Pub Date : 2019-11-14DOI: 10.1109/SCORED.2019.8896240
A. Mahmoud, A. A. Hssain, Guillaume Alinier, I. Hassan, U. Khurshid, Aiman Abducarim, S. Mahmud, Omrane Abdallah, Elshaikh Mohamed, A. Alsalemi, F. Bensaali, A. Amira
Extracorporeal Membrane Oxygenation (ECMO) is a highly complex/critical lifesaving procedure known to support patients with cardiac and respiratory issues. Patients on ECMO are monitored 24/7 by a team of highly trained ECMO team comprising nurses, physicians, respiratory therapists, and perfusionists promptly intervening to any potential emergency situation. Simulation-Based Training (SBT) allows clinicians to experience and practice realistic hands-on procedures and scenarios without any risk. In ECMO, cannulation is a critical procedure performed to externally reroute the blood flow so it can be re-oxygenated by the ECMO machine before being recirculated through the patient's body. In a close collaboration with Hamad Medical Corporation (HMC), this project aims to develop a cost effective, realistic, and user-friendly ECMO simulator focusing on the venous and arterial cannulation procedure, The main features of this simulator include cannulation emergencies caused by low pressure flow, excessive force, recirculation, or mispositioned wire/cannula. Therefore, the ECMO cannulation simulator will not only greatly contribute to the initial and ongoing local training of HMC ECMO clinicians but also contribute to improving patient care by lowering the risks associated with the cannulation process.
{"title":"Preliminary Implementation of the Next Generation Cannulation Simulator","authors":"A. Mahmoud, A. A. Hssain, Guillaume Alinier, I. Hassan, U. Khurshid, Aiman Abducarim, S. Mahmud, Omrane Abdallah, Elshaikh Mohamed, A. Alsalemi, F. Bensaali, A. Amira","doi":"10.1109/SCORED.2019.8896240","DOIUrl":"https://doi.org/10.1109/SCORED.2019.8896240","url":null,"abstract":"Extracorporeal Membrane Oxygenation (ECMO) is a highly complex/critical lifesaving procedure known to support patients with cardiac and respiratory issues. Patients on ECMO are monitored 24/7 by a team of highly trained ECMO team comprising nurses, physicians, respiratory therapists, and perfusionists promptly intervening to any potential emergency situation. Simulation-Based Training (SBT) allows clinicians to experience and practice realistic hands-on procedures and scenarios without any risk. In ECMO, cannulation is a critical procedure performed to externally reroute the blood flow so it can be re-oxygenated by the ECMO machine before being recirculated through the patient's body. In a close collaboration with Hamad Medical Corporation (HMC), this project aims to develop a cost effective, realistic, and user-friendly ECMO simulator focusing on the venous and arterial cannulation procedure, The main features of this simulator include cannulation emergencies caused by low pressure flow, excessive force, recirculation, or mispositioned wire/cannula. Therefore, the ECMO cannulation simulator will not only greatly contribute to the initial and ongoing local training of HMC ECMO clinicians but also contribute to improving patient care by lowering the risks associated with the cannulation process.","PeriodicalId":231004,"journal":{"name":"2019 IEEE Student Conference on Research and Development (SCOReD)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116638971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/SCORED.2019.8896274
Ester Dhenise G. Vinarao, Michelle Nicole B. de Guzman, Edward A. Fernandez, Danica Jane V. Quije, Rheaxena C. Gorres, Eliseo D. Francisco, Reynold A. Delizo, Edward N. Cruz
The study aims to develop a Mobile Based Application for Woman's Safety to help authorities track criminals through the use of the said application by providing real-time SMS Notification, GPS Tracking, and direct emergency call to nearby police station inside the province. Rizal province was chosen as the beneficiary of this study during this phase. The system will also help authorities prevent crimes before it happens depending on the user response. The study is best suited for individuals commuting to uncomfortable destinations. The study requires users to have an active mobile network load to maximize the potential of the system. It involves host server which accept and process complaints initiated by the users. The development of the “Athena: A Mobile Based Application for Woman's Safety with GPS Tracking and Police Notification for Rizal Province” utilizes Agile methodology in Android platform provide the following functions: sends notification via SMS, video and image capturing, and direct calling the police and GPS tracking in time of distress. The developed system also showed its effectivity in processing the different features stated in the scope and delimitations of the study.
{"title":"Athena: A Mobile Based Application for Women's Safety with GPS Tracking and Police Notification for Rizal Province","authors":"Ester Dhenise G. Vinarao, Michelle Nicole B. de Guzman, Edward A. Fernandez, Danica Jane V. Quije, Rheaxena C. Gorres, Eliseo D. Francisco, Reynold A. Delizo, Edward N. Cruz","doi":"10.1109/SCORED.2019.8896274","DOIUrl":"https://doi.org/10.1109/SCORED.2019.8896274","url":null,"abstract":"The study aims to develop a Mobile Based Application for Woman's Safety to help authorities track criminals through the use of the said application by providing real-time SMS Notification, GPS Tracking, and direct emergency call to nearby police station inside the province. Rizal province was chosen as the beneficiary of this study during this phase. The system will also help authorities prevent crimes before it happens depending on the user response. The study is best suited for individuals commuting to uncomfortable destinations. The study requires users to have an active mobile network load to maximize the potential of the system. It involves host server which accept and process complaints initiated by the users. The development of the “Athena: A Mobile Based Application for Woman's Safety with GPS Tracking and Police Notification for Rizal Province” utilizes Agile methodology in Android platform provide the following functions: sends notification via SMS, video and image capturing, and direct calling the police and GPS tracking in time of distress. The developed system also showed its effectivity in processing the different features stated in the scope and delimitations of the study.","PeriodicalId":231004,"journal":{"name":"2019 IEEE Student Conference on Research and Development (SCOReD)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128313745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/SCORED.2019.8896291
Jahedul Islam, P. Vasant, B. M. Negash, J. Watada
This paper proposes a modified crow search algorithm with local search and niching technique. The primitive crow search algorithm is a newly developed population-based algorithm which gained attention from the researchers of many fields as it needs only one parameter to be tuned. Despite its easy implementation, crow search algorithm has weakness to find global optima and suffers from slow convergence rate in multi-modal optimization problems. The search agent of the primitive crow search algorithm does not always follow the best solution obtained so far. Another disadvantage is that the search agents updates its location randomly. In order to enhance its searching capacity, a global search operator is introduced. Also, The proposed method modifies the search techniques and incorporates niching method to increase exploration capacity. The proposed technique is tested on 23 benchmark functions. The results of the proposed method demonstrated faster convergence rate and better solution in most cases when compared with the standard crow search algorithm.
{"title":"A modified crow search algorithm with niching technique for numerical optimization","authors":"Jahedul Islam, P. Vasant, B. M. Negash, J. Watada","doi":"10.1109/SCORED.2019.8896291","DOIUrl":"https://doi.org/10.1109/SCORED.2019.8896291","url":null,"abstract":"This paper proposes a modified crow search algorithm with local search and niching technique. The primitive crow search algorithm is a newly developed population-based algorithm which gained attention from the researchers of many fields as it needs only one parameter to be tuned. Despite its easy implementation, crow search algorithm has weakness to find global optima and suffers from slow convergence rate in multi-modal optimization problems. The search agent of the primitive crow search algorithm does not always follow the best solution obtained so far. Another disadvantage is that the search agents updates its location randomly. In order to enhance its searching capacity, a global search operator is introduced. Also, The proposed method modifies the search techniques and incorporates niching method to increase exploration capacity. The proposed technique is tested on 23 benchmark functions. The results of the proposed method demonstrated faster convergence rate and better solution in most cases when compared with the standard crow search algorithm.","PeriodicalId":231004,"journal":{"name":"2019 IEEE Student Conference on Research and Development (SCOReD)","volume":"177 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116341352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/SCORED.2019.8896249
Clifford A. Calleja, Paul John E. Candelaria, Dann Neil R. Cape, Ma. Katrina A. Lazarte, Bernie S. Fabito
Mobile Learning or M-Learning has been gaining attention in research to determine its impact on the learning experiences of the students. The use of technology, particularly of mobile learning, is essential in education due to its capability to provide individual learning experiences. M-Learning can be defined as Learning using mobile devices like Smart Phones and Tablets. This platform can be integrated into Blended Learning where students learn inside and outside the four walls of the classroom. Given the advantages of M-Learning for students, this study sought to design and develop a mobile application that helps preschoolers enhance their learning experience in science in one Daycare Center in the Philippines. The application includes lessons from the Department of Social Welfare and Development (DSWD). Quizzes as a form of assessment can be taken after each lesson. Succeeding lessons are locked and cannot be accessed until the teacher unlocks these lessons. The mobile application was assessed using ISO 9126 to determine the acceptability among the teachers and parents of the pupils of the Daycare Center. The overall result yielded an average mean of 4.0 which is verbally interpreted as Very Satisfactory. A longitudinal-experimental study for the mobile application is recommended to further assess the impact of the application on the learning experience of the pupils.
{"title":"Nursery Science: A Mobile Application for Learning Science for Pre-Schoolers","authors":"Clifford A. Calleja, Paul John E. Candelaria, Dann Neil R. Cape, Ma. Katrina A. Lazarte, Bernie S. Fabito","doi":"10.1109/SCORED.2019.8896249","DOIUrl":"https://doi.org/10.1109/SCORED.2019.8896249","url":null,"abstract":"Mobile Learning or M-Learning has been gaining attention in research to determine its impact on the learning experiences of the students. The use of technology, particularly of mobile learning, is essential in education due to its capability to provide individual learning experiences. M-Learning can be defined as Learning using mobile devices like Smart Phones and Tablets. This platform can be integrated into Blended Learning where students learn inside and outside the four walls of the classroom. Given the advantages of M-Learning for students, this study sought to design and develop a mobile application that helps preschoolers enhance their learning experience in science in one Daycare Center in the Philippines. The application includes lessons from the Department of Social Welfare and Development (DSWD). Quizzes as a form of assessment can be taken after each lesson. Succeeding lessons are locked and cannot be accessed until the teacher unlocks these lessons. The mobile application was assessed using ISO 9126 to determine the acceptability among the teachers and parents of the pupils of the Daycare Center. The overall result yielded an average mean of 4.0 which is verbally interpreted as Very Satisfactory. A longitudinal-experimental study for the mobile application is recommended to further assess the impact of the application on the learning experience of the pupils.","PeriodicalId":231004,"journal":{"name":"2019 IEEE Student Conference on Research and Development (SCOReD)","volume":"357 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116469872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/SCORED.2019.8896270
Wang Chia Woon, N. Yahya, N. Badruddin
EEG signal is one of the main sources for implementation of Brain-Computer Interface (BCI) technology. The BCI is a non-muscle communication link between brain and external device, which commonly designed to enable patients with neurological condition to interact with others using their brain signals. In this work, we investigated the classification of EEG eye state data using statistical and CSP filter technique. Statistical feature has been applied in EEG signal classifications of eye-close and eye-open conditions but the accuracy is reported to be less than 78%. CSP filter is a well-known method for classification of motor imagery EEG in the BCI field but when applied for EEG eye state classification, it only gives accuracy similar to statistical feature, that is less than 78%. These indicate that both methods give good discrimination of the eye state condition but on it own, will not be sufficient to produce good classification accuracy. Hence, this work aims to develop an algorithm using statistical-CSP feature for eye state classification from EEG signal. This is taking advantage on the discriminative feature provided by both methods, statistical and CSP filter, which is expected to increase the accuracy of the eye state classification algorithm. The process of developing the EEG eye state classification algorithm, includes data extraction, pre-processing, data normalization, feature extraction, feature selection and classification are detailed out in this paper. Number of selected electrodes are divided into 3 groups, with 2 groups having a set of 7 different electrodes and 1 group that combined both sets of 7 electrodes giving a total of 14 electrodes. Using ten-fold cross validation, the highest accuracy of statistical feature is at 54.3% and the highest accuracy of CSP feature is at 72.3% generated using fine Gaussian SVM classifier. Result from this work has shown that combining both statistical and CSP features from 7 electrodes of Group I has shown to result in good accuracy of 99.92%.
{"title":"EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter","authors":"Wang Chia Woon, N. Yahya, N. Badruddin","doi":"10.1109/SCORED.2019.8896270","DOIUrl":"https://doi.org/10.1109/SCORED.2019.8896270","url":null,"abstract":"EEG signal is one of the main sources for implementation of Brain-Computer Interface (BCI) technology. The BCI is a non-muscle communication link between brain and external device, which commonly designed to enable patients with neurological condition to interact with others using their brain signals. In this work, we investigated the classification of EEG eye state data using statistical and CSP filter technique. Statistical feature has been applied in EEG signal classifications of eye-close and eye-open conditions but the accuracy is reported to be less than 78%. CSP filter is a well-known method for classification of motor imagery EEG in the BCI field but when applied for EEG eye state classification, it only gives accuracy similar to statistical feature, that is less than 78%. These indicate that both methods give good discrimination of the eye state condition but on it own, will not be sufficient to produce good classification accuracy. Hence, this work aims to develop an algorithm using statistical-CSP feature for eye state classification from EEG signal. This is taking advantage on the discriminative feature provided by both methods, statistical and CSP filter, which is expected to increase the accuracy of the eye state classification algorithm. The process of developing the EEG eye state classification algorithm, includes data extraction, pre-processing, data normalization, feature extraction, feature selection and classification are detailed out in this paper. Number of selected electrodes are divided into 3 groups, with 2 groups having a set of 7 different electrodes and 1 group that combined both sets of 7 electrodes giving a total of 14 electrodes. Using ten-fold cross validation, the highest accuracy of statistical feature is at 54.3% and the highest accuracy of CSP feature is at 72.3% generated using fine Gaussian SVM classifier. Result from this work has shown that combining both statistical and CSP features from 7 electrodes of Group I has shown to result in good accuracy of 99.92%.","PeriodicalId":231004,"journal":{"name":"2019 IEEE Student Conference on Research and Development (SCOReD)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128107450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/SCORED.2019.8896316
Tran duc Chung, R. Ibrahim
This paper presents an approach to measure building ambient temperature using industrial wireless mesh technology (WirelessHART) based on command line interface (CLI) with wireless network manager from a laptop host. Based on the experiment with five wireless nodes (motes) in a laboratory environment, it is found that on average, the measured temperatures are close to 22°C. In addition, all motes have similar temperature pattern even though they are located at different places in the laboratory. When there is a change in the laboratory's environment i.e., the entry door is opened / closed, the measured temperatures at all motes increase / decrease accordingly. In addition, the mote nearest to the entry door has the highest average temperature while the mote furthest to the door has the lowest average temperature. Furthermore, the mote attached to a time-varying heat source, i.e., the laptop fan, has the highest temperature deviation.
{"title":"Building Ambient Temperature Measurement using Industrial Wireless Mesh Technology","authors":"Tran duc Chung, R. Ibrahim","doi":"10.1109/SCORED.2019.8896316","DOIUrl":"https://doi.org/10.1109/SCORED.2019.8896316","url":null,"abstract":"This paper presents an approach to measure building ambient temperature using industrial wireless mesh technology (WirelessHART) based on command line interface (CLI) with wireless network manager from a laptop host. Based on the experiment with five wireless nodes (motes) in a laboratory environment, it is found that on average, the measured temperatures are close to 22°C. In addition, all motes have similar temperature pattern even though they are located at different places in the laboratory. When there is a change in the laboratory's environment i.e., the entry door is opened / closed, the measured temperatures at all motes increase / decrease accordingly. In addition, the mote nearest to the entry door has the highest average temperature while the mote furthest to the door has the lowest average temperature. Furthermore, the mote attached to a time-varying heat source, i.e., the laptop fan, has the highest temperature deviation.","PeriodicalId":231004,"journal":{"name":"2019 IEEE Student Conference on Research and Development (SCOReD)","volume":"45 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130753332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/SCORED.2019.8896286
Soong Qian Xin, N. Yahya, L. I. Izhar
In this paper, we investigate techniques to classify the neurological status based on the biosensor signals. The sensor used in this work, recorded reading of acceleration (accX, aceY, accZ), temperature and electrodermal activity (EDA). Four neurological conditions are considered; cognitive stress, emotional stress, physical stress, and relaxation mode. Statistical feature extraction methods used in this work include mean, maximum (max), minimum (min), mean absolute deviation (MAD), Standard deviation (STD), interquartile range (IQR) and total summation. The extracted features are then fed into the Support Vector Machines (SVM) and ensemble classifier which are supervised learning models. The accuracy of the classifier used in determining the neurological status of the subjects with and without the feature extraction was computed and analyzed to conclude on the ability as well as the accuracy of each method in determining the neurological status. The ensemble classifier achieved an accuracy of 99.8% without feature extraction and 94.5% with feature extraction while the SVM classifier achieved an accuracy of 62.4% without feature extraction and 87% with feature extraction. This indicates ensemble is a better classifier when using no feature extraction whereas, SVM performs better with feature extraction in classifying different neurological status from biosensor signals.
{"title":"Classification of Neurological States from Biosensor Signals Based on Statistical Features","authors":"Soong Qian Xin, N. Yahya, L. I. Izhar","doi":"10.1109/SCORED.2019.8896286","DOIUrl":"https://doi.org/10.1109/SCORED.2019.8896286","url":null,"abstract":"In this paper, we investigate techniques to classify the neurological status based on the biosensor signals. The sensor used in this work, recorded reading of acceleration (accX, aceY, accZ), temperature and electrodermal activity (EDA). Four neurological conditions are considered; cognitive stress, emotional stress, physical stress, and relaxation mode. Statistical feature extraction methods used in this work include mean, maximum (max), minimum (min), mean absolute deviation (MAD), Standard deviation (STD), interquartile range (IQR) and total summation. The extracted features are then fed into the Support Vector Machines (SVM) and ensemble classifier which are supervised learning models. The accuracy of the classifier used in determining the neurological status of the subjects with and without the feature extraction was computed and analyzed to conclude on the ability as well as the accuracy of each method in determining the neurological status. The ensemble classifier achieved an accuracy of 99.8% without feature extraction and 94.5% with feature extraction while the SVM classifier achieved an accuracy of 62.4% without feature extraction and 87% with feature extraction. This indicates ensemble is a better classifier when using no feature extraction whereas, SVM performs better with feature extraction in classifying different neurological status from biosensor signals.","PeriodicalId":231004,"journal":{"name":"2019 IEEE Student Conference on Research and Development (SCOReD)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132745932","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/SCORED.2019.8896333
Fariba Islam, A. Zubair, Nabila Fairuz
Wearable and portable devices are appearing prominently in consumer electronics over the last decade and are becoming inevitable in this modern era. However, powering and recharging these devices are still tremendous challenges. Here, we designed thermoelectric nanogenerators and a novel textile based thermoelectric energy harvester based on carbon nanotube (CNT) which can be solution to the problem. These energy harvesters can harness solar or thermal energy to generate electricity. The reason for preferring textile based thermoelectric generator is that it can be used ubiquitously and can be used to power up wearable devices whenever needed. CNT is selected as the material of choice due to extreme tensile strength of CNTs so that long fibers required for textile can be manufactured with it and extraordinary tunability of electrical and thermal properties of CNTs. Though, some other thermoelectric materials like Bi2Te3and PbTe have greater Seebeck coefficient than that of CNT, their tensile strength is much smaller and they are toxic. In our textile based energy harvester, the CNT fibers are incorporated with conventional textile fibers like cotton. We proposed different configurations of textile based energy harvester and corresponding generated thermoelectric voltage was estimated. In series configuration, we found voltage of 55.2 μV for 1 K temperature difference in a 44 mm long fiber.
{"title":"Wearable Thermoelectric Nanogenerator Based on Carbon Nanotube for Energy Harvesting","authors":"Fariba Islam, A. Zubair, Nabila Fairuz","doi":"10.1109/SCORED.2019.8896333","DOIUrl":"https://doi.org/10.1109/SCORED.2019.8896333","url":null,"abstract":"Wearable and portable devices are appearing prominently in consumer electronics over the last decade and are becoming inevitable in this modern era. However, powering and recharging these devices are still tremendous challenges. Here, we designed thermoelectric nanogenerators and a novel textile based thermoelectric energy harvester based on carbon nanotube (CNT) which can be solution to the problem. These energy harvesters can harness solar or thermal energy to generate electricity. The reason for preferring textile based thermoelectric generator is that it can be used ubiquitously and can be used to power up wearable devices whenever needed. CNT is selected as the material of choice due to extreme tensile strength of CNTs so that long fibers required for textile can be manufactured with it and extraordinary tunability of electrical and thermal properties of CNTs. Though, some other thermoelectric materials like Bi2Te3and PbTe have greater Seebeck coefficient than that of CNT, their tensile strength is much smaller and they are toxic. In our textile based energy harvester, the CNT fibers are incorporated with conventional textile fibers like cotton. We proposed different configurations of textile based energy harvester and corresponding generated thermoelectric voltage was estimated. In series configuration, we found voltage of 55.2 μV for 1 K temperature difference in a 44 mm long fiber.","PeriodicalId":231004,"journal":{"name":"2019 IEEE Student Conference on Research and Development (SCOReD)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115183634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/SCORED.2019.8896251
Noor Al-Qaysi, Norhisham Mohamad-Nordin, M. Al-Emran, Mohammed A. Al-Sharafi
Social media use by university students attracted the interest of several scholars worldwide. However, a limited amount of research articles was published to investigate the students' attitudes towards social media usage in the Arab world universities. As a case study, the core objective of this research is to measure the students' attitudes towards the use of social media at an academic institute in Oman. The study intends to examine the differences in these attitudes from the lenses of several attributes, including gender, age, year of study, and social media application. A total of 198 students took part in the study through an online survey. Although the findings showed no significant differences in attitudes with regard to the aforementioned studied attributes, it is imperative to report that all the participated students were mutually interested in using social media applications in learning practices.
{"title":"Understanding the differences in students' attitudes towards social media use: A case study from Oman","authors":"Noor Al-Qaysi, Norhisham Mohamad-Nordin, M. Al-Emran, Mohammed A. Al-Sharafi","doi":"10.1109/SCORED.2019.8896251","DOIUrl":"https://doi.org/10.1109/SCORED.2019.8896251","url":null,"abstract":"Social media use by university students attracted the interest of several scholars worldwide. However, a limited amount of research articles was published to investigate the students' attitudes towards social media usage in the Arab world universities. As a case study, the core objective of this research is to measure the students' attitudes towards the use of social media at an academic institute in Oman. The study intends to examine the differences in these attitudes from the lenses of several attributes, including gender, age, year of study, and social media application. A total of 198 students took part in the study through an online survey. Although the findings showed no significant differences in attitudes with regard to the aforementioned studied attributes, it is imperative to report that all the participated students were mutually interested in using social media applications in learning practices.","PeriodicalId":231004,"journal":{"name":"2019 IEEE Student Conference on Research and Development (SCOReD)","volume":"221 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114497278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/SCORED.2019.8896324
A. K. Alazzawi, H. Rais, S. Basri, Y. A. Alsariera
Software testing becoming significant part of our daily life due to a software-development process that led to increase the components number and the associated time. Due to the financial resources and time constraints, practically exhaustive testing is hopeless. For this reason, numerous researchers have adopted pairwise testing to decrease the exhaustive number of test cases. Pairwise testing is one of a powerful Combinatorial Testing Technique (CTT) that used widely for test data generation. Various existing research works were developed using a meta-heuristic algorithm as a basis for pairwise testing strategies. Supplementing to earlier research work, this paper proposed a new pairwise test suite generation called pairwise hybrid artificial bee colony (PhABC) strategy based on hybridize of an artificial bee colony (ABC) algorithm with a particle swarm optimization (PSO) algorithm. The output of PhABC is a set of promising optimal test set combinations. The results of the experiments showed that PhABC outperformed and yielded better test sets than other existing other research strategies even with the existing constraints.
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