expanded monitoring will increase NASA’s ability to better characterize conditions resulting from astronaut occupational exposures. To meet this need, NASA has begun an extensive exploration of the overall approach, cost, and policy implications of expanding the medical monitoring of former NASA astronauts under the Astronaut Occupational Health program. Increasing the breadth of monitoring services will ultimately enrich the existing evidence base of occupational health risks to astronauts. Such an expansion would therefore improve the understanding of the health of the astronaut population as a whole, and the ability to identify, mitigate, and manage such risks in preparation for deep space exploration missions.

Keywords: astronaut, long-term health, NASA, occupational health, surveillance

Procedia PDF Downloads 506
8443 Model of a Context-Aware Middleware for Mobile Workers

Authors: Esraa Moustafa, Gaetan Rey, Stephane Lavirotte, Jean-Yves Tigli

Abstract:

With the development of Internet of Things and Web of Things, computing becomes more pervasive, invisible and present everywhere. In fact, in our environment, we are surrounded by multiple devices that deliver (web) services that meet the needs of the users. However, the mobility of these devices as the users has important repercussions that challenge software design of these applications because the variability of the environment cannot be anticipated at the design time. Thus, it will be interesting to dynamically discover the environment and adapt the application during its execution to the new contextual conditions. We, therefore, propose a model of a context-aware middleware that can address this issue through a monitoring service that is capable of reasoning and observation channels capable of calculating the context during the runtime. The monitoring service evaluates the pre-defined X-Query predicates in the context manager and uses Prolog to deduce the services needed to respond back. An independent Observation Channel for each different predicate is then dynamically generated by the monitoring service depending on the current state of the environment. Each channel sends its result directly to the context manager which consequently calculates the context based on all the predicates’ results while preserving the reactivity of the self-adaptive system.

Keywords: auto-adaptation, context-awareness, middleware, reasoning engine

Procedia PDF Downloads 226
8442 An Audit on Tracheal Tube Cuff Pressure Check and Monitoring during Current Practice

Authors: Mahmoud Hassanin, Roshan Thawale, Kiran Yelamati

Abstract:

Background: During current practice, intraoperative regular endotracheal cuff pressure monitoring is not routine, despite the significant number of clinicians interested in checking it after intubation to ensure a good seal and adequate ventilation. Aims and objectives: to highlight that the current practice has no guidance related to regular intra-operative monitoring of the endotracheal tube cuff pressure, which can improve patient safety and post-operative experience. Methods: local department survey was done targeting anaesthetists' current practice, measuring their knowledge and problem awareness to improve patient satisfaction and change the current approach. Results: The participants were not using the manometer, despite their interest in ensuring that the cuff pressure was high enough and there was a proper seal. More than 50% of the participant don't know the ideal range of the endotracheal tube cuff pressure range, and 32% don't know whether it is available or not in the theatre. Despite the previous finding, 100% of the participants used different methods to ensure adequate cuff pressure. The collected data revealed that at least 26% of the participant confirmed that they had seen patients having post-intubation complications. Conclusion: There is an increasing importance placed on quality assurance. Clinical practice varies widely among practitioners, with the only consistency being the omission of cuff manometers during routine intra-operative management, despite their proven benefit and efficacy. Encourage the anaesthetists and ODPs to use cuff pressure manometers. The availability of portable pressure manometers can help to maintain safe cuff pressures in patients requiring endotracheal intubation.

Keywords: endotracheal cuff pressure, intra-operative monitoring, current practice, patient satisfaction

Procedia PDF Downloads 86
8441 Development and Usability Assessment of a Connected Resistance Exercise Band Application for Strength-Monitoring

Authors: J. A. Batsis, G. G. Boateng, L. M. Seo, C. L. Petersen, K. L. Fortuna, E. V. Wechsler, R. J. Peterson, S. B. Cook, D. Pidgeon, R. S. Dokko, R. J. Halter, D. F. Kotz

Abstract:

Resistance exercise bands are a core component of any physical activity strengthening program. Strength training can mitigate the development of sarcopenia, the loss of muscle mass or strength and function with aging. Yet, the adherence of such behavioral exercise strategies in a home-based setting are fraught with issues of monitoring and compliance. Our group developed a Bluetooth-enabled resistance exercise band capable of transmitting data to an open-source platform. In this work, we developed an application to capture this information in real-time, and conducted three usability studies in two mixed-aged groups of participants (n=6 each) and a group of older adults with obesity participating in a weight-loss intervention (n=20). The system was favorable, acceptable and provided iterative information that could assist in future deployment on ubiquitous platforms. Our formative work provides the foundation to deliver home-based monitoring interventions in a high-risk, older adult population.

Keywords: application, mHealth, older adult, resistance exercise band, sarcopenia

Procedia PDF Downloads 150
8440 Ecotoxicity Evaluation and Suggestion of Remediation Method of ZnO Nanoparticles in Aqueous Phase

Authors: Hyunsang Kim, Younghun Kim, Younghee Kim, Sangku Lee

Abstract:

We investigated ecotoxicity and performed an experiment for removing ZnO nanoparticles in water. Short-term exposure of hatching test using fertilized eggs (O. latipes) showed deformity in 5 ppm of ZnO nanoparticles solution, and in 10ppm ZnO nanoparticles solution delayed hatching was observed. Herein, chemical precipitation method was suggested for removing ZnO nanoparticles in water. The precipitated ZnO nanoparticles showed the form of ZnS after addition of Na2S, and the form of Zn3(PO4)2 for Na2HPO4. The removal efficiency of ZnO nanoparticles in water was closed to 100% for two case. In ecotoxicity evaluation of as-precipitated ZnS and Zn3(PO4)2, they did not cause any acute toxicity for D. magna. It is noted that this precipitation treatment of ZnO is effective to reduce the potential cytotoxicity.

Keywords: ZnO nanopraticles, ZnS, Zn3(PO4)2, ecotoxicity evaluation, chemical precipitation

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8439 The Implementation of Teaching and Learning Quality Assurance System at the Chaoyang University of Technology for Academic Year 2013-2015

Authors: Ting Hsiang Chang

Abstract:

Nowadays in Taiwan, higher education, which was previously more emphasized on teaching-oriented approaches, has gradually shifted to an approach more focusing on students learning outcomes. With student employment rate as an important indicator for University Program Evaluation periodically held by the Ministry of Education, it becomes extremely critical for a university to build up a teaching and learning quality assurance system to bridge the gap between learning and practice. Teaching and Learning Quality Assurance System has been built and implemented at Chaoyang University of Technology for years and has received substantial results. By employing various forms of evaluation and performance appraisals, the effectiveness of teaching and learning can consistently be tracked as a means of ensuring teaching and learning quality. This study aims to explore the evaluation system of teaching and learning quality assurance system at the Chaoyang University of Technology by means of content analysis. The study contents the evaluation reports on the teaching and learning quality assurance at the Chaoyang University of Technology in the Academic Year 2013-2015. The quantitative results of the assessment were analyzed using the five-point Likert Scale. Quality assurance Committee meetings were further held for examining and discussions on the results. To the end, the annual evaluation report is to be produced as references used to improve approaches in both teaching and learning. The findings indicate that there is a respective relationship between the overall teaching evaluation items and the teaching goals and core competencies. In addition, graduates’ feedbacks were also collected for further analysis to examine if the current educational planning is able to achieve the university’s teaching goal and cultivation of core competencies.

Keywords: core competencies, teaching and learning quality assurance system, teaching goals, university program evaluation

Procedia PDF Downloads 269
8438 Evaluation Using a Bidirectional Microphone as a Pressure Pulse Wave Meter

Authors: Shunsuke Fujiwara, Takashi Kaburagi, Kazuyuki Kobayashi, Kajiro Watanabe, Yosuke Kurihara

Abstract:

This paper describes a novel sensor device, a pressure pulse wave meter, which uses a bidirectional condenser microphone. The microphone work as a microphone as well as a sensor with high gain over a wide frequency range; they are also highly reliable and economical. Currently aging is becoming a serious social issue in Japan causing increased medical expenses in the country. Hence, it is important for elderly citizens to check health condition at home, and to care the health conditions through daily monitoring. Given this circumstances, we developed a novel pressure pulse wave meter based on a bidirectional condenser microphone. This novel pressure pulse wave meter device is used as a measuring instrument of health conditions.

Keywords: bidirectional microphone, pressure pulse wave meter, health condition, novel sensor device

Procedia PDF Downloads 525
8437 An Intelligent Nondestructive Testing System of Ultrasonic Infrared Thermal Imaging Based on Embedded Linux

Authors: Hao Mi, Ming Yang, Tian-yue Yang

Abstract:

Ultrasonic infrared nondestructive testing is a kind of testing method with high speed, accuracy and localization. However, there are still some problems, such as the detection requires manual real-time field judgment, the methods of result storage and viewing are still primitive. An intelligent non-destructive detection system based on embedded linux is put forward in this paper. The hardware part of the detection system is based on the ARM (Advanced Reduced Instruction Set Computer Machine) core and an embedded linux system is built to realize image processing and defect detection of thermal images. The CLAHE algorithm and the Butterworth filter are used to process the thermal image, and then the boa server and CGI (Common Gateway Interface) technology are used to transmit the test results to the display terminal through the network for real-time monitoring and remote monitoring. The system also liberates labor and eliminates the obstacle of manual judgment. According to the experiment result, the system provides a convenient and quick solution for industrial non-destructive testing.

Keywords: remote monitoring, non-destructive testing, embedded Linux system, image processing

Procedia PDF Downloads 195
8436 Data Integration with Geographic Information System Tools for Rural Environmental Monitoring

Authors: Tamas Jancso, Andrea Podor, Eva Nagyne Hajnal, Peter Udvardy, Gabor Nagy, Attila Varga, Meng Qingyan

Abstract:

The paper deals with the conditions and circumstances of integration of remotely sensed data for rural environmental monitoring purposes. The main task is to make decisions during the integration process when we have data sources with different resolution, location, spectral channels, and dimension. In order to have exact knowledge about the integration and data fusion possibilities, it is necessary to know the properties (metadata) that characterize the data. The paper explains the joining of these data sources using their attribute data through a sample project. The resulted product will be used for rural environmental analysis.

Keywords: remote sensing, GIS, metadata, integration, environmental analysis

Procedia PDF Downloads 96
8435 Invisible to Invaluable - How Social Media is Helping Tackle Stigma and Discrimination Against Informal Waste Pickers of Bengaluru

Authors: Varinder Kaur Gambhir, Neema Gupta, Sonal Tickoo Chaudhuri

Abstract:

Bengaluru, a rapidly growing metropolis in India, with a population of 12.5 million citizens, generates 5,757 metric tonnes of solid waste per day. Despite their invaluable contribution to waste management, society and the economy, waste pickers face significant stigma, suspicion and contempt and are left with a sense of shame about their work. In this context, BBC Media Action was funded by the H&M Foundation to develop a 3-year multi-phase social media campaign to shift perceptions of waste picking and informal waste pickers amongst the Bengaluru population. Research has been used to inform project strategy and adaptation, at all stages. Formative research to inform campaign strategy used mixed methods– 14 focused group discussions followed by 406 online surveys – to explore people’s knowledge of, and attitudes towards waste pickers, and identify potential barriers and motivators to changing perceptions. Use of qualitative techniques like metaphor maps (using bank of pictures rather than direct questions to understand mindsets) helped establish the invisibility of informal waste pickers, and the quantitative research enabled audience segmentation based on attitudes towards informal waste pickers. To pretest the campaign idea, eight I-GDs (individual interaction followed by group discussions) were conducted to allow interviewees to first freely express their feelings individually, before discussing in a group. Robert Plucthik’s ‘wheel of emotions’ was used to understand audience’s emotional response to the content. A robust monitoring and evaluation is being conducted (baseline and first phase of monitoring already completed) using a rotating longitudinal panel of 1,800 social media users (exposed and unexposed to the campaign), recruited face to face and representative of the social media universe of Bengaluru city. In addition, qualitative in-depth interviews are being conducted after each phase to better understand change drivers. The research methodology and ethical protocols for impact evaluation have been independently reviewed by an Institutional Review Board. Formative research revealed that while waste on the streets is visible and is of concern to the public, informal waste pickers are virtually ‘invisible’, for most people in Bengaluru Pretesting research revealed that the creative outputs evoked emotions like acceptance and gratitude towards waste-pickers, suggesting that the content had the potential to encourage attitudinal change. After the first phase of campaign, social media analytics show that #Invaluables content reached at least 2.6 million unique people (21% of the Bengaluru population) through Facebook and Instagram. Further, impact monitoring results show significant improvements in spontaneous awareness of different segments of informal waste pickers ( such as sorters at scrap shops or dry waste collection centres -from 10% at baseline to 16% amongst exposed and no change amongst unexposed), recognition that informal waste pickers help the environment (71% at baseline to 77% among exposed and no change among unexposed) and greater discussion about informal waste pickers among those exposed (60%) as against not exposed (49%). Using the insights from this research, the planned social media intervention is designed to increase the visibility of and appreciation for the work of waste pickers in Bengaluru, supporting a more inclusive society.

Keywords: awareness, discussion, discrimination, informal waste pickers, invisibility, social media campaign, waste management

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8434 Human Tracking across Heterogeneous Systems Based on Mobile Agent Technologies

Authors: Tappei Yotsumoto, Atsushi Nomura, Kozo Tanigawa, Kenichi Takahashi, Takao Kawamura, Kazunori Sugahara

Abstract:

In a human tracking system, expanding a monitoring range of one system is complicating the management of devices and increasing its cost. Therefore, we propose a method to realize a wide-range human tracking by connecting small systems. In this paper, we examined an agent deploy method and information contents across the heterogeneous human tracking systems. By implementing the proposed method, we can construct a human tracking system across heterogeneous systems, and the system can track a target continuously between systems.

Keywords: human tracking system, mobile agent, monitoring, heterogeneous systems

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8433 Research on Sensing Performance of Polyimide-Based Composite Materials

Authors: Rui Zhao, Dongxu Zhang, Min Wan

Abstract:

Composite materials are widely used in the fields of aviation, aerospace, and transportation due to their lightweight and high strength. Functionalization of composite structures is a hot topic in the future development of composite materials. This article proposed a polyimide-resin based composite material with a sensing function. This material can serve as a sensor to achieve deformation monitoring of metal sheets in room temperature environments. In the deformation process of metal sheets, the slope of the linear fitting line for the corresponding material resistance change rate is different in the elastic stage and the plastic strengthening stage. Therefore, the slope of the material resistance change rate can be used to characterize the deformation stage of the metal sheet. In addition, the resistance change rate of the material exhibited a good negative linear relationship with temperature in a high-temperature environment, and the determination coefficient of the linear fitting line for the change rate of material resistance in the range of 520-650℃ was 0.99. These results indicate that the material has the potential to be applied in the monitoring of mechanical properties of structural materials and temperature monitoring of high-temperature environments.

Keywords: polyimide, composite, sensing, resistance change rate

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8432 Using Reservoir Models for Monitoring Geothermal Surface Features

Authors: John P. O’Sullivan, Thomas M. P. Ratouis, Michael J. O’Sullivan

Abstract:

As the use of geothermal energy grows internationally more effort is required to monitor and protect areas with rare and important geothermal surface features. A number of approaches are presented for developing and calibrating numerical geothermal reservoir models that are capable of accurately representing geothermal surface features. The approaches are discussed in the context of cases studies of the Rotorua geothermal system and the Orakei-korako geothermal system, both of which contain important surface features. The results show that models are able to match the available field data accurately and hence can be used as valuable tools for predicting the future response of the systems to changes in use.

Keywords: geothermal reservoir models, surface features, monitoring, TOUGH2

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8431 Development of Multifunctional Yarns and Fabrics for Interactive Textiles

Authors: Muhammad Bilal Qadir, Danish Umer, Amir Shahzad

Abstract:

The use of conductive materials in smart and interactive textiles is gaining significant importance for creating value addition, innovation, and functional product development. These products find their potential applications in health monitoring, military, protection, communication, sensing, monitoring, actuation, fashion, and lifestyles. The materials which are most commonly employed in such type of interactive textile include intrinsically conducting polymers, conductive inks, and metallic coating on textile fabrics and inherently conducting metallic fibre yarns. In this study, silver coated polyester filament yarn is explored for the development of multifunctional interactive gloves. The composite yarn was developed by covering the silver coated polyester filament around the polyester spun yarn using hollow spindle technique. The electrical and tensile properties of the yarn were studied. This novel yarn was used to manufacture a smart glove to explore the antibacterial, functional, and interactive properties of the yarn. The change in electrical resistance due to finger movement at different bending positions and antimicrobial properties were studied. This glove was also found useful as an interactive tool to operate the commonly used touch screen devices due to its conductive nature. The yarn can also be used to develop the sensing elements like stretch, strain, and piezoresistive sensors. Such sensor can be effectively used in medical and sports textile for performance monitoring, vital signs monitoring and development of antibacterial textile for healthcare and hygiene.

Keywords: conductive yarn, interactive textiles, piezoresistive sensors, smart gloves

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8430 Experimental Evaluation of UDP in Wireless LAN

Authors: Omar Imhemed Alramli

Abstract:

As Transmission Control Protocol (TCP), User Datagram Protocol (UDP) is transfer protocol in the transportation layer in Open Systems Interconnection model (OSI model) or in TCP/IP model of networks. The UDP aspects evaluation were not recognized by using the pcattcp tool on the windows operating system platform like TCP. The study has been carried out to find a tool which supports UDP aspects evolution. After the information collection about different tools, iperf tool was chosen and implemented on Cygwin tool which is installed on both Windows XP platform and also on Windows XP on virtual box machine on one computer only. Iperf is used to make experimental evaluation of UDP and to see what will happen during the sending the packets between the Host and Guest in wired and wireless networks. Many test scenarios have been done and the major UDP aspects such as jitter, packet losses, and throughput are evaluated.

Keywords: TCP, UDP, IPERF, wireless LAN

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8429 Lung HRCT Pattern Classification for Cystic Fibrosis Using a Convolutional Neural Network

Authors: Parisa Mansour

Abstract:

Cystic fibrosis (CF) is one of the most common autosomal recessive diseases among whites. It mostly affects the lungs, causing infections and inflammation that account for 90% of deaths in CF patients. Because of this high variability in clinical presentation and organ involvement, investigating treatment responses and evaluating lung changes over time is critical to preventing CF progression. High-resolution computed tomography (HRCT) greatly facilitates the assessment of lung disease progression in CF patients. Recently, artificial intelligence was used to analyze chest CT scans of CF patients. In this paper, we propose a convolutional neural network (CNN) approach to classify CF lung patterns in HRCT images. The proposed network consists of two convolutional layers with 3 × 3 kernels and maximally connected in each layer, followed by two dense layers with 1024 and 10 neurons, respectively. The softmax layer prepares a predicted output probability distribution between classes. This layer has three exits corresponding to the categories of normal (healthy), bronchitis and inflammation. To train and evaluate the network, we constructed a patch-based dataset extracted from more than 1100 lung HRCT slices obtained from 45 CF patients. Comparative evaluation showed the effectiveness of the proposed CNN compared to its close peers. Classification accuracy, average sensitivity and specificity of 93.64%, 93.47% and 96.61% were achieved, indicating the potential of CNNs in analyzing lung CF patterns and monitoring lung health. In addition, the visual features extracted by our proposed method can be useful for automatic measurement and finally evaluation of the severity of CF patterns in lung HRCT images.

Keywords: HRCT, CF, cystic fibrosis, chest CT, artificial intelligence

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